Download Neuroendocrine Stress Response after Burn Trauma

Digital Comprehensive Summaries of Uppsala Dissertations
from the Faculty of Medicine 908
Neuroendocrine Stress
Response after Burn Trauma
ANDREAS LINDAHL
ACTA
UNIVERSITATIS
UPSALIENSIS
UPPSALA
2013
ISSN 1651-6206
ISBN 978-91-554-8686-0
urn:nbn:se:uu:diva-198466
Dissertation presented at Uppsala University to be publicly examined in Skoogsalen, Entrance
78-79, Akademiska Sjukhuset, Uppsala, Friday, June 14, 2013 at 09:15 for the degree of
Doctor of Philosophy (Faculty of Medicine). The examination will be conducted in Swedish.
Abstract
Lindahl, A. 2013. Neuroendocrine Stress Response after Burn Trauma. Uppsala universitet.
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine
908. 66 pp. Uppsala. ISBN 978-91-554-8686-0.
Some aspects of the stress response during acute intensive care for severe burns are described
and quantified by measuring hormonal and neuroendocrine patterns and relating these to organ
function in the short term. This includes an assessment of whether there are markers for the
severity of stress that are better than conventional descriptors of the severity of a burn in
predicting failing organ function.
P-CgA after a major burn injury is an independent and better predictor of organ dysfunction
assessed as SOFA score than the traditionally used TBSA% burned. The results also suggest
that the extent of neuroendocrine activation is related to organ dysfunction, and this motivates
a more extensive effort to evaluate P-CgA as a prognostic marker with respect to mortality and
long-term outcome.
P-NT-proBNP exhibited a complex pattern with considerable inter-individual and day-today variations. Values of P-NT-proBNP were related to size of burn, water accumulation and
systemic inflammatory response. A considerable covariation with trauma response and SOFA
scores was observed in day by day analyses, but with weight change only on day 2.
Maximum P-NT-proBNP showed a stronger correlation with SOFA score on day 14, with
mortality, and with LOS, than did age and TBSA% burned. High values were also independent
predictors of all subsequent SOFA scores up to two weeks after injury.
P-NT-proBNP and NT-proANP reflect and predict organ function after burn injury similarly,
notwithstanding a significantly larger intra-individual variability for P-NT-proBNP. P-NTproBNP, but not NT-proANP, reflects the systemic inflammatory trauma response.
Free cortisol concentration was related to the size of burns, as was the circadian cortisol
rhythm. This effect of burn size was, at least in part, related to its effect on organ function.
This thesis points to the fact that the stress response is richly interwoven, and cannot be
adequately assessed by one biomarker only. All biomarkers studied here can be viewed as
representing efferent limbs of the stress reaction, and they would need to be supplemented by
biomarkers representing individual physiologic responses that follow the stress signaling.
Keywords: Burn, Injuries, Neuroendocrine, Intensive Care, Cortisol, Chromogranin A,
Natriuretic peptides
Andreas Lindahl, Uppsala University, Department of Surgical Sciences, Plastic Surgery,
Akademiska sjukhuset, SE-751 85 Uppsala, Sweden.
© Andreas Lindahl 2013
ISSN 1651-6206
ISBN 978-91-554-8686-0
urn:nbn:se:uu:diva-198466 (http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-198466)
To my parents
“Complete freedom from stress can
be expected only after death.”
Hans Hugo Bruno Selye
List of Papers
The thesis is based on the following publications. They are referred to in the
text by their Roman numerals.
I
Lindahl A, Low A, Stridsberg M, Sjöberg F, Ekselius L, Gerdin B.
Plasma Chromogranin A: A New Severity Marker in Burn Intensive
Care. Neuropeptides 2012 Nov 30.doi:pii: S0143-4179(12)00109-6.
10.1016/j.npep.2012.10.004. [Epub ahead of print]
II
Lindahl A, Stridsberg M, Sjöberg F, Ekselius L, Gerdin B. Natriuretic
Peptide type B in Burn Intensive Care. J Trauma Acute Care Surg
74:855-61, 2013
III
Lindahl A, Stridsberg M, Sjöberg F, Ekselius L, Gerdin B. Concentrations of ANP and BNP convey different types of information in Burn
Intensive Care. Submitted for publication
IV
Lindahl A, Stridsberg M, Sjöberg F, Ekselius L, Gerdin B. Circadian
Cortisol Rhythm after Burn Injury. Submitted for publication
Reprints were made with permission from the respective publishers.
Contents
Abbreviations .................................................................................................xi
Introduction ................................................................................................... 13
Trauma ..................................................................................................... 13
Burn trauma .............................................................................................. 14
Epidemiology....................................................................................... 14
Basic pathophysiology ......................................................................... 14
Stress response ......................................................................................... 15
History and concepts of stress ............................................................. 15
Current concepts .................................................................................. 16
Neuroendocrinology of the stress response ......................................... 17
Effects of long-standing stress ................................................................. 23
Trauma, burn trauma, ICU care and the stress response .......................... 24
Assessment of severity of illness in the ICU ............................................ 25
Current investigation ..................................................................................... 27
Context ..................................................................................................... 27
Aims ......................................................................................................... 28
Material and Methods ................................................................................... 29
Patients ..................................................................................................... 29
Procedure.................................................................................................. 29
Measurements........................................................................................... 31
Clinical routine ......................................................................................... 31
Statistical analyses.................................................................................... 32
Techniques ........................................................................................... 32
Data presentation ................................................................................. 32
Directed Acyclic Graphs...................................................................... 33
Ethics ........................................................................................................ 33
Results ........................................................................................................... 34
Paper I ...................................................................................................... 34
Paper II ..................................................................................................... 36
Paper III .................................................................................................... 37
Paper IV ................................................................................................... 41
Discussion ..................................................................................................... 45
Specific discussion ................................................................................... 45
Chromogranin A .................................................................................. 45
Natriuretic peptides.............................................................................. 47
Cortisol ................................................................................................ 49
General discussion.................................................................................... 50
The integrated neuroendocrine response ............................................. 50
The neuroendocrine response and late sequels .................................... 52
Summing up ......................................................................................... 53
Conclusions ................................................................................................... 54
Acknowledgments......................................................................................... 55
References ..................................................................................................... 58
Abbreviations
ABLS
ACTH
ANP
ATLS
BICU
BNP
CCI
CgA
CRH
CBG
CV
HPA-axis
ICU
ICUAW
LOS
NP
NT-proANP
NT-proBNP
PTSD
PVN
ROC
SOFA
TBSA
Advanced Burn Life Support
Adrenocorticotropic hormone
Natriuretic Peptide type A (previously known as Atrial
Natriuretic Peptide)
Advanced Trauma Life Support
Burn Intensive Care Unit
Natriuretic Peptide type B (previously known as Brain
Derived Natriuretic Peptide)
Chronic Critical Illness
Chromogranin A
Corticotrophin-releasing hormone
Cortisol Binding Globulin
Coefficient of Variability
Hypothalamic-pituitary-adrenal axis
Intensive Care Unit
ICU-acquired weakness
Length of Stay (Days)
Natriuretic peptide
N-terminal proANP; an inactive pro-peptide co-released
with ANP
N-terminal proBNP; an inactive pro-peptide co-released
with BNP
Posttraumatic Stress Disorder
Paraventricular Nucleus
Receiver Operator Curve
Sequential Organ Failure Assessment, formerly Sepsis
Organ Failure Assessment
Total Body Surface Area
xi
Introduction
The term “stress” is used in this thesis to describe a non-specific response to
extreme demands on the human organism. While it is true that individuals
react differently to stress, it is equally true that there are common characteristics and universal features in the physiological stress response in the human
organism.
Trauma, an important cause of morbidity and mortality worldwide, induces a strong stress response. Burn trauma is special in at least two respects: it
is one of the most severe types of trauma imaginable, and it is quantifiable in
a way other types of trauma are not.
The stress response is complex and is controlled by nervous and endocrine regulation. Its purpose is to secure survival when there is a severe and
acute threat to the individual. After prolonged or excessive stress, however,
destructive effects can be observed on the organism. The stress response
modulates cardiovascular function, immune function and metabolism.
Scrutiny and elucidation of the stress response after burn injury will ultimately enhance our understanding of different types of posttraumatic pathology, as well as advance burn care.
Trauma
Trauma, originating from the Greek word meaning "wound", refers to "an
injury (such as a wound) to living tissue caused by an extrinsic agent" [88].
While initially used in a purely somatic context the term has recently also
been used more extensively to describe psychiatric consequences of somatic
or psychiatric events, "psychiatric trauma". In the present thesis, the term is
used in its strict somatic context, if not specifically stated otherwise.
A trauma of a magnitude with a significant risk of ending up in disability
or death is defined as a "major trauma". Examples of such injuries are serious head injuries, severe gunshot wounds and different types of accidents
caused by high-energy forces. A major trauma demands optimal acute trauma care to combat organ- or life-threatening consequences of the injury.
Such resuscitation of a trauma patient often involves multiple management
procedures. Trauma is the sixth leading cause of death worldwide, accounting for 10% of all mortality, and is a serious public health problem with significant social and economic costs [82].
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An excellent model for major trauma is the catastrophic experience of being
afflicted with an extensive burn injury.
Burn trauma
A burn is a tissue injury caused by exposure to thermal energy. Exposure to
caustic chemicals or radiation causes similar injuries that, from a practical
point of view, are therefore regarded as "burn injuries".
Epidemiology
Burn injuries are among the most devastating of injuries and constitute a
major global public health crisis [40]. Burns are the fourth most common
type of trauma worldwide, following traffic accidents, falls, and interpersonal violence [140]. Approximately 90 percent of burns occur in low to middle
income countries, regions that generally lack the necessary infrastructure to
reduce the incidence and severity of burns [93]. In the United States, 4500
people die from burn injuries each year, and up to 10 000 die every year
from burn related infections.
It is estimated that just over 30 000 burn injuries require medical attention
each year in Sweden, and that roughly 1000 patients require hospitalization
due to burn injuries, of whom about 300 are treated as part of National Specialized Medical Care in centers for treatment of severe burns. These figures
mean that the current incidence of burn injuries requiring hospital admission
in Sweden is about 11 per 100 000 inhabitants [134], which can be compared
to 29 per 100 000 inhabitants in Great Britain [109] and 31 per 100 000 inhabitants in Southern Italy [9]. The most reliable figure for the entire United
States is 14-15 per 100 000 [5].
The most common causes of burn injuries in the Western world are heat
exposure due to scalding, flame and contact with hot objects [5; 19]. Among
these, flame injuries are most common except in children under the age of
five, who are more prone to scalding accidents. Electrical and chemical burn
injuries represent a minority but can be very serious [18; 6]
Risk groups for burn injuries are children and the elderly, the disabled,
individuals with alcohol- or drug abuse, and the socioeconomically disadvantaged. About one fourth of those who are admitted to a hospital require
specialized burn care [6].
Basic pathophysiology
The key pathophysiologic features of tissue exposure to heat are related to
immediate or late cell damage or death. An important feature is the virtually
immediate alteration in connective tissue properties that results in a rapid
14
transport of intravascular water to the damaged site. In larger injuries the
loss of intravascular water leads to severe hemoconcentration and burn
shock, unless adequately corrected. The main aim during the resuscitation
phase is to titrate the replacement of intravascular fluid to maintain an optimal circulation without detrimental consequences due to excessive water
overload.
In parallel, there is activation of most inflammatory cascade systems in
the body as part of an intense posttraumatic response, which is largely proportional to the magnitude of the burn, and which under unfavorable conditions may lead to failure of isolated or multiple organs over the forthcoming
weeks. A serious effect is also an endogenous immunodepression, which has
negative consequences regarding resistance to infections.
The resuscitation phase, which generally is 24 to 48 hours for a major
burn, is followed by a phase dominated by the negative consequences of
water overload, which in some patients may be 20 liters or more and is
threatening to organ function.
During this time catecholamines are often manifoldly increased, leading
to a state of hypermetabolism, insulin resistance and glucose intolerance, an
increase in peripheral lipolysis, and catabolism of peripheral protein [142].
Towards the end of the first week the risk of infection with sepsis and
subsequent organ failure becomes the main threat, and most of the inhospital mortality occurs after this time.
Rehabilitative measures are undertaken from day one and become a greater focus as wounds heal during the later stages of the acute phase. Main issues include minimizing handicaps from scarring and improving physical
and psychosocial function.
Stress response
History and concepts of stress
The history of stress has been summarized elegantly by George Fink [37].
The French physiologist Claude Bernard (1813-1878) was the first to formally explain how cells and tissues in multicellular organisms might be protected from stress. In 1859 he pointed out that the fixity, or stability, of the
"milieu intérieur" is the prerequisite for free and independent life.
In the early 20th century, Walter Bradford Cannon suggested the designation "homeostasis" for the coordinated physiological processes that maintain
steady states in the organism. He also coined the expression “fight or flight”
to describe an animal’s response to threat by means of a general discharge of
the sympathetic nervous system to prime the animal for fighting or fleeing.
This was later recognized as the first stage, the acute stress response, of a
15
general adaptation syndrome (GAS) postulated by the “father of stress”,
Hans Selye of Vienna. He observed that patients with a variety of illnesses
had many of the same “nonspecific” symptoms that were a common response to stressful stimuli experienced by the body.
In the 1980s, Peter Sterling and Joseph Eyer advanced the concept of
"allostasis", providing “stability through change” brought about by central
nervous regulation of the set points that adjust physiological parameters to
meet the stress/challenge [127]. This concept is in contrast to homeostasis,
meaning “stability through constancy” around an already fixed set point.
At the center of the adaptation to stress are precise alterations in expression of a multitude of genes, and at the molecular level the cellular response
to high temperatures and other types of stress is represented by a changed
transcription pattern resulting in alterations in the synthesis of a variety of
proteins [43]. Among such “stress proteins”, much attention has been focused on the heat shock proteins (HSPs) [43]. HSPs are involved in the
maintenance of the folding of proteins and their purpose is to protect the
protein structure and thereby all cellular functions when under environmental threat. The heat shock response is ubiquitous and highly conserved in all
organisms.
Current concepts
The first and most generic definition of stress, “Stress is the nonspecific
response of the body to any demand”, still holds. Stress involves a stressor
and a stress response. The stressors are "identified" by, and the "response" is
keyed by, the brain [22]. The term “allostasis” is less ambiguous than the
term “stress response”. Allostasis is the meaningful physiological neuroendocrine response that helps us meet our everyday challenges as well as more
threatening situations. “Allostatic load” and “allostatic overload” are terms
designated for the situation of a dysregulated or protracted stress response
that does not help the organism back to homeostasis, but rather has deleterious effects [58]. Nevertheless, the term “stress” is so firmly established that
it will be used in this text. While body injuries cause various degrees of
acute stress, chronic stress is more often ascribed to psychological (or experiential) factors. Depending on the type of stimulus, the time and the individual factors that are involved, the stress response pattern varies widely.
Acute stress is characterized by an overactive sympathetic nervous system
and an increased output of various hormones. More protracted physical [138]
and psychological [14] stress involves an exhausted response. In major depression there is a similar exhaustion [106]. It is of interest that traumatic
events in childhood affect the stress response pattern in adult life [95].
There are considerable individual differences in how stress is handled and
responded to. The term “resilience” can be viewed as a reciprocal characteristic or antonym to the concept of “vulnerability”. Resilience is a crucial
16
component in determining the way in which individuals react to and deal
with stress [23]. The expression locus of control, which can be either internal
or external, is important. In the awake patient the experience of external
locus of control is associated with chronicity of the stress response, i.e.
allostatic overload. An internal locus of control is thought to have a stress
relieving effect [37]
Neuroendocrinology of the stress response
The brain is the key organ in the response to stress and defines internal and
external events that may be threatening and potentially harmful, as well as
the physiological and behavioral responses. Those responses can be either
adaptive or damaging [85]. Stress involves a two-way communication between the brain and the cardiovascular, immune, and other systems via neural and endocrine mechanisms. However, different stressors are sensed by
different “afferent” systems. Some types of stress such as pain, for example,
are sensed and keyed by the nervous system, but stressors that primarily
affect the viability of cells, such as a burn or an infection, are sensed directly
by affected cells in the damaged tissue and are propagated by endocrine
mechanisms. The response is subsequently propagated by tightly coupled
and integrated neurogenic as well as endocrine efferent mechanisms. In addition, the stress response can be initiated or potentiated by the cortex of the
brain when it interprets experiences as threatening. Stress in relation to physical trauma is regulated mostly on an unconscious level, and is therefore
present in the sedated patient during intensive care, as well as in the awake
patient.
A hallmark of the stress response is activation of the autonomic nervous
system and hypothalamic-pituitary-adrenal (HPA) axis – see below, which
leads to the “fight-or-flight” response, the classical way of envisioning the
behavioral and physiological response to a threat. This occurs regardless of
the type of danger, whether it is an attacking lion, a hostile attack by another
person, a car accident, or the perception of a danger that in reality does not
exist.
Neurogenic acute responses are mediated by the autonomous nervous system and are dominated by sympathetic activation in the form of epinephrine
and norepinephrine release from sympathetic nerves or the adrenal medulla.
The endocrine effector response involves signaling from the hypothalamus, the pituitary gland, which has been called “the conductor of the neuroendocrine orchestra” [36], as well as from peripheral organs.
There are many mediators participating in allostasis. They are linked together in a network of regulation that is nonlinear, meaning that each mediator has the ability to regulate the activity of the other mediators, sometimes
in a biphasic manner. An intrinsic phenomenon in this nonlinearity is that
when any one mediator is increased or decreased, there are compensatory
17
changes in the other mediators. These related changes depend on the time
course and level of change of each of the mediators. Unfortunately, biomedical technology cannot yet measure all components of this system simultaneously and must rely on measurements of only a few of them in any one study
[85]. Nevertheless, the nonlinearity must be kept in mind when interpreting
the results that are obtained.
An example of nonlinearity is the release of the major “stress hormone”
cortisol, produced by the adrenal cortex in response to the adrenocorticotropic hormone (ACTH) from the pituitary gland, which in turn is stimulated
by corticotrophin-releasing hormone (CRH) from neurons originating in the
hypothalamus. It has recently been demonstrated that positive feedback from
neurosteroids onto CRH neurons is required to mount the physiological response to stress [116]. The effect is mediated by GABA receptors on these
neurons. Further, is has been shown that by turning off a subunit of these
receptors, no stress response can be initiated. The release of a number of proand anti-inflammatory cytokines from a variety of cells that regulate each
other, and that in turn are regulated by glucocorticoids and catecholamines,
are other examples. Whereas catecholamines can increase the production of
proinflammatory cytokines [13], glucocorticoids are known to inhibit this
production [115]. There are exceptions, however, such as proinflammatory
effects of glucocorticoids that depend on dose and cell or tissue type [31;
79].
The parasympathetic nervous system also plays an important regulatory
role in the nonlinear network of allostasis, since it generally opposes the
sympathetic nervous system. It has a negative chronotropic effect on the
heart as well as anti-inflammatory effects [15; 133].
There are enormous individual differences in the response to stress that
are based on genetics [112] and on the experiences of the individual in early
life [50]. Early life maternal care in rodents is a powerful determinant of lifelong emotional reactivity and stress hormone reactivity, and increases in
both are associated with earlier cognitive decline and a shorter life span [21;
41]. It is not uncommon to hear that hardships have “aged” a person, and,
indeed, the “weathering hypothesis” [45] proposes that stressful life experiences accelerate aging.
Studies on endocrine mediators of stress reactions have so far mostly been
focused on the HPA-axis and on the role of glucocorticoids, above all cortisol. However, knowledge concerning the regulation of established stress
hormones and of the HPA-axis is continuously growing. In addition, and
supported by the view of the complexity of the stress system, new mediators,
and new functions of established mediators, have recently become evident.
In addition to an outline of the HPA-axis and glucocorticoid regulation, three
such mediators with characteristics that make them candidates for a role in
the acute stress response after injury, are described below.
18
HPA-axis and cortisol
The hypothalamic-pituitary-adrenal (HPA) axis is a key adaptive neuroendocrine system that is fundamental to all responses to stress in the human organism. This tightly coupled hormone axis is highly enlaced with the central
nervous system, and it exerts control over glucocorticoid (cortisol in humans) secretion, which is essential to combating all forms of allostatic load
in mammals and is critical to life [135; 84].
The HPA-axis can be described as a feedback loop that includes the hypothalamus, the pituitary and the adrenal glands. Structurally, it consists of
the paraventricular nucleus of the hypothalamus (PVN), which secretes corticotrophin-releasing hormone (CRH), and also arginine vasopressin (AVP);
the pituitary gland, which responds to incoming controlling stimuli, and
produces ACTH; the adrenal gland cortex, which secretes the glucocorticoids, mainly cortisol in humans, and dihydroepiandrostendione (DHEA) in
response to interaction with ACTH. Hormones from all different levels of
the HPA-axis act within the axis by modulating release of hormones from
other levels, and/or from central or peripheral sites outside the axis.
Control of cortisol secretion
Corticotrophin Releasing Hormone (CRH), a 41 amino acid peptide, is the
main physiological regulator of the HPA axis. It is produced in a subset of
neurons in the paraventricular nucleus (PVN) of the hypothalamus, which is
a key center of the central nervous system that integrates neuroendocrine
responses to allostatic load. Once secreted, CRH enters the pituitary portal
system and reaches its anterior lobe where it stimulates another subset of
neurons, corticotrophs, to release ACTH [48]. ACTH release is also stimulated by AVP, but its role is not as generally well accepted. The current perspective is that AVP serves as an additive controller of ACTH release from
the pituitary [48]. There are two principally different vasopressinergic systems in the brain. First, AVP produced in the supraoptic nucleus and in
magnocellular cells in the PVN is transported to the neurohypophysis (posterior pituitary), which delivers AVP and oxytocin to the peripheral circulation
where they regulate water homeostasis and blood pressure. Second, AVP is
produced in parvicellular neurons in the PVN, from where AVP is secreted
via the local portal system to the anterior pituitary. AVP seems to interact
with CRH in controlling release of ACTH [48].
Numerous afferent neural pathways carry information about the stressor
and thereby influence regulation of these CRH neurons, which are also regulated through negative feedback mechanisms that are central to the
autoregulation of the HPA-axis. Examples of afferent neural inputs are projections from ascending catecholaminergic pathways, from the limbic system, the hippocampus and the amygdala [53]. There are also indirect pathways from sensory systems in the forebrain that may stimulate CRH neurons
19
by activating stimulatory (glutamatergic) or repressing inhibitory (GABAergic) interneurons [52].
The central sensors of feedback to the HPA-axis are two corticosteroid
receptors, the high-affinity mineralcorticoid receptors (MR) and the lowaffinity glucocorticoid receptors (GR), which are expressed in the brain and
on the corticotrophs, i.e. the basophilic cells of the anterior pituitary responsible for ACTH secretion. A direct inhibitory effect of glucocorticoids on
CRH transcription underlies the central mechanisms of feedback regulation
and desensitization of the HPA-axis to stress responses [3].
The CRH that enters the anterior lobe induces secretion of adrenocorticotropic hormone (ACTH). ACTH triggers release of cortisol and
dihydroepiandrostendione (DHEA) from the adrenal cortex. There is evidence that the mechanistic link between ACTH and cortisol is less tight than
previously thought since there are studies indicating dissociation between the
two factors [28]. Cortisol acts on specific receptors present in most peripheral tissues and the brain and triggers the metabolic, immune,
neuromodulatory, and behavioral changes needed to cope with the impact of
the stressors [78].
To underline the complexity of this stress response system alone, it is
necessary to clarify that the adaptive influence of the HPA-axis under stress
is realized not only through cortisol, but also through ACTH and the hypothalamic neuropeptides CRH and AVP that are released in the brain, where
they are responsible for behavioral and autonomic responses to stress. Furthermore, to fully understand regulation of HPA-axis activity, network approaches must be taken as brain regions do not function as monolithic activators or inhibitors [53].
In the resting condition, cortisol secretion has a circadian rhythm that is a
net result of ultradian changes with pulsatile secretion that are greater in
amplitude during the phase of wakefulness. This leads to higher average
levels of glucocorticoids during the day in humans. Rhythmicity in the HPAaxis is essential for the normal functioning of the brain and of all other glucocorticoid responsive organs, and this is an example of a key adaptation to
cope with the different environmental challenges the organism faces at different times of day, such as changes in lighting conditions and temperature,
food availability or the presence of predators [28]. These circadian changes
are driven by an endogenous biological pacemaker made up of two components: one central pacemaker in the suprachiasmatic nucleus (SCN) and one
peripheral pacemaker in the adrenal cortex affecting sensitivity to ACTH
[28]. AVP is believed to regulate circadian rhythms [61] and is expressed in
the SCN [66].
Measurements of cortisol
Assessment of the peripheral concentration of cortisol has long been a way
of estimating the extent of activation of the HPA-axis, and thus the stress
20
response. Decades ago, accumulative measurements of the metabolic end
products 17-hydroxycorticosteroids in the urine were introduced as an integrated measure of corticosteroid production. As modern technologies
emerged, however, direct measurement of cortisol in plasma or serum was
made available. This measurement only partly reflects the concentration of
cortisol available for cells, as most of the cortisol is bound to Cortisol Binding Globulin (CBG), and to some degree also to albumin. The free fraction is
not commonly measured with methods used in clinical practice, and requires
ultrafiltration of samples or equilibrium dialysis. To handle this problem a
number of mathematical models are used to estimate the free serum cortisol
fraction [24; 32]. Attempts have recently been made to measure the interstitial concentration of cortisol, but there is currently no intellectual framework
for interpretation of those data.
The cortisol concentration in saliva correlates well with the free concentration in plasma or serum and has frequently been used as a proxy for these
measurements.
Chromogranin A
The concentration of chromogranin A (CgA) in plasma (P-CgA) is a biomarker of stress and sympathetic overactivity [26]. CgA is a glycoprotein/prohormone which is co-secreted with epinephrine and norepinephrine
by chromaffin cells from the adrenal medulla and also together with other
hormones from the neuroendocrine system [131].
CgA is not only a biomarker. Both the parent molecule and peptides derived during its proteolysis, such as vasostatin, pancreastatin, catestatin, and
serpinins, have biological effects [51; 74]. For example, both CgA and
vasostatin-1 are important modulators of the endothelial barrier function
[74], while both vasostatin-1 and catestatin directly suppress myocardial
inotropy and lusitropy, exerting remarkable anti-adrenergic modulation [83],
while the serpinin peptides appear to act in an opposite, β-agonist-like manner [74]. A hypothesis is that, via its vasostatin-1 and catestatin domains, the
normal levels of circulating CgA may provide a homeostatic buffer function
against effects of an excessive stress response [51].
The concentration of CgA in plasma responds to large-scale perturbations
of the sympathetic nervous system, appears relatively insensitive to shortterm behavioral challenge, and seems to be an early marker of severity in
critically ill patients [148]. P-CgA responds to significant alterations in the
sympathetic nervous system, but is said to be relatively insensitive to acute
stress [29]. However, it has been observed that the concentration of CgA has
a close relation to the release of norepinephrine, which is why it can be seen
as a reflector of sympathetic activity [30].
It was recently shown that the concentration of CgA [148; 113], and of its
downstream product vasostatin-1[117], were strong and independent predic21
tors of mortality [148; 113] in patients with critical illness. However, the
integrated role of CgA in clinical stress reactions has not been elucidated.
Natriuretic peptides
Natriuretic peptides constitute a peptide family which, in addition to peripheral effects on the regulation of water balance, have receptors throughout the
CNS and constitute a neuromodulatory system with influence on emotional
behavior, for example anxiety and arousal. They are also involved in the
regulation of the HPA-axis and the autonomous nervous system [57; 141].
There are currently three structurally related hormones in this family that
are coded by separate genes. The first to be discovered was ANP, originally
named “atrial natriuretic peptide” [62], but later “A-type natriuretic peptide”,
followed by BNP, “brain natriuretic peptide” [114], renamed “B-type natriuretic peptide”. Years later the third member of the family, C-type natriuretic
peptide, CNP, was discovered [128]. They all utilize a common receptor
family with three members mediating their effect and / or their internalization and degradation [107]. In addition to their widespread distribution in the
vasculature, the adrenals and the kidney, there is abundant evidence that
natriuretic peptides and their receptors are widely distributed in the central
nervous system, suggesting possible roles in modulating physiological functions of the CNS [20].
The natriuretic peptides increase venous capacitance and promote a
natriuresis that reduces extracellular fluid volume. This is partly due to direct
effects on both glomerular and tubular functions of the kidney and partly on
suppression of the angiotensin–aldosterone axis [73] They also reduce sympathetic tone in the peripheral vasculature. This reduction is probably caused
by dampening of baroreceptors, by suppression of the release of
catecholamines from autonomic nerve endings, and especially by suppression of sympathetic outflow from the CNS [73]. CNP inhibits aldosterone
secretion, but it has little effect on arterial pressure or salt and water excretion [54].
ANP is mainly stored and released from granules in the atrial myocardium [34], while BNP is stored and released from granules in both the atria
and ventricles [80]. Less is known concerning CNP, but it is the most widely
expressed NP, with synthesis in the brain, chondrocytes and endothelial
cells. CNP is thought to act locally as a paracrine/autocrine regulator, since it
is cleared rapidly from the circulation and present at very low concentrations
in plasma [77]. In chronic heart failure ventricular synthesis is upregulated,
above all for BNP, which is why BNP is known as a ventricular hormone
[55; 76; 92]. ANP, BNP, and CNP are formed by enzymatic cleavage of a
prohormone to form similar amounts of the carboxy-terminal biologically
active peptides and amino-terminal biologically inactive fragments [47; 80;
77]
22
Higher concentration of the A-type natriuretic peptide (ANP) than in controls has been observed in burn patients, but the reason for the increased
level is unclear [97]. The B-type Natriuretic peptide (BNP) has recently been
extensively investigated as a biomarker for a failing ventricular myocardium,
where it is primarily synthesized [80]. Here, gene expression of the BNP
prohormone is rapidly increased during periods of ventricular wall stretch.
The concentration in plasma is therefore considered to reflect volume load
on the heart, and is used in diagnosing heart failure. The BNP molecules
activate surface receptors, the activation of which results in a decreased cardiac pre- as well as after-load by several mechanisms including that of a
reduced sympathetic tone.
In ICU settings and in chronic inflammation, however, data suggest that
the concentration of BNP is also affected by non-heart-related mechanisms.
BNP concentrations have been suggested as markers of hydration state in
patients with severe burns and predictors of outcome in critically ill patients,
but results are contradictory.
Effects of long-standing stress
Severe stress affects the structure and function of the nervous system.
Chronic stress in animal models causes atrophy of neurons in the hippocampus and prefrontal cortex, brain regions involved in memory, selective attention, and executive function, and causes hypertrophy of neurons in the
amygdala, a brain region involved in fear and anxiety as well as aggression
[85]. Several studies, for example [16], also correlate stress with atrophy of
the hippocampus in man, due at least partly to an increased release of glucocorticoids via glutamatergic toxic effects [70]. There are also receptors for
glucocorticoids in the hippocampus [44]. It seems that such an effect of glucocorticoids on the hippocampus is reversible [126]. To complicate this issue, recent data have made previous studies difficult to interpret as it seems
that the pre-exposure size of the hippocampus is actually related to the susceptibility to stress [46]. The hippocampus plays a role in shutting off the
HPA stress response, and damage to or atrophy of the hippocampus impairs
the shut off and leads to a more prolonged HPA response to psychological
stressors [52].
Stress also has an impact on other cortical and subcortical brain structures
[78]. Finally, factors other than glucocorticoids also play a role in the impact
of stress on the CNS [84].
Sleep deprivation produces an allostatic overload that can have deleterious consequences. Sleep restriction to four hours of sleep per night increases
blood pressure, decreases parasympathetic tone, increases evening cortisol
and insulin levels, and promotes increased appetite, possibly through the
23
elevation of ghrelin, a pro-appetitive hormone, along with decreased levels
of leptin [72; 124; 125]
To summarize, chronic stress has negative consequences for learning,
memory, and decision-making, as well as increasing levels of anxiety and
aggression. The adult brain is a malleable organ and adapts structurally and
functionally to experiences that are stressful and potentially deleterious.
Some of these changes do not necessarily constitute “damage” but may nevertheless be long lasting.
Trauma, burn trauma, ICU care and the stress response
A severe burn trauma is one of the most stressful conditions that can befall
man. It affects all main integrating systems in the body and from an overall
perspective it can be viewed as an excellent model for a severe trauma as
such. The acute stress response after burn trauma involves catecholamines
[142] as well as cortisol [137] and glucagon [59]. The stress response, the
altered vascular dynamics, and pain are the three most important reasons
why severely burned persons are treated in Burn Intensive Care Units
(BICU).
Injured individuals exhibit widely differing premorbid characteristics that
affect their ability to combat stress. They have different psychiatric histories,
personalities and socioeconomic backgrounds, somatic health and fitness,
types and perceptions of care, and they differ concerning their adaptation
and outcome.
There are several factors to consider when analyzing why treatment in a
BICU is associated with considerable, often long-standing and iterative
stress. First, the condition that motivates ICU care is associated with a stress
response. Second, burn patients are commonly subjected to secondary insults
in the form of surgery and infections. Third, ICU patients often present with
disturbances in sleep [99], loss of a normal melatonin secretion pattern [96]
and a disruption in circadian rhythms of the HPA-axis [138]. Fourth, various
components of the care, for example repeated painful procedures [101]and
the expectation of pain from such procedures [105], have been suggested to
be contributory. In fact, frightening experiences during ICU care and length
of stay in the ICU have been related to late problems in the form of depression or PTSD [111; 110]. However, how the underlying illness as such and
the length of the ICU period affect the characteristics of the stress response
has not yet been determined.
Patients treated in intensive care units are often victims of the so-called
ICU syndrome, which is comprised in the definition of a delirious state [86].
Delirium during ICU care is actually quite common, and has been related to
a longer length of stay and an increased mortality. Well established causes
are infections and medication, but there are also reports of delirium in cases
24
of psychic stress and sleep deprivation [86]. ICU patients often suffer from a
poor quality of sleep [42], which is considered to be at least partly related to
an inappropriate pattern of release of melatonin [122], a disturbed circadian
rhythm of the HPA-axis, and the release of endogenous opiates [87]. During
burn ICU care more or less severe psychic symptoms, including sleep problems, psychoses, behavioral problems, anxiety and depression are common
[100]. A protracted course under a high stress load in critical care may lead
to the development of chronic critical illness (CCI) [25]. CCI is a relatively
common clinical entity characterized by prolonged ventilatory support, neuromuscular weakness, brain dysfunction, malnutrition, endocrinopathies and
symptom distress [94]. A major complication of critical illness, also thought
to be related to aspects of a sustained severe stress load, is ICU-acquired
weakness (ICUAW), which is probably a generalized progression of critical
illness polyneuropathy and myopathy with consequent progressive muscle
atrophy [33].
There are important characteristics of a burn injury that contrast with a
“true” fight or flight situation. Prolonged hormone and neurotransmitter elevation, absence of increased muscle work, and presence of massive tissue
injury are exacerbated by surgical debridement of burn wounds and skin
grafting procedures. Many questions remain regarding this prolonged activation, but it is clear that neuroendocrine changes regulate metabolic, cardiovascular and immune function, and ultimately wound healing, recovery and
survival. As critical care advances and intensive care unit mortality declines,
the number of survivors of critical illness is increasing. These patients frequently experience long-lasting complications, and it is therefore important
to understand why they appear and to implement evidence-based practices to
minimize them.
In spite of rapidly growing knowledge concerning components of the
stress response, there is currently no integrated description of the stress activation patterns in patients receiving burn intensive care, or of which endocrine pathways are more activated than others, or of the relationships between different pathways. Furthermore, treatment strategies for severe burns
have changed dramatically during the last few decades, which is why previously obtained fragmentary knowledge concerning hormonal changes after
burns needs to be revised.
Assessment of severity of illness in the ICU
The need to describe the severity of illness in patients in the ICU in a manner
that allows for comparisons based on large patient cohort data has motivated
the development of ICU-scoring systems. The models can be categorized
into general-purpose severity models and models of organ dysfunction. In
the first group, the Acute Physiology and Chronic Health Evaluation
25
(APACHE) [65], the Mortality Prediction Model (MPM) [71], and the Simplified Acute Physiology Score (SAPS) [69] have become the most well
accepted, further developed and widely used models. The most important
systems in the second group are the Sequential Organ Failure Assessment
(SOFA) [145], the Multiple Organ Dysfunction Score (MODS) [81] and the
Logistic Organ Dysfunction System (LODS) [68].
The first group of scores predicts mortality based on physiological variables collected in the first 24 h of ICU stay, ignoring the fact that morbidity
and mortality are very closely correlated, and that changes in the initial parameters may influence patient outcome [60]. The fundamental premise of
these systems is that clinical variables at or near the time of ICU admission
are associated with the risk of hospital mortality [132].
The second group, the organ dysfunction scores, assesses severity of illness over time as organ systems show signs of worsening function or failure
[143], and these scores are also used for prediction of mortality. It was therefore possible to use these models as a measure of outcome in this thesis.
However, during the development of these scoring models burns were often
excluded [64; 63].
The Sepsis-related Organ Failure Assessment score was originally designed to quantitatively describe organ dysfunction over time and to evaluate
morbidity in septic patients [145]. It was later understood that the score
could also be applied in non-septic patients, which is why the acronym "SOFA" now refers instead to Sequential Organ Failure Assessment [144]. The
SOFA score is the sum of subscores for the following six organ systems:
respiratory, circulatory, renal, hematology, hepatic and central nervous systems, depending on the level of dysfunction (rated as 1 to 4 points) for each.
The SOFA score has also been used to predict mortality, although it was not
originally developed for this function. The prognostic performance of the
SOFA score used in various models for predicting mortality in adult patients
in medical and/or surgical ICUs was recently systematically reviewed [89].
There are few studies on the use of SOFA in burns. Pavoni et al reported
that survivors had lower SOFA scores on admission than non-survivors
[102]. Palmieri et al found that the maximum SOFA score was an independent risk factor for mortality [98]. In an assessment of 439 burn patients,
Lorente et al [75] used SOFA at day 4 as a measure of late organ dysfunction, as previous studies suggested that dysfunction developing soon after
trauma reflects, to a greater extent, reversible derangement in organ function
induced by the inciting event or incomplete resuscitation, while later measurement of organ function would better define multiple organ failure and
prognosis [90]. They observed that the SOFA scores at days 1 and 4 were
independent predictors of mortality.
26
Current investigation
Context
This study is part of a broad approach to assess the effect of a burn injury on
the organism. The research group has previously produced an array of papers
focusing on the psychosocial outcome after a severe burn injury, including
studies on individual factors that affect the outcome. These studies have
pointed to the fact that many individuals suffer from cognitive or other late
psychiatric sequels after severe burns.
The overall concept is that a multitude of factors interact in defining the
final integrated outcome in the long term, including preinjury individual
factors, the type and extent of burn trauma, and the sometimes immense
stress on the organism during the long period of intensive care, and also
events during the long rehabilitation phase (Figure 1).
Repeated stress and pain during care Environmental factors
Cognition Psychiatric morbidity
Personality
Physical health
Interaction with family, school, work and other structures
Recovery/
Adaptation
Burn
Genetics
Individual
Injury
Acute care
Rehabilitation phase
Figure 1. The interactive mechanisms defining the final outcome after a severe
burn.
Based on recent literature describing similar long-term consequences of other types of protracted life-threatening states, the general research questions
concern possible causative relations between the extent of physical stress
during acute care and late neurofunctional sequels. In order to approach this
hypothesis in a serious manner, more detailed knowledge is needed concerning components of the physiological stress response during acute care.
27
Aims
The main aim of this thesis is to elucidate, describe and quantify some aspects of the stress response during the acute intensive care phase for severe
burns by measuring hormonal and neuroendocrine patterns, and to elicit how
those aspects are related to organ function in the short term. This includes an
assessment of whether there are markers for the severity of stress that are
better than conventional descriptors of the severity of a burn in predicting
failing organ function.
The overall aim of this thesis can be summed up in four points:




28
to investigate the release pattern of CgA in acute care of severe burns
and to relate this to organ function
to investigate the release pattern of BNP in acute care of severe burns by
measuring its co-released propeptide NT-proBNP, and to relate this to
water load, inflammatory response, and organ function
to investigate the relationships between circulating concentrations of
NT-proANP and NT-proBNP in an attempt to reveal different mechanisms in their release and turn-over
to investigate the diurnal variability of cortisol in severe burns and to
assess mechanisms affecting this variability
Material and Methods
Patients
The patients reported on in this thesis were recruited consecutively during
2003 through 2009 from the ICU at The Burn Center at Uppsala University
Hospital, which is one of two national centers responsible for the in-hospital
care of severe burn victims in Sweden, which has a population of 9.3 million. The Uppsala Burn Center is a referral center for patients primarily from
the northern and middle parts of Sweden.
Inclusion criteria were i) age between 18 and 60 years; ii) burn injury exceeding 10 % TBSA; iii) admission to the Burn Center within 48 h after
injury; iv) without ongoing steroid treatment; v) no ongoing steroid intake
and vi) no known neuroendocrine tumor. Before enrollment, information
about the study was given to the patient, or in sedated patients to a next of
kin, by a research nurse who also secured formal approval for participation.
Fifty-two patients fulfilled the inclusion criteria. Only one of these declined participation, resulting in the inclusion of 51 patients. In paper II and
paper III sufficient data were not obtained for one of the male subjects, resulting in the inclusion of 50 patients. In paper IV 2 male subjects were excluded for the same reason, resulting in the inclusion of 49 patients. Table 1
shows the study population.
Procedure
The Uppsala and Linköping Burn Centers together treat all severe burn injuries in Sweden, and are now also responsible for longitudinal
multiprofessional follow-up. This is a new situation that will ensure population based recruitment for interdisciplinary studies. Since 2000, all severely
burned patients admitted to the Uppsala University Hospital who have given
their consent have been enrolled in the Uppsala Burn Center Research Program
The investigations of these patients include many psychiatric evaluations
and tests outside the scope of this thesis, and also include an assessment of
the physical stress load during the ICU period and during recovery.
29
Table 1. Characteristics of the individuals included in the studies. Data are given as
integers or median and range.
Included
Did not want to participate
Insufficient data
Study population
Gender (female/male)
Mean age (years)
TBSA2
TBSA full thickness2
Length of stay (days)
Died during stay
Cause of injury
Fire3
Scald
Electrical
Chemical
Study 1
52
-1
-12
39
Study 2
52
-1
-1
50
Study 3
52
-1
-1
50
Study 4
52
-1
-2
49
12/27
45 (20-82)
31 (10-96)
13 (0-95)
21 (4-183)
4
15/35
41 (19-60)
31 (10-96)
14 (0-95)
20 (4-230)
4
15/35
41 (19-60)
31 (10-96)
14 (0-95)
20 (4-230)
4
15/34
41 (19-60)
31 (10-96)
32
3
2
2
41
4
3
2
41
4
3
2
21 (4-230)
4
40
4
3
2
1
Data are given as integers or median and range, 2Percent, 3Including explosion and
contact.
Blood samples were taken four times daily at 6 am, 12 pm, 6 pm, and 12 am
on days 1, 2, 3, 4, 5, 7, 10, and 14 of ICU care, and then once a week until
discharge. For some analyses samples were collected only at 6 am and 6 pm,
or at 6 am only. The samples were sent to the certified Clinical Chemistry
Laboratory (CCL) at the University Hospital, where they were analyzed
immediately and also stored frozen in aliquots for later analysis. Arterial
blood gas analysis was also performed at all sampling times.
Data were later imported from the CCL for scrutiny and validation and
subsequently included in a relational database (Microsoft® Access). This
database also includes demographic data, summaries of chart text, daily SOFA scores, and other variables such as vital parameters, arterial blood gas
measurements, ongoing septic processes, concurrent surgical procedures,
TBSA %, length of stay and mortality. Clinical information required for
intensive care scoring and other important information was documented as
part of a structured ICU-routine and later included into the database. Building, expanding, restructuring and validating this database has been a prioritized part of the work throughout the writing of this thesis. Although the
number of included patients is large with respect to measuring molecular
30
biomarkers in burn patients, it still is a fairly small number with respect to
statistical modeling. Therefore, great care has been taken to maximize the
quality of our study database.
Measurements
Samples of serum (S-) and EDTA-plasma (P-) were obtained at predetermined sampling times, transported to the CCL, analyzed and then stored
frozen at –70°C in aliquots for future reference.
P-CgA was determined using a commercial radioimmunoassay
(Eurodiagnostica, Malmö, Sweden).
P-NT-proBNP was analyzed on a Cobas E601 instrument (Roche Diagnostics, Basel, Switzerland). The sample was allowed to react with a
biotinylated monoclonal NTproBNP-specific antibody and a rutheniumcomplex labeled monoclonal NTproBNP-specific antibody. The complexes
were bound to streptavidin coated micro particles and the amount of bound
ruthenium complex was analyzed by chemoluminescence emission. The total
imprecision was <4%. The results were converted to the same unit as S-NTproANP (pmol/L) using a molecular weight of 8.5 kDa.
S-NT-pro-ANP was measured in an in-house ELISA with light stimulated
fluorescence detection (DELFIA) [39]. The assay was of non-competitive
design and had a total imprecision of <12%.
S-Cortisol was measured on a Cobas E601 instrument. The free cortisol
concentration was estimated using the equation of Coolens et al [24] and
based on the concept that the concentration of cortisol binding globulin decreased in parallel with the decrease in albumin concentration, and a normal
concentration of CBG of 625 nM [32].
C-reactive protein in plasma (P-CRP) was used as a measure of physiological response to trauma. B-platelets, P-creatinine, and S-bilirubin were
analyzed for the purpose of SOFA-scoring. The quality of all analyses was
continuously controlled according to certification procedures.
Weight gain was used as a measure of accumulated edema, and weight
loss after maximum weight was reached was used as a measure of net edema
mobilized back into the circulation. SOFA scores were calculated according
to the Swedish Intensive Care Registry (SIR) guidelines [1].
Clinical routine
The Parkland formula served as a resuscitative strategy during the first 24
post burn hours. Hourly diuresis of 0.5 ml/kg/h was aimed for. Patients were
artificially ventilated upon arrival in the unit until no longer necessary. Ventilator support was guided by the “open lung concept” [2]. Routine burn
31
treatment consisted of early excision and grafting in all cases. Early enteral
nutrition was based on calculated caloric needs. Regular wound revisions
were done under general anesthesia using standardized dressings.
Statistical analyses
A major theme in this thesis is exploration of various neuroendocrine peptide
concentrations at certain time points, as well as changes over time. These
have then been related to each other as well as to more thoroughly studied
parameters in intensive care such as age, TBSA % burned, organ dysfunction
score, length of stay, mortality, and well-known blood work parameters such
as CRP. Hence, appropriate tools have mainly been various regression techniques.
Techniques
The predominating techniques were multiple linear and multiple logistic
regressions. A linear mixed model procedure (LMM), which accounts for the
hierarchical nature of the data, was also an important tool.
For correlation analysis Pearson and Spearman tests were utilized. Parametric methods were used whenever possible. Variables significantly
skewed judged from the Kolmogorov-Smirnov test were logarithmically
transformed to obtain normality. The Chi-square test was used for categorical variables, and the Mann Whitney U-test was used for ordinal and continuous variables in paper I. The paired-samples t-test with Bonferroni correction was performed for each day to test for diurnal variations in paper II.
All calculations were performed using the IBM SPSS Software Statistics,
versions 19 or 21. All analyses were defined a priori.
Data presentation
When the parameter times are presented in relation to time of admission to
the Burn Center, they refer to actual assessment times, which were the same
for all patients. Day zero was then defined as beginning the first time after
admission that the clock showed 6 am. When the parameter time is presented
in relation to time of injury, the closest match with respect to time after injury was used. Area under the curve (AUC) calculations for concentration vs.
time curves was based on linear interpolation.
Dichotomization of SOFA scores was achieved by defining high SOFA as
4 or more, which is stricter than in some studies but was chosen to split the
cohort as equally as possible; 44 % were in the high SOFA group. Receiver
Operator Curve (ROC) analysis based on dichotomized models was used for
evaluating overall adequacy of the risk predictions.
32
Missing data were replaced utilizing a last observation carried forward strategy (LOCF) when appropriate, but never when analyzing changes over time,
i.e. regarding cortisol rhythmicity or CV calculations. CV was calculated as
SD/mean.
Directed Acyclic Graphs
In a non-experimental setting, the goal of covariate selection is to remove
confounding by only including appropriate covariates in equation modeling.
This was done in a traditional way in the first three papers, i.e. through clinical reasoning combined with statistical selection through simple regressions.
In paper IV a method for covariate selection predominantly used in epidemiological research was introduced, a directed acyclic graph (DAG) model.
This approach is based on counterfactual theory for defining causal effects,
and has been validated as efficient in selecting confounders [139]. Two good
reasons for using DAGs are that the procedure is more transparent to the
reader than other alternatives and is based entirely on biology and clinical
reasoning, and also that through reductive logic a minimal sufficient adjustment set for estimating the direct effect between a proposed exposure and
outcome is found [123]. Covariates are selected in view of their internecine
biological relationships, and are not treated as monolithic entities that have
to pass a mechanistic statistical test.
Ethics
The studies were approved by the Uppsala University Ethics Committee, and
the investigations were performed according to the Declaration of Helsinki.
33
Results
For detailed results the reader may turn to the underlying publications.
Paper I
The aim was to assess characteristics of the release of CgA after burn injury
and explore relations to organ dysfunction one week after injury.
There were considerable differences between different patients with respect to the secretion pattern over time. Two different secretion patterns
could be discerned based on variability between measurements. About two
thirds of the patients had a low variability in P-CgA concentration during the
first 7 days, and the remaining third of the patients clearly had more variability over time. A high variability group, defined as the greatest difference
between samples being more 6 nmol/L, had a greater overall increase in PCgA during the first 7 days than a low variability group. These patients were
also older, had larger deep burns and more frequent surgery during the first 7
days. They also exhibited a worse multiple organ function at day 7 (SOFA
score 5.6±3.4 vs. 3.0±2.5; p = 0.007).
All four different measures of P-CgA used for predictions correlated with
SOFA scores at day 7. In univariate regression models (Table 2), age, TBSA
% burned and three of the different measures of CgA were found to be significant predictors of SOFA at day 7, while the fourth, P-CgA-AUC 1 to 7
days, was not.
In subsequent multiple regressions, age and TBSA% burned significantly
predicted SOFA at day 7 with an adjusted R2 of 0.27 (Table 3).
Adding P-CgA in the models improved prediction. The addition of the 24
hours after injury value, the clinically most practical measure of P-CgA, thus
resulted in a prediction equation with an adjusted R2 of 0.34. The addition of
the mean or maximum P-CgA value resulted in similar predictions.
To better assess the relation between sympathetic stress measured by PCgA and clinically relevant multiple organ dysfunction, the day 7 SOFA
value was dichotomized into one group with high scores and one group with
low scores in a way that as nearly as possible split the study population in
half, which was done by defining low SOFA as less than 4 and high SOFA
as 4 or more. Receiver operator curves showed that TBSA% burned and age
weakly predicted having a high SOFA score respectively.
34
Table 2. Univariate regressions with age, TBSA burned, and the different measures
of P-CgA as independent variables and SOFA scores at day 7 as the dependent variable. (1logarithmically transformed data)
Covariates
beta
p-value
adjusted R2
Age
0.27
0.10
0.05
TBSA partial thickness burn1
TBSA full thickness burn1
TBSA burned1
0.03
0.31
0.42
0.86
0.07
0.009
-0.03
0.07
0.17
P-CgA at 24 hours1
P-CgA maximum value up to day 71
P-CgA mean value up to day 71
P-CgA AUC 1 to 7 days1
0.45
0.47
0.42
0.33
0.005
0.003
0.008
0.11
0.18
0.20
0.16
0.07
Table 3. Multiple regressions with age, TBSA burned, and different measures of PCgA as independent variables and SOFA scores at day 7 as the dependent variable.
Covariates
beta p-value adjusted R2 p-value
Age
0.38
0.01
TBSA burned1
0.50
0.001
0.27
0.001
Age
TBSA burned1
P-CGA at 24 hours1
Age
TBSA burned1
P-CGA mean value to day 71
Age
TBSA burned1
P-CgA maximum value to day 71
0.25
0.43
0.44
0.23
0.47
0.35
0.22
0.41
0.34
0.09
0.004
0.004
0.34
0.001
0.34
0.001
0.33
0.001
0.14
0.002
0.026
0.17
0.006
0.03
Age
TBSA burned1
0.26
0.18
P-CgA AUC 1 to 7 days1
1
logarithmically transformed data; ns = not significant
ns
35
Each of the four CgA related variables were better predictors, with AUCs
under the ROC curve varying between 0.75 and 0.80. While TBSA % and
age together gave a value of 0.81, the best prediction was achieved with
those two in addition to CgA at 24 hours, with a value of 0.90.
Paper II
The P-NT-proBNP showed large day to day and between patient variations
during the first 14 days after injury. The general pattern was that of a gradual
increase for a few days and then a certain decline after reaching a maximum
value on day 5 (5; 4-8) (Figure 2).
Figure 2. Individual concentration vs. time curves for NT-proBNP. Concentration is
expressed as % of maximum value for each patient and the curves are smoothed to
visualize individual patterns.
The peak concentration varied greatly between individuals and was clearly
elevated in all cases compared to established cut-offs for congestive heart
failure [56].
The maximum weight occurred on day 2 (median 2; 1-2) and timing correlated negatively with TBSA% burned, i.e. those with larger burns reached
their maximum weight earlier. On the contrary, the time for maximum PNT-proBNP correlated positively with TBSA%, i.e. those with larger burns
reached their maximum value later. Furthermore, maximum P-NT-proBNP
occurred later in patients with greater total weight gain, in patients who had
lost more weight, i.e. mobilized more edema, at their maximum concentration, and in patients with higher maximum concentrations. TBSA% was
correlated with maximum weight gain.
36
Maximum P-NT-proBNP correlated with the total amount of resuscitation
fluid administered during the first 24 hours and with the amount of edema at
maximum weight gain, but not with the weight gain at the time for maximum P-NT-proBNP. Nor did P-NT-proBNP at the time for maximum
weight gain correlate with the value for maximum weight gain.
To discern whether the extent of edema mobilization had an immediate
impact on P-NT-proBNP, weight loss for every 24-hour period was tested
against morning P-NT-proBNP at the end of the same period. The only significant correlation was on day 2.
Similar to P-NT-proBNP, the P-CRP value showed a peak formation.
Maximum P-CRP occurred on day 5 (median 5; 3-7). Time for peak P-CRP
correlated with time for maximum P-NT-proBNP, i.e. these parameters
showed covariation within individuals. Time for peak P-CRP correlated with
TBSA%, i.e. larger burns had a later P-CRP peak. Furthermore, daily morning P-NT-proBNP and P-CRP correlated significantly on day 0, and on day 2
until and including day 6.
Organ dysfunction measured as SOFA deteriorated the first few days with
the highest SOFA score on day 3 (median 3; 2-4), after which it reached a
plateau with a very slow decline (Figure 6). Time for maximum SOFA correlated with TBSA, i.e. maximum SOFA was reached later in larger burns.
P-NT-proBNP correlated significantly with concomitant SOFA scores
from day 3 until and including day 11, and on day 14.
Maximum P-NT-proBNP measured within the first 14 days after burn injury correlated with the SOFA score on day 14 after injury and with length
of stay, and was also significantly related to mortality (t-test; p<0.001).
In linear regressions together with age at injury and TBSA, P-NT-proBNP
assessed on days 3 to 8 was an independent predictor for every SOFA score
measured one or more days later up to day 14 (Table 4). TBSA and age at
injury assessed the first two days were independent predictors of later SOFA
scores, after which P-NT-proBNP and TBSA both contributed to prediction
of subsequently assessed SOFA scores. Age appeared to be an independent
predictor early after injury and for short-term prediction as compared to the
other two predictors.
Paper III
Both S-NT-proANP and P-NT-proBNP showed a time dependent pattern
with an increase followed by a plateau phase (Figure 3 top). Variability over
time was, however, much less for S-NT-proANP than for P-NT-proBNP.
The mean inter-individual CV, calculated over all 14 days, was 81 %; SD 14
% for S-NT-proANP and 1572 %; SD 329 % for P-NT-proBNP (p< 0.001),
and the corresponding mean intra-individual CV was 44 %; SD 19 % vs.
651%; SD 227 % (p< 0.001).
37
Table 4. Regressions with SOFA on different days as dependent variables and PNT-proBNP assessed at different days, TBSA% and age at injury as independent
variables.1 Only significant p-values are displayed.
SOFA Day
Day
6
7
8
9
10
11
12
13
14
1 BNP
TBSA 0.006 0.002 0.002 0.001 0.001 0.001 0.002 0.002 0.009
Age 0.04
2 BNP
TBSA 0.04
0.03
Age
0.006
0.04
0.01
0.05
0.005 0.002
0.03
3 BNP 0.004
TBSA 0.04
Age
0.03
0.01
0.006
0.003
0.01
0.009
0.007
0.04
0.000
0.002
0.000
0.001
0.000
0.004
0.003 0.005
0.003 0.02
4 BNP 0.008
TBSA 0.03
0.02
Age
0.010
0.005
0.05
0.007
0.01
0.05
0.02
0.007
0.03
0.002
0.002
0.004
0.001
0.001
0.004
0.006 0.02
0.004 0.02
5 BNP 0.001
TBSA 0.04
0.03
Age
0.002
0.006
0.002
0.01
0.05
0.002
0.007
0.04
0.001
0.002
0.001
0.001
0.000
0.005
0.001 0.003
0.003 0.02
6 BNP 0.002
TBSA
Age
0.05
0.003
0.01
0.007
0.02
0.002
0.02
0.002
0.005
0.002
0.003
0.001
0.01
0.008 0.008
0.007 0.03
7 BNP
TBSA
Age
0.001
0.001
0.002
0.05
0.000
0.03
0.000
0.001
0.01
0.001
0.05
0.005 0.008
0.02
0.001
0.001
0.004
0.003
0.014
8 BNP
0.000 0.000 0.000 0.000 0.000 0.000 0.001
TBSA
0.03
0.03
Ag e
1
Enter model; p-values for independent variables are shown. Age = Age at injury;
BNP = P-NT-proBNP
P-NT-proBNP, but not S-NT-proANP, was also related to the size of the
burn; r=0.40, p<0.01 for P-NT-proBNP and r=0.23, p=0.11 for S-NTproANP, and reached its highest concentrations earlier than S-NT-proANP.
(Figure 3 bottom).
38
Figure 3. S-NT-proANP and P-NT-proBNP expressed as pmol/L during the 14 days
of Burn Intensive Care. Top: All patients; Bottom left: Patients with a TBSA <20%
(n= 13); Bottom right: TBSA≥20 %. (n=37). Mean ± SEM. No values are calculated
for day 12 due to the low number of samples.
The absolute values for the two analytes correlated only moderately well (r =
0.38 – 0.67 for different days; p = 0.012 to <0.001). The corresponding dayto-day changes also correlated moderately well. This suggested that the two
analytes were controlled and expressed differently.
To elucidate these differences more clearly the quotient between S-NTproANP and P-NT-proBNP was plotted. This revealed two essential features. First, on a group level there was a temporary decrease in the S-NTproANP/P-NT-proBNP ratio after 3 to 7 days, most pronounced at days 4
and 5, and thereafter a return to the initial level (Figure 4). Second, there was
considerable inter- and intra-individual variability in the ratio, and also substantial day-to-day fluctuations (Figure 5). The fluctuations of P-NTproBNP, assessed as the day-to-day change, only correlated with those of
CRP at days 4 and 5 (p=0.01; r = 0.38 both days), and not at all with those of
S-NT-proANP.
39
Figure 4. Natriuretic peptide (NP) ratio, calculated as S-NT-proANP (pmol/L) / PNT-proBNP (pmol/L), and P-CRP (mg/L) during the 14 days of Burn Intensive
Care. Mean ± SEM.
Figure 5. Natriuretic peptide (NP) ratio, calculated as S-NT-proANP (pmol/L) / PNT-proBNP (pmol/L) for each patient the first 14 days after injury.
As differences in the relation to clinical variables might shed light on possible differences in regulation of the two NPs, simple regressions were made
for the different days in the BICU. This revealed differences between S-NTproANP and P-NT-proBNP. The most consistent observations were that the
40
age of the individual was a predictor of both NPs measured during the entire
course of the illness. Furthermore, P-CRP only predicted S-NT-proANP at
day 2, but it predicted P-NT-proBNP from day 2 up to and including day 6.
Cardiovascular SOFA scores predicted S-NT-proANP at days 3 to 9 and
days 13 and 14, and P-NT-proBNP at days 2 to 9. Respiratory SOFA scores
also predicted both NPs, although with less statistical strength and only at 4
of the 14 days of observation for each of them. Finally, Renal SOFA scores
predicted both NPs; P-NT-proBNP from day 5 and thereafter, and S-NTproANP from day 7 and thereafter. A somewhat unexpected observation was
that the extent of burn injury described as TBSA burned only predicted PNT-proBNP at two time periods, days 7 and 8. Weight change the last 24
hours was only related to P-NT-proBNP at day 2 and to S-NT-proANP at
day 14, and current excess weight was not related to P-NT-proBNP at any
time in this analysis.
There was no difference in either NP between genders (not shown).
Paper IV
Although immense variations in S-cortisol between individual patients were
immediately obvious, a number of initial statistical approaches suggested
that the free cortisol concentration was related to the size of the burn. First,
in a linear regression approach, the daily mean free cortisol concentration
was significantly related to burn size for all days except for days 2 and 4
(data not shown). Furthermore, when utilizing values from all study days,
burn size correlated with mean free cortisol (r2=0.31, p<0.001), as well as
maximum free cortisol (r2=0.25, p<0.001).
As seen in Figure 6, there were very large differences in cortisol concentration patterns on day 1, which corresponded to a very large variability in
time since injury until patients arrived at the BICU, from two to 36 hours
with a median of eight hours, and until time for the first morning value, from
five to 56 hours, with a median of 24 hours (Table 1). Therefore, some patients had their first morning concentration assessed very early after injury,
and during the resuscitation phase, while others had it long thereafter. Cortisol dynamics during the first 24 hours in the BICU were therefore considered too unreliable in an assessment of disturbances in circadian rhythm, and
the resuscitation phase was deliberately excluded in all patients, and detailed
assessments were made from day 2 and onwards.
The free cortisol concentrations behaved differently in patients with burns
larger than 20 % compared to those with burns smaller than 20 %. It was
initially very high in those with large burns, after which a slight decline occurred, and both burn size groups had similar concentrations over the forthcoming days. Subsequently the concentration declined in those with small
burns, while it remained high in those with larger burns (Figure 6).
41
Figure 6. Free cortisol concentration assessed four times daily in BICU and expressed in nmol/L. Smoothened curves. Insert shows times for sampling. Mean ±
SEM. Solid line, large burns, and broken line, small burns.
When constructing slope variables it was clear that the circadian zenith for
free cortisol frequently occurred later than would be expected in a healthy
population. Median time for daily peak cortisol was 12pm, rather than the
expected 6am. Circadian zenith in different patients occurred at all four assessment times, but distribution was heavily skewed towards early and late
morning. The time of circadian zenith was not explained by burn size group,
ongoing ventilator care, or surgery the preceding day (data not shown). It
was, however, related to the current SOFA score (p=0.035).
A DAG was performed to identify a set of confounding variables with a
potential impact on cortisol slope (Figure 7). A minimal sufficient adjustment set for estimating the direct effect of burn size group on cortisol slope
was found to include age, P-NT-proBNP, P-CgA, and SOFA score. Thus
these variables were included as covariates in subsequent analyses. Multilevel modeling revealed that burn size explained cortisol slope. Patients with
large burns had significantly flatter slopes than patients with small burns
(p=0.033; Table 6). Adjustments for age and gender and for covariates from
the DAG excluding SOFA score did not diminish the effect (p=0.028 and
0.030, respectively; Table 6). After adjustments for all covariates from the
DAG, including the SOFA score, there was no independent effect of burn
size group. Rather, the only significant covariate in that model was the SOFA score itself (Table 6).
Furthermore, burn size also explained the cortisol slope after adjustment
for ventilator treatment. Here, ventilator treatment had an independent effect,
both together with burn size (Table 6), and also alone (p< 0.013; data not
42
Figure 7. The DAG obtained in the DAGitty software as basis for the multilevel
statistical analysis.
shown). Surgery the preceding day did not explain the cortisol slope (data
not shown).
Thereafter an analysis of whether the difference in slope was related to
specific differences at any defined time point in the day was made. This was
done using free cortisol concentration measurements at the four assessment
time points as dependent variables. Differences between large and small
burns were only noticed at 6pm (Table 6), while there was no significant
difference in free S-cortisol between burn size groups at 6am, 12pm or 12am
(data not shown). This suggests that the burn-size-dependent flattening of the
slope was due primarily to a slower decline in free cortisol from morning to
evening. When adjusting for all covariates from the DAG, including SOFA
score, slope at 6pm was explained by burn size group as well as by P-CgA
and SOFA score (Table 6).
Finally, two secondary outcome measures were assessed, the coefficient
of variability (CV) in free cortisol concentration as a measure of variability
over the day, and AUC as a measure of the magnitude of cortisol release
each day. Burn size group explained daily CV for free cortisol after adjusting
for all covariates from the DAG (Table 6). In that model, SOFA score was
also significantly related to the CV. Similarly, burn size group explained
AUC after adjustment according to the DAG (Table 6). In addition, in the
adjusted model P-CgA and SOFA score independently explained AUC.
43
0.02
0.02
0.051
2.479
0.34
0.34
0.051
0.044
2.479
2.513
0.003
0.002
0.002
0.002
0.002
-0.009
-0.009
-0.009
-0.009
-0.010
SEM
Mean
44
AUC for free cortisol concentration3
No adjustments
31.7
0.7
Adjusted as DAG1
32.6
0.5
- in that model: SOFA score
- in that model: P-CgA
1
age, P-NT-proBNP, P-CgA, and SOFA score, 2 values are in Log (nmol/L),
3
values are in Log (nmol/L) * h.
Coefficient of variation for free cortisol concentration
No adjustments
Adjusted as DAG1
- in that model: SOFA score
Log free cortisol concentration at 6pm2
No adjustments
Adjusted as DAG1
- in that model: Burn size group
- in that model: P-CgA
- in that model: SOFA score
Adjusted for ventilator treatment
-in that model: ventilator treatment
Outcome and significant covariates
Free cortisol slope
No adjustments
Adjusted by age and gender
Adjusted as DAG1 without SOFA
Adjusted as DAG1
- in that model: SOFA score
27.8
29.7
0.46
0.46
2.620
2.620
2.618
-0.019
-0.017
-0.017
-0.017
-0.014
Mean
1.2
0.9
0.04
0.04
0.030
0.030
0.024
0.003
0.003
0.003
0.003
0.003
SEM
Burn size group
TBSA>20 %
TBSA≤ 20 %
SEM
3.94
2.81
0.77
0.35
-0.12
-0.12
-0.02
0.141
0.114
0.015
0.019
0.141
0.008
0.009
0.008
0.008
0.009
0.006
0.001
1.40
1.06
0.18
0.12
0.05
0.05
0.01
0.059
0.051
0.005
0.007
0.059
0.003
0.004
0.004
0.004
0.004
0.004
0.001
Fixed effect
Mean
Table 6. Multilevel analysis of the effect on cortisol related measures for days 2 to 7 after burn in the 49 patients.
0.008
0.013
0.000
0.005
0.013
0.012
0.031
0.021
0.047
0.002
0.009
0.021
0.017
0.013
0.033
0.028
0.030
0.147
0.032
p
Discussion
The primary aim of the present thesis was to acquire more knowledge concerning the neuroendocrine stress response after burn injury. It must be kept
in mind that this response is regulated by a system with many interlaced
parts that work together in a non-linear fashion. Ideally, therefore, network
based approaches with interventions with respect to important variables
should be the best way to elucidate relationships between different interlaced
parts. When a patient with a serious burn injury is admitted to the BICU,
however, opportunities for controlled randomized interventions are small, as
every possible measure is focused on optimizing the physiologic variables
known to influence survival. Therefore this thesis is strictly based on observational studies – with a plethora of interventions that have to be adjusted
for. Furthermore, burn injuries are relatively rare in Sweden, which limits
the number of study subjects. Consequently, results must be interpreted
humbly and carefully.
Specific discussion
Chromogranin A
Burn care is demanding in terms of resources and time, and the inflow of
patients cannot be controlled or planned. The course of care is often long,
with different phases that are influenced by varying interventions and complications, and it is therefore difficult to predict. Tools for predicting different outcome variables such as LOS in the ICU, LOS in the hospital, and
mortality are important when optimizing care for patients. Currently, the
gold standard for prediction in burn care is based on TBSA and age. Prediction models can be marginally improved with the addition of other currently
available variables, but at the price of complexity, and a model is good only
if it is used.
Paper I was based on the concept that many aspects of care, and the effects of complications that arise during care, add to the burden of the inciting
event, and the net result of all these stressors in combination with the patient’s ability to handle them determines the outcome. The hypothesis in
paper I was that CgA may be a biomarker for such aggregated stress after
45
burn injury. Since CgA is synthesized and co-released with catecholamines
in neuroendocrine tissue [30], it is believed that it can serve as an integrated
measure of sympathetic activation. Simply measuring S-catecholamines
would introduce new problems, as large exogenous amounts of amines are
irregularly administered as part of burn intensive care. Also, adrenergic betareceptor blockers are commonly used as part of the ICU routine, which could
affect the peripheral concentration of amines. However, it has been observed
that exogenous administration of adrenergic beta-receptor blockers does not
affect the P-CgA concentration [130].
Mortality, a crude and dichotomous measure of outcome, has decreased
considerably in hospitalized burn patients during the past few decades [19;
108]. Mortality in the present cohort was four of the 51 patients, which limits
statistical power. In this work, a decision was made to measure overall organ
dysfunction in terms of the SOFA score, and use this as a proxy measure.
The SOFA score was originally designed to quantitatively describe organ
dysfunction over time in patients with sepsis [143]. It was later understood
that the score could also be applied in non-septic patients [144]. The SOFA
score, which is the sum of sub-scores for six organ systems, has also been
used to predict mortality, although it was not originally developed for this
function. The prognostic performance of the SOFA score when used in various models for predicting mortality in adult patients in medical and/or surgical ICUs was recently systematically reviewed [89]. SOFA score on admission, or various models of combinations of sequential SOFA scores, were
confirmed to predict mortality in patients in general medical and/or surgical
ICUs.
A subgroup of patients in this study was classified as having a high variability in CgA concentrations. It was observed that this population was older,
had larger deep burns, more often underwent surgery and had higher SOFA
scores than the other patients. Although few studies have been conducted on
the intra-individual variability of P-CgA, the variability in the present study
is larger than previously reported in healthy individuals or in individuals not
treated in ICUs. For the sake of perspective it should be noted that even under intense to extreme acute sympathoadrenal stimulation, CgA levels do not
increase more than twofold [26; 35]. The large variability observed in the
present cohort must therefore be interpreted as intense and protracted
sympathoadrenal stimulation. The fact that CgA variability was positively
related to organ dysfunction, together with the other observations, indicates
that CgA is a valid reflector of stress activation in BICU populations. However, measuring variability is not practical in clinical settings.
The present work also supports the hypothesis that high P-CgA values
during the first week after a serious burn injury correlate positively with
SOFA scores one week after injury, and therefore can be used to predict
organ dysfunction. Further, it is known that organ dysfunction after one
week in the ICU constitutes a great risk that the patient will not leave the
46
hospital [136].These data are convincing, since not only a point measure 24
h after injury, but also the mean, maximum and integrated values of P-CgA
during the first 7 days correlated with the SOFA score at day 7. The data
support P-CgA as a stronger predictor of organ dysfunction than TBSA
burned, and that both are independent predictors of organ dysfunction. The
results clearly show that not only the extent of the burn injury, but also characteristics of the individual’s response to injury, define the risk for organ
dysfunction during acute intensive care. A similar approach has recently
obtained considerable support, as the serum protein pattern assessed by proteomic methodology was found to be an independent prognostic factor with
respect to survival in burned children [38].
Natriuretic peptides
A large burn injury is followed by changes in microvascular characteristics
with increased leakage of water, solutes and proteins from the blood to the
interstitium, which lead to hemoconcentration and hypovolemic shock.
Treatment is based on the conception of upholding acceptable circulatory
characteristics during the first 24 hours, during which most leakage to the
interstitium occurs. After that time period there is mobilization of the excess
edema that was formed during the first 24 hours.
The discovery of the natriuretic peptide system gave a rational explanation for the mode by which the central circulation can mediate control of
water homeostasis. These discoveries conveyed a picture of the heart as an
endocrine organ that releases natriuretic peptides from the myocardium
based on atrial and ventricular distension. In this thesis three key questions
concerning NPs have been addressed. First, what are their concentration
dynamics in response to burn trauma? Second, do they convey the same or
different types of information? Third, how are they related to outcome in
terms of organ dysfunction?
Concerning the first question, there was a palpably large variability in NP
secretion in terms of CV, both between patients and within patients over
time, and especially in the case of NT-proBNP. Mechanisms underlying this
variability have been only partially elucidated. In fact, even in non-critically
ill patients with stable chronic heart failure there is significant between-day
variation in P-NT-proBNP [17; 11]. Surprisingly, this phenomenon has been
insufficiently analyzed, but it indicates a very phasic effect of BNP in maintaining stable atrial and ventricular wall tension by virtue of volume control.
The most likely mechanism for differences in concentration dynamics is
related to differences in storage, synthesis and mechanisms of release. ANP
has a larger storage pool that can rapidly be released, but induction of synthesis is faster for BNP. Theoretically, this may lead to a temporary dominance of BNP once storage pools for ANP become depleted. This is supported by the inverse relation seen when the NP ratio for the first sample ob47
tained is plotted versus time after injury.
Concerning the second question, both NPs were weakly related to cardiac,
lung and kidney function, with minor differences. The most striking difference between the two NPs concerning their relation to other variables was
that NT-proBNP, but not NT-proANP, was related to the systemic inflammatory trauma response measured as CRP.
Notably, TBSA showed no significant relation to S-NT-proANP in the
present study, in contrast to a weak relation to P-NT-proBNP. It may be
argued that the relation between TBSA and P-NT-proBNP is related to an
effect of the systemic inflammatory response on P-NT-proBNP.
The somewhat surprising answer to the third question concerning the relation to outcome is that despite their volatility, both NPs were related to
forthcoming overall organ dysfunction, in fact very consistently, and starting
early after injury in the case of NT-proBNP. This is in line with previous
observations that BNP is elevated in critically ill patients who lack any other
observations suggesting incipient myocardial failure, and increased levels
are related to mortality [121].
Although no immediate clinical utility for either NP has been revealed,
future possibilities are implied. Clearly, NP concentrations hold information
that determines forthcoming overall organ dysfunction, and thus can aid the
clinician in determining prognosis. It is premature to say in what way this
should be done. However, given the high variability, stable predictions will
likely demand serial sampling. The explained variance in regressions between various specific organ dysfunctions and either NP as outcome were in
general low, with adjusted R2 values of less than 0.10. Mechanisms not included in the variables investigated here must therefore affect NP concentration. This, and the immense day-to-day variability in both NPs as well as in
the NP ratio, indicates that hoping for organ-specific clinically valuable information from NPs in trauma patients may be futile.
The significance of these findings is that they clarify the immense variability in NP concentration after trauma. This challenges the interpretation of
numerous previous studies based on only one or a few measurements from
each patient. Additionally, this work provides texture to the volatile secretion of these NPs, which seems chaotic on outset. The conclusion that both
NPs are similarly related to overall organ dysfunction, but not well suited to
differentiate cardiac from lung dysfunction, or monitor fluid balance, is also
an important contribution to the understanding of burn stress.
Generalization to other types of trauma may not be appropriate, since NPs
are strongly involved in the regulation of water homeostasis, which is clearly
very challenged in burn trauma.
48
Cortisol
Cortisol, perhaps the most investigated of the stress hormones, is secreted in
a circadian fashion and is involved in the regulation of a diverse number of
processes related to development, homeostasis, metabolism, cognition and
inflammation [12]. It can therefore be thought of as a reference hormone in
biochemical characterization of a stress response. In addition to furthering
the understanding of cortisol secretion and rhythmicity after burn injury, the
present work firmly positions burn research in surrounding stress and glucocorticoid research and provides a comparative measure of stress intensity.
The main finding was that rhythmicity was more disturbed in large than
in small burns. More specifically, large burns had smaller daily CV values,
flatter cortisol slopes and an inability to downregulate cortisol secretion late
in the day, as seen in small burns and healthy subjects. Furthermore, and in
accordance with observations made by other groups, S-cortisol levels were
well elevated after burns, and more so for larger burns.
The disruption of circadian rhythm observed during the initial seven days
of ICU care reflect considerable allostatic load, as validated by our CgA
study. While no conclusions about long-term negative effects on the organism can be drawn based on the present data, they establish that clear alterations of cortisol rhythmicity, which indicate loss of regulatory competence of
the HPA-axis [119], occur early and are related to the size of the burn injury.
This may have serious implications, since there is accumulating evidence
that the rhythmicity of cortisol secretion is of fundamental importance for an
optimal functioning of the cortisol signaling system [28; 147]. Furthermore,
cortisol slope has previously been shown to predict mortality as well as other
clinical outcomes in various patient populations, which makes the present
findings particularly interesting.
The effect of burn size on cortisol rhythmicity was overshadowed by the
effect of the SOFA score in statistical modeling. The SOFA score can be
viewed as a consequence of all stressors a patient is subjected to, which
makes it plausible that cortisol rhythm, just like CgA and NPs, can be
viewed as an integrated measure of multiple stressors. Which of the four that
is the most optimal reflector of overall stress remains to be determined.
It has previously been stated that thermal injury of more than 20% of
TBSA leads to disturbances in cortisol metabolism and the equilibrium of
the hypothalamic-pituitary-adrenal axis [103], but to our knowledge this is
the first study on burn stress that utilizes cortisol slope, the most prevalent
measure in circadian cortisol research in various patient groups [120]. The
present study is also based on a larger patient material and utilizes a more
sophisticated statistical strategy to reveal patterns in cortisol rhythmicity
than in previous assessments. The present results further support the generally accepted view that injury of more than 20% of TBSA leads to serious
allostatic load, and should be treated in specialized burn units.
49
A separate rhythm disturbance was observed that was not associated with
burn size, surgery or intubation: the cortisol zenith occurred later in the
morning than would be expected in a healthy population. The data do not
supply an answer regarding which mechanisms underlie the delay, but this
phenomenon has been observed by others in burn patients [104]. One reason
could be related to the critical illness as such, as there was a weak relation to
SOFA score. Other tentative reasons could be features of care, such as sleep
disturbances, delayed wake up times or exposure to stressful care situations
which usually occur before lunch time. External factors as well as internal
changes in chronobiological rhythmicity must be considered, as this phenomenon occurred very early after the inciting traumatic event.
The significance of this work is that it elucidates the cortisol stress response after burn injury by means of a more general approach to measuring
cortisol rhythmicity and more advanced statistical modeling than in previous
burn research. Furthermore, the most relevant fraction of cortisol, the free
fraction, has been analyzed. Interestingly, this did not change results compared to calculations using total cortisol, but it slightly improved levels of
significance.
Further improvement in our understanding of the biological consequences
of altered cortisol dynamics probably require approaches to measure the
cellular response in a more detailed manner than today, i.e. in relation to
receptor activation and cortisol specific transcription events, as has also been
concluded by others [12].
General discussion
The neuroendocrine afferent and efferent communication between the brain
and the rest of the body, which is central to the stress response after trauma,
is complex, highly interlaced, and impacts metabolism, immune function and
the circulatory as well as the nervous system. This web of communication is
not specifically designed for or used in combating trauma, but is a universal
system for maintaining allostasis in any situation where there is a threat to
the organism, perceived or real. A stress response can be initiated by widely
differing stressors and by activation steps in several locations in the neuroendocrine system. Consequently, research in many different fields has contributed to the understanding of the physiological processes aimed at combating allostatic overload.
The integrated neuroendocrine response
The stress response system is a truly integrated system characterized by a
large number of interactions and interrelations between agonists and their
receptors. Individual characteristics affect details of the stress response sys50
tem, and consequences of stress system activation for the individual. There
is, thus, genetic variability in various signaling systems in the stress response. Such is the case for the tumor-necrosis factor (TNF)-α and -β gene
[7; 129], but also for the BDNF-gene, where a distinct polymorphism,
Val66Met, is related to an attenuated HPA-axis and cardiovascular reactivity
to stress [4]. Burn survival has been related to polymorphism in the Toll like
receptor 4 gene and the TNF-α gene [8]. In addition, the cortisol levels are
subjected to a large number of genetic influences [10]. These studies all
point to the fact that there are a multitude of putative gene polymorphisms
affecting physiological responses to somatic and psychological stressors in a
way that may have an impact on late perceived outcome. Obviously, therefore, the stress response that is initiated affects individuals differently. This
is established with respect to the risk of developing somatic organ damage
after septic episodes, for example, where certain genetic features are related
to an increased risk for multi-organ failure. As a corollary to this observation, the question arises as to whether there are individual differences in the
ways the stress response harms different organ systems, i.e. whether there
are characteristics that leave some individuals with renal damage and other
individuals with pulmonary sequels, for example, after a similar somatic
insult. This question has not been scientifically investigated.
There are various questions concerning survivors of critical illness that
are related to the integrative and individual nature of the stress response and
to which there are not yet any good answers. Why do some patients remain
catabolic after wounds have healed? What determines whether patients will
acquire CCI? Are there sequels to an inadequate stress response? Are the late
cognitive problems that sometimes arise a consequence of the stress response in the brain? Why do some patients never return to work or become
lethargic, even if they have healed well? Why do some, but not others, get
PTSD? How can structural and permanent adverse modification of the stress
system be prevented? Our data cannot answer these questions, but this thesis
is a stepping-stone on the long journey towards understanding and handling
adverse consequences of the post-traumatic stress response.
This integrative nature of the stress system must be considered with respect to the present work, which should not be viewed as representing four
completely different aspects of the stress response. For example, there is
evidence that there is co-localization of CgA and BNP in secretory granules
of cardiomyocytes, and interactions between the down-stream products of
CgA, vasostatin-1 and catestatin, NPs and catecholamine receptors are proposed as a paradigm of the heart’s capacity to organize complex integration
processes for maintaining homeostasis under stress [83]. There are also observations suggesting that release of CgA is more closely connected to the
myocardial release of natriuretic peptides and the inflammatory response
than to activation of the sympathoadrenergic system in patients with heart
failure [67]. Free cortisol and BNP were recently found to correlate strongly
51
in septic ICU patients [5]. The neuroendocrine response also depends on
whether a stressor occurs in the ascending or descending phase of a cortisol
secretory pulse [54], in that the response is stronger when the stressor acts on
the ascending phase. This suggests that stochastic processes are involved in
the interplay between glucocorticoid receptor activation and stress response.
All these findings severely complicate the interpretations of our findings.
Finally, all present measurements were made outside the blood brain barrier, which precludes any attempt to understand details in the central regulation of the response.
The neuroendocrine response and late sequels
Trauma continues to be a serious public health problem that invokes a strong
stress response that is effective most of the time. Modern intensive care of
trauma patients is more effective than at any previous time in history, and
many patients now survive horrendous traumas that previously would have
led to certain death. One price these patients pay is having to undergo extensive periods of life supporting interventions and hence of allostatic overload.
From an evolutionary perspective such prolonged and intense stress responses have not been compatible with survival, and it is generally accepted that
long periods of life-saving ICU care have adverse consequences. Prior studies on the stress response during critical illness have, however, largely focused on the immediate physiological effects and consequences of the critical care itself in order to ascertain survival and minimize life threatening
secondary organ injuries. As survival from severe critical illness has become
the expected outcome for most patients in the past few decades, a number of
recent studies have focused on the late sequels that represent non-lifethreatening organ damage. Compromised lung and renal function, and
ICUAW constitute such damage.
It has been confirmed to some extent that the protracted and intense stress
response in itself can generate different types of pathophysiology. Problems
these patients face, which may or may not be caused or exacerbated by
stress, include catabolism and weight loss, asthenia, dyspnea, joint stiffness,
anxiety and depression [49]. Some of these problems may be unrecognized
during care, but become apparent once the patient returns home.
Attention has recently focused on whether the long-standing stress that
accompanies ICU care for critical illness also results in organic consequences for the brain. A number of arguments support such a notion, while no
arguments indicate why the brain should be free from organ damage when
other organs “fight for their lives”. White matter lesions have been observed
by MRI in the aftermath of critical illness [91]. It was recently noted that
severe somatic stress in the form of sepsis [118] or critical illness in general
[91] was sufficient for such lesions to appear. It has also been observed that
higher functions are truly affected, both in the form of cognitive impairment,
52
which occurs in up to one-third of ICU-survivors [127], and in the form of
properly diagnosed psychiatric conditions, both during and after general
intensive care [27; 39]. With respect to burns, those afflicted have smaller
hippocampus volumes than controls [146], which is an indication of a severe
stress lesion in the brain.
Summing up
How should the stress response after trauma best be understood?
Major trauma results in multiple organ dysfunction and elicits a strong
stress response and, in accordance with what has been discussed, activation
of all branches of the neuroendocrine stress response system. The interlacement of branches of the stress system obstructs research focused on specific
aspects of the stress response.
In this thesis the stress response has been assessed from four different
perspectives. A common feature seems to be that if anyone of the biomarkers
studied signals a strong stress response, this reflects and predicts that the
patient is or will become more affected by the disease or trauma in question
than would otherwise be the case. It is, however, futile to believe that the
richly interwoven stress response can be adequately assessed by one biomarker only. All biomarkers studied can be viewed as representing efferent
limbs of the stress reaction, and they would need to be supplemented by
biomarkers representing afferent response signaling, and by measures of the
ensuing individual physiologic changes that follow the stress signaling.
One question that arises from analyzing our data is reminiscent of the
chicken and the egg - which came first? A trauma results in wounds and
yields a stress response – that weakens immune function and induces a catabolic state – that yields infection and sepsis – that worsens wounds and
yields more stress – that results in organ dysfunction…and so on. Obviously,
a stress response is both a consequence and the etiology of tissue and organ
damage.
This thesis has clarified in certain ways some co-variations between stress
and different clinical parameters, but based on the nature of the underlying
data it cannot provide any definitive answers about causality. From an assessment and prediction perspective the question of causality does not have
to be answered; the stress response and organ dysfunction seem to progress
in tandem. Other issues, however, such as manipulating the stress response
through hormone therapy, need to be viewed from a causality perspective
and will have to be dealt with in future studies.
53
Conclusions

P-CgA after a major burn injury is an independent and better predictor of
organ dysfunction assessed as SOFA score than the traditionally used
TBSA% burned.

The results suggest that the extent of neuroendocrine activation is related
to organ dysfunction and they motivate a more extensive effort to evaluate P-CgA as a prognostic marker with respect to mortality and longterm outcome.

P-NT-proBNP exhibited a complex pattern with considerable interindividual and day-to-day variations.

Values of P-NT-proBNP were related to size of burn, water accumulation and systemic inflammatory response. A considerable covariation
with trauma response and SOFA scores was observed in day by day
analyses, but with weight change only on day 2.

Maximum P-NT-proBNP showed a stronger correlation with SOFA
score on day 14, with mortality, and with LOS, than did age and
TBSA% burned. High values were also independent predictors of all
subsequent SOFA scores up to two weeks after injury.

Both NPs reflect and predict organ function after burn injury similarly,
notwithstanding a significantly larger intra-individual variability for PNT-proBNP.

P-NT-proBNP, but not NT-proANP, reflects the systemic inflammatory
trauma response.

Free cortisol concentration was related to the size of burns, as was also
the circadian cortisol rhythm. This effect of burn size was, at least in
part, related to its effect on organ function.
54
Acknowledgments
This thesis is the result of collaboration between the Departments of Surgical
Sciences and Neuroscience, University Hospital, and the Department of Psychology, Uppsala University. It originated from a project aiming at identifying long-term sequels after burn injury that was supported by the National
Board of Health and Welfare, and it subsequently developed into a
multiprofessional longitudinal research project. During the project I have
collaborated with many people who have helped me in various ways.
I wish to express my sincere gratitude to the following:
Bengt Gerdin, my supervisor, for excellent supervision and guidance, and
for generously sharing your time, your brilliant mind, and your vast experience. Thank you also for respecting good family values and playing loads of
good music. Working with you has been truly inspiring, and without you this
project would not have amounted to much.
Lisa Ekselius, my co-supervisor, who together with Bengt was the initiator
of this project, for your generosity, energy and support, for always being
enchanting and optimistic, and for keeping track of Bengt.
My co-authors: Folke Sjöberg for providing an outside perspective on this
project, and for valuable insights, anesthesiologic input and optimism; Mats
Stridsberg for valuable input concerning clinical chemistry; Aili Low for
teaching me burn surgery.
Kristofer Rubin, for agreeing to be my extra co-supervisor just in case...
The research group, one and all, primarily from the Department of Neuroscience, for valuable input, enjoyable lunch meetings and for exposing me to
a non-surgical perspective regarding science and healthcare.
Morten Kildal and Monica Eriksson, former and present chiefs of staff for
the Department of Plastic Surgery, for support and for granting me time off
from clinical work to conduct my research.
55
All my colleagues in the Department of Plastic Surgery, past and present,
from near and far, for encouragement and exemplary professionalism, and
for my training in burn surgery as well as in all branches of plastic surgery.
Malin Hakelius, my clinical mentor, for all the support and for vouching for
me so that this adventure could begin.
Fredrik Huss for valuable insights in burn care.
Anders Hedlund for time-saving advice on Apple software, computer trouble-shooting, and for tips in burn care from a wily old bird.
All the staff at Uppsala Burn Center, Ward 65A, the Outpatient Clinic and
the Operation Unit for their unflagging efforts in taking care of the patients.
Lisa Wernroth and Lars Berglund for statistical advice.
Olav Laudi for expert help with SPSS add-on programming.
Daniel Lundin and Birgitta Olsson for expert help with Microsoft Access
programming.
Emelie Gauffin for excellent contributions to the database, and for updating
my adolescent lingo.
Anders Vesterlund for spending time with me at the KTH Royal Institute of
Technology, and helping me when no one else could.
Viveca Lindahl for listening and showing me open source software when
other solutions were hard to find.
Eric Lindahl for expert advice on Photoshop.
Jane Wigertz for superb linguistic expertise.
Carina Warme for fantastic administrative support.
Thomas Berg, Job Andersson and Thunder, my wonderful office mates
and friends, for countless good laughs.
John Michael Dorian, Christopher Duncan Turk, Elliot Reid, Carla
Espinosa, Perry Ulysses Cox, Robert Kelso and The Janitor for all those
crazy moments that made me want to go back to the hospital.
56
My parents, Lars and Ylwa, to whom this thesis is dedicated, for giving me
a loving childhood and for going to great lengths to expose me to rewarding
experiences, and for encouraging me to do my homework and stay in school;
and to my brother and sister, Tobias and Johanna, for growing up together
with me and giving me roots.
Finally, thank you Katarina, the love of my life, for making my life fun and
easy, for constant support and attentive listening, and for being the bright
mind in our family and the loving mother of our children; and my children,
Filippa, Alexander and Eleonora, for filling my life with purpose and joy,
and showing me what is truly important. You mean the world to me.
Financial support has been received from the Swedish Research Council, the
Faculty of Medicine, and Uppsala County Council funds (ALF).
57
References
1
2
3
4
5
6
7
8
9
10
11
12
13
58
"SOFA, Swedish Intensive Care Registry; Riktlinjer/SOFA Registrering,".
2012-04-12. <http://www.icuregswe.org/sv/Riktlinjer/SOFA-registrering/>.
Ventilation with lower tidal volumes as compared with traditional tidal
volumes for acute lung injury and the acute respiratory distress syndrome.
The Acute Respiratory Distress Syndrome Network,. N Engl J Med
2000;342: 1301-8.
Aguilera G. HPA axis responsiveness to stress: implications for healthy
aging. Exp Gerontol 2011;46: 90-5.
Alexander N, Osinsky R, Schmitz A, Mueller E, Kuepper Y, et al. The
BDNF Val66Met polymorphism affects HPA-axis reactivity to acute stress.
Psychoneuroendocrinology 2010;35: 949-53.
American Burn Association. "Burn Incidence and Treatment in the United
States: 2012 Fact Sheet". http://www.ameriburn.org/resources_factsheet.php.
American
Burn
Association.
2012
http://www.ameriburn.org/2012NBRAnnualReport.pdf.
Azevedo ZM, Moore DB, Lima FC, Cardoso CC, Bougleux R, et al. Tumor
necrosis factor (TNF) and lymphotoxin-alpha (LTA) single nucleotide
polymorphisms: importance in ARDS in septic pediatric critically ill
patients. Hum Immunol 2012;73: 661-7.
Barber RC, Aragaki CC, Rivera-Chavez FA, Purdue GF, Hunt JL, et al.
TLR4 and TNF-alpha polymorphisms are associated with an increased risk
for severe sepsis following burn injury. J Med Genet 2004;41: 808-13.
Barret JP, Gomez P, Solano I, Gonzalez-Dorrego M, Crisol FJ.
Epidemiology and mortality of adult burns in Catalonia. Burns 1999;25:
325-9.
Bartels M, Van den Berg M, Sluyter F, Boomsma DI, de Geus EJ.
Heritability of cortisol levels: review and simultaneous analysis of twin
studies. Psychoneuroendocrinology 2003;28: 121-37.
Bentzen H, Pedersen RS, Pedersen HB, Nyvad O, Pedersen EB. Abnormal
rhythmic oscillations of atrial natriuretic peptide and brain natriuretic
peptide in heart failure. Clin Sci (Lond) 2003;104: 303-12.
Biddie SC, Conway-Campbell BL, Lightman SL. Dynamic regulation of
glucocorticoid signalling in health and disease. Rheumatology (Oxford)
2012;51: 403-12.
Bierhaus A, Wolf J, Andrassy M, Rohleder N, Humpert PM, et al. A
mechanism converting psychosocial stress into mononuclear cell
activation. Proc Natl Acad Sci U S A 2003;100: 1920-5.
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
Biondi M, Picardi A. Psychological stress and neuroendocrine function in
humans: the last two decades of research. Psychother Psychosom 1999;68:
114-50.
Borovikova LV, Ivanova S, Zhang M, Yang H, Botchkina GI, et al. Vagus
nerve stimulation attenuates the systemic inflammatory response to
endotoxin. Nature 2000;405: 458-62.
Bremner JD, Vythilingam M, Vermetten E, Southwick SM, McGlashan T,
et al. MRI and PET study of deficits in hippocampal structure and function
in women with childhood sexual abuse and posttraumatic stress disorder.
Am J Psychiatry 2003;160: 924-32.
Bruins S, Fokkema MR, Romer JW, Dejongste MJ, van der Dijs FP, et al.
High intraindividual variation of B-type natriuretic peptide (BNP) and
amino-terminal proBNP in patients with stable chronic heart failure. Clin
Chem 2004;50: 2052-8.
Brusselaers N, Juhasz I, Erdei I, Monstrey S, Blot S. Predictive value of the
Belgian Outcome in Burn Injury (BOBI) prediction model. Burns 2010;
Brusselaers N, Monstrey S, Vogelaers D, Hoste E, Blot S. Severe burn
injury in Europe: a systematic review of the incidence, etiology, morbidity,
and mortality. Crit Care 2010;14: R188.
Cao LH, Yang XL. Natriuretic peptides and their receptors in the central
nervous system. Prog Neurobiol 2008;84: 234-48.
Cavigelli SA, McClintock MK. Fear of novelty in infant rats predicts adult
corticosterone dynamics and an early death. Proc Natl Acad Sci U S A
2003;100: 16131-6.
Charney DS. Psychobiological mechanisms of resilience and vulnerability:
implications for successful adaptation to extreme stress. Am J Psychiatry
2004;161: 195-216.
Connor KM. Assessment of resilience in the aftermath of trauma. J Clin
Psychiatry 2006;67 Suppl 2: 46-9.
Coolens JL, Van Baelen H, Heyns W. Clinical use of unbound plasma
cortisol as calculated from total cortisol and corticosteroid-binding
globulin. J Steroid Biochem 1987;26: 197-202.
Cox CE. Persistent systemic inflammation in chronic critical illness. Respir
Care 2012;57: 859-64; discussion 64-6.
Cryer PE, Wortsman J, Shah SD, Nowak RM, Deftos LJ. Plasma
chromogranin A as a marker of sympathochromaffin activity in humans.
Am J Physiol 1991;260: E243-6.
Desai SV, Law TJ, Needham DM. Long-term complications of critical
care. Critical care medicine 2011;39: 371-9.
Dickmeis T. Glucocorticoids and the circadian clock. J Endocrinol
2009;200: 3-22.
Dimsdale JE, O'Connor D, Ziegler M, Mills P. Does chromogranin A
respond
to
short-term
mild
physiologic
challenge?
Neuropsychopharmacology 1989;2: 237-40.
Dimsdale JE, O'Connor DT, Ziegler M, Mills P. Chromogranin A
correlates with norepinephrine release rate. Life Sci 1992;51: 519-25.
59
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
60
Dinkel K, MacPherson A, Sapolsky RM. Novel glucocorticoid effects on
acute inflammation in the CNS. J Neurochem 2003;84: 705-16.
Dorin RI, Pai HK, Ho JT, Lewis JG, Torpy DJ, et al. Validation of a simple
method of estimating plasma free cortisol: role of cortisol binding to
albumin. Clin Biochem 2009;42: 64-71.
Dos Santos CC, Batt J. ICU-acquired weakness: mechanisms of disability.
Curr Opin Crit Care 2012;18: 509-17.
Edwards BS, Zimmerman RS, Schwab TR, Heublein DM, Burnett JC, Jr.
Atrial stretch, not pressure, is the principal determinant controlling the
acute release of atrial natriuretic factor. Circ Res 1988;62: 191-5.
Elias AN, Wilson AF, Pandian MR, Kayaleh R. Chromogranin A
concentrations in plasma of physically active men after acute exercise. Clin
Chem 1992;38: 2348-9.
Fink G. Encyclopedia of stress. 2nd ed. 4 vols. Amsterdam ; Boston:
Academic Press, 2007.
Fink G. "Stress, Definition and History." In: Stress Science:
Neuroendocrinology. Ed. Fink, G. San Diego, CA: Academic Press Elsevier, 2009. 3-9.
Finnerty CC, Ju H, Spratt H, Victor S, Jeschke MG, et al. Proteomics
improves the prediction of burns mortality: results from regression spline
modeling. Clin Transl Sci 2012;5: 243-9.
Flaatten H. Mental and physical disorders after ICU discharge. Current
opinion in critical care 2010;16: 510-5.
Forjuoh SN. Burns in low- and middle-income countries: a review of
available literature on descriptive epidemiology, risk factors, treatment,
and prevention. Burns 2006;32: 529-37.
Francis D, Diorio J, Liu D, Meaney MJ. Nongenomic transmission across
generations of maternal behavior and stress responses in the rat. Science
1999;286: 1155-8.
Freedman NS, Gazendam J, Levan L, Pack AI, Schwab RJ. Abnormal
sleep/wake cycles and the effect of environmental noise on sleep disruption
in the intensive care unit. Am J Respir Crit Care Med 2001;163: 451-7.
Fulda S, Gorman AM, Hori O, Samali A. Cellular stress responses: cell
survival and cell death. Int J Cell Biol 2010;2010: 214074.
Gerlach JL, McEwen BS. Rat brain binds adrenal steroid hormone:
radioautography of hippocampus with corticosterone. Science 1972;175:
1133-6.
Geronimus AT. The weathering hypothesis and the health of AfricanAmerican women and infants: evidence and speculations. Ethn Dis 1992;2:
207-21.
Gilbertson MW, Shenton ME, Ciszewski A, Kasai K, Lasko NB, et al.
Smaller hippocampal volume predicts pathologic vulnerability to
psychological trauma. Nat Neurosci 2002;5: 1242-7.
Goetze JP, Friis-Hansen L, Rehfeld JF, Nilsson B, Svendsen JH. Atrial
secretion of B-type natriuretic peptide. Eur Heart J 2006;27: 1648-50.
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
Goncharova ND. Stress responsiveness of the hypothalamic-pituitaryadrenal axis: age-related features of the vasopressinergic regulation. Front
Endocrinol (Lausanne) 2013;4: 26.
Granja C, Amaro A, Dias C, Costa-Pereira A. Outcome of ICU survivors: a
comprehensive review. The role of patient-reported outcome studies. Acta
Anaesthesiol Scand 2012;56: 1092-103.
Gudsnuk KM, Champagne FA. Epigenetic effects of early developmental
experiences. Clin Perinatol 2011;38: 703-17.
Helle KB. The chromogranin A-derived peptides vasostatin-I and catestatin
as regulatory peptides for cardiovascular functions. Cardiovasc Res
2010;85: 9-16.
Herman JP, Cullinan WE. Neurocircuitry of stress: central control of the
hypothalamo-pituitary-adrenocortical axis. Trends Neurosci 1997;20: 7884.
Herman JP, Ostrander MM, Mueller NK, Figueiredo H. Limbic system
mechanisms of stress regulation: hypothalamo-pituitary-adrenocortical
axis. Prog Neuropsychopharmacol Biol Psychiatry 2005;29: 1201-13.
Hunt PJ, Richards AM, Espiner EA, Nicholls MG, Yandle TG. Bioactivity
and metabolism of C-type natriuretic peptide in normal man. J Clin
Endocrinol Metab 1994;78: 1428-35.
Hystad ME, Geiran OR, Attramadal H, Spurkland A, Vege A, et al.
Regional cardiac expression and concentration of natriuretic peptides in
patients with severe chronic heart failure. Acta Physiol Scand 2001;171:
395-403.
Januzzi JL, Jr., Camargo CA, Anwaruddin S, Baggish AL, Chen AA, et al.
The N-terminal Pro-BNP investigation of dyspnea in the emergency
department (PRIDE) study. Am J Cardiol 2005;95: 948-54.
Jaszberenyi M, Bujdoso E, Telegdy G. Effects of brain natriuretic peptide
on pituitary-adrenal activation in rats. Life Sci 2000;66: 1655-61.
Jezek K, Lee BB, Kelemen E, McCarthy KM, McEwen BS, et al. Stressinduced out-of-context activation of memory. PLoS Biol 2010;8: e1000570.
Jones BJ, Tan T, Bloom SR. Minireview: Glucagon in stress and energy
homeostasis. Endocrinology 2012;153: 1049-54.
Kajdacsy-Balla Amaral AC, Andrade FM, Moreno R, Artigas A, Cantraine
F, et al. Use of the sequential organ failure assessment score as a severity
score. Intensive Care Med 2005;31: 243-9.
Kalsbeek A, Fliers E, Hofman MA, Swaab DF, Buijs RM. Vasopressin and
the output of the hypothalamic biological clock. J Neuroendocrinol
2010;22: 362-72.
Kangawa K, Fukuda A, Minamino N, Matsuo H. Purification and complete
amino acid sequence of beta-rat atrial natriuretic polypeptide (beta-rANP)
of 5,000 daltons. Biochem Biophys Res Commun 1984;119: 933-40.
Knaus WA. APACHE II: a severety of disease classification system.
Critical care medicine 1985: 818-29.
Knaus WA, Wagner DP, Draper EA, Zimmerman JE, Bergner M, et al. The
APACHE III prognostic system. Risk prediction of hospital mortality for
critically ill hospitalized adults. Chest 1991;100: 1619-36.
61
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
62
Knaus WA, Zimmerman JE, Wagner DP, Draper EA, Lawrence DE.
APACHE-acute physiology and chronic health evaluation: a
physiologically based classification system. Crit Care Med 1981;9: 591-7.
Kondratova AA, Kondratov RV. The circadian clock and pathology of the
ageing brain. Nat Rev Neurosci 2012;13: 325-35.
Larsen AI, Helle KB, Christensen M, Kvaloy JT, Aarsland T, et al. Effect of
exercise training on chromogranin A and relationship to N-ANP and
inflammatory cytokines in patients with chronic heart failure. Int J Cardiol
2008;127: 117-20.
Le Gall JR, Klar J, Lemeshow S, Saulnier F, Alberti C, et al. The Logistic
Organ Dysfunction system. A new way to assess organ dysfunction in the
intensive care unit. ICU Scoring Group. JAMA 1996;276: 802-10.
Le Gall JR, Loirat P, Alperovitch A, Glaser P, Granthil C, et al. A
simplified acute physiology score for ICU patients. Crit Care Med 1984;12:
975-7.
Lee AL, Ogle WO, Sapolsky RM. Stress and depression: possible links to
neuron death in the hippocampus. Bipolar Disord 2002;4: 117-28.
Lemeshow S, Teres D, Pastides H, Avrunin JS, Steingrub JS. A method for
predicting survival and mortality of ICU patients using objectively derived
weights. Crit Care Med 1985;13: 519-25.
Leproult R, Copinschi G, Buxton O, Van Cauter E. Sleep loss results in an
elevation of cortisol levels the next evening. Sleep 1997;20: 865-70.
Levin ER, Gardner DG, Samson WK. Natriuretic peptides. N Engl J Med
1998;339: 321-8.
Loh YP, Cheng Y, Mahata SK, Corti A, Tota B. Chromogranin A and
derived peptides in health and disease. J Mol Neurosci 2012;48: 347-56.
Lorente JA, Vallejo A, Galeiras R, Tomicic V, Zamora J, et al. Organ
dysfunction as estimated by the sequential organ failure assessment score
is related to outcome in critically ill burn patients. Shock 2009;31: 125-31.
Luchner A, Stevens TL, Borgeson DD, Redfield M, Wei CM, et al.
Differential atrial and ventricular expression of myocardial BNP during
evolution of heart failure. Am J Physiol 1998;274: H1684-9.
Lumsden NG, Khambata RS, Hobbs AJ. C-type natriuretic peptide (CNP):
cardiovascular roles and potential as a therapeutic target. Curr Pharm Des
2010;16: 4080-8.
Lupien SJ, Lepage M. Stress, memory, and the hippocampus: can't live
with it, can't live without it. Behav Brain Res 2001;127: 137-58.
MacPherson A, Dinkel K, Sapolsky R. Glucocorticoids worsen excitotoxininduced expression of pro-inflammatory cytokines in hippocampal cultures.
Exp Neurol 2005;194: 376-83.
Mair J. Biochemistry of B-type natriuretic peptide--where are we now? Clin
Chem Lab Med 2008;46: 1507-14.
Marshall JC, Cook DJ, Christou NV, Bernard GR, Sprung CL, et al.
Multiple organ dysfunction score: a reliable descriptor of a complex
clinical outcome. Crit Care Med 1995;23: 1638-52.
Mathers CD, Boerma T, Ma Fat D. Global and regional causes of death. Br
Med Bull 2009;92: 7-32.
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
Mazza R, Imbrogno S, Tota B. The interplay between chromogranin Aderived peptides and cardiac natriuretic peptides in cardioprotection
against catecholamine-evoked stress. Regul Pept 2010;165: 86-94.
McEwen BS. The neurobiology of stress: from serendipity to clinical
relevance. Brain Res 2000;886: 172-89.
McEwen BS. Physiology and neurobiology of stress and adaptation:
central role of the brain. Physiol Rev 2007;87: 873-904.
McGuire BE, Basten CJ, Ryan CJ, Gallagher J. Intensive care unit
syndrome: a dangerous misnomer. Arch Intern Med 2000;160: 906-9.
McIntosh TK, Bush HL, Yeston NS, Grasberger R, Palter M, et al. Betaendorphin, cortisol and postoperative delirium: a preliminary report.
Psychoneuroendocrinology 1985;10: 303-13.
Meriam-Webster
Dictionary.
<http://www.merriamwebster.com/dictionary/trauma>.
Minne L, Abu-Hanna A, de Jonge E. Evaluation of SOFA-based models for
predicting mortality in the ICU: A systematic review. Crit Care 2008;12:
R161.
Moore FA, Sauaia A, Moore EE, Haenel JB, Burch JM, et al. Postinjury
multiple organ failure: a bimodal phenomenon. J Trauma 1996;40: 501-10;
discussion 10-2.
Morandi A, Rogers BP, Gunther ML, Merkle K, Pandharipande P, et al.
The relationship between delirium duration, white matter integrity, and
cognitive impairment in intensive care unit survivors as determined by
diffusion tensor imaging: the VISIONS prospective cohort magnetic
resonance imaging study*. Critical care medicine 2012;40: 2182-9.
Mukoyama M, Nakao K, Hosoda K, Suga S, Saito Y, et al. Brain
natriuretic peptide as a novel cardiac hormone in humans. Evidence for an
exquisite dual natriuretic peptide system, atrial natriuretic peptide and
brain natriuretic peptide. J Clin Invest 1991;87: 1402-12.
Murray CJL L, AD. . The global burden of disease: a comprehensive
assessment of mortality and disability from diseases, injuries, and risk
factors in 1990 and projected to 2020, World Health Organization,
Swizerland 2006. 2006;
Nelson JE, Cox CE, Hope AA, Carson SS. Chronic critical illness. Am J
Respir Crit Care Med 2010;182: 446-54.
Nemeroff CB. Neurobiological consequences of childhood trauma. J Clin
Psychiatry 2004;65 Suppl 1: 18-28.
Olofsson K, Alling C, Lundberg D, Malmros C. Abolished circadian
rhythm of melatonin secretion in sedated and artificially ventilated
intensive care patients. Acta Anaesthesiol Scand 2004;48: 679-84.
Onuoha GN, Alpar EK, Gowar J. Plasma levels of atrial natriuretic peptide
in severe burn injury. Burns 2000;26: 449-53.
Palmieri T, Lavrentieva A, Greenhalgh DG. Acute kidney injury in
critically ill burn patients. Risk factors, progression and impact on
mortality. Burns 2010;36: 205-11.
Parthasarathy S, Tobin MJ. Sleep in the intensive care unit. Intensive Care
Med 2004;30: 197-206.
63
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
64
Patterson DR, Everett JJ, Bombardier CH, Questad KA, Lee VK, et al.
Psychological effects of severe burn injuries. Psychol Bull 1993;113: 36278.
Patterson DR, Tininenko J, Ptacek JT. Pain during burn hospitalization
predicts long-term outcome. J Burn Care Res 2006;27: 719-26.
Pavoni V, Gianesello L, Paparella L, Buoninsegni LT, Barboni E. Outcome
predictors and quality of life of severe burn patients admitted to intensive
care unit. Scand J Trauma Resusc Emerg Med 2010;18: 24.
Pileri D, Accardo-Palumbo A, D'Amelio L, D'Arpa N, Arnone G, et al.
Serum Levels of Cortisol, Immunoglobulin, and C-reactive Protein in Burn
Patients. Ann Burns Fire Disasters 2009;22: 3-5.
Pina G, Brun J, Tissot S, Claustrat B. Long-term alteration of daily
melatonin, 6-sulfatoxymelatonin, cortisol, and temperature profiles in burn
patients: a preliminary report. Chronobiol Int 2010;27: 378-92.
Ploghaus A, Tracey I, Gati JS, Clare S, Menon RS, et al. Dissociating pain
from its anticipation in the human brain. Science 1999;284: 1979-81.
Posener JA, DeBattista C, Williams GH, Chmura Kraemer H, Kalehzan
BM, et al. 24-Hour monitoring of cortisol and corticotropin secretion in
psychotic and nonpsychotic major depression. Arch Gen Psychiatry
2000;57: 755-60.
Potter LR, Abbey-Hosch S, Dickey DM. Natriuretic peptides, their
receptors, and cyclic guanosine monophosphate-dependent signaling
functions. Endocr Rev 2006;27: 47-72.
Pruitt BA, Jr., Wolf SE. An historical perspective on advances in burn care
over the past 100 years. Clin Plast Surg 2009;36: 527-45.
Rajpura A. The epidemiology of burns and smoke inhalation in secondary
care: a population-based study covering Lancashire and South Cumbria.
Burns 2002;28: 121-30.
Rattray J, Crocker C, Jones M, Connaghan J. Patients' perceptions of and
emotional outcome after intensive care: results from a multicentre study.
Nurs Crit Care 2010;15: 86-93.
Rattray JE, Hull AM. Emotional outcome after intensive care: literature
review. J Adv Nurs 2008;64: 2-13.
Redei EE. Molecular genetics of the stress-responsive adrenocortical axis.
Ann Med 2008;40: 139-48.
Røsjø H, Masson S, Latini R, Flyvbjerg A, Milani V, et al. Prognostic
value of chromogranin A in chronic heart failure: data from the GISSIHeart Failure trial. Eur J Heart Fail 2010;12: 549-56.
Saito Y, Nakao K, Itoh H, Yamada T, Mukoyama M, et al. Brain
natriuretic peptide is a novel cardiac hormone. Biochem Biophys Res
Commun 1989;158: 360-8.
Sapolsky RM, Romero LM, Munck AU. How do glucocorticoids influence
stress responses? Integrating permissive, suppressive, stimulatory, and
preparative actions. Endocr Rev 2000;21: 55-89.
Sarkar J, Wakefield S, MacKenzie G, Moss SJ, Maguire J.
Neurosteroidogenesis is required for the physiological response to stress:
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
role of neurosteroid-sensitive GABAA receptors. J Neurosci 2011;31:
18198-210.
Schneider F, Bach C, Chung H, Crippa L, Lavaux T, et al. Vasostatin-I, a
chromogranin A-derived peptide, in non-selected critically ill patients:
distribution, kinetics, and prognostic significance. Intensive Care Med
2012;38: 1514-22.
Semmler A, Widmann CN, Okulla T, Urbach H, Kaiser M, et al. Persistent
cognitive impairment, hippocampal atrophy and EEG changes in sepsis
survivors. J Neurol Neurosurg Psychiatry 2013;84: 62-9.
Sephton S, Spiegel D. Circadian disruption in cancer: a neuroendocrineimmune pathway from stress to disease? Brain Behav Immun 2003;17:
321-8.
Sephton SE, Sapolsky RM, Kraemer HC, Spiegel D. Diurnal cortisol
rhythm as a predictor of breast cancer survival. J Natl Cancer Inst 2000;92:
994-1000.
Shah KB, Nolan MM, Rao K, Wang DJ, Christenson RH, et al. The
characteristics and prognostic importance of NT-ProBNP concentrations
in critically ill patients. Am J Med 2007;120: 1071-7.
Shilo L, Dagan Y, Smorjik Y, Weinberg U, Dolev S, et al. Patients in the
intensive care unit suffer from severe lack of sleep associated with loss of
normal melatonin secretion pattern. Am J Med Sci 1999;317: 278-81.
Shrier I, Platt RW. Reducing bias through directed acyclic graphs. BMC
Med Res Methodol 2008;8: 70.
Spiegel K, Leproult R, Van Cauter E. Impact of sleep debt on metabolic
and endocrine function. Lancet 1999;354: 1435-9.
Spiegel K, Tasali E, Penev P, Van Cauter E. Brief communication: Sleep
curtailment in healthy young men is associated with decreased leptin levels,
elevated ghrelin levels, and increased hunger and appetite. Ann Intern Med
2004;141: 846-50.
Starkman MN, Giordani B, Gebarski SS, Berent S, Schork MA, et al.
Decrease in cortisol reverses human hippocampal atrophy following
treatment of Cushing's disease. Biol Psychiatry 1999;46: 1595-602.
Sterling P, Eyer J. "Allostasis: A new paradigm to explain arousal
pathology." Handbook of Life Stress, Cognition and Health. . Ed. (Eds.), In:
S. Fisher and J. Reason: John Wiley & Sons, New York., 1988.
Sudoh T, Minamino N, Kangawa K, Matsuo H. C-type natriuretic peptide
(CNP): a new member of natriuretic peptide family identified in porcine
brain. Biochem Biophys Res Commun 1990;168: 863-70.
Surbatovic M, Grujic K, Cikota B, Jevtic M, Filipovic N, et al.
Polymorphisms of genes encoding tumor necrosis factor-alpha, interleukin10, cluster of differentiation-14 and interleukin-1ra in critically ill patients.
J Crit Care 2010;25: 542 e1-8.
Takiyyuddin MA, Baron AD, Cervenka JH, Barbosa JA, Neumann HP, et
al. Suppression of chromogranin-A release from neuroendocrine sources in
man: pharmacological studies. J Clin Endocrinol Metab 1991;72: 616-22.
Taupenot L, Harper KL, O'Connor DT. The chromogranin-secretogranin
family. N Engl J Med 2003;348: 1134-49.
65
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
66
Teres D. Peer review, publication policy, and APACHE. Crit Care Med
1989;17: S169-72.
Thayer JF, Lane RD. A model of neurovisceral integration in emotion
regulation and dysregulation. J Affect Disord 2000;61: 201-16.
The National Board of Health and Welfare. "Statistics database (Swedish
version)". 2013. <http://www.socialstyrelsen.se/statistik/statistikdatabas>.
Tsigos C, Chrousos GP. Hypothalamic-pituitary-adrenal axis,
neuroendocrine factors and stress. J Psychosom Res 2002;53: 865-71.
Van den Berghe G. Novel insights into the neuroendocrinology of critical
illness. European Journal of Endocrinology 2000;143: 1-13.
Van den Berghe GH. The neuroendocrine stress response and modern
intensive care: the concept revisited. Burns 1999;25: 7-16.
Vanhorebeek I, Langouche L, Van den Berghe G. Endocrine aspects of
acute and prolonged critical illness. Nat Clin Pract Endocrinol Metab
2006;2: 20-31.
Weng HY, Hsueh YH, Messam LL, Hertz-Picciotto I. Methods of covariate
selection: directed acyclic graphs and the change-in-estimate procedure.
Am J Epidemiol 2009;169: 1182-90.
WHO. The Global Burden of Disease: 2004 Update. World Health
Organization,
Geneva
2008
www.who.int/healthinfo/
global_burden_disease/ GBD_report_2004update_full.pdf;
Wiedemann K, Jahn H, Kellner M. Effects of natriuretic peptides upon
hypothalamo-pituitary-adrenocortical system activity and anxiety
behaviour. Exp Clin Endocrinol Diabetes 2000;108: 5-13.
Wilmore DW, Long JM, Mason AD, Jr., Skreen RW, Pruitt BA, Jr.
Catecholamines: mediator of the hypermetabolic response to thermal
injury. Ann Surg 1974;180: 653-69.
Vincent JL, de Mendonca A, Cantraine F, Moreno R, Takala J, et al. Use of
the SOFA score to assess the incidence of organ dysfunction/failure in
intensive care units: results of a multicenter, prospective study. Working
group on "sepsis-related problems" of the European Society of Intensive
Care Medicine. Crit Care Med 1998;26: 1793-800.
Vincent JL, Ferreira F, Moreno R. Scoring systems for assessing organ
dysfunction and survival. Crit Care Clin 2000;16: 353-66.
Vincent JL, Moreno R, Takala J, Willatts S, De Mendonca A, et al. The
SOFA (Sepsis-related Organ Failure Assessment) score to describe organ
dysfunction/failure. On behalf of the Working Group on Sepsis-Related
Problems of the European Society of Intensive Care Medicine. Intensive
Care Med 1996;22: 707-10.
Winter H, Irle E. Hippocampal volume in adult burn patients with and
without posttraumatic stress disorder. Am J Psychiatry 2004;161: 2194200.
Young EA, Abelson J, Lightman SL. Cortisol pulsatility and its role in
stress regulation and health. Front Neuroendocrinol 2004;25: 69-76.
Zhang D, Lavaux T, Sapin R, Lavigne T, Castelain V, et al. Serum
concentration of chromogranin A at admission: an early biomarker of
severity in critically ill patients. Ann Med 2009;41: 38-44.
Acta Universitatis Upsaliensis
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