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Survival Prospects and Circumstances of Death in Contemporary Adult Congenital
Heart Disease Patients under Follow-up at a
Large Tertiary Centre
Gerhard-Paul Diller MD MSc PhD [1,2,3,4]*, Aleksander Kempny MD [1,2,3]*,
Rafael Alonso-Gonzalez MD MSc[1,2,3], Lorna Swan MD FRCP [1,2,3],
Anselm Uebing MD PhD [1,2,3], Wei Li MD PhD [1,2,3], Sonya Babu-Narayan MB BS, BSc,
MRCP, PhD [1,2,3], Stephen J Wort PhD [1,2,3], Konstantinos Dimopoulos MD MSc PhD [1,2,3],
Michael A. Gatzoulis MD PhD [1,2,3]
[1] Adult Congenital Heart Centre and National Centre for Pulmonary Hypertension, Royal Brompton
Hospital, London, UK.
[2] NIHR Cardiovascular Biomedical Research Unit, Royal Brompton Hospital and National Heart
and Lung Institute, Imperial College London, UK.
[3] National Heart and Lung Institute, Imperial College School of Medicine, London, UK.
[4] Division of Adult Congenital and Valvular Heart Disease, Department of Cardiology and
Angiology, University Hospital Muenster, Germany.
* G.P. Diller and A. Kempny contributed equally to this manuscript.
Correspondence to:
Dr Aleksander Kempny MD
Adult Congenital Heart Centre
Royal Brompton and Harefield NHS Foundation Trust
Sydney Street, SW3 6NP London, UK
Tel+44 207351 8602, Fax+44 207351 8629
E-mail: [email protected]
Manuscript word count: xxxx
1
Abstract
Background:
Adult congenital heart disease (ACHD) patients have ongoing morbidity and reduced longterm survival. Recently, the importance of specialized follow-up at tertiary ACHD centres
has been highlighted. We aimed to assess survival prospects and clarify causes of death in a
large cohort of patients at a single, tertiary centre.
Methods and Results:
We included 6,969 adult patients (age 29.9±15.4 years) under follow-up at our institution
between 1991 and 2013. Causes of death were ascertained from official death certificates.
Survival was compared with the expected survival in the general age and gender matched
population and standardized mortality rates were calculated. Over a median follow-up time of
9.1 years (IQR 5.2-14.5), 524 patients died. Leading causes of death were chronic heart
failure (45%), pneumonia (10%), sudden-cardiac death (8%), cancer (6%) and haemorrhage
(5%), while perioperative mortality was low. Isolated simple defects exhibited mortality rates
similar to those in the general population, while patients with Eisenmenger syndrome,
complex congenital heart disease and Fontan physiology had much poorer long-term survival
(P<0.0001 for all). The probability of cardiac death decreased with increasing patient’s age
(odds-ratio 0.85/decade, P=0.0005), whereas the proportion of patients dying from noncardiac causes, such as cancer, increased (odds-ratio 1.84, P<0.0001).
Conclusions:
ACHD patients continue to be afflicted by increased mortality compared to the general
population as they grow older. Highest mortality rates were observed amongst patients with
complex ACHD, Fontan physiology and Eisenmenger syndrome. Our contemporary data
show a clear shift from perioperative to chronic cardiac mortality and non-cardiac death.
Abstract - word count: 250
2
Introduction
Life expectancy of patients born with congenital heart disease (CHD) has improved
dramatically over the past few decades.1 In fact, over 90% of these patients are now expected
to survive to adulthood.2 This has led to the development of a large and growing population
of adults with congenital heart disease (ACHD). Despite the surgical, interventional and
medical advancements, these patients are not cured and require life-long specialized health
care. Beyond the obvious ongoing morbidity, including cardiac symptoms, reduced exercise
capacity and the need for electrophysiological, interventional or surgical procedures,
mortality is increased in this population of patients with chronic cardiac disease.3 Previous
studies have investigated the long term mortality of various ACHD cohorts and have
delineated causes of death in this population.4-6 Due to ongoing improvement of care,
survival prospects of adults with congenital heart disease are likely to have changed over
recent decades. However, accurate data to this end are lacking. A recent population-based
Canadian study has suggested that ACHD patients under follow-up at tertiary centres have
superior survival prospects compared to those not attending such institutions.7 Given the
recent advances in the field and the notion that patients under follow-up at large supraregional tertiary centres may have superior outcome compared to those followed in the
community, the current study was designed to evaluate specifically such a contemporary
ACHD cohort from a single tertiary centre and attempt comparison with data from previous
studies. In addition, we provide herewith, mortality data in relationship to the general
population, adjusted for age and gender and propose a novel approach for presenting this data
to health professionals, health policy makers and patients alike.
3
Patients and Methods
We retrospectively reviewed data on all adult patients with congenital heart disease under
active follow-up at the Royal Brompton Hospital, London between 1991 and 2014. For the
scope of this study we defined the start of adulthood as age ≥16. Patients were divided into
subgroups based on the major underlying heart defect. Patients with more than one major
defect but without Eisenmenger syndrome were classified as complex. Data on clinical status
were obtained from medical records. Data on overall mortality were retrieved from the Office
for National Statistics, which registers all United Kingdom deaths. The cause of death was
established from medical records and death certificates, available for all patients, by one
investigator (G-P. D.). Where the likely immediate cause of mortality remained unclear, the
case was discussed with one the co-principal investigators (A.K.) and consensus was reached.
In addition, the records of the deceased patients were cross checked with data from the local
surgical and interventional audit database to ascertain that no perioperative death was missed.
As this was a retrospective analysis based on data collected for routine clinical care and
administrative purposes (UK National Research Ethics Service guidance), individual
informed consent was not required. The study was locally registered and approved.
Statistical Analysis
Continuous variables are presented as mean±standard deviation or median and interquartile
range (IQR), while categorical variables are presented as number (percentage). The
association between various causes of mortality and age was assessed using logistic
regression analysis and spine plots are produced to illustrate the results. To estimate
standardized mortality ratios (SMRs) compared to an age and gender matched sample of the
general population the method reported by Finkelstein et al. was used. Survival was
compared to that predicted for an age- and gender-matched healthy cohort of UK residents
4
using life table data (2007-2009 interim life tables) published by the Government Actuary's
Department (http://www.gad.gov.uk), as previously described.8 ‘Equivalent’ age was defined
as the age of UK population with the most similar 5-year mortality (i.e. minimal sum of
absolute differences). Statistical analyses were performed using R-package version 3.0.2 9. A
two-sided P-value of <0.05 was considered indicative of statistical significance.
Results
Demographics and mortality
We included 6,969 patients (49.9 % females) under active follow-up at our institution as
illustrated in Table 1. The mean age at baseline was 29.9±15.4 years. Overall, 69%, 26%, and
5% of patients were in the NYHA functional class I, II, and III/IV, respectively. According to
the Bethesda disease complexity classification 52 % of patients had simple defects, 33%
moderate and 15% complex defects.
During a median follow-up time of 9.1 years (IQR 5.2-14.5; corresponding to a total of
70,967 patient-years), 524 (7.7%) patients died yielding a mortality rate of 0.72%/patientyear.
The majority of patients (429; 81.9%) died outside hospital, whereas the remainder died in
our institution or within 24h from discharge. Death occurred after an elective or emergency
cardiac operation in 25 patients (Fontan-revision/conversion related surgery in 6, tricuspid
valve surgery in 5, pulmonary valve replacement in 4, aortic surgery in 4, and other/complex
surgery in 5). In addition, one Eisenmenger patient died early after heart-lung transplantation,
whereas 4 patients succumbed to complications related to cardiac interventional procedures.
5
Table 2 provides an overview over the causes of death in this population. It illustrates that the
leading cause of mortality in our cohort was chronic cardiac failure, followed by pneumonia
and sudden cardiac death. Remarkably, cardiac surgery/cardiac intervention related mortality
ranked only 5h in this statistic, after pneumonia and cancer. The same table also demonstrates
the relatively high proportion of patients dying from non-cardiac causes such as cancer, major
bleeding (56% cerebral, 19% pulmonary, 11% gastrointestinal), infection or cerebrovascular
events. In addition, we provide the percentage of patients dying due to aortic dissection or
hepatic failure, both, recognized causes of mortality in selected subgroups of patients with
CHD.
With increasing patient age, the proportion of patients dying due to cardiac reasons decreased
and, by implication, proportionally more patients died due to competing non-cardiac causes.
This was especially evident for cancer and pneumonia related deaths (Figure 1, Table 3.).
Regarding reasons for cardiac death, a negative association was seen between age and sudden
cardiac death or cardiac surgery/intervention related mortality, while the risk of acute
myocardial infarction related mortality increased with age (see Table 3).
Survival in the entire ACHD cohort was significantly worse compared to the expected
mortality for an age and gender matched sample from the general UK population
(SMR=2.29, 95% CI=2.08-2.52, Logrank P<0.0001). There were, however, significant
differences in mortality between subgroups of patients (Logrank P<0.0001; see Figure 2 and
Supplemental-Figure A). The SMR was highest in patients with Fontan circulation
(SMR=23.4, 95% CI 16.0-34.3, P<0.0001), complex CHD (SMR=14.1, 95%CI 10.7-18.6,
P<0.0001) and Eisenmenger syndrome (SMR=12.8, 95% CI 9.7-16.9, P<0.0001). In contrast,
no significant difference in mortality was present in patients with ductus arteriosus and atrial
6
or uncomplicated ventricular septal defects when compared to the general UK population
(P>0.05, for all). The SMRs based on the Bethesda classification10 were 1.3 [95% CI 1.1 1.5], 2.2 [95% 1.8-2.3], and 10.9 [95% 9.3-12.8] for patients with simple, medium
complexity and complex heart defects (P<0.001 for all). In addition, NYHA functional class
was associated with prognosis for the overall cohort. The SMR increased from 1.6 (95% CI
1.3-1.9, P<0.0001) for class 1, to 3.6 (95% CI 3.0-4.2, P<0.0001) for class 2 and 4.6 (95% CI
3.6-6.0, P<0.0001) for class 3 or 4.
Based on the fitted SMR models we calculated predicted 5-year risk of death for each
diagnostic subgroup for hypothetical 40-year old patients with congenital heart disease. These
mortality risks were compared to the projected risk of the general population to obtain an
‘equivalent age’ with regards to mortality risk for each ACHD subgroup (Figure 3). For
example, a 40-year old average patient with Fontan physiology from our cohort had a 5-year
risk of death (18.0 % [95% CI 11.9-24.6%]) comparable to that of a 75 year-old person
without CHD. In addition, Figure 4 illustrates the ‘equivalent age’ for the different diagnostic
groups and various ages in comparison to that observed in persons without congenital heart
disease.
7
Discussion
Our data provides a contemporary overview over the causes of mortality in ACHD
patients followed at a large, established supra-regional centre. In comparison with
previous reports a shift from perioperative death to long term cardiac and especially
non-cardiac mortality was evident. Moreover, long term survival prospects of
patients with simple, isolated congenital defects were found to be excellent and not
statistically different from those expected in the general UK population. In contrast,
patients with uncorrected, palliated, complex or cyanotic underlying heart defects
continue to be afflicted by substantial mortality. In addition, mortality rates in
various diagnostic subgroups were compared with the mortality observed in the
general population. To illustrate survival prospects, we introduce the concept of
‘equivalent age’. We contend that this may aid counselling of patients by projecting
mortality risks for individual diagnostic subgroups compared to what is naturally
expected at older age.
Previous studies have investigated primary causes of mortality in ACHD patients;
these studies were different from the present report either because they referred to
historical ACHD cohorts or because they represented registry studies including
patients followed-up at numerous institutions. Oechslin and Connolly have described
the circumstances of death in ACHD patients under follow-up at two large supraregional Canadian and US centres (Toronto and Mayo clinic) in the 1980s and early
1990s, respectively.4,11 They reported a perioperative mortality of 18% and 37.7%, in
what are now historic cohorts. These mortality rates were largely consistent with the
proportion of patients dying perioperatively (26.3%) reported by Nieminen et al. as
part of a population based Finnish study (albeit the latter study included also
children).12 In contrast, our data suggests that the focus of ACHD mortality has
8
nowadays shifted to long-term cardiac and non-cardiac complications of the disease.
Moreover, the perioperative mortality reported here is even lower compared to
results from a recent Dutch national registry (7.1% perioperative deaths between
2002 and 2008),6 supporting the role of concentrating care at tertiary ACHD
centres.7 The proportion of patients dying from heart failure in our study is, however
similar to that seen in previous studies.4,5,12 It is likely that frequency of heart failure
is increasing in ACHD patients,13 and - given the increasing complexity of disease as
well as the growing incidence of co-morbid conditions - more patients present with
advanced forms of heart failure. On the other hand, progress in the management of
advanced heart failure in ACHD has been slow and arguably unsatisfactory. The fact
remains that standard heart failure therapy has still an unproven and possibly
limited effect in this heterogeneous group of patients,14-16 while novel therapeutic
options such as cardiac resynchronization therapy and assist systems have had a
limited uptake so far. In contrast, sudden cardiac death rate was lower in the present
study compared to previous reports, probably as a result of better risk stratification1719
and more liberal use of implantable cardiac defibrillators in the current era.20 The
most remarkable finding, however, was the large proportion of patients dying due to
non-cardiac complications, including cancer, cerebrovascular disease, infection and
pneumonia. This is consistent with previous data published by Khairy, Afilalo and
our group.20-22 The main causes of mortality are changing, presumably as a
consequence of the aging ACHD population. Similar to these previous studies we
could confirm that, with increasing age, the proportion of ACHD patients
succumbing to myocardial infarction increases. However, we could not confirm that
acute myocardial infarction (AMI) is becoming the leading cause of death with
advanced age, neither in our cohort as whole, nor in non-cyanotic patients, or in any
9
specific subgroup of patients. This is in contrast to a population-based US study,
reporting AMI as the leading cause of death in elderly non-cyanotic ACHD patients.23
It is not surprising that survival prospects of ACHD patients are inferior to those
observed in the general population. However, Figure 2 illustrates that especially
Fontan, Eisenmenger syndrome and complex CHD patients have greatly increased
mortality rates. In contrast, simple defects were not found to fare significantly worse
in terms of survival compared to the general population. We believe our findings are
a testimony to the advances in the CHD field, but also demonstrate the challenges
which lie ahead and the areas in which future research efforts need to be intensified.
Discussing life expectancy issues and short-to-mid-term risks of death with patients
can be challenging. Beyond, obvious psychological barriers and anxiety associated
with this difficult subject, there may also be inherent difficulties in understanding
risks. Patients are normally unfamiliar with statistical concepts such as hazard ratios
or standardized mortality rates. In addition, although an X-fold increased mortality
rate may sound high in relative terms, it may still be negligible in absolute numbers.
Furthermore, absolute annual mortality rates are generally low in young people and
therefore fractions are commonly employed to illustrate risk of death (e.g. a 20-year
old UK female has annual risk of death of 1/5,130). While the meaning of this ratio
may seem obvious to the reader, it may not be so for many patients.24 In fact, a recent
study on statistical numeracy amongst people in the US and Germany, showed that
24.7-28.2% of patients were unable to correctly answer the question “Which of the
following numbers represents the biggest risk […]? 1 in 100, 1 in 1000, or 1 in 10?”.25
One of the key deliverables of our report is, therefore, the information on ‘equivalent
age’: survival prospects for ACHD patients can be illustrated by comparison to the
general population. Thus, an average 40-year old patient with a Fontan-type
circulation in our study had a mortality rate comparable to that of 75 year old
10
individuals in the general population. We contend that, unlike SMRs and Cox
regression-model derived hazard ratios, these numbers may be useful for counselling
patients as they are more intuitive than mortality rates. Furthermore, unlike
percentages or ratios of mortality ‘equivalent ages’ implicitly express the stochastic
nature of such estimates. However, equivalent ages presented here apply to large,
heterogeneous diagnostic cohorts and do not account for anatomical and clinical
differences within subgroups, which may influence survival. This is discussed further
in the Limitations section.
Strength of the current report
To the best of our knowledge, the current report represents the largest single centre
study assessing the causes of mortality in contemporary patients (70,967 patientyears vs. 25,900 patient years in a previous nationwide registry study). This is
explained by the relatively long history and the well-established nature of our centre.
Compared to a previously published national registry database (6,933 patients, 197
deceased)5 and a pan-European registry study (4,110 patients, 115 deceased),26 a
group of 524 deceased patients formed the statistical basis of the current report. In
addition, unlike registry data we had access to the entire medical/surgical database
of the patients and could clarify equivocal information based on original medical
records. This approach has been described to improve data quality and reliability of
mortality data in the setting of ACHD.27 The mortality data presented here is based
on official death certificates complemented by additional information available to us
and should, therefore, provide robust estimates of the causes of mortality. A further
theoretical advantage of this single centre study is the consistent approach with a
shared diagnostic and therapeutic strategy employed over time.
11
Limitations
As this represents a single centre retrospective study, the sample of patients included
may not necessarily represent the pattern of ACHD patients present in the
community. Studying long-term outcomes of community based ACHD patients is,
therefore, a recognized strength of registry based studies. Like all similar studies, the
distinction between the primary cause of death is not always unequivocal (e.g.
pneumonia, which may be a consequence of cardiac pulmonary congestion).
However, all causes of deaths were checked for plausibility through comparison with
our clinical database and especially the data on surgical mortality is cross validated
with information from our clinical / official surgical audit to improve data quality
and minimize the number of patients with death due to unspecified reasons. The
proportion of patients dying perioperatively is not equivalent to surgical mortality.
Formally, the former is a function of surgical mortality, competing risks of deaths
and the number of operations performed. Therefore, this parameter cannot be
compared directly with other studies reporting specifically surgical mortality rates.
However, it can be compared to previous studies investigating circumstances of
death in ACHD patients, in general, using the same metric.4,5,12
Estimates of mortality provided herewith and "equivalent ages" correspond to
"average patients" stratified by diagnosis. Individual patients are likely to exhibit
different mortality to the group estimate, depending on additional factors specific to
each patient. For example, while a high mortality and equivalent age was estimated
for the "Fontan cohort", younger patients with total cavopulmonary connection and
those with a morphologically left systemic ventricle are likely to have a much better
outcome compared to older patients with an atriopulmonary Fontan or a
morphologically right ventricle. While our paper provides guidance in terms of
12
expected survival, clinicians should complement this with up-to-date clinical
information and their expertise before prognosticating on individual patients for
clinical or insurance purposes.
Conclusions
The current report confirms that ACHD patients continue to be afflicted by increased
mortality compared to general population as they grow older. Highest mortality rates
were observed amongst patients with complex ACHD, Fontan physiology an
Eisenmenger syndrome. Our contemporary data show a clear shift from
perioperative to chronic cardiac mortality and non-cardiac death.
13
Acknowledgements
Dr Kempny was supported by the Deutsche Herzstiftung e.V. Prof Gatzoulis and the Adult
Congenital Heart Centre and National Centre for Pulmonary Hypertension have received
support from the Clinical Research Committee and the British Heart Foundation. This
project was supported by the NIHR cardiovascular Biomedical Research Unit at the Royal
Brompton and Harefield NHS Foundation Trust and Imperial College London. Sonya V.
Babu-Narayan is supported by an Intermediate Clinical Research Fellowship from the
British Heart Foundation (FS/11/38/28864).
14
Table 1. Demographics and baseline characteristics.
Diagnosis
n
Female
%
Deceased
n (%)
Age at
baseline
years
Follow-up time
years
NYHA*
% I/II/III/IV
ASD
1,092
61.3
66 (6.2)
39.8±18.3
8.2±6.0
69/28/3/0
PDA
117
77.8
2 (1.7)
32.8±16.4
8.7±6.4
84/11/5/0
VSD
713
50.6
19 (5.9)
26.1±12.5
10.4±6.5
85/12/3/0
Marfan syndrome
296
43.6
23 (7.8)
32.0±14.5
8.4±5.7
93/7/0/0
Valvar disease
1442
44.7
85 (5.9)
29.9±15.6
11.7±7.0
76/20/4/0
Aortic Coarctation
860
41.3
39 (4.6)
28.9±14.3
10.6±6.5
88/11/1/0
Ebstein
153
54.9
19 (12.6)
34.5±16.2
9.4±6.2
51/41/8/0
AVSD
255
57.6
15 (5.9)
29.1±14.8
10.5±6.2
70/26/3/0
Tetralogy of Fallot
869
45.9
54 (6.3)
26.8±13.1
11.5±7.0
68/29/3/0
TGA arterial switch
171
30.5
3 (2.4)
17.0±4.4
8.6±4.2
76/21/3/0
Systemic RV
279
46.0
34 (12.5)
27.6±12.4
10.8±6.7
61/30/8/0
Complex CHD
265
52.7
67 (25.8)
24.2±10.1
11.6±6.4
36/55/9/1
Eisenmenger
277
63.5
64 (23.4)
30.6±12.3
10.3±6.5
4/56/38/1
Fontan
180
53.3
34 (19.2)
21.4±7.4
10.6±6.3
43/52/5/0
6,969
49.9
524 (7.7)
29.9±15.4
10.4±6.6
69/26/5/0
All patients
ASD = atrial septal defect, AVSD = atrioventricular septal defect, CHD = congenital heart
disease, NYHA=New York Heart Association Functional Class, PDA = patent ductus
arteriosus, RV = right ventricle, TGA = transposition of the great arteries, VSD =
ventricular septal defect.
15
Table 2. Distribution of causes of death in different diagnostic subgroups and the ACHD overall population.
nk
Ra
1
2
3
4
5
6
7
8
9
10
*
**
e
us
Ca
Heart failure
Pneumonia
Sudden cardiac death
Cancer
Cardiac Surgery/Intervention
Haemorrhage
Sepsis/Infection
Cerebrovascular
Acute myocardial infarction
Endocarditis
n
io
at
ct
r
oa
cc
rti
D
o
A
AS
31%
28%
8%
17%
11%
14%
11%
2%
8%
6%
8%
8%
8%
6%
5%
-
Aortic dissection
Hepatic failure
11%
-
of
h
at
de
2%
5%
e
pl
HD
xC
57%
7%
14%
7%
7%
7%
-
m
Co
57%
2%
11%
5%
8%
6%
3%
2%
in
ste
Eb
38%
13%
19%
6%
6%
6%
-
-
6%
SD
AV
m
en
Eis
45%
16%
9%
2%
9%
3%
5%
2%
-
r
ge
en
an
nt
Fo
52%
13%
3%
19%
3%
3%
-
n
fa
ar
M
30%
5%
5%
25%
5%
5%
10%
3%
5%
-
m
ro
nd
sy
e
RV
ic
em
t
s
Sy
A*
PD
50%
50%
-
66%
13%
9%
3%
3%
-
-
3%
g
lo
f
yo
t
llo
Fa
w
ls
ria
te
r
a
h
itc
Te
40%
18%
6%
4%
12%
8%
8%
4%
A
TG
33%
33%
-
lvu
Va
40%
17%
6%
2%
1%
7%
4%
7%
1%
-
-
1%
1%
tra
d
lar
e
as
ise
n
ie
at
lp
l
A
D
VS
39%
6%
11%
22%
11%
11%
-
42.5%
10.2%
7.0%
6.3%
6.1%
5.5%
4.5%
4.1%
2.7%
1.6%
-
1.4%
1.4%
ts
ASD = atrial septal defect, AVSD = atrioventricular septal defect, CHD = congenital heart disease, PDA = patent ductus arteriosus, RV = right
ventricle, TGA = transposition of the great arteries, VSD = ventricular septal defect.
16
Table 3. Results of the logistic regression analysis investigating the association between age and various causes of death. Oddsratios of cause specific death are presented. Odds-ratios and 95% confidence intervals are per decade of age, respectively.
Mode of death
Heart failure
Pneumonia
Sudden cardiac death
Cancer
Haemorrhage
Cardiac Surgery/Intervention
Sepsis/Infection
Cerebrovascular event
Acute myocardial infarction
Odds-ratio
95% confidence interv.
P-value
0.945
1.761
0.642
1.838
0.921
0.725
1.070
1.194
1.951
0.864 - 1.032
1.515 - 2.053
0.513 - 0.786
1.523 - 2.232
0.746 - 1.123
0.559 - 0.912
0.860 - 1.327
0.959 - 1.149
1.452 - 2.678
0.21
<0.0001
<0.0001
<0.0001
0.428
0.009
0.54
0.112
<0.0001
17
Figure Legends:
Figure 1. Spine plots illustrating the distribution of various circumstances of death with age. The Figure illustrates that the proportion of cardiac
death (dark area) decreases with increasing age, while the likelihood of non-cardiac mortality increases (light area). An exception are acute
myocardial infarction (AMI) related deaths, which becomes more likely as patients age. The dotted blue lines present the predicted proportions
for heart failure, sudden cardiac death and perioperative mortality based on the results of the logistic regression analysis, while the red dotted
lines show the predicted values for cardiac death, cancer related death, pneumonia death and AMI related mortality. In addition, odds-ratios
[OR] and 95% confidence intervals [CI] are provided.
Figure 2. Standardised mortality ratios (SMR) in various subgroups of patients. Points present the SMR, and horizontal lines the 95%
confidence-interval range. An SMR of 1 suggests that patients have comparable mortality as a gender and age matched sample from the general
population.
Figure 3. Projected 5 year mortality rates for 40-years old ACHD patients compared to that expected for the general UK population based
on the results of the SMR analysis. Points present the estimated mortality within 5-years (on the x-axis) and also indicate the ‘equivalent
age’ – expressed as the age of subgroup of UK population with the most similar 5-years mortality (y-axis). Red lines represent 95%
confidence intervals for the 5-years mortality. The black curve presents 5-years mortality for the UK-population based on life table data.
Figure 4. Mortality in subgroups of patients compared to mortality in age matched UK-population. Numbers on the colored surface present the
‘equivalent age’ – expressed as the age of subgroup of UK population, having similar 5-years mortality rates. Colors reflect the difference
between the “relative age” and the “actual age” of patients.
18
Figure 1.
19
20
Figure 2.
21
22
Figure 3.
23
24
25
Figure 4.
ASD
Valvar disease
VSD
Aortic Coarctation
AVSD
Marfan syndrome
Tetralogy of Fallot
TGA arterial switch
Ebstein anomaly
Systemic RV
Eisenmenger syndrome
Complex CHD
Fontan
20
25
29
28
32
33
37
37
38
42
46
57
58
64
25
26
31
30
33
34
38
38
39
43
48
58
59
65
Patient's age (years)
30 35 40 45 50
32 38 42 47 52
36 40 45 49 54
36 40 44 49 53
38 43 47 52 56
39 44 48 52 57
42 46 50 54 59
42 47 50 54 60
44 48 52 56 61
47 51 54 59 63
51 55 59 63 67
62 65 69 73 77
63 67 70 74 78
68 72 75 78 82
55
57
59
59
62
62
64
65
66
68
72
81
82
86
60
61
63
63
66
66
68
69
70
72
76
84
85
91
Age difference:
>40
30-40
20-30
10-20
5-10
2-5
<2
Values present relative age adjusted for predicted 5-years mortality. Colors
reflect the difference between relative and actual age. For example a 40 year old
Fontan patient has a mortality rate that is comparable to that of a 75 year old
individual without CHD.
26
Supplemental – Figure A
Kaplan Meier survival curves compared to expected mortality of an age and gender matched sample from the general UK population stratified
by diagnostic group. SMR = standardized mortality rates.
27
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