Download Risk Factors for Mortality among Patients with Nonperinatal

MAJOR ARTICLE
Risk Factors for Mortality among Patients
with Nonperinatal Listeriosis in Los Angeles
County, 1992–2004
Ramon E. Guevara,1 Laurene Mascola,1 and Frank Sorvillo2
1
Acute Communicable Disease Control Program and 2Office of Vital Records, Los Angeles County Department of Public Health,
Los Angeles, California
Background. Listeriosis is a relatively rare foodborne disease with significant public health implications. The
causative pathogen, Listeria monocytogenes, grows well in refrigeration, is associated with a case-fatality rate of
20%, and causes an estimated 28% of all foodborne disease–related deaths. Nevertheless, data on the risk factors
for listeriosis mortality are limited.
Methods. Using the passive surveillance listeriosis database of the County of Los Angeles Department of Public
Health, we conducted a 13-year retrospective cohort study to describe nonperinatal listeriosis mortality in Los
Angeles County during the period 1992–2004. A nonperinatal listeriosis case was defined as one occurring in a
nonpregnant person 142 days of age who resided in Los Angeles County and had a culture positive for L.
monocytogenes.
Results. Unconditional multivariable logistic regression analysis of 281 nonperinatal listeriosis cases with 29
main effects variables resulted in finding nonhematological malignancy (odds ratio [OR], 5.92; 95% confidence
interval [CI], 1.85–18.9), alcoholism (OR, 4.63; 95% CI, 1.36–15.8), age ⭓70 years (OR, 3.44; 95% CI, 1.50–7.87),
steroid medication (OR, 3.34; 95% CI, 1.38–8.08), and kidney disease (OR, 2.94; 95% CI, 1.18–7.31) to be
statistically significant risk factors for mortality. Other listeriosis mortality risk factors with adjusted odds ratios
11.5 included blood transfusion, asthma, black race, Asian race, use of antibiotics, hypertension, receipt of chemotherapy, and Hispanic race. Patients admitted to the hospital with a diagnosis of sepsis alone had the highest
mortality (23.7%), whereas patients with cases of meningitis alone had the lowest mortality (3.13%).
Conclusions. The findings of this study should be used to help researchers and clinicians focus on specific
risk factors to prevent nonperinatal listeriosis–related deaths.
Listeriosis is a foodborne disease caused by the bacterium Listeria monocytogenes. Although L. monocytogenes
is a ubiquitous pathogen in the environment, it is a
rare cause of human illness, compared with other foodborne pathogens. However, infection can lead to severe
disease, including sepsis, meningitis, stillbirth, and
death. L. monocytogenes is associated with a case-fatality
rate of 20%, which is second only to that associated
with Vibrio vulnificus (39%), and it causes an estimated
Received 17 October 2008; accepted 3 February 2009; electronically published
27 April 2009.
Reprints or correspondence: Dr. Ramon E. Guevara, Acute Communicable
Disease Control, 313 N. Figueroa St., Rm. 212, Los Angeles, CA 90012
([email protected]).
Clinical Infectious Diseases 2009; 48:1507–15
2009 by the Infectious Diseases Society of America. All rights reserved.
1058-4838/2009/4811-0003$15.00
DOI: 10.1086/598935
28% of all foodborne disease–related deaths, which is
second only to the amount attributable to nontyphoidal
Salmonella (31%) [1]. Listeriosis mortality unrelated to
pregnancy has been estimated at 35% in the United
States [2] and as high as 44% in other countries [3–
7].
L. monocytogenes, which is an opportunistic and intracellular pathogen, usually causes disease among people with immature or compromised immune systems,
particularly infants, pregnant women, elderly individuals, and persons receiving immunosuppressive medication [6, 8–13]. Previously identified risk factors for
invasive listeriosis include advanced age [8, 14–16],
cancer [3, 5, 12, 16, 17], receipt of immunosuppressive
therapy (such as steroid medication) [8, 12, 15–20],
alcoholism [3, 15, 16, 21], renal disease [3, 5, 12, 15–
17, 19, 20, 22], liver disease [3, 5, 10, 15, 16, 23–26],
Nonperinatal Listeriosis Mortality • CID 2009:48 (1 June) • 1507
Table 1. Demographic and clinical characteristics of 285 patients with nonperinatal listeriosis and known survival outcome,
Los Angeles County, 1992–2004.
Variable
No. (%)
of patients
Age, years
!5
5–14
2 (0.70)
6 (2.11)
15–34
35–44
28 (9.82)
21 (7.37)
45–54
55–64
33 (11.6)
43 (15.1)
65–74
⭓75
75 (26.3)
77 (27.0)
Race and ethnicity
Asian
Black
Hispanic
White
Sex
Male
Female
30 (10.5)
30 (10.5)
65 (22.8)
160 (56.1)
157 (55.1)
128 (44.9)
Infection type
Bacteremia (asymptomatic)
Sepsis only
Meningitis only
Sepsis and meningitis
Infection other than sepsis or meningitis
2
198
32
25
(0.70)
(69.5)
(11.2)
(8.77)
28 (9.82)
hemochromatosis [8, 16, 27], anemia [8, 16, 23, 28], diabetes
mellitus [3, 5, 12, 15, 16, 21, 28], antacid use [15, 28–30],
antibiotic use [28], and other factors that can decrease immunity in the intestine or throughout the body [2, 16, 31].
Few data exist on risk factors for mortality associated with
L. monocytogenes infection. Using the Los Angeles County
(LAC) surveillance database for the period 1992–2004, we assessed risk factors for listeriosis-related death among individuals with nonperinatal cases.
PATIENTS, MATERIALS, AND METHODS
Sources of data. The Acute Communicable Disease Control
Program of the LAC Department of Pubic Health has conducted surveillance for listeriosis since the large Southern California outbreak in 1985 [32]. The Acute Communicable Disease Control Program passive surveillance system receives case
reports from health care providers, hospitals, and laboratories
throughout the county, because they are all required to report
listeriosis by an LAC mandate. These reporting sources or their
diagnostic laboratories send Listeria isolates to the LAC Public
Health Laboratory (Los Angeles, California) for confirmation
by conventional biochemical methods [33]. During case in1508 • CID 2009:48 (1 June) • Guevara et al.
vestigations, medical professionals complete standardized epidemiology forms and case abstraction forms.
With use of available paper documents archived at the Acute
Communicable Disease Control Program, which included epidemiology forms, case abstraction forms, patient history and
physical notes, laboratory reports, and death certificates, we
confirmed that database case records met the Acute Communicable Disease Control Program surveillance criteria of laboratory-confirmed isolation of L. monocytogenes and patient
residency in LAC, and we verified survival outcome, risk factors,
and dates of disease onset, specimen collection, diagnosis, hospital admission, birth, and death.
Definitions. Positive culture of L. monocytogenes from a
normally sterile body site or from a stool culture obtained
during a listeriosis outbreak defined a listeriosis case. A nonperinatal listeriosis case was defined as occurring in a nonpregnant case patient 142 days old. Listeriosis mortality was
defined by a confirmed death without documented evidence
of recovery or clearing of infection or by listeriosis being listed
as a cause or contributory cause of death. All case survivors
recovered or had culture results negative for L. monocytogenes.
Infection type was categorized into mutually exclusive
groups, as follows: bacteremia, sepsis only, meningitis only,
sepsis and meningitis, and other infections. Bacteremia was
defined as present in a patient with positive blood culture results
but no symptoms, whereas sepsis was defined present in a
patient with a positive blood culture result with any symptoms
of illness (e.g., fever, chills, abdominal pain, diarrhea, vomiting,
backache, and headache). Meningitis was defined as present in
a patient with a positive cerebrospinal fluid (CSF) culture result.
Other infection was defined as having symptoms and a positive
culture result obtained for a site other than blood or CSF.
Racial and ethnic groups were case-defined as mutually exclusive groups of Asian, black, Hispanic, and white. Preexisting
risk factors that were routinely asked about on epidemiology
forms included chronic alcoholism, gastrointestinal disease, autoimmune disorder, history of organ transplant, asthma, kidney
disease, chronic lung disease, liver disease, iron overload, cancer, diabetes, human immunodeficiency virus (HIV) infection,
AIDS, intravenous drug use, age ⭓65 years, receipt of antibiotics, receipt of chemotherapy, receipt of radiation therapy,
receipt of chemoradiation, receipt of steroids, receipt of other
immunosuppressive therapy, use of antacids, use of folk medicine, and history of gastric surgical procedures. Preexisting risk
factors preceded onset of listeriosis. The presence of these factors was primarily defined by reporting physicians and infection-control professionals and was secondarily defined by medical chart review. Patients with AIDS, by definition, had HIV
infection. The definition of lung disease did not include asthma.
Receipt of chemoradiation was defined as receipt of both chemotherapy and radiation therapy.
Figure 1. Survival outcome and mortality among 285 patients with nonperinatal listeriosis, Los Angeles County, 1992–2004. A total of 53 patients
died (black bars), and 232 patients survived (gray bars). The black line with black diamond markers indicates mortality, expressed as a percentage.
Analysis. In addition to calculating crude relative risks
(RR) of mortality, we performed unconditional multivariable
logistic regression to estimate adjusted odds ratios (OR) and
95% confidence intervals (CIs) for nonperinatal listeriosis mortality. Through causal modeling [34, 35] based on biological
plausibility, prior knowledge, and available data, we established
a 29-variable main effects model. Reference groups for sex, age,
and race and ethnicity were female sex, age !70 years, and
white, respectively. Age, sex, and race and ethnicity were assumed to be possible confounders for any preexisting risk factor. In addition, sex and race and ethnicity were considered to
be confounders for age. Various interaction terms were explored, such as age and race and ethnicity; age and sex; sex and
race and ethnicity; age, sex, and race and ethnicity; cancer and
steroid use; cancer and receipt of nonsteroid cancer treatments;
receipt of steroids and receipt of antibiotics; diabetes and heart
disease or hypertension; kidney disease and receipt of transfusion; cancer and age; and cancer and race and ethnicity.
For each risk factor, adjusted OR estimates were compared
between the main effects model and a smaller multivariable
logistic regression model that focused on the risk factor and
possible confounders. These results will not be presented here,
but most of the adjusted OR estimates were very similar between models. Data management and analysis were performed
using Microsoft Access, Microsoft Excel, and SAS, version 9.1
(SAS).
RESULTS
Study population. More than one-half of the study population (53.3%) was ⭓65 years of age (table 1). The predominant
race was white (56.1% of patients). There were slightly more
male patients (55.1%) than female patients (44.9%). The most
common infection type was sepsis only (69.5% of patients).
With the exception of 7 patients with outbreak cases that occurred in 2001 (from the only outbreak that occurred during
the study period) and a blood donor, all patients were hospitalized, and 90% of patients had invasive disease.
Mortality. Of 285 cases of nonperinatal listeriosis with
known survival outcome that occurred during the period 1992–
2004, 53 (18.6%) resulted in death. The annual number of
deaths ranged from 2 to 9, and annual mortality ranged from
7.41% to 31.0% (figure 1). Fewer deaths were observed over
time; the median number of annual deaths was 5 for the period
1992–1998 and 2 for the period 1999–2004. In addition, mean
annual mortality was 22.0% for 1992–1998 and 13.3% for
1999–2004.
Mortality was highest for patients with sepsis only (47
[23.7%] of 198 cases ended in death; median age, 68.5 years).
Mortality was 12.0% for patients with both sepsis and meningitis (3 of 25 cases ended in death; median age, 62 years),
7.14% for patients with other infections (2 of 28 cases ended
in death; median age, 62 years), and 3.13% for patients with
meningitis only (1 of 32 cases ended in death; median age, 56.5
years). Neither of the 2 cases of bacteremia ended in death
(median age, 67 years).
Demographic risk factors. Nonperinatal listeriosis mortality for male patients was 19.8% (31 of 157 male patients died)
and 17.2% for female patients (22 of 128 female patients died).
Compared with female patients, male patients had a crude RR
of death of 1.15 (95% CI, 0.70–1.88).
In general, nonperinatal listeriosis mortality increased with
age (table 2) and was highest for patients 65–74 years of age
Nonperinatal Listeriosis Mortality • CID 2009:48 (1 June) • 1509
Table 2. Mortality among 285 patients with nonperinatal listeriosis, Los
Angeles County, 1992–2004.
Age, years
!5
5–14
15–34
35–44
No. (%)
of patients
(n p 285)
No. of
deaths
Mortality, %
RR of mortality (95%
confidence interval)
2 (0.70)
6 (2.11)
0
0
0.00
0.00
…
…
28 (9.82)
21 (7.37)
4
1
14.3
4.76
1.00
0.33 (0.04–2.77)
45–54
55–64
33 (11.6)
43 (15.1)
5
7
15.2
16.3
1.06 (0.31–3.57)
1.14 (0.37–3.54)
65–74
⭓75
75 (26.3)
77 (27.0)
15
21
20.0
27.3
1.35 (0.49–3.71)
1.84 (0.69–4.89)
NOTE. RR, relative risk.
(20.0%) and patients ⭓75 years of age (27.3%). Compared
with patients !65 years of age, patients ⭓65 years of age had
a 1.85 times higher risk of death (95% CI, 1.09–3.14). Similarly,
compared with patients !65 years of age, patients ⭓75 years
of age had a 2.13 times higher risk of death (95% CI, 1.20–
3.79).
Analysis by race and ethnicity found mortality to be highest
among Asians (26.7%; 8 deaths among 30 cases), followed by
blacks (23.3%; 7 deaths among 30 cases), whites (17.5%; 28
deaths among 160 cases), and Hispanics (15.4%; 10 deaths
among 65 cases). With Hispanics as the reference group, the
crude RRs of nonperinatal listeriosis mortality were 1.73 (95%
CI, 0.76–3.95) for Asians, 1.52 (95% CI, 0.64–3.60) for blacks,
and 1.14 (95% CI, 0.59–2.21) for whites.
Preexisting risk factors. In bivariable analyses, nonperinatal listeriosis mortality was highest for patients with blood
transfusions (60.0%), patients with both hematological and
nonhematological malignancies (40.0%), patients with nonhematological malignancy (39.6%), patients who received radiation therapy (31.6%), patients with lung disease (30.0%),
patients with asthma (30.0%), patients with kidney disease
(29.6%), patients with hypertension (28.0%), patients with alcoholism (27.6%), patients with cancer (25.8%), and patients
with liver disease (25.7%) (table 3). When comparing patients
who had a specific preexisting risk factor with patients who
did not have that risk factor, crude RRs of mortality were
highest among patients with blood transfusions (3.36; 95% CI,
1.57–7.17), nonhematological malignancy (2.79; 95% CI, 1.74–
4.48), age ⭓70 years (1.99; 95% CI, 1.22–3.24), and kidney
disease (1.85; 95% CI, 1.12–3.07). Of 20 patients with cases of
nonperinatal listeriosis who had lung disease, 4 had lung cancer;
2 of these patients died. None of the 14 patients with nonperinatal listeriosis who did not have any recognized preexisting
risk factor died.
Multivariable modeling. With data from 281 patients with
nonperinatal listeriosis (data from 4 patients could not be used,
1510 • CID 2009:48 (1 June) • Guevara et al.
because their cancer could not be classified as hematological
or nonhematological), the 29-variable main effects multivariable logistic regression model had statistically significant adjusted ORs for nonhematological malignancy (adjusted OR,
5.92; 95% CI, 1.85–18.9), alcoholism (adjusted OR, 4.63; 95%
CI, 1.36–15.8), age ⭓70 years (adjusted OR, 3.44; 95% CI, 1.50–
7.87), receipt of steroid medication (adjusted OR, 3.34; 95%
CI, 1.38–8.08), and kidney disease (adjusted OR, 2.94; 95% CI,
1.18–7.31) (table 4). Other risk factors with adjusted ORs 11.50
included undergoing blood transfusion (adjusted OR, 6.80),
having asthma (adjusted OR, 4.60), black race (adjusted OR,
2.77), Asian race (adjusted OR, 2.70), receipt of antibiotics
(adjusted OR, 1.70), having hypertension (adjusted OR, 1.69),
receiving chemotherapy (adjusted OR, 1.66), and Hispanic race
(adjusted OR, 1.55). None of the interaction terms explored
were statistically significant; however, the effect estimate of the
interaction of receipt of steroid medication and antibiotic use
was strong (adjusted OR, 5.06; 95% CI, 0.86–29.7) and changed
the effect estimates for Asian race (adjusted OR, 3.04; 95% CI,
0.90–10.2), receipt of blood transfusion (adjusted OR, 8.61;
95% CI, 0.70 -105.9), receipt of chemotherapy (adjusted OR,
1.95; 95% CI, 0.52–7.39), and having both hematological and
nonhematological malignancies (adjusted OR, 2.20; 95% CI,
0.13–38.2).
DISCUSSION
With use of a multivariable logistic regression model to control
confounding and estimate the direct effects of several possible
causal risk factors, we found that nonhematological malignancy,
alcoholism, age ⭓70 years, use of steroid medication, and kidney disease have strong statistically significant associations with
nonperinatal listeriosis mortality. Other factors with strong but
not statistically significant associations with listeriosis mortality
were undergoing blood transfusion, having asthma, black race,
Asian race, and use of both steroid medication and antibiotics.
Table 3. Crude relative risks (RRs) of mortality among 285 patients with nonperinatal listeriosis, by preexisting risk
factors, Los Angeles County, 1992–2004.
No. of patients
(n p 285)
No. of deaths
(n p 53)
Risk, %
RR (95% CI)
113
30
26.5
1.99 (1.22–3.24)
139
30
21.6
1.37 (0.84–2.24)
Cancer
Hematological malignancy
Nonhematological malignancy
Both hematological and nonhematological malignancies
93
46
48
5
24
6
19
2
25.8
13.0
39.6
40.0
1.71
0.67
2.79
2.21
Steroid use
Receipt of radiation therapy
96
19
21
6
21.9
31.6
1.29 (0.79–2.11)
1.79 (0.88–3.64)
Receipt of chemotherapy
Receipt of chemoradiationb
50
12
24.0
1.38 (0.78–2.42)
9
2
22.2
1.20 (0.35–4.19)
Receipt of other immunosuppressive drug
History of organ transplant
Autoimmune disorder
Alcoholism
15
12
28
29
1
2
2
8
6.67
16.7
7.14
27.6
0.35
0.89
0.36
1.57
Asthma
Lung diseasec
10
3
30.0
1.65 (0.62–4.39)
20
6
30.0
1.69 (0.83–3.47)
Kidney disease
Liver disease
Diabetes
Antibiotic use
54
35
68
76
16
9
14
17
29.6
25.7
20.6
22.4
1.85
1.46
1.15
1.30
Gastrointestinal disease
Antacid use
25
24
2
3
8.00
12.5
0.41 (0.11–1.58)
0.65 (0.22–1.94)
HIV infection
AIDS
Oral iron intake
Otherd
13
7
9
1
0
1
7.69
0.00
11.1
0.40 (0.06–2.69)
No deaths
0.59 (0.09–3.80)
Hypertension
25
7
28.0
1.58 (0.80–3.13)
22
5
14
6
3
0
27.3
60.0
0.00
1.53 (0.74–3.17)
3.36 (1.57–7.17)
No deaths
Preexisting risk factor
Age ⭓70 years
Weakened immune systema
Heart disease
Receipt of blood transfusion
None (unknown)
(1.06–2.76)
(0.30–1.47)
(1.74–4.48)
(0.73–6.65)
(0.05–2.34)
(0.25–3.24)
(0.09–1.40)
(0.82–3.00)
(1.12–3.07)
(0.78–2.73)
(0.66–1.98)
(0.78–2.17)
NOTE. CI, confidence interval; HIV, human immunodeficiency virus.
a
Defined as having any of the following: autoimmune disorder, steroid use, receipt of chemotherapy, receipt of radiation, receipt of
chemoradiation, immunosuppressive drug use, history of organ transplant, HIV infection, or AIDS.
b
Defined as receipt of both chemotherapy and radiation therapy.
c
The definition of lung disease does not include asthma.
d
Preexisting risk factor designated but not routinely determined.
Our findings are supported by the 2 other published studies
on listeriosis mortality. Bennion et al. [36] showed a decreasing
trend in listeriosis mortality in the United States during the
period 1990–2005, higher listeriosis mortality rates among
Asians and blacks, increasing mortality rates with advancing
age, and adjusted OR estimates reflective of the ones that we
determined for kidney disease, diabetes, and liver disease. Our
measure for liver disease, however, would correspond to the
combination of their measures for liver and bile duct cancer,
liver disease, and viral hepatitis. In addition, their statistically
significant effect estimate for anemia suggests that the variable
for blood transfusion might demonstrate statistical significance
if data were available for a larger number of cases. The pop-
ulation-based study from Denmark for the period 1994–2003
by Gerner-Smidt et al. [37] also presented similar mortality
rates for all cases (21%) and for patients with bloodstream
infection (21%), and they reported similar bivariable results
for sex (RR, 1.0), alcoholism (RR, 1.5), hematological malignancy (RR, 0.59), nonhematological malignancy (RR, 2.0), and
diabetes (RR, 1.35).
The multivariable analysis of our study is unique, because it
is based on a comprehensive causal model that describes the
relationships among numerous risk factors for listeriosis. Gerner-Smidt et al. [37] published what is, to our knowledge, the
only other cohort study thus far, and their multivariable models
included serogroup and age, but they either aggregated most
Nonperinatal Listeriosis Mortality • CID 2009:48 (1 June) • 1511
Table 4. Odds ratios (ORs) from a 29-variable logistic regression model based on causal diagrams for
nonperinatal listeriosis mortality, Los Angeles County, 1992–2004.
No. of patients
(n p 281)
No. of deaths
(n p 52)
OR (95% CI)
112
30
3.44 (1.50–7.87)
Asian
28
7
2.70 (0.81–8.94)
Black
Hispanic
30
65
7
10
2.77 (0.81–9.47)
1.55 (0.58–4.12)
155
46
30
6
0.95 (0.44–2.05)
0.40 (0.08–1.98)
Nonhematological malignancy
Both hematological and nonhematological malignancies
48
5
19
2
5.92 (1.85–18.9)
1.36 (0.08–22.2)
Receipt of steroid medication
Receipt of chemotherapy
95
49
21
12
3.34 (1.38–8.08)
1.66 (0.46–5.92)
Receipt of radiation therapy
a
Receipt of chemoradiation
Receipt of other immunosuppressive drug
Autoimmune disease
19
9
6
2
0.89 (0.19–4.17)
0.42 (0.05–3.70)
15
27
1
2
0.28 (0.03–3.10)
0.26 (0.04–1.56)
HIV infection
History of organ transplant
13
12
1
2
0.53 (0.05–6.25)
0.88 (0.12–6.35)
Alcoholism
Asthma
Lung diseaseb
Kidney disease
27
10
20
54
7
3
6
16
4.63
4.60
1.37
2.94
Liver disease
Diabetes
34
66
8
14
1.45 (0.50–4.22)
1.01 (0.42–2.45)
Gastrointestinal disease
Antacid use
Receipt of antibiotics
Hypertension
25
24
76
25
2
3
17
7
0.50
0.29
1.70
1.69
Heart disease
Receipt of blood transfusion
Oral iron intake
Receipt of steroid medication and antibioticsc
22
4
9
6
2
1
1.36 (0.40–4.66)
6.80 (0.61–76.3)
0.18 (0.01–3.39)
38
11
5.06 (0.86–29.7)
Variable
Age ⭓70 years
Race and ethnicity
Male sex
Hematological malignancy
(1.36–15.8)
(0.81–25.9)
(0.39–4.78)
(1.18–7.31)
(0.09–2.65)
(0.06–1.28)
(0.73–3.96)
(0.47–6.02)
NOTE.Of 285 patients with a known survival outcome, 4 did not have enough information in their records for their cancer
to be classified as hematological or nonhematological. Therefore, the number of patients included in the multivariable analysis
is 281. The reference groups for age, race and ethnicity, and sex were age !70 years, white race, and female sex, respectively.
All variables except receipt of steroids and antibiotics were included in the main effects model. CI, confidence interval; HIV,
human immunodeficiency virus.
a
Defined as receipt of both chemotherapy and radiation therapy.
The definition of lung disease does not include asthma.
Addition of this interaction term to the main effects model only changed the effect estimates for Asian race and ethnicity
(OR, 3.04; 95% CI, 0.90–10.2), receipt of blood transfusion (OR, 8.61; 95% CI, 0.70 –105.9), receipt of chemotherapy (OR,
1.95; 95% CI, 0.52–7.39), and having both hematological and nonhematological malignancies (OR, 2.20; 95% CI, 0.13–38.2).
b
c
of the preexisting risk factors into one variable to represent the
presence of any preexisting risk factor or selected one preexisting risk factor of interest. Although this method of analysis
increases statistical power, it may oversimplify the causal relationships among risk factors and listeriosis mortality. Because
nonperinatal listeriosis cases can have a variety of different
preexisting risk factors, we accounted for confounders and intermediate factors as distinct variables in a single multivariable
model to estimate the direct effects of each specific risk factor
on mortality.
1512 • CID 2009:48 (1 June) • Guevara et al.
Biological plausibility and prior knowledge were the driving
factors of our analysis. Therefore, we did not seek to combine
or exclude variables on the basis of statistical significance, especially when patient counts were small. Such methods would
decrease the accuracy of effect measures and would add unnecessary assumptions to the analysis. Although our model
distinguishes the effects of documented risk factors for listeriosis on mortality, additional studies involving a greater number of cases and a comprehensive causal model are required to
provide more-exact estimates.
Because the variables that were associated with statistically
significant adjusted ORs in our analysis are fairly well recognized risk factors for listeriosis, we will not discuss their biological plausibility. However, these factors should be considered
in future research on listeriosis mortality.
Our results regarding the impact of blood transfusion,
asthma, black race, Asian race, receipt of cancer treatment, and
receipt of a combination of steroid medication and antibiotics
are intriguing and require additional research. Because iron is
a virulence factor in listeriosis and because iron overload and
hemachromatosis are disease risk factors [13, 27, 38–40], future
research should include measures on patient history of blood
disorders, donation and receipt of blood components, and receipt of dialysis. Only additional studies of how asthma might
cause listeriosis [41] will help to explain the strong adjusted
OR that we found for asthma. Although Bennion et al. [36]
had similar findings, researching social factors concerning
health care access, cultural perceptions, and tendencies to seek
care might elucidate why Asians and blacks have the highest
risks for listeriosis mortality. The cancer treatment variables—
receipt of steroid medication, chemotherapy, radiation, and
chemoradiation—show a diminishing causal effect on listeriosis
mortality. Regarding receipt of steroid medication and antibiotics, effect modification is possible, because antibiotics disrupt the intestinal flora and can allow L. monocytogenes to
proliferate, resulting in an enhanced opportunity to infect the
blood through the intestinal mucosa, whereas steroid medication suppresses cell-mediated immunity.
Of interest, we found that mortality was lowest among patients with meningitis only, was higher among patients with
both sepsis and meningitis, and was highest among patients
with sepsis only. Possible explanations for this finding, which
contrasts with that of the study by Gerner-Smidt et al. [37],
include differences in definitions for infection types, in diagnostic testing practices, and in the treatment of patients with
meningitis. Both studies lack data on antibiotic treatment.
However, a possible explanation is that antibiotic treatment is
more appropriate for patients with listeriosis who have meningitis only than it is for patients with other infection types,
particularly sepsis. L. monocytogenes is a primary suspect in
cases of bacterial meningitis, and treatment guidelines cite ampicillin for coverage [42]. However, such is not so in cases of
sepsis, and initial antibiotic treatment might not cover L. monocytogenes. Differences in median patient ages might also explain
differences in mortality by infection type.
Although the 3 studies of listeriosis mortality had similar
results, there are important differences regarding effect estimates of risk factors for mortality. The cohort studies support
each other, regardless of differences in statistical significance,
because differences stem from the different approaches in modeling the analysis. However, Bennion et al. [36] found lymphoid
and hematopoeitic cancer, HIV infection, systemic lupus erythematosus, and history of organ transplant to be strongly associated with listeriosis in death certificates. Conclusions from
their adjusted ORs require assumptions that the control subjects
represent the base population (i.e., the control subjects represent the case patients, such that, had the control subjects been
exposed to Listeria species, they would have been just as likely
to become case patients and to have died), consistency of coding
in death certificate data, high sensitivity and specificity of death
certificates in identifying listeriosis deaths and predisposing
conditions, and confounding only by age, race, sex, and HIV
infection status. Nevertheless, their findings are important, because they are biologically plausible and, except for lymphoid
and hematopoeitic cancer, the cohort studies might not have
involved a sufficient number of cases to show a strong (or even
positive) association in multivariable analyses. Thus, the variables that did not demonstrate strong or positive associations
in our multivariable analysis should still be considered to be
possible risk factors for death when assessing individual cases
of listeriosis.
Although these 3 studies have measures for specific risk factors, none of them have a measure for a person’s health status.
We looked at a number of risk factors as predictors for listeriosis
mortality, and we found no positive association. For this reason,
a measure for how sick or weakened a person is should be
established for more-accurate effect estimates of risk factors for
listeriosis mortality.
Our study has limitations. Laboratory-confirmed clearance
of L. monocytogenes was not always obtained; serogrouping was
not performed; antibiotic treatment data were not collected;
the presence and absence of preexisting risk factors was not
ascertained beyond the archived case records; and preexisting
blood transfusion, hypertension, and heart disease data were
not routinely collected, because they were not specified on the
standardized forms. In addition, data on kidney dialysis were
not collected. Given our findings regarding receipt of blood
transfusion, dialysis might be an important intermediate factor
in the causal pathway from kidney disease to death. Thus, the
adjusted OR for kidney disease might be different when dialysis
is accounted for. Types of cancer, diabetes, and lung disease,
as well as stage of cancer, were not distinguished; however, with
analysis of a large enough number of cases, they might show
different effects on mortality. For a few risk factors, small patient counts caused wide 95% CIs and unstable effect estimates
that could have been more easily affected by the number of
covariates in multivariable analyses. Because of the number of
risk factors that were considered in this study, another concern
was finding a statistically significant association by chance as a
result of multiple comparisons, despite the consideration of
causal relationships and the results of bivariable analyses. Finally, causal modeling was based on current knowledge. ThereNonperinatal Listeriosis Mortality • CID 2009:48 (1 June) • 1513
fore, it is possible that not all possible confounders are represented in the models, and some factors that are designated
as confounders might not actually be so.
Invasive nonperinatal listeriosis is an important cause of
preventable mortality. This study should help researchers and
clinicians to focus on specific risk factors to prevent nonperinatal listeriosis–related deaths. Improvements in preventing mortality are strongly needed for patients who present with sepsis
only. Additional population-based studies with multivariable
analyses structured on causal models are required to confirm
the findings of this study, specifically when more observations
were needed and measures of risk factors were not routinely
obtained. Furthermore, the mechanisms of how asthma, receipt
of blood transfusion, kidney disease, and alcoholism increase
the odds of mortality should be explored, because they might
not be specific to listeriosis. Finally, public health and preventive
medicine efforts should involve the education of medical communities, including pharmacists, regarding the use of steroids
and antibiotics, and the general population should be educated
on the associated risk groups and high-risk foods, so that individuals who are at high risk for infection, their health care
providers, and their family caregivers remain aware of listeriosis
and the increased risk of death.
22.
Acknowledgments
23.
We acknowledge Amy Gallagher for her help in the verification of case
data.
Financial support. County of Los Angeles, Department of Public Health.
Potential conflicts of interest. L.M. is on the speakers’ bureaus for
Merck and MedImmune. All other authors: no conflicts.
11.
12.
13.
14.
15.
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17.
18.
19.
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21.
24.
25.
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