Prognosis and Determinants of Survival in Patients Newly
Hospitalized for Heart Failure
A Population-Based Study
Philip Jong, MD; Erika Vowinckel, MD; Peter P. Liu, MD; Yanyan Gong,
MSc; Jack V. Tu, MD, PhD
Background The prognosis in unselected community-dwelling patients with heart
failure has not been widely studied.
Objective To determine the short- and long-term mortality of patients after
first hospitalizations for heart failure and to examine how age, sex, and
comorbidities influence survival.
Methods We used the Canadian Institute for Health Information database to
construct a retrospective population-based cohort of 38 702 consecutive
patients with first-time admissions for heart failure from April 1994 through
March 1997 in Ontario, Canada. Prognostic variables were collected from
hospital discharge abstracts. Vital status at 30 days and 1 year was determined
through linkage with the Ontario Registered Persons Database. Regression
analyses were used to identify the relationships among survival, age, sex, and
comorbidities.
Results The crude 30-day and 1-year case-fatality rates after first
admissions for heart failure were 11.6% and 33.1%, respectively. Advancing age,
male sex, and the presence of comorbidities as identified by the Charlson Index
were independently associated with poorer survival. The 30-day and 1-year
mortality ranged from 2.3% and 7.6%, respectively, in the youngest subgroup
with minimal comorbidity to 23.8% and 60.7%, respectively, in the oldest
comorbidity-laden subgroup. Complex interactions among age and sex, sex and
comorbidities, and age and comorbidities were observed in models of short- and
long-term survival.
Conclusions The prognosis of unselected community-dwelling patients with heart
failure remains poor, despite advances in treatment, with substantial variation
seen across different subgroups. Although age, sex, and comorbidities were
confirmed to be independent prognostic indicators of heart failure, their
complex interaction with survival should be considered in future studies.
Arch Intern Med.
2002;162:1689-1694
ALTHOUGH DECREASING mortality rates observed in
clinical trials of heart failure during the past decades suggest improved prognosis
in patients with heart failure (hereafter referred to as heart failure
patients) who were enrolled in those trials,1 it is unclear whether
such improvement is also seen in heart failure patients from the general
population. In particular, the prognosis of unselected community-dwelling
patients who are newly hospitalized for heart failure has not been well
studied. This omission is not surprising, since subjects enrolled in clinical
trials are often unrepresentative of heart failure patients from the community,
who are likely to be older women and to have significant comorbidities.2, 3
To better characterize the prognosis of heart
failure patients from the general population, past epidemiological studies4, 5 have used
administrative databases to assemble cohorts of largely unselected heart
failure patients in whom outcomes can be tracked over time on a population
level. However, most studies6-11 have not eliminated
the confounding effect of disease duration when determining the prognosis of
these patients by failing to select only those with newly diagnosed heart
failure. Thus, an accurate description of the outcomes of this population and
the factors that influence their outcomes is needed. In this study, we
conducted a population-based analysis using hospital discharge abstracts to
determine the short- and long-term survival of patients who have been admitted
for the first time for heart failure in Ontario, Canada, a province with a
population of 11 million. We hypothesized that in the era of contemporary
therapy for heart failure, the case-fatality rates due to heart failure in the
community remain high, and that the poor prognosis of this population bears a
complex relationship to age, sex, and comorbidities that has not been well
described.
PATIENTS AND METHODS
DATA SOURCES
The Canadian Institute for Health Information collects and collates data on all
hospital discharges in Canada.12 This database can be
linked to other data sources using encrypted health card numbers to anonymously
track outcomes of individuals over time. The accuracy of the Canadian Institute
for Health Information data has been described previously.13, 14 Using this database,
we constructed a cohort of consecutive patients who were hospitalized for the
first time for heart failure in the province of Ontario from April 1994 to
March 1997. We identified all individuals (N = 75 642) who were admitted
with a most-responsible diagnosis of congestive heart failure (International Classification of Diseases, Ninth
Revision, Clinical Modification [ICD-9-CM], code 428). We excluded
subjects who were younger than 20 years (n = 273), those without a valid
Ontario heath card number (n = 927), and those who were admitted to chronic
care facilities (n = 713). To minimize referral bias from outside our catchment
area, we excluded all non-Ontario residents (n = 660) and those who transferred
from other acute care facilities (n = 1626). We also excluded subjects for whom
heart failure was coded as a hospital complication (n = 493) to prevent
confounding by the latter coding on survival. To avoid double counting of
cases, we excluded all individuals for whom this was not the first admission
for heart failure (n = 23 268). We also excluded all subjects with
previous admissions for heart failure or who had a diagnosis of heart failure
coded during any hospital admission in the 5 years before this study (n =
8980).
INDICATORS AND OUTCOMES
We used the ICD-9-CM codes
recorded on the discharge abstracts of all hospitalizations, including and
within 5 years before the index admission, to identify the presence of any
comorbid condition. The abstract provided up to 15 fields for secondary or
other diagnoses to record comorbid conditions. Comorbidities were abstracted
using the adaptation of the Charlson Index for administrative databases by Deyo
et al.15 The Charlson
Index is a composite score of comorbidity measures commonly used for case-mix
adjustments in studies assessing longitudinal health outcomes.16 We linked our cohort
to the Ontario Registered Persons Database to determine the vital status of
each patient at 30 days and 1 year after the index admission. The annual
emigration rate from Ontario is less than 0.01%.17 Additional deaths
were also captured by searching for subsequent hospital admissions from the
Canadian Institute for Health Information data that coded for in-hospital
deaths.
STATISTICAL ANALYSIS
We calculated the crude 30-day and 1-year case-fatality rates and tabulated the
crude case-fatality rates stratified by age, sex, and the Charlson comorbidity
score. We used Cochran-Mantel-Haenszel statistics18 to test for sex
differences in the case-fatality rates while controlling for the confounding
effect of age. We tested the age-specific case-fatality rates for trend using
the Mantel extension test19 to control for the
confounding effect of sex. We used the 
2 statistic to test the relationship between
case-fatality rates and the Charlson score.
To determine the independent effects of age,
sex, and comorbidities on prognosis, we constructed multivariable logistic
regression models for the 30-day and 1-year mortality. All comorbidities with a
prevalence of at least 1% in our cohort were considered for inclusion in our
models. A univariate logistic regression model was first performed for each
covariate. Only covariates that had a significance level of P<.20 were entered into the
multivariable logistic models. A backwards elimination procedure (cutoff, P>.10) was then used to arrive at a
final regression model for each outcome. Because the logit risk for death
increased nonlinearly with age, a 4-level age group was used in the model
regression. We tested model calibration by means of the Hosmer-Lemeshow20 2 test, and assessed model discrimination by
means of the c statistic.21 Significance of each
covariate in the final models was tested using the Wald 2 statistic.
We examined the interdependence among age, sex,
and comorbidities on survival by adding a first-order interaction term among
age group, sex, and the Charlson score in a pairwise fashion to the models.
Significance of interactions was tested using the likelihood ratio tests22 for comparing
different logistic models. All analyses were conducted using SAS software,
Version 8.0 (SAS Institute Inc, Cary, NC).
RESULTS
POPULATION DEMOGRAPHICS
A total of 38 702 patients were hospitalized for heart failure for the
first time in Ontario during the 3-year period. More than half (51.1%) of the
cohort were women. Most patients (84.6%) were 65 years or older, and 57.9% were
75 years or older.
CRUDE CASE-FATALITY RATES
The crude 30-day and 1-year case-fatality rates after first-time admissions for
heart failure were 11.6% and 33.1%, respectively (Table 1).
In men, these rates were 11.4% and 34.0%, respectively; in women, 11.8% and
32.3%, respectively. After adjustment for age, men showed a higher 30-day
mortality rate than women (odds ratio [OR], 1.09; 2 = 10.3; P
= .001). This difference persisted at 1 year after discharge (OR, 1.16; 2 =
101.9; P<.001).
As expected, case-fatality rates roses sharply
with increasing age. The 30-day case-fatality rate increased from 4.5% in those
younger than 50 years to 15.1% in those 75 years or older. The effect of age on
the case-fatality rate at 1 year was even more dramatic. The 1-year
case-fatality rate was 13.5% in those younger than 50 years, which increased to
40.1% in those 75 years or older. Controlling for the confounding effect of sex
did not diminish the powerful effect of age on 30-day (2 = 580.9; P<.001)
or 1-year (2 =
1278.0; P<.001) mortality.
The 30-day and 1-year case-fatality rates were
strongly correlated to the Charlson score (2 = 350.4 and 2 = 1042.0, respectively; P<.001 for both) (Table 2).
Among patients with no major comorbidity (Charlson score of 0) except for heart
failure, the 30-day and 1-year mortality rates were 9.3% and 26.8%,
respectively; these rates increased to 18.8% and 50.6% among those with
comorbidity scores of 3 or more.
Table 3
describes the 30-day and 1-year case-fatality rates observed in our cohort
stratified by age, sex, and the Charlson score. The 30-day and 1-year mortality
rates ranged from 2.3% and 7.6%, respectively, in the lowest-risk group to
23.8% and 60.7%, respectively, in the highest-risk group. The lowest-risk group
consisted of patients younger than 50 years with minimal comorbidity except for
heart failure. The highest-risk group included men 75 years or older with
significant comorbidities.
INDEPENDENT EFFECTS OF AGE,
SEX, AND COMORBIDITIES
Multivariate modeling confirmed the strong independent effect of age on
mortality after the first hospitalization for heart failure (Table 4).
We found a stepwise increase in the risk for death with advancing age. Patients
in the highest-age bracket had ORs for death of 3.55 at 30 days and 4.24 at 1
year (P<.001 for both)
compared with those in the lowest-age bracket. In contrast, sex exerted an
independent effect on long but not short-term survival. Compared with men,
women had a significantly higher survival at 1 year (OR, 0.84; P<.001) but not at 30 days.
Furthermore, most comorbid conditions identified by the Charlson Index were
found to be significant independent predictors of 30-day and 1-year mortality.
These included malignancy (ORs, 2.32 and 2.89 [for 30-day and 1-year mortality,
respectively]; P<.001 for
both), renal disease (OR, 1.97 and 2.35; P<.001
for both), dementia (ORs, 1.77 and 1.85; P<.001
for both), cerebrovascular disease (ORs, 1.57 and 1.60; P<.001 for both), rheumatologic disease
(ORs, 1.32 and 1.47; P = .04 and P<.001), peripheral vascular disease
(ORs, 1.17 and 1.42; P = .03 and P<.001), and previous myocardial
infarction (ORs, 1.16 and 1.12; P<.001
for both). The presence of chronic pulmonary disease and diabetes mellitus with
chronic complications were significant predictors of mortality at 1 year (ORs,
1.13 and 1.52; P<.001 for
both) but not at 30 days. The Hosmer-Lemeshow tests showed no lack of fit for
our 30-day and 1-year models (28
= 10.68 and 27
= 6.30; P = .22 and P = .51). The c statistics were 0.64 and 0.65, respectively, on par with
other models23 that incorporated the
Deyo adaptation of the Charlson Index in predicting survival in the population
with heart failure.
INTERACTIONS AMONG AGE, SEX,
AND COMORBIDITIES
The effect of sex on survival after first hospitalizations for heart failure
differed across age groups (Table 5).
We found an interaction between age group and sex that approached statistical
significance in the model that predicted 30-day mortality (23 = 6.64; P = .08) and became statistically
significant in the model that predicted 1-year mortality (23 = 8.39; P = .04). In particular, among patients 75
years or older, the gender gaps in the ORs for death at 30 days and 1 year were
only 10.8% and 40.3%, respectively, of the gaps observed among the group
younger than 50 years. Likewise, the cumulative effect of comorbidity on
survival after first-time admissions for heart failure differed between the
sexes. We found significant interactions between the Charlson score and sex in
models that predicted 30-day and 1-year mortality (21 = 30.34 and 21 = 149.87, respectively; P<.001 for both). The direction of the
interaction in both models suggested that the sex gaps in mortality diminished
with increasing comorbidities. Any survival advantage possessed by women was
lost when the Charlson score was greater than 2 in our 30-day model and greater
than 3 in our 1-year model. Significant interactions were also seen between age
group and the Charlson score when predicting 30-day and 1-year mortality after
first hospitalizations for heart failure (23 = 140.61 and 23 = 416.69, respectively; P<.001 for both). The gap in mortality
rates owing to differences per unit of the Charlson score was lower among
patients 75 years or older than among those in the next 2 younger age brackets.
In all cases, addition of these significant interactions improved the
discriminative powers of our models (c
statistic increases, 0.003-0.013) in predicting mortality.
COMMENT
Our study has documented the high short- and
long-term mortality rates after first-time admissions for heart failure in
unselected patients from a large population-based sample in Ontario. We also
demonstrated a substantial variation in the case-fatality rates across
different patient subgroups. Only young subjects with minimal comorbidity had
the low mortality rates that were typically seen in contemporary clinical
trials of heart failure.1 For most
community-dwelling subjects with heart failure who were more likely to be older
women with significant comorbidities, their prognosis remained poor.
The large disparity between case-fatality rates
observed in our study and those reported in clinical trials is due to selection
bias of the populations enrolled in these trials. Contemporary clinical trials
of heart failure have largely been conducted in white, male populations with
mean ages of about 60 years and a minimal number of comorbidities.1 Although it is unclear
what percentage of patients with heart failure encountered in clinical practice
would not qualify for participation in these trials, studies evaluating the
effect of screening on trial enrollment suggest that typically 35% to 85% of those
undergoing screening were excluded from participation.24 Therefore, a serious
concern is raised that the evidence-based practice that currently exists for
heart failure may only be appropriate for the limited segment of the population
with heart failure included in the trials.
Our ability to track the outcomes of anonymous
subjects in a large community using unique identifiers may improve on another
study4 that used only
probabilistic matching to link subjects between databases, because there is no
guarantee in the latter approach that an individual from the first database
corresponds to the same individual from a different database. Furthermore,
because Canada uses a single-payer healthcare system, our database provides
uniform information covering an entire geographic area across a broad population
inclusive of all socioeconomic strata that is not readily available in the
United States. By selecting only subjects with newly diagnosed heart failure,
we minimized the confounding effects of disease duration on survival.
Prevalence (as opposed to incidence) studies6-11 that reported on
survival after heart failure are prone to bias25 because they may miss
early fatal cases with survival not long enough to be counted.
We were aware of only 5 large-scale studies4, 5, 26-28 that provided
longitudinal health data from heart failure patients on a community level in a
contemporary setting. The Scottish Heart Failure Study4 used probabilistic
linkages to track the outcomes of 66 547 patients admitted to the hospital
for the first time with heart failure from 1986 to 1995 in Scotland. The crude
1-year case-fatality rate in that study was 44.5% (44.0% in men and 44.9% in
women). Moreover, our study and theirs showed that chronic comorbidities
independently increased the mortality rates of patients with newly diagnosed
heart failure. The Framingham Heart Study26 followed up 652
subjects undergoing screening from 1948 through 1988 and in whom new-onset
heart failure developed. The 1-year mortality rates were 43% in men and 36% in
women. As in the Scottish Heart Failure Study, the rates in the Framingham
Heart Study were higher than in our own, perhaps owing to progress made in
heart failure therapy since the early 1990s and to differences in the
underlying population. Unlike our study, new cases of heart failure in the
Framingham Heart Study were captured by interval examinations performed every 2
years rather than by hospital discharge abstracts.
In contrast, our approach is similar to a that
of Swedish study5 in which 2461 patients
from 1980 to 1987 were followed up after their first hospitalizations for heart
failure. The 1-year mortality rate was just above 20%. The lower mortality rate
in that study compared with our own might be related to the younger age
composition of the population with heart failure in Sweden. About half of the
subjects in that study were aged 61 to 65 years, whereas more than half of our
cohort were 75 years or older. The Rochester Epidemiology Project28 described the
prognosis of 107 and 141 patients who presented with new-onset heart failure in
1981 and 1991, respectively. The 1-year mortality rate was 28% in the first cohort
and 23% in the second. The same group of investigators also followed up 216
patients from Olmstead County, Minnesota, who had a first diagnosis of heart
failure in 1991.27 They found a 1-year
case-fatality rate of 24%. Because comorbidities were not systematically listed
in either of these studies, it was unclear whether the lower observed mortality
rates compared with our own were related to a lower prevalence of comorbidities
in their cohorts of heart failure patients.
Although a number of studies5, 11, 27, 28 have identified
prognostic indicators in unselected community-dwelling heart failure patients,
few studies4, 26 have addressed how
these indicators interact with each other in determining mortality. This
omission is understandable because interactions between predictors in
prognostic models are often difficult to quantify and interpret clinically. We
demonstrated that such interactions could be readily quantifiable and that
their inclusion might elucidate meaningful understanding of the competing risks
among age, sex, and comorbidity in influencing survival in the population with
heart failure. The Framingham Heart Study has long recognized that the
mortality rate due to heart failure in men but not in women increased at more
than a simple exponential rate with advancing age.26 MacIntyre et al4 reported a significant
age-sex interaction in their Scottish cohort of heart failure patients for the
30-day case-fatality rate, although the interaction did not persist at 1 year.
An age-sex interaction was evident in our population and we found meaningful
interactions between sex and comorbidity and between age and comorbidity.
Barring statistical variations, these interactions qualitatively raise,
although do not prove, the hypothesis that a common mechanism of competing
risks may determine heart failure survival, ie, that the presence of one risk
diminishes the gap in survival created by the presence or the absence of a
second risk. The improvement in the performance of our models by the addition
of these interaction terms implies a complex interdependence among age, sex, and
comorbidity that should not be ignored in any future prognostic modeling of
mortality due to heart failure.
There are several limitations to our study. We
tracked only subjects who were hospitalized for the first time for heart
failure. Thus, we omitted individuals with newly diagnosed heart failure who
had not been admitted for any reason in the 5 years before our study. This
omission is unlikely to alter the outcome of our study, because about 80% of
the new heart failure patients are presented through hospital admissions,29 and because community
surveys30 have shown
that the remaining heart failure patients would have been hospitalized at least
once within the first 2 years of identification. Also, the use of ICD-9-CM codes might result in an
undernumeration of heart failure cases,31 although this problem
is less important in Canada than in the United States. We also did not apply
standardized diagnostic criteria through random chart reviews to confirm the
diagnosis of heart failure in this study cohort. At the time of our study, we
could not distinguish heart failure patients with normal vs reduced ejection
fractions or classify the cause of the heart failure. In particular,
undercoding of hypertension in discharge abstracts forbade estimation of the
true prevalence of hypertension, a common cause of heart failure, in our
population. We could not take into account differences between subpopulations
of heart failure patients in use of drugs that would influence their survival.
Some demographic variables, such as ethnicity and socioeconomic status, were
missing in our database and could not be adjusted for. Although undercoding of
comorbid conditions in our cohort was certainly possible, serious comorbid
conditions were unlikely to be missed.
CONCLUSIONS
Our study highlights the high case-fatality
rates in unselected community-dwelling patients after first-time
hospitalizations for heart failure. Furthermore, the complex relationships among
age, sex, and comorbidity and their relationship to survival are likely more
involved than previously described and demand validation in other heart failure
populations. Despite recent advances in medical treatment, we found persistent
high mortality rates in our contemporary cohort of heart failure patients. This
finding should be a sobering note to the medical community that much more
remains to be done to improve the outcomes of this seriously ill population
than is currently believed.
Author/Article Information
From the Heart & Stroke/Richard Lewar Centre of Excellence and the Toronto
General Hospital, University Health Network (Drs Jong, Vowinckel, and Liu), and
the Departments of Medicine, Public Health Sciences, and Health Administration
(Ms Gong and Dr Tu), University of Toronto; the Institute for Clinical
Evaluative Sciences (Ms Gong and Dr Tu), and the Division of General Internal
Medicine and the Clinical Epidemiology and Health Care Research Program,
Sunnybrook and Women's College Health Sciences Centre (Ms Gong and Dr Tu),
Toronto, Ontario.
Corresponding author and reprints: Jack V. Tu, MD, PhD, Institute for Clinical
Evaluative Sciences, G-106, 2075 Bayview Ave, Toronto, Ontario, Canada M4N 3M5
(e-mail: [log in to unmask]).
Accepted for publication April 8, 2002.
This study was supported by a Canadian Institute
for Health Research Fellowship (Ottawa, Ontario) (Dr Jong), a Heart &
Stroke Studentship Award (Dr Vowinckel), a Canada Research Chair in Health
Services Research (Dr Tu), and an operating grant from the Canadian Institute
of Health Research and the Heart & Stroke Foundation, Toronto, Ontario.
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Edward E.
Rylander, M.D.
Diplomat American
Board of Family Practice.
Diplomat American
Board of Palliative Medicine.