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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
Arch Intern Med. 2002;162:1689-1694.
ABSTRACT
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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.
INTRODUCTION
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).
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Table 1. Age- and Sex-Stratified Case-Fatality Rates 30 Days and 1
Year After First Hospitalization for Heart Failure
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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.
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Table 2. Relationship Between Comorbidities and Crude 30-Day and 1-Year
Case-Fatality Rates After First Hospitalization for Heart Failure
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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.
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Table 3. Impact of Age, Sex, and Comorbidities on 30-Day and 1-Year
Mortality After First Hospitalization for Heart Failure
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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.
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Table 4. Independent Effects of Age, Sex, and Comorbidites on 30-Day
and 1-Year Mortality After First Hospitalization for Heart Failure*
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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.
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Table 5.  Coefficients for Interaction Terms Among Age, Sex,
and Comorbidities in Models for 30-Day and 1-Year Mortality After First Hospitalization
for Heart Failure
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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 INFORMATION
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.
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: tu{at}ices.on.ca).
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.
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J Am Coll Cardiol 2009;53:597-599.
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Heart failure and chronic obstructive pulmonary disease: diagnostic pitfalls and epidemiology
Hawkins et al.
Eur J Heart Fail 2009;11:130-139.
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Acute heart failure syndromes in patients with coronary artery disease early assessment and treatment.
Flaherty et al.
J Am Coll Cardiol 2009;53:254-263.
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Pharmacotherapy according to treatment guidelines is associated with lower mortality in a community-based sample of patients with chronic heart failure A prospective cohort study
Stork et al.
Eur J Heart Fail 2008;10:1236-1245.
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Long-Term Prospective, Randomized, Controlled Study Using Repetitive Education at Six-Month Intervals and Monitoring for Adherence in Heart Failure Outpatients: The REMADHE Trial
Bocchi et al.
Circ Heart Fail 2008;1:115-124.
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Effect of different angiotensin-converting-enzyme inhibitors on mortality among elderly patients with congestive heart failure
Pilote et al.
CMAJ 2008;178:1303-1311.
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Clinical Uncertainty, Diagnostic Accuracy, and Outcomes in Emergency Department Patients Presenting With Dyspnea
Green et al.
Arch Intern Med 2008;168:741-748.
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Prognostic role of pro- and anti-inflammatory cytokines and their polymorphisms in acute decompensated heart failure
Miettinen et al.
Eur J Heart Fail 2008;10:396-403.
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Effect of Cardiac and Noncardiac Conditions on Survival After Defibrillator Implantation
Lee et al.
J Am Coll Cardiol 2007;49:2408-2415.
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N-Terminal Pro-B-Type Natriuretic Peptide Testing Improves the Management of Patients With Suspected Acute Heart Failure: Primary Results of the Canadian Prospective Randomized Multicenter IMPROVE-CHF Study
Moe et al.
Circulation 2007;115:3103-3110.
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Management of octogenarians hospitalized for heart failure in Euro Heart Failure Survey I
Komajda et al.
Eur Heart J 2007;28:1310-1318.
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A comprehensive view of sex-specific issues related to cardiovascular disease
Pilote et al.
CMAJ 2007;176:S1-S44.
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Long-term Survival After Heart Failure: A Contemporary Population-Based Perspective
Goldberg et al.
Arch Intern Med 2007;167:490-496.
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Effects of cardiac resynchronization therapy on overall mortality and mode of death: a meta-analysis of randomized controlled trials
Rivero-Ayerza et al.
Eur Heart J 2006;27:2682-2688.
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Long-term Survival in Elderly Patients Hospitalized for Heart Failure: 14-Year Follow-up From a Prospective Randomized Trial.
Huynh et al.
Arch Intern Med 2006;166:1892-1898.
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Outcome of heart failure with preserved ejection fraction in a population-based study.
Bhatia et al.
NEJM 2006;355:260-269.
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The Timing for Transplantation: Superior Genetics or Social Prejudice?
Feldman
J Am Coll Cardiol 2006;47:2243-2244.
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Beta-blockade in CHF: pathophysiological considerations
Silke
Eur Heart J Suppl 2006;8:C13-C18.
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Effectiveness of comprehensive disease management programmes in improving clinical outcomes in heart failure patients. A meta-analysis
Roccaforte et al.
Eur J Heart Fail 2005;7:1133-1144.
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Sleep disordered breathing and its treatment in congestive heart failure
Cormican and Williams
Heart 2005;91:1265-1270.
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In-Hospital Mortality in Patients With Acute Decompensated Heart Failure Requiring Intravenous Vasoactive Medications: An Analysis From the Acute Decompensated Heart Failure National Registry (ADHERE)
Abraham et al.
J Am Coll Cardiol 2005;46:57-64.
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Differences in outcomes of patients with congestive heart failure prescribed celecoxib, rofecoxib, or non-steroidal anti-inflammatory drugs: population based study
Hudson et al.
BMJ 2005;330:1370.
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Heart failure management programmes: Delivering the message
Eur J Heart Fail 2005;7:291-293.
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Complexity of program and clinical outcomes of heart failure disease management incorporating specialist nurse-led heart failure clinics. A meta-regression analysis
Phillips et al.
Eur J Heart Fail 2005;7:333-341.
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Effects of a nurse-led, clinic and home-based intervention on recurrent hospital use in chronic heart failure
Thompson et al.
Eur J Heart Fail 2005;7:377-384.
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Impact of specialist follow-up in outpatients with congestive heart failure
Ezekowitz et al.
CMAJ 2005;172:189-194.
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Cardiac resynchronisation therapy: when the drugs don't work.
Bleasdale and Frenneaux
Heart 2004;90:vi2-vi4.
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Systematic Review: Cardiac Resynchronization in Patients with Symptomatic Heart Failure
McAlister et al.
ANN INTERN MED 2004;141:381-390.
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Heart failure clinics and outpatient management: review of the evidence and call for quality assurance
Gustafsson and Arnold
Eur Heart J 2004;25:1596-1604.
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Variables Predictive of Poor Postdischarge Outcomes for Hospitalized Elders in Heart Failure
Roe-Prior
West J Nurs Res 2004;26:533-546.
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A clinical prediction model predicted 30 day and 1 year mortality in patients admitted to hospital for heart failure
Henriksson
Evid. Based Med. 2004;9:92-92.
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Predischarge B-type natriuretic peptide assay for identifying patients at high risk of re-admission after decompensated heart failure
Logeart et al.
J Am Coll Cardiol 2004;43:635-641.
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One-year follow-up of heart failure patients after their first admission
Formiga et al.
QJM 2004;97:81-86.
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Instruments to measure acceptability of information and acquisition of knowledge in patients with heart failure
Gwadry-Sridhar et al.
Eur J Heart Fail 2003;5:783-791.
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Predicting Mortality Among Patients Hospitalized for Heart Failure: Derivation and Validation of a Clinical Model
Lee et al.
JAMA 2003;290:2581-2587.
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Prognosis for South Asian and white patients newly admitted to hospital with heart failure in the United Kingdom: historical cohort study
Blackledge et al.
BMJ 2003;327:526-531.
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The association of left ventricular ejection fraction, mortality, and cause of death in stable outpatients with heart failure
Curtis et al.
J Am Coll Cardiol 2003;42:736-742.
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Social Support, Home Health Service Use, and Outcomes Among Four Racial-Ethnic Groups
Peng et al.
Gerontologist 2003;43:503-513.
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Care and Outcomes of Patients Newly Hospitalized for Heart Failure in the Community Treated by Cardiologists Compared With Other Specialists
Jong et al.
Circulation 2003;108:184-191.
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A Dose of Our Own Medicine: Alternative Medicine, Conventional Medicine, and the Standards of Science
Morreim
J Law Med Ethics 2003;31:222-235.
Prognosis for patients newly admitted to hospital with heart failure: survival trends in 12 220 index admissions in Leicestershire 1993-2001
Blackledge et al.
Heart 2003;89:615-620.
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Long-term survival in patients hospitalized with congestive heart failure: relation to preserved and reduced left ventricular systolic function
Gustafsson et al.
Eur Heart J 2003;24:863-870.
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Cardiovascular Effects of Continuous Positive Airway Pressure in Patients with Heart Failure and Obstructive Sleep Apnea
Kaneko et al.
NEJM 2003;348:1233-1241.
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End-of-Life Care and Congestive Heart Failure
Workman
Arch Intern Med 2003;163:737-737.
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Frailty Is a Strong Modulator of Heart Failure-Associated Mortality
Rozzini et al.
Arch Intern Med 2003;163:737-738.
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Diabetes and the heart: compromised myocardial function -- a common challenge
Bartnik et al.
Eur Heart J Suppl 2003;5:B33-B41.
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First Heart-Failure Hospitalization Portends Poor Prognosis
Journal Watch Cardiology 2002;2002:4-4.
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