Prognosis and Determinants of Survival in Patients Newly Hospitalized for Heart Failure
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".