Influence of Hospitalization for Cardiovascular Versus Noncardiovascular Reasons on Subsequent Mortality in Patients With Chronic Heart Failure Across the Spectrum of Ejection Fraction
Bibliographic record
Abstract
BACKGROUND: Noncardiovascular (non-CV) comorbidities may contribute to hospitalizations in patients with heart failure (HF). We examined the incidence of mortality following hospitalization for cardiovascular (CV) versus non-CV reasons in the Candesartan in Heart Failure: Assessment of Reduction in Mortality and Morbidity (CHARM) Program. METHODS AND RESULTS: First hospitalizations for CV or non-CV reasons during the CHARM trial (N=7599) were related to subsequent risk of all-cause death using time-updated proportional hazards models. Over median 37.7 month follow-up, 2816 subjects (37.1%) were not hospitalized, 2893 (38.1%) were first hospitalized for CV reasons, and 1890 (24.9%) for non-CV reasons. The death rate (per 100 patient-years) among those not hospitalized was 2.8 compared with 17.8 after CV and 16.5 after non-CV hospitalization (both P<0.001 versus not hospitalized). Mortality at 30 days was higher after CV than non-CV hospitalization; however, among 30-day survivors of CV and non-CV hospitalization, rates of subsequent mortality were similar (14.5 versus 14.6 per 100 patient-years; P=0.62). Rates of CV hospitalization were higher for those with ejection fraction (EF) ≤40% than those with EF >40% (P<0.001), but rates of non-CV hospitalization did not vary by EF. Low EF patients had higher risk for mortality than preserved EF patients after any hospitalization, but within each EF subgroup, mortality in 30-day survivors of CV versus non-CV hospitalization was similar. CONCLUSIONS: Non-CV hospitalization is frequent in patients with symptomatic heart failure and associated with risk of subsequent mortality similar to CV hospitalization across the spectrum of EF. These findings may have implications for developing strategies to prevent readmissions. CLINICAL TRIAL REGISTRATION URL: http://www.clinicaltrials.gov. Unique identifier: NCT00634309 (CHARM-Added), NCT00634712 (CHARM-Preserved), NCT00634400 (CHARM-Alternative).
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".