Outcomes in patients with heart failure treated in hospitals with varying admission rates: population-based cohort study
Bibliographic record
Abstract
STUDY OBJECTIVES: Hospital admission rates for patients with heart failure (HF) presenting for emergency department (ED) care vary, and the implications of direct discharge home from the ED are unknown. We examined whether patients treated in hospitals with low admission rates exhibit higher rates of repeat ED visits, hospital readmissions and death. METHODS: We divided EDs into low-, medium- and high-admission-rate tertiles by their standardised HF admission rate in Ontario, Canada. Among adults (≥18 years) with HF discharged from an ED between April 2004 and March 2010, we evaluated the primary outcomes of repeat ED visits or hospitalisations for HF, and secondary outcomes, which included death, within 30 days stratified by HF admission-rate tertile. RESULTS: 89 878 patients with HF presented to low- (n=29 929), medium- (n=30 900) or high- (n=29 049) admission-rate institutions, with hospitalisation rates of <67%, 67-75% and >75%, respectively. Among 28 175 ED-discharged patients, the multivariable-adjusted HR for repeat ED visit or hospitalisation for HF at low-admission-rate institutions was 1.18 (95% CI 1.07 to 1.29, p<0.001) compared with high-admission institutions. Similarly, the HR for repeat ED visits for HF was 1.28 (95% CI 1.14 to 1.44, p<0.001) at low-admission hospitals. Compared with discharged patients in the high-admission-rate tertile, adjusted HR for 30-day mortality was 1.19 (95% CI 0.95 to 1.47) at low-admission-rate hospitals. The HRs for all of the above outcomes were not significantly increased at medium-admission-rate hospitals. DISCUSSION: Patients seeking care at institutions with lower rates of HF admission showed higher rates of repeat ED visits or hospitalisations after previous ED discharge.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".