Sex-specific clinical outcomes and healthcare resource utilization in the 5 years following hospitalization for heart failure
Bibliographic record
Abstract
Abstract Background Heart failure (HF) a leading cause of hospitalization, and sex differences in care have been described. Purpose We assessed sex-specific clinical outcomes and healthcare resource utilization following hospitalization for HF. Methods This was an exploratory analysis of patients hospitalized for HF across 10 Canadian hospitals enrolled in the Patient-Centred Care Transitions in HF pragmatic cluster-randomized trial. Primary outcome was all-cause mortality. Secondary outcomes included all-cause readmissions, HF readmissions, emergency department (ED) visits, and healthcare resource utilization. Outcomes were obtained via linkages with administrative datasets. Results The 4441 patients (50.7% female) had high event rates. At 5 years of follow-up, 63.6% male and 65.5% of male and female patients, respectively, had died (p=0.19); 85.4% and 84.4% of male and female patients, respectively, were readmitted with no sex differences in mean [SD] all-cause readmissions (males, 2.8 [7.8] and females, 3.0 [8.4], p=0.54) or HF readmissions (males, 0.9 [3.6] and females, 0.9 [4.5], p=0.80) per person. The mean (SD) annual total healthcare costs per patient was $80334 (116762) for males and $81010 (112625) for females, with no sex difference (p=0.90); however, there were sex differences in cost breakdown: males incurred greater costs from specialist, hemodialysis, and day surgical care, and females incurred greater costs from home visits and long-term care. Conclusions Males and females were at similarly high risk of mortality and readmissions, and had similar total healthcare costs following hospitalized for HF. Notwithstanding similar risks, males received relatively more specialist and invasive care, and females received relatively more supportive care.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".