The Clinical Course of Health Status and Association with Outcomes in Patients Hospitalized for Heart Failure: Insights from ASCEND-HF
Bibliographic record
Abstract
AIMS: A longitudinal and comprehensive analysis of health-related quality of life (HRQOL) was performed during hospitalization for heart failure (HF) or soon after discharge. METHODS AND RESULTS: A post-hoc analysis was performed of the ASCEND-HF trial. The EuroQOL five dimensions questionnaire (EQ-5D) was administered to study participants at baseline, 24 h, discharge/day 10, and day 30. EQ-5D includes functional dimensions mapped to corresponding utility scores (i.e. 0 = death and 1 = perfect health), and a visual analogue scale (VAS) ranging from 0 (i.e. 'worst imaginable health state') to 100 (i.e. 'best imaginable health state'). The association between baseline and discharge EQ-5D measurements and subsequent clinical outcomes including death and rehospitalization were assessed using multivariable logistic regression and Cox proportional hazards regression. A total of 6943 patients (97%) had complete EQ-5D data at baseline. Mapped utility and VAS scores (mean ± SD) increased over time, respectively, from 0.56 ± 0.23 and 45 ± 22 at baseline to 0.67 ± 0.26 and 58 ± 22 at 24 h and to 0.79 ± 0.20 and 68 ± 22 at discharge, and remained stable at day 30. Lower mapped utility scores at baseline [odds ratio (OR) per 0.1 decrease in utility score 1.03, 95% confidence interval (CI) 1.00-1.06] and discharge (OR 1.10, 95% CI 1.05-1.15) and VAS scores at baseline (OR per 10 point decrease 1.05, 95% CI 1.01-1.09) were significantly associated with increased risk of 30-day all-cause death or HF rehospitalization. CONCLUSIONS: Patients hospitalized for HF had severely impaired health status at baseline and, although this improved substantially during admission, health status remained abnormal at 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".