Unreadiness for hospital discharge predicts readmission among cardiac patients: results from the national DenHeart survey
Bibliographic record
Abstract
AIMS: Readiness for hospital discharge describes a patient's perception of feeling prepared to leave the hospital. In mixed patient populations, readiness for hospital discharge has shown to predict readmission and mortality in the short term. The objectives of a population of men and women with cardiac diseases, were to investigate: (i) whether readiness for hospital discharge predicts readmission and mortality within 1-year post-discharge, as well as (ii) the association between 'physical stability', 'adequate support', 'psychological ability', and 'adequate information and knowledge' and readiness for hospital discharge. METHODS AND RESULTS: Data from the national cross-sectional survey DenHeart were used and included patients with cardiac diseases at hospital discharge. Readiness for hospital discharge was evaluated by one self-reported question, and attributes were illuminated by Short-Form-12, the Edmonton Symptom Assessment Scale and ancillary questions. Data were combined with national registries at baseline and at 1-year follow-up. Cox proportional-hazards model were used to regress readmission and mortality. The analysis included 13 114 patients (response rate: 52%). The majority responded that they felt ready for hospital discharge (95%). Feeling unready (n = 618) was a predictor of 1 year, all-cause readmission among women and men [hazard ratio (HR) = 1.43, 95% confidence interval (CI) 1.18-1.74; HR = 1.59, 95% CI 1.34-1.90]. No significant results were found on all-cause mortality. The four attributes were associated with unreadiness at hospital discharge. CONCLUSION: Not feeling ready for hospital discharge was a predictor of increased readmission risk in women and men with cardiac disease during 1 year after hospital discharge. Four attributes were significantly impaired in patients feeling unready for hospital discharge.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".