Predictors of 30-day readmission among those treated with alcohol withdrawal in acute hospitals in England
Bibliographic record
Abstract
AIMS: To examine predictors of 30-day readmissions to acute hospitals in England for patients treated for alcohol withdrawal (AW). METHODS: Retrospective cross-sectional analysis of routine hospital administrative data (i.e. Hospital Episode Statistics-Admitted Patient Care records) for adults admitted to non-specialist hospitals in England 2017-18. RESULTS: AW admissions were associated with digestive, circulatory, respiratory, and endocrine disorders and were of short duration (median 3 days). Of the 19 588 completed AW admissions examined in 2017-18, 3957 (20.2%) resulted in readmission within 30 days. The strongest predictors of 30-day readmission were being no fixed abode (Adjusted Odds Ratio (AOR) 1.81, 95%CI 1.44-2.26), prior discharge against medical advice (AOR 1.57, 95%CI 1.40-1.77), and greater Charlson comorbidity index total score (AOR 1.02, 95%CI 1.02-1.03). DISCUSSION: AW 30-day admissions are common and associated to complex case presentations that require high levels of community support on discharge. Hospital-based alcohol teams should prioritize strategies, which maximize medically managed AW, effective transitions to specialist community care including outreach teams and strong collaborations with physical and mental health outpatient services. Together with specialist initiatives within community mental health teams, assertive outreach, and homeless services 30-day readmissions may be minimized.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".