Depressive symptoms are associated with higher rates of readmission or mortality after medical hospitalization: A systematic review and meta‐analysis
Bibliographic record
Abstract
Depressive symptoms during a medical hospitalization may be an overlooked prognostic factor for adverse events postdischarge. Our aim was to evaluate whether depressive symptoms predict 30-day readmission or death after medical hospitalization. We conducted a systematic review of studies that compared postdischarge outcomes by in-hospital depressive status. We assessed study quality and pooled published and unpublished data using random effects models. Overall, one-third of 6104 patients discharged from medical wards were depressed (interquartile range, 27%-40%). Compared to inpatients without depression, those discharged with depressive symptoms were more likely to be readmitted (20.4% vs 13.7%, risk ratio [RR]: 1.73, 95% confidence interval [CI]: 1.16-2.58) or die (2.8% vs 1.5%, RR: 2.13, 95% CI: 1.31-3.44) within 30 days. Depressive symptoms were common in medical inpatients and are associated with an increased risk of adverse events postdischarge. Journal of Hospital Medicine 2016;11:373-380. © 2016 The Authors Journal of Hospital Medicine published by Wiley Periodicals, Inc. on behalf of Society of Hospital Medicine.
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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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.021 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".