Symptoms Reported by Frail Elderly Adults Independently Predict 30‐Day Hospital Readmission or Emergency Department Care
Bibliographic record
Abstract
OBJECTIVES: To assess the degree to which self-reported symptoms predict unplanned readmission or emergency department (ED) care within 30 days of high-risk, elderly adults enrolled in a posthospitalization care transition program (CTP). DESIGN: Retrospective cohort study. SETTING: Posthospitalization CTP at Mayo Clinic, Rochester, Minnesota, from January 1, 2013, through March 3, 2015. PARTICIPANTS: Frail, elderly adults (N = 230; mean age 83.5 ± 8.3, 46.5% male). MEASUREMENTS: Charlson Comorbidity Index (CCI) and self-reported symptoms, measured using the Edmonton Symptom Assessment System (ESAS), were ascertained upon CTP enrollment. RESULTS: Mean CCI was 3.9 ± 2.3. Of 51 participants returning to the hospital within 30 days of discharge, 13 had ED visits, and 38 were readmitted. Age, sex, and CCI were not significantly different between returning and nonreturning participants, but returning participants were significantly more likely to report shortness of breath (P = .004), anxiety (P = .02), depression (P = .02), and drowsiness (P = .01). Overall ESAS score was also a significant predictor of hospital return (P = .01). CONCLUSION: Four self-reported symptoms and overall ESAS score, but not CCI, ascertained after hospital discharge were strong predictors of hospital return within 30 days. Including symptoms in risk stratification of high-risk elderly adults may help target interventions and reduce readmissions.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".