Frailty Is Associated With Early Hospital Readmission in Older Medical Patients
Bibliographic record
Abstract
Given the pervasiveness of frailty and its negative effects on health care-related outcomes, we evaluated patient frailty and comorbidity and determined the relationship between these measures and the probability of early readmission and length of hospital stay. Our retrospective analysis includes 435 patients evaluated using the Reported Edmonton Frailty Scale and the Age-Adjusted Charlson Comorbidity Index. We found that frailty as measured by the Reported Edmonton Frailty Scale was a significant predictor of hospital readmission and length of stay, and frailty outperformed the explanatory power of our comorbidity metric. One unit of increase in the Reported Edmonton Frailty Scale increased the odds of readmission by a factor of 1.12 (95% confidence interval [CI]: [1.04, 1.20]), and an increase of 10 units tripled the odds of readmission (odds ratio = 3.02, 95% CI: [1.48, 6.24]). These findings underscore the importance of prompt identification and management of frailty by bedside clinicians.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".