The Ability of Frailty to Predict Outcomes in Older People Attending an Acute Medical Unit
Bibliographic record
Abstract
BACKGROUND: This study assessed the role of frailty assessment in the AMU. METHODS: Patients were assessed for frailty and their outcomes ascertained at 90 days. RESULTS: The Canadian Study on Health and Aging Clinical Frailty Scale categorised 29% of patients as moderately-severely frail. Frailty did not differentially identify those likely to be discharged within one day, nor with long stays. Mortality at 90 days was 32%; frailty was associated with the risk of dying, odds ratio 1.4. 21% of patients were readmitted at 30 days, and 33% at 90 days, but frailty was not predictive. DISCUSSION: Moderate-severe frailty in people aged 70+ was common and was predictive of higher mortality, but did not appear to predict admission, length of stay or readmission.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".