Association between clinical frailty, illness severity and post-discharge survival: a prospective cohort study of older medical inpatients in Norway
Bibliographic record
Abstract
PURPOSE: Study associations between frailty, illness severity and post-discharge survival in older adults admitted to medical wards with acute clinical conditions. METHODS: Prospective cohort study of 195 individuals (mean age 86; 63% females) admitted to two medical wards with acute illness, followed up for all-cause mortality for 20 months after discharge. Ward physicians screened for frailty and quantified its degree from one to eight using Clinical Frailty Scale (CFS), while clinical illness severity was estimated by New Early Warning Score 2 (NEWS2) and laboratory illness severity was calculated by a frailty index (FI-lab) using routine blood tests. RESULTS: CFS, NEWS2 and FI-lab scores were independently associated with post-discharge survival in an adjusted Cox proportional hazards model with age, ward category (acute geriatric and general medical) and comorbidity as covariates. Adjusted hazard ratios and 95% confidence intervals were 1.54 (1.24-1.91) for CFS, 1.12 (1.03-1.23) for NEWS2, and 1.02 (1.00-1.05) for FI-lab. A frailty × illness severity category interaction effect (p = 0.003), suggested that the impact of frailty on survival was greater in those experiencing higher levels of illness severity. Among patients with at least moderate frailty (CFS six to eight) and high illness severity according to both NEWS2 and FI-lab, two (13%) were alive at follow-up. CONCLUSION: Frailty screening aided prognostication of survival following discharge in older acutely ill persons admitted to medical wards. The prognostic value of frailty increased when combined with readily available illness severity markers acquired during admission.
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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 | 0.005 | 0.013 |
| 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 | 0.000 | 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 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".