Postoperative Admission to a Dedicated Geriatric Unit Decreases Mortality in Elderly Patients with Hip Fracture
Bibliographic record
Abstract
BACKGROUND: Elderly patients with hip fracture have a 5 to 8 fold increased risk of death during the months following surgery. We tested the hypothesis that early geriatric management of these patients focused on co-morbidities and rehabilitation improved long term mortality. METHODS AND FINDINGS: In a cohort study over a 6 year period, we compared patients aged >70 years with hip fracture admitted to orthopedic versus geriatric departments in a time series analysis corresponding to the creation of a dedicated geriatric unit. Co-morbidities were assessed using the Cumulative Illness Rating Scale (CIRS). Each cohort was compared to matched cohorts extracted from a national registry (n = 51,275) to validate the observed results. Main outcome measure was 6-month mortality. We included 131 patients in the orthopedic cohort and 203 in the geriatric cohort. Co-morbidities were more frequent in the geriatric cohort (median CIRS: 8 vs 5, P<0.001). In the geriatric cohort, the proportion of patients who never walked again decreased (6% versus 22%, P<0.001). At 6 months, re-admission (14% versus 29%, P = 0.007) and mortality (15% versus 24%, P = 0.04) were decreased. When co-morbidities were taken into account, the risk ratio of death at 6 months was reduced (0.43, 95%CI 0.25 to 0.73, P = 0.002). Using matched cohorts, the average treatment effects on the treated associated to early geriatric management indicated a reduction in hospital mortality (-63%; 95% CI: -92% to -6%, P = 0.006). CONCLUSIONS: Early admission to a dedicated geriatric unit improved 6-month mortality and morbidity in elderly patients with hip fracture.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".