ONE-YEAR MORTALITY AFTER HIP FRACTURE IN OLD AND VERY OLD PATIENTS
Bibliographic record
Abstract
Prospective cohort of patients included in the Institutional Registry of elderly patients with Hip fracture between june 2014 and december 2016. We excluded pathologic, periprosthetic, subtrochanteric or secondary to polytrauma fractures. We classified patients as: old patients (OP) ≥65 and <85 years and very old patients (VOP) ≥85 years. We used Kaplan Meier method to estimated one year survival. We used a Cox model to estimate OP Hazard Ratios with 95% confidence intervals (95%CI). We included 759 patients, 43% were OP and 57% were VOP. Proportion of women was 83% and 85% respectively, p0.45. They had similar frequency of polymedication (46% and 47%, p0.78) and proportion of people having two or more Charlson score (28% and 32%, p0.26). VOP were more dependent by Barthel score (36% and 65%, p<0.01) and more fail Edmonton score (34% and 67%, p<0.01). One year survival was 96% (95%CI 93–98) in OP and 84% (95%CI 79–88) in VOP. Complications were more frequent in VOP, 26% and 34% p0.02. Readmission were 30% and 41%, p<0.01. Age is an independent risk factor for one year mortality with a crude HR 4.59 (IC95% 2.16–9.73, p <0.01), adjusted for frailty, functionality, ASA score, Charlson, polymedication and nutrition HR 3.52 (95%CI 1.63–7.6, p<0.01).
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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 | 0.000 | 0.001 |
| 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".