Association of body mass index with functional outcome and rehabilitation length of stay after hip fracture: A retrospective cohort study
Bibliographic record
Abstract
High BMI has been associated with adverse perioperative outcomes but it remains unclear whether these impacts carry over into functional outcomes. Our objective was to investigate the association of body mass index (BMI) with Functional Independence Measure (FIM) and length of stay (LOS) among patients admitted to inpatient rehabilitation after hip fracture. Retrospective cohort study of 641 patients after hip fracture surgery admitted to to inpatient rehabilitation between January 1, 2016 and December 31, 2019. The primary predictor variable was BMI. Outcome were Functional Independence Measure (FIM) and rehabilitation LOS. Multivariable non-linear regression analysis was performed. The effect of BMI on both change in FIM and LOS was dependent on the FIM score at admission. Older age (Estimate -0.337, 95% CI [-0.466, -0.209], p <0.001) and dementia (Estimate 8.408, 95% CI [-11.560, -5.255,], P <0.001) were shown to be associated with lower FIM score change. Older age (Estimate -0.029, 95% CI [-0.209, -0.466], p <0.001) and dementia (Estimate -0.272, 95% CI [-5.255, -11.560], p =0.032) were associated with decreased FIM efficiency. Age or dementia were associated with poorer FIM change and FIM efficiency. Being male (Estimate 2.867, 95% CI: [0.695, 5.039], p=0.01) and living alone pre-fracture (estimate 2.574, 95% CI: [0.522, 4.627], p=0.014), were associated with longer LOS. The effect of BMI on both change in FIM and LOS in rehabilitation was dependent on the FIM score at admission. The statistical association between BMI and change in FIM was not clinically significant in the context of inpatient rehabilitation. Factors including advanced age or dementia were associated with poorer FIM change and FIM efficiency, while living alone pre-fracture and being male were associated longer LOS.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".