Determinants of discharge destination following elective total hip replacement
Bibliographic record
Abstract
OBJECTIVE: To identify the factors associated with discharge to an inpatient rehabilitation facility versus discharge directly to home after elective total hip replacement (THR). METHODS: Data were obtained from a medical record review and a cross-sectional survey of a population-based cohort of patients who received elective primary or revision THR in 1995. Postoperative functional status was measured as the ability to walk independently prior to discharge. A multivariate regression model was developed with discharge to an inpatient rehabilitation facility versus directly to home as the dependent variable. The model adjusted for demographic characteristics, socioeconomic features, and several preoperative and postoperative clinical factors. RESULTS: We included 1,276 patients age 65-94 years in the analysis. Of these, 58% were discharged from the acute care hospital to a rehabilitation facility. The cohort had mean age of 73 years; 96% were white; 62% were female; 32% were living alone; 38% had an annual income less than $20,000; and 78% were unable to walk independently in the hospital before discharge. For primary THR patients, multivariate analysis showed a significant association between being discharged to a rehabilitation facility and being unable to walk at discharge, older age, obesity, and living alone. For revision THR patients, multivariate analysis also showed a significant association between being discharged to a rehabilitation facility and being unable to walk at discharge. CONCLUSION: In a large population-based sample, postoperative functional status, age, obesity, and social support all influenced the discharge destination following elective THR.
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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 | 0.006 |
| 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 | 0.001 |
| 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".