Factors influencing inpatient rehabilitation length of stay following revision hip replacements: a retrospective study
Bibliographic record
Abstract
BACKGROUND: The annual incidence of revision hip replacements has increased in both Canada and United States, particularly in younger adults. Patients following revision hip replacements often require longer hospital length of stay (LOS) but little is known about predictors of inpatient rehabilitation LOS in this group of patients. The purpose of this study was to evaluate the socio-demographic, pre-surgery, surgery and post-surgery related factors that might influence rehabilitation LOS of inpatients following revision hip replacements. METHODS: This study included inpatients discharged from a musculoskeletal ward between 2002 and 2006 following rehabilitation revision hip replacement. Data sources included the National Reporting System, a standardized, provincial administrative database and augmented by chart abstraction. The collected elements included the outcome LOS and the following independent variables: age, sex, support at home, environmental barriers, language barrier, number of revision surgeries on the affected hip, comorbidity, previous orthopaedic surgeries in the lower extremities (L/ES), the hip component(s) revised, weight-bearing status, hemoglobin level, complications, days lapsed from surgery to rehabilitation admission and admission scores on the Functional Independence Measure (FIM). Simple linear regression was used to take forward any predictors significant at p < .10 level. Variables that satisfied the significance level were grouped in blocks and entered for regression analyses. RESULTS: The 275 patients in this sample had a mean age of 69 years; 62% were female and the mean LOS was 29.6 days. Statistically significant predictors of longer LOS were low admission FIM score, female sex, revision of only the femoral component, 2 or more prior surgeries in the L/Es and 2 or more hip revisions (redo revision). The final model explained 28% of variance in inpatient LOS. CONCLUSIONS: A score of 9-14 points lower in admission FIM, female sex, revision of only the femoral component, prior surgeries in the L/Es and redo hip revision are all independent factors associated with 4-6 days longer LOS. These results may facilitate an understanding of bed flow. Additionally, patients with one or a combination of the above characteristics may benefit from enhanced care plans that facilitate achievement of rehabilitation goals for discharge home.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".