Periprosthetic Fractures About the Hip
Bibliographic record
Abstract
INTRODUCTION: Little research has examined postrehabilitation functional outcomes of periprosthetic hip fractures. Predicted functional deficits and acceptable rehabilitation outcomes for these patients are not established. This study aimed to compare functional outcomes of periprosthetic fractures to matched patients with total hip arthroplasty (THA). MATERIALS AND METHODS: Cases with periprosthetic fracture (PPF) were matched for age, gender, and surgeon to primary THA cases. Only patients who had completed at least 1 year of rehabilitation were included. Western Ontario and McMaster Universities Arthritis Index (WOMAC) scores were calculated for all surviving cases with PPF and primary THA. Secondary outcomes included length of stay and mortality. Statistical analysis was performed using Microsoft Excel and the 2-tailed Wilcoxon signed rank test. A P value of <.05 was accepted as indicative of statistical significance. RESULTS: We identified 25 patients with PPF. Three patients were unsuitable for functional assessment. Of the cases with PPF suitable for functional assessment, 14 (14/22) were male. The median age of the PPF and the THA groups was 71 years and 68 years respectively. The median WOMAC score for the PPF group was 26 (interquartile range [IQR] 5.5-49.5) compared to that of the primary THA group, 3 (IQR 2.0-24.5; P < .05). In the PPF group, there were 7 deaths and 3 of the surviving patients had significant complications. The median length of stay in the PPF group was 13 days (IQR 10.5-35) compared to the matched group of 5 days (IQR 5-8.5; P < .05). CONCLUSION: Patients with PPF have markedly poorer functional outcomes than age-, gender-, and surgeon-matched patients with THA as well as prolonged length of stay. Future research should target the identification of factors that may improve functional outcomes in this growing cohort.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".