Evaluating the Functional and Psychological Outcomes Following Periprosthetic Femoral Fracture After Total Hip Arthroplasty
Bibliographic record
Abstract
Background: A fall after total hip arthroplasty (THA) that results in a periprosthetic femoral fracture (PPF) can have devastating functional and psychological consequences in older adults. There are few studies that have evaluated both functional and psychological outcomes of PPF post-THA in the same cohort. Methods: This is a retrospective study of 130 people who underwent revision THA between 2005 and 2019 due to PPF. The Western Ontario and McMaster Universities Osteoarthritis (WOMAC), Harris Hip Score (HHS), and Short Form-12 (SF-12) assessed physical function, hip joint function, and psychological well-being, respectively. Descriptive statistics using means and standard deviation or frequencies and percentages were used to define the sample. The association between baseline demographic, clinical, and surgical factors on WOMAC, HHS, and SF-12 scores at 1-year post-PPF surgery was modelled using multivariable linear regression. The mean age (n = 130) was 80.6 ± 9.0 years, and 55.4% (n = 72) were female. The mortality rate was 15.4% (n = 20) at 1-year post-PPF surgery. One-year follow-up data were available for 35.4% (n = 46) of patients. Results: The WOMAC (n = 37), HHS (n = 32), and SF-12 mental component summary (n = 46) scores at 1-year post-PPF surgery were 67.9 ± 20.3, 78.3 ± 15.0, and 52.7 ± 9.1, respectively. No significant association was found among age, gender, previous history of lower extremity surgery, Vancouver classification, and femoral bone grafting on WOMAC, HHS, and SF-12 scores. Conclusions: Our study found that patients with PPF have fair hip joint function, poor physical function and psychological well-being, and a high mortality rate at 1-year post-PPF surgery.
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 | 0.001 | 0.005 |
| 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 | 0.000 |
| 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".