EXAMINING MORTALITY RATES FOLLOWING PERIPROSTHETIC FEMUR FRACTURES IN PATIENTS UNDERGOING PRIMARY AND REVISION TOTAL HIP ARTHROPLASTY: RETROSPECTIVE COHORT RESEARCH
Bibliographic record
Abstract
Introduction Following total knee and hip arthroplasty (TKA and THA), periprosthetic fractures (PPF) have risen. The study evaluated morbidity and mortality after PPF surgery for the knee and hip. Methods A level-1 trauma center examined 248 patients, throughout two years. These patients were included retrospectively. Mortality was taken into consideration as the main event in Fine and Gray's model when assessing risk factors for postoperative morbidity. Cox regression models, both univariate and multivariate, were used to identify death risk variables. Result The mean age was 77 years; 77.40% were female with PPF of the hip (n = 194) and knee (n = 54). Out of all the fracture types in Vancouver, B2 (n = 78; 42.4%) was the most common, followed by B1 (n = 46; 25.00%). Form I fractures (n=28; 51.9%) were the most common form of Lewis-Rorabeck fracture in the PPF of the knee. Complication rates for PPF of the knee and hip were 44.0% and 29.9%, respectively. Six patients experienced early and late problems, 50 had early complications, and 38 had late implant-related complications that required surgery. Conclusion Younger patients and those undergoing ORIF have higher postoperative morbidity from implant issues. Accounting for mortality prevents underestimating complications. The retrospective study at a level 1 trauma hospital shows that, with careful planning, surgeries longer than two days do not harm patient outcomes. Recommendation An earlier study found that for patients with native hip fractures or periprosthetic fractures, surgery is still advised 24 to 48 hours after admission.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".