Evaluation of total hip arthroplasty for management of acetabular fracture complications: A prospective cohort study
Bibliographic record
Abstract
Objectives: Total hip arthroplasty (THA) has been recommended as an effective tool for restoring joint function. This study aimed to evaluate the functional and clinical outcomes of THA management of acetabular fracture late complications such as arthritis by both Harris-Hip Score (HHS) and Western Ontario McMaster Osteoarthritis Index (WOMAC) score, anticipate, and prevent the most common complications such as infection and dislocation. Methods: This prospective case series included 30 patients with THA to manage acetabular fracture complications such as arthritis. The study started in November 2021 and ended in September 2023. Inclusion criteria were patients with acetabular fractures with secondary arthritis (pre-existing osteoarthritis were excluded) aged 25– 70 and who had at least 1 year from fracture to arthroplasty. Exclusion criteria were patients with a history of previous infection. Results: Heterotopic ossification (HO) improved statistically significantly after using ketorolac at an 18-month follow-up compared to preoperatively. Using both the HHS and WOMAC scores, a statistically significant difference was found between pre-operative and post-operative functional outcomes for estimating HO development using radiographs. Conclusion: THA was safe and effective in managing late acetabular fracture complications. Ketorolac use showed promising results in prophylaxis against HO.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".