Efficacy of Direct Anterior Approach Versus Posterior Lateral Approach for Total Hip Replacement in Patients with Parkinson’s Disease
Bibliographic record
Abstract
BACKGROUND The present study was performed to evaluate the efficacy of direct anterior approach (DAA) versus posterolateral approach (PLA) for total hip arthroplasty (THA) in patients with Parkinson's disease (PD). The aim of the study was to compare the speed of recovery of hip function and postoperative complications between the 2 approaches. MATERIAL AND METHODS The study included 285 Parkinson's patients who underwent THA; 209 eligible patients were recruited for analysis as per the inclusion criteria and assigned into DAA group (n=90) and PLA group (n=119) according to the surgical approach. Postoperative Harris Hip Score (HHS), Western Ontario and McMaster University Osteoarthritis Index (WOMAC), and Forgotten joint score (FJS) were collected to assess hip function. RESULTS The DAA had a statistically lower incidence of postoperative complications than the PLA, particularly the rate of postoperative dislocation. Perioperative outcomes showed a longer operative time in the DAA than in the PLA group and more intraoperative blood loss in the DAA than in the PLA group. At 3 months postoperatively, the HHS and WOMAC scores in the DAA group showed significantly higher scores compared to the PLA group versus the DAA group. However, these differences disappeared at 6 months postoperatively and the FJS in the DAA group had a statistically higher score compared to the PLA group. CONCLUSIONS In patients with Parkinson's disease complicated with hip disease, the DAA approach exhibited a lower rate of dislocation than the PLA approach and had faster recovery of hip function.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".