Comparison of postoperative outcomes between bikini-incision via direct anterior approach and posterolateral approach in simultaneous bilateral total hip arthroplasty: a randomized controlled trial
Bibliographic record
Abstract
The purpose of this study was to compare an oblique bikini-incision via direct anterior approach (BI-DAA) to a conventional posterolateral approach (PLA) during simultaneous bilateral total hip arthroplasty (simBTHA) in terms of early patient outcomes, postoperative functional recovery, and complications. From January 2017 to January 2020, 106 patients receiving simBTHA were enrolled and randomly allocated to the BI-DAA or PLA group. Primary outcomes were measured using hemoglobin (HGB) drop, transfusion rate, the length of stay (LOS), the visual analog scale (VAS) for pain, the Harris hip score, Western Ontario and McMaster Universities Osteoarthritis Index, and the scar cosmesis assessment and rating scale. Secondary outcomes were the operative time, radiographic measurements, including femoral offset, femoral anteversion, stem varus/valgus angle, and leg length discrepancy (LLD). The occurrence of postoperative complications was also recorded. There were no differences in demographic or clinical characteristics before surgery. Compared to the PLA, the patients in the BI-DAA group had lower HGB drop (24.7 ± 13.3 g/L vs. 34.7 ± 16.7, P < .01) and transfusion rates (9/50 vs. 18/50, P = .04) and a shorter LOS (5.12 ± 1.5 vs. 6.40 ± 2.0 days, P < .01) without increasing the operative time (169.7 ± 17.3 vs. 167.5 ± 21.8 min, P = .58). The BI-DAA group yielded a smaller LLD (2.1 ± 2.3 vs. 3.8 ± 3.0 mm, P < .01) and less variability in component orientation than the PLA group (100% vs. 93%, P = .01). As for the scar, the BI-DAA group produced a shorter incision length (9.7 ± 1.6 vs. 10.8 ± 2.0 mm, P < .01) and higher postoperative recovery satisfaction than the PLA group. Furthermore, the BI-DAA group had a reduced VAS score one week after surgery and had better functional recovery in three months postoperatively. The BI-DAA group had a higher incidence of LFCN dysesthesia (12/100 vs. 0/100 thighs, P < .01), while other complications did not differ significantly between the two groups. For simBTHA, the bikini incision offers early recovery, less variance in components orientation, better postoperative outcomes, and scar healing than the PLA. Therefore, the bikini incision could be a safe and feasible option for simBTHA recipients.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".