Direct anterior approach versus posterior approach in total hip arthroplasty: A systematic review and meta-analysis
Bibliographic record
Abstract
Background: The optimal surgical approach for total hip arthroplasty (THA) is still debated. Recently, a growing surgical trend toward the utilization of minimally invasive techniques, such as the direct anterior approach (DAA), has emerged in the THA area. However, there are ongoing concerns regarding its technical complexity and perioperative outcomes relative to the posterior approach (PA). Therefore, we aim to compare DAA and PA regarding perioperative, functional, and safety outcomes. Methods: A comprehensive systematic search of PubMed, Web of Science, Scopus, and Cochrane Library was executed. We included randomized controlled trials (RCTs) and observational studies comparing DAA and PA in patients undergoing THA. The primary endpoints were all-cause surgery revision, dislocation, and fracture. Secondary endpoints encompassed the duration of hospital stay, incision length, functional recovery measured using the Harris Hip Score (HHS), and complications. Mean difference (M.D.) or Risk ratio (R.R.) with a 95 % confidence interval (C.I.) were employed to analyse the continuous or dichotomous outcomes. Results: with 7138 patients in the DAA cohort and 37,299 patients in the PA cohort. Our pooled analysis demonstrated comparable estimates of all-cause surgery revision (R.R. = 0.90, 95 % C.I. [0.71, 1.15], p = 0.40), dislocation (R.R. = 0.78, 95 % C.I. [0.53, 1.16], p = 0.22), intraoperative fracture (R.R. = 0.85, 95 % C.I. [0.51, 1.42], p = 0.54), and periprosthetic fracture (R.R. = 2.14, 95 % C.I. [0.85, 5.38], p = 0.11). Notably, DAA showed a significantly shorter hospital stay (M.D. = -0.31 days, 95 % C.I. [-0.55, -0.07], p = 0.01) and shorter incision length (M.D. = -33.75 mm, 95 % C.I. [-42.97, -24.54], p = 0.001) compared to the PA. No significant variations were noticed between the two approaches regarding HHS. Conclusion: Our meta-analysis highlighted that DAA is effective as PA in mitigating the risk of major complications following THA, such as all-cause surgery revision, dislocation, and fracture. In contrast, DAA showed better perioperative results, including shorter hospital stays and incision lengths, without compromising the safety outcomes compared to PA.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.029 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".