Robotic-Assisted Total Hip Arthroplasty Provides Greater Implant Placement Accuracy and Lower Complication Rates, but Not Superior Clinical Results Compared to the Conventional Manual Approach: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Accurate component placement plays a critical role in the outcome of total hip arthroplasty (THA). Robotic-assisted THA (R-THA) has emerged as an option to optimize this aspect compared to the conventional manual THA (C-THA). The aim of this meta-analysis was to analyze the studies comparing R-THA and C-THA. The hypothesis was that the use of robotic technology could improve component positioning, but this advantage may not translate into clinically relevant benefits. METHODS: The literature search was conducted on three databases (PubMed, Cochrane Library, and Web of Science) in January 2024. The screening process and analysis were conducted separately by two independent observers according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. The inclusion criteria were comparative studies, English language, no time limitation, and focusing on the comparison of R-THA and C-THA. Among the 1,883 articles retrieved, 38 studies (10,055 patients) were included. The meta-analysis covered radiological outcomes, clinical outcomes, perioperative parameters, complications, and revisions. The quality of each article was assessed using the "Downs and Black's checklist for measuring quality". RESULTS: Robotic THA provided superior radiological results compared to C-THA in terms of acetabular cup placement within the Lewinnek safe zone (P < 0.01) and horizontal change of the rotation center (P = 0.03). No statistically significant difference was obtained in terms of clinical scores between the two approaches, including Harris Hip Score, Western Ontario and McMaster Universities Arthritis Index, Forgotten Joint Score, and Merle d'Aubigné Hip Score. Robotic THA showed longer operative time (P < 0.01), but lower complication rates (P = 0.04). No difference was obtained in terms of intraoperative blood loss and revision rates. CONCLUSIONS: The results of this meta-analysis suggest that R-THA can provide more accurate cup placement and better restoration of the native hip anatomy while reducing complication rates compared to C-THA. However, these benefits did not translate into clinical differences in terms of patient-reported outcomes between the two approaches, and R-THA required longer operative time. While the overall results suggest some benefits with the robotic technology, future studies should investigate if further technical improvements will translate into clinically relevant benefits for patients undergoing THA.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".