CT-based, robotic-arm assisted total hip arthroplasty (Mako) through anterior approach provides improved cup placement accuracy but no difference in clinical outcomes when compared to conventional technique
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: With the restoration of the natural hip biomechanics, a successful total hip arthroplasty (THA) and long-term survival is pursued. Although robotic THA (rTHA) has been developed to increase accuracy of implant positioning, leg lengths and offsets, discussions about its radiological and clinical advantages over conventional THA (cTHA) continues. OBJECTIVE: The aim of this study was to compare clinical and radiological outcomes of robotic and conventional THA. METHODS: This retrospective study compares functional and radiological outcomes of 82 rTHA with a matched group of 82 cTHA in terms of age, sex, body mass index and preoperative functional scores. The minimum follow up was 12 months for all patients. Functional outcomes were Harris Hip Score (HHS) and the Western Ontario and McMaster University Osteoarthritis index (WOMAC) evaluated pre- and postoperatively. Radiological evaluations included position of cup placement according to Lewinnek and Callanan safe zones, Canal Fill Ratio (CFR), Leg Length Discrepancy (LLD), Lateral offset (LO) and Femoral Component Alignment (FCA). Complications were also evaluated. RESULTS: In the rTHA group, 91.5% (75 out of 82) of the acetabular cups were positioned within the safe zone whereas it was 63.4% (52 out of 82) for the cTHA group (p< 0.001). According to Callanan, they were 84.1% and 50%, respectively (p< 0.001). Between the groups, no statistically significant difference was found in CFR, LLD, HO, FCA, AI, AA, WOMAC, HHS and major complication rates. CONCLUSION: rTHA is superior to cTHA in terms of accuracy and reproducibility of the cup placement, however no apparent clinical benefit was found in short term follow.
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
| 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 it