Does Robotic‐Assisted Total Knee Arthroplasty Improve Outcomes of Adult Osteoarthritis Patients—A Systematic Review and Trial Sequential Meta‐Analysis
Bibliographic record
Abstract
ABSTRACT Background and Objectives Total knee arthroplasty (TKA) is a standard treatment for end‐stage knee osteoarthritis (KOA). While conventional TKA (cTKA) is widely used, robotic‐assisted TKA (rTKA) has gained attention for its potential precision and improved outcomes. However, the comparative efficacy and safety of rTKA versus cTKA remain unclear due to inconsistent findings in existing studies. This study aims to systematically review and compare the efficacy and safety of rTKA and cTKA in patients with KOA. Methods A total of seven databases were searched. Only randomized controlled trials (RCTs) were included in this systematic review. Subgroup analysis, sensitivity analysis, and trial sequential analysis (TSA) were used to evaluate the stability of the results. Results Twenty‐five RCTs involving 3156 patients with KOA were included. The only statistically significant clinical difference between patients who received rTKA and cTKA was that the rTKA group was associated with a longer operative duration (MD = 22.38 mins; 95% confidence interval [CI] [12.86, 31.91]; p < 0.00001; I 2 = 98%). As for functional parameters, the two groups had similar results in postoperative Knee Society Score (KSS), the Western Ontario and McMaster Universities (WOMAC), and Hospital for Special Surgery Score (HSS). Regarding the tibiofemoral angle and the coronal femoral component angle, no significant difference was observed between the two groups. Patients in the rTKA group had a higher hip–knee–ankle angle (HKA) (MD = 0.63; 95% CI [0.23, 1.03]; p = 0.002; I 2 = 52%), lower HKA deviation (MD = −0.99; 95% CI [−1.24, −0.74]; p < 0.00001; I 2 = 0%), and a higher coronal tibial component angle (MD = 0.46; 95% CI [0.07, 0.85]; p = 0.02; I 2 = 81%) after the surgery. Conclusions While rTKA appears to be a feasible and safe alternative to cTKA, the mixed evidence from our study highlights the need for further research to fully understand its clinical implications and long‐term outcomes. Trial Registration: PROEPERO: CRD42024541052
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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 | 0.009 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.022 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".