RESULTS OF ROBOTIC ASSISTED VS CONVENTIONAL TOTAL KNEE ARTHROPLASTY AT 1 YR FOLLOW UP
Bibliographic record
Abstract
Background: Osteoarthritis (OA) of the knee is a prevalent condition among older individuals, causing significant discomfort and impairments in quality of life. Conventional total knee arthroplasty (COTKA) is a common treatment, but issues such as inadequate soft tissue balance and prosthesis misalignment can impact outcomes. Robotic-assisted total knee arthroplasty (RATKA) has emerged as a potential solution, offering enhanced precision in prosthesis placement. While observational studies suggest benefits, comprehensive reviews of randomized controlled trials (RCTs) are lacking. This study aims to fill this gap by evaluating the clinical, functional, and radiological outcomes of RATKA compared to COTKA in adult patients with primary knee OA. Methods: This prospective study was conducted at a specialized orthopedic center, involving patients diagnosed with symptomatic knee OA eligible for total knee replacement (TKR). Patients were allocated to either conventional TKR (Group A) or robotic-assisted TKR (Group B). Outcome measures included Visual Analog Scale (VAS) for pain, Knee Society Score (KSS), Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), patient satisfaction, and quality of life assessments. Radiological outcomes were assessed using standardized radiographs. Statistical analyses included descriptive statistics, group comparisons, and repeated measures analysis of variance (ANOVA). Results: Baseline characteristics showed similar distributions between Group A (n=30) and Group B (n=30). Clinical outcomes demonstrated significant improvements over time in both groups, with Group B consistently outperforming Group A across all measures. Notably, Group B exhibited lower pain scores (VAS), higher functional scores (KSS), lower disability scores (WOMAC), higher patient satisfaction, and better quality of life assessments. Radiological outcomes also favored Group B, with improved mechanical axis deviation and component positioning. Conclusion: Robotic-assisted TKR demonstrated superior clinical, functional, and radiological outcomes compared to conventional TKR in patients with knee OA. These findings support the growing body of evidence favoring the use of robotic technology in TKR procedures, particularly for optimizing implant placement and alignment. Future research should focus on cost-effectiveness and long-term outcomes to further inform clinical practice and enhance patient care.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".