Computer-Navigated versus Conventional Total Knee Arthroplasty: A Meta-Analysis of Functional Outcomes from Level I and II Randomized Controlled Trials
Bibliographic record
Abstract
Abstract The main purpose of this article is to provide an up-to-date systematic review and meta-analysis comparing functional outcomes of total knee arthroplasty using either computer navigation (NAV-TKA) or conventional methods (CON-TKA) from the latest assemblage of evidence. This study was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses and Meta-Analysis of Observational Studies in Epidemiology guidelines. All Level I and II randomized controlled trials (RCTs) in PubMed, EMBASE, and Cochrane that compared functional outcomes after NAV- and CON-TKA were included in the review. Selected end points for random effects, pairwise meta-analysis included Knee Society Knee Score (KSKS), KS Function Score (KSFS), KS Total Score (KSTS), Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), and range of motion at three arbitrary follow-up times. A total of 24 prospective RCTs comprising 3,778 knees were included from the initial search. At long-term follow-up (>5 years), NAV-TKA exhibited significantly better raw KSKS (p = 0.001) (low-quality evidence), contrary to CON-TKA, which reflected significantly better raw KSTS (p = 0.004) (high-quality evidence). While change scores (KSKS, WOMAC) from preoperative values favor CON-TKA at short-term (<6 months) and medium-term follow-up (6–60 months), long-term follow-up change scores in KSKS suggest the superiority of NAV-TKA over CON-TKA (p = 0.02) (very low-quality evidence). Overall, sizeable dispersion of nonstatistically significant functional outcomes in the medium term was observed to eventually converge in the long term, with less differences in functional outcome scores between the two treatment methods in short- and long-term follow-up. While raw functional outcome scores reflect no differences between NAV and CON-TKA, long-term follow-up change scores in KSKS suggest superiority of NAV-TKA over its conventional counterpart. Prospective studies with larger power are required to support the pattern of diminishing differences in functional outcome scores from medium- to long-term follow-up between the two modalities.
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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 | 0.025 | 0.051 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.027 | 0.055 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| 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".