Surgery-related predictors of kneeling ability following total knee arthroplasty: a systematic review and meta-analysis
Bibliographic record
Abstract
PURPOSE: Kneeling ability is among the poorest outcomes following total knee arthroplasty (TKA). The purpose of this meta-analysis was to: (1) quantify kneeling ability after TKA; (2) identify surgical approaches and prosthesis designs that improve kneeling ability following TKA; and (3) quantify the effectiveness of these approaches. METHODS: We performed a systematic review in accordance with the PRISMA guidelines of multiple medical databases. Data relating to demographics, TKA technique, prosthesis design, and kneeling-specific outcomes were extracted. Comparative outcomes data were pooled using a random effects model. RESULTS: Thirty-six studies met the eligibility criteria. The proportion of patients able to kneel increased with longer follow-up (36.8% at a minimum of 1 year follow-up versus 47.6% after a minimum of 3 years follow-up, p < 0.001). The odds of kneeling were greater for patients undergoing an anterolateral incision compared with an anteromedial incision (OR 3.0, 95% CI 1.3-6.9, p = 0.02); a transverse incision compared with a longitudinal incision (OR 3.5, 95% CI 1.4-8.7, p = 0.008); and a shorter incision compared with a longer incision (OR 8.5, 95% CI 2.3-30.9, p = 0.001). The odds of kneeling were worse for a mobile prosthesis compared with a fixed platform design (OR 0.3, 95% CI 0.1-0.7, p = 0.005). CONCLUSION: A large majority of patients are unable to kneel following TKA, although the ability to kneel improves over time. This evidence may facilitate preoperative patient counseling. Variations in choice of incision location and length may affect ability to kneel; however, high-quality randomized trials are needed to corroborate our findings.
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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 | 0.019 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.025 | 0.012 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".