Return to Sport and Work Following Distal Femoral Varus Osteotomy: A Systematic Review
Bibliographic record
Abstract
Background: Distal femoral varus osteotomy (DFVO) is an effective surgical intervention for the management of symptomatic valgus malalignment of the knee. Because it preserves the native knee joint and its ligamentous stability, DFVO is preferred to total knee arthroplasty (TKA) in the young, active population. Purpose: We sought to assess return to work (RTW) and return to sport (RTS) rates following DFVO for valgus malalignment of the knee. Methods: For this systematic review, we searched EMBASE, MEDLINE, and Web of Science from inception through December 31, 2020. English language studies of all levels of evidence explicitly reporting on RTS and RTW rates following DFVO for valgus malalignment of the knee were eligible for inclusion. Results: Seven studies and 127 patients were included in our analysis. Mean age was 32.4 ± 8.8 years with men comprising 46.7% ± 22.3% of study populations. The mean RTS rate was 87.2% ± 10.7%, with a return to preoperative activity levels rate of 65.4% ± 26.8%. The mean RTW rate was 81.8% ± 23.3%, with a return to preoperative activity levels of 72.8% ± 18.1%. The mean reoperation rate was 35.6% ± 18.8% within a mean follow-up period of 5.5 ± 1.9 years. Conclusions: This systematic review of low-level studies found DFVO to be a safe and effective procedure for the management of genu valgum in young, active populations, with most patients returning to sport and/or work, although not all at their preoperative activity levels. A paucity of data surrounds RTS and RTW rates following DFVO. Future studies should explicitly report both return to activity rates and whether patients returned to their preoperative activity levels.
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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 | 0.005 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".