Intraoperative femurofibular angle combined with tibiofibular angle measurement has fewer correction errors in open-wedge high tibial osteotomy
Bibliographic record
Abstract
AIM: This study aimed to verify the accuracy of intraoperative femurofibular angle combined with tibiofibular angle (FFA-TFA) measurement and compare it with traditional alignment line methods in open-wedge high tibial osteotomy (OWHTO). METHODS: A total of 174 knees of 122 patients undergoing OWHTO and using an alignment line or FFA-TFA measurement as an index of optimal correction were included in this retrospective study. The intraoperative alignment line passed through the targeted weight-bearing line (WBL) of the tibial plateau in the alignment line group. The intraoperative FFA-TFA aligned to the preplanned FFA-TFA angle in the FFA-TFA group. WBL, FFA, TFA, and knee joint-line convergence angle of the femur and tibia were assessed as radiological results preoperatively and one year after surgery. The Knee Society Score and the Western Ontario and McMaster Universities were assessed as objective clinical results. RESULTS: Postoperative WBL in the FFA-TFA group was closer to the target WBL than in the alignment line group (FFA-TFA vs alignment line group: 1.43 ± 1.20% vs 3.82 ± 3.29%; P < 0.001). The FFA-TFA group had fewer over-correction and under-correction rates than the alignment line group (28.7% and 12.6% vs 11.5% and 3.40%; P < 0.001). No significant differences were observed in the clinical results between the two groups one year after surgery (P > 0.05). CONCLUSIONS: The intraoperative measurement of FFA-TFA had fewer complications in terms of under-correction and over-correction compared with the alignment line measurement. No significant differences between the two methods were observed in clinical results one year after surgery.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.001 | 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; 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".