Functional outcome of total knee arthroplasty after high tibial osteotomy.
Bibliographic record
Abstract
OBJECTIVE: To evaluate the functional outcome for patients who undergo total knee arthroplasty (TKA) after high tibial osteotomy (HTO). DESIGN: Retrospective matched cohort study. SETTING: University of Toronto affiliated hospital. PATIENTS: Twenty patients who underwent TKA after HTO and 20 matched patients who received a primary TKA. INTERVENTION: TKA. OUTCOME MEASURES: The Medical Outcomes Study Short Form (SF-36) health survey score and the Western Ontario and McMaster Universities (WOMAC) Osteoarthritis Index. Univariate analyses were used to compare the case and control groups with respect to baseline variables using the t-test, chi2 test or Fisher's exact test. Functional outcomes were assessed by multivariate analyses. RESULTS: Operative problems were more frequently encountered in the study group, which had longer operative times (p < 0.0001), more difficulties with patellar eversion (p = 0.021) and an increased number of lateral releases performed (p = 0.0089). There were trends toward a significant difference in the pain (p = 0.07), function (p = 0.18) and stiffness (p = 0.14) categories of the WOMAC Osteoarthritis Index between the 2 groups, suggesting poorer functional outcomes of TKA after HTO, but the results did not reach statistical significance. A previous HTO does not affect the general health of patients after TKA, as there was no difference between the 2 groups in SF-36 scores. CONCLUSIONS: TKA after HTO is a technically more challenging procedure than primary TKA. The functional outcomes at a mean follow-up of 5 years after TKA in patients with a previous HTO tended to be inferior but the differences were not significant (p > or = 0.05).
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".