The effect of patient, provider and surgical factors on survivorship of high tibial osteotomy to total knee arthroplasty: a population-based study
Bibliographic record
Abstract
PURPOSE: The aim of this study was to identify the survivorship of high tibial osteotomy (HTO) to total knee arthroplasty (TKA) on a population level, and identify the patient, provider and surgical factors that influenced eventual TKA. METHODS: Administrative records from physician billings and hospital admissions were used to identify all adults in Ontario, Canada, who underwent an HTO from 1994 to 2010. The primary outcome was time to TKA, which was estimated using Kaplan-Meier (KM) survival analysis. A Cox proportional hazards model examined the risk associated with patient factors (age, sex, income and co-morbidity score), provider factors (hospital status, surgeon volume and surgeon year in practice) and surgical factors (concurrent ligament reconstruction or bone grafting; and previous chondral or meniscal surgery). RESULTS: A total of 2671 patients who underwent HTO met inclusion. The median age was 46 years (interquartile range 39-53 years), and 62 % were male. The KM survivorship of HTO to TKA at 10 years was 0.67 ± 0.01. Older age [HR 1.05 (95 % CI 1.04, 1.06), p < 0.001; 5 % increased risk for each year over age 46], female sex [HR 1.35 (95 % CI 1.17, 1.55), p < 0.001], higher comorbidity score [HR 1.58 (95 % CI 1.12, 2.22), p = 0.009] and a prior history of arthroscopy/meniscectomy [HR 1.24 (95 % CI 1.08, 1.43), p = 0.002] increased the risk of eventual TKA. However, HTO with concurrent ligament reconstruction was associated with lower [HR 0.62 (95 % CI 0.43, 0.88), p = 0.008] risk of eventual TKA. CONCLUSION: In this population, two-thirds of patients were able to avoid a TKA for 10 years after HTO. Specific factors such as older age, female sex, higher comorbidity and prior meniscectomy lowered survival rates. An understanding of patient risk factors for conversion to TKA may help guide surgeons in their selection of patients who will benefit most from HTO. LEVEL OF EVIDENCE: Retrospective cohort study, III.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".