Medical Comorbidities and Functional Dependent Living Are Independent Risk Factors for Short-Term Complications Following Osteotomy Procedures about the Knee
Bibliographic record
Abstract
Objective To characterize rates and risk factors for adverse events following distal femoral osteotomy (DFO), high tibial osteotomy (HTO), and tibial tubercle osteotomy (TTO) procedures. Design Patients undergoing DFO, HTO, or TTO procedures during 2005 to 2016 were identified in the American College of Surgeons National Surgical Quality Improvement Program. Rates of adverse events were characterized for each procedure. Demographic, comorbidity, and procedural factors were tested for association with occurrence of any adverse events. Results A total of 1,083 patients were identified. Of these, 305 (28%) underwent DFO, 273 (25%) underwent HTO, and 505 (47%) underwent TTO. Mean ages for patients undergoing each procedure were the following: DFO, 51 ± 23 years; HTO, 40 ± 13 years; and TTO, 31 ± 11 years. The most common comorbidities for DFO were hypertension (34%) and smoking (17%); for HTO, hypertension (22%) and smoking (21%); and for TTO, smoking (20%) and hypertension (11%). Independent risk factors for occurrence of any adverse event were age ⩾45 years for DFO (odds ratio [OR] = 3.1, P < 0.001) and HTO (OR = 2.3, P = 0.029), and body mass index >30 for HTO (OR = 2.5, 95% confidence interval = 1.1-5.7, P = 0.031). When all osteotomy procedures were analyzed collectively, additional variables including diabetes mellitus (OR = 2.2, P = 0.017), chronic obstructive pulmonary disease (OR = 5.5, P = 0.003), and dependent functional status (OR = 3.0, P = 0.004) were associated with adverse events. Conclusions The total rate of adverse events was not independently associated with the type of osteotomy procedure. In addition, patients with age >45, diabetes mellitus, chronic obstructive pulmonary disease, and dependent functional status have greater odds for adverse events and should be counseled and monitored accordingly.
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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 | 0.001 |
| 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) | 0.002 | 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".