Obesity, Comorbidities, and the Associated Risk among Patients Who Underwent Total Knee Arthroplasty in Alberta
Bibliographic record
Abstract
Abstract Obesity, a common risk factor for osteoarthritis (OA), accelerates joint deterioration resulting in the need for early total knee arthroplasty (TKA). The role of obesity in the management of OA remains a controversial topic. In this study, we examined whether obesity along with other comorbidities is associated with peri/postoperative complications in patients who underwent primary unilateral TKA in Alberta, Canada. A retrospective secondary analysis was performed on data extracted from data repository of patients (n = 15,151) who underwent TKA between 2012 and 2016. The sample was divided into five groups based on body mass index (BMI) classification developed by the World Health Organization. The associations between dependent variable (presence or absence of a complication or comorbidity) with the independent variables (year of surgery, age, sex, length of surgery, and BMI groups) were examined using binomial logistic regression. Results showed that obese classes I, II, and III, irrespective of other covariates, were more likely to have diabetes and pulmonary embolism (p < 0.001) compared with the normal BMI group. Patients with obese class III compared with the patients in normal BMI group were more likely to have deep wound infection (p = 0.04). Patients with comorbidities were more likely to have a blood transfusion, infection, pulmonary embolism, and readmission. Patients in higher BMI groups or with comorbidities were more likely to experience peri/postoperative complications following TKA, though the level of risk depends on the severity of obesity. These findings may be used by health care providers to educate patients in higher BMI groups about the risks of TKA and optimize comorbidities prior to the surgery.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".