Risk factors for urinary retention after hip or knee replacement: a cohort study
Bibliographic record
Abstract
INTRODUCTION: In 2006, our provincial government initiated a program to reduce wait times for total hip or knee replacements by referring patients to a single tertiary-care centre. This program provided an opportunity to identify risk factors for perioperative complications as part of a continuing quality improvement project. We report the risk of postoperative urinary retention after hip and knee replacements and the risk factors associated with this complication. METHODS: After local Research Ethics Board approval, data were abstracted from charts of patients who underwent elective primary unilateral total hip or knee replacement surgery. The outcome was urinary retention in the first 24 hr after surgery. Risk factors were identified using multivariable logistic regression, and they were expressed as odds ratios (OR) or 95% confidence intervals (CI). RESULTS: From April 1, 2006 to May 31, 2007, 1,440 patients underwent 1,515 elective total hip replacement or total knee replacement. We abstracted data from 1,031 (71.3%) patients: mean age, 62 yr (interquartile range [IQR] 55-70); 53.7% female; 605 total hip replacements; and 426 total knee replacements. The procedures were performed under spinal (81.8%), general (10.2%), or combined spinal and general (8.0%) anesthesia. Patients spent 100 [IQR 90-114] min in the operating room and 3 [IQR 3-4] days in hospital. The 24-hr incidence of urinary retention was 43.3% (446/1031). Male sex (odds ratio [OR] 3.9; 95% CI 3.0 to 5.2), total hip replacement (OR 1.4; 95% CI 1.1 to 1.9), and intrathecal morphine were risk factors. DISCUSSION: Postoperative urinary retention is a common complication after total hip or total knee replacement, especially amongst men and patients receiving intrathecal morphine.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".