Influence of sex on surgical time in primary total knee arthroplasty.
Bibliographic record
Abstract
BACKGROUND: Total knee arthroplasty (TKA) is widely recognized as an effective procedure for treatment of knee arthritis. However, there have been documented differences between men and women with respect to anatomic variability, timing of access to surgical care and surgical outcomes. We examined the influence of sex on the technical difficulty of TKA using a tourniquet and overall surgical time as a surrogate for complexity of exposure, soft-tissue balancing and implantation. METHODS: We performed a retrospective database review of patients who underwent primary TKA over a 5-year period. Tourniquet time, wound closure time and surgical time from 54 consecutive men (58 knees) and 48 women (58 knees) who underwent primary cemented TKA were recorded. RESULTS: The mean surgical time among men (108.2, standard deviation [SD] 17 min) was significantly longer than among women (96.8 [SD 14.8] min; p = 0.001). Similarly, the mean tourniquet time among men (75.9 [SD 11.7] min) was significantly longer than among women (65.9 [SD 11.8] min; p = 0.001). CONCLUSION: Total knee arthroplasty in men requires more time than in women because of the complexity of exposure and to achieve the desired alignment of the components. Our data may allow a better resolution of surgery time planning, which could lead to better use of health system resources.
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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 | 0.007 |
| 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".