Prolonged surgical time increases the odds of complications following total knee arthroplasty
Bibliographic record
Abstract
Background: The aim of this study was to evaluate the influence of operating time on complications and readmission within 30 days of total knee arthroplasty (TKA) and to determine if there were specific time intervals associated with worse outcomes. Methods: The American College of Surgeons’ National Surgical Quality Improvement Program database was used to identify patients 18 years of age and older who underwent TKA between 2006 and 2017, using procedural codes. Patient demographic characteristics, operation length and 30-day major and minor complication and readmission rates were captured. We used multivariable regression to determine if the rates of complications and readmission differed depending on the length of the operation, while adjusting for relevant covariables. Results: A total of 263 174 patients who underwent TKA were identified from the database. Their mean age was 66.8 (standard deviation 9.7) years. Within 30 days of the index procedure, 5700 patients (2.2%) experienced a major complication, 5185 (2.0%) experienced a minor complication and 7730 (3.1% of 249 746 patients from 2011 to 2017) were readmitted. Mean operation length was 91.7 minutes (range 30–240 min). After adjustment for relevant covariables, an operating time of 90 minutes or more was a significant predictor of major and minor complications as well as readmission. There was no difference in the odds of complications or readmission for operations lasting 30–49, 50–69 or 70–89 minutes (p > 0.05). Conclusion: Our data suggest that operating times of 90 minutes or more may be associated with an increase in the 30-day odds of complications and readmission following TKA. Further studies are needed to confirm our findings and determine the influence of surgical time on outcomes when there is increased case complexity.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.000 |
| 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 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".