Evaluating the impact of surgery sequence on infection rates in hip or knee arthroplasty: does sequence matter?
Bibliographic record
Abstract
PURPOSE: The potential influence of surgical sequence of elective hip-and-knee reconstructive surgery in relation to an infection-related procedure on postoperative infection rates is not clearly understood. Therefore, we aimed to examine the impact of surgical sequence on the incidence of postoperative infections within one-year and the longest available follow-up period in patients undergoing hip-and-knee reconstructive surgery. METHODS: A case-control study with propensity matching was utilized to examine elective surgeries conducted at Sunnybrook Holland Orthopaedic & Arthritic centre, Toronto, Canada between 2015 and 2018. We determined and categorized them based on their operating room (OR) sequence in relation to an infected case; the cases were those performed right after (post-infection cohort), and the controls were those performed before an infection-related procedure in the same OR (pre-infection cohort). We employed survival analysis to compare the infection incidence within one year and at the longest available follow-up among the propensity-matched cohort. RESULTS: A total of 13,651 cases were identified during the four year period. We successfully matched 153 cases (21 post-infection and 132 pre-infection) using propensity scores. Demographic and clinical characteristics were balanced through matching. Kaplan-Meier survival analysis showed no significant difference in infection-free survival within one year and at a median follow-up of 2.2 years [interquartile range 0.9-5.0] between surgeries conducted before and after infected cases (both log-rank p-values = 0.4). The hazard ratios for infection within one year and the longest follow-up period were both 0.37 [95%Confidence Interval 0.03-4.09, p = 0.418], as no more events occurred after one year. CONCLUSION: The sequence of surgical procedures, whether or not an elective arthroplasty or lower limb reconstructive procedure occurs before or after an infection-related case in the same OR, does not significantly affect postoperative infection rates. This finding supports the efficacy of the current infection control measures and suggests a reconsideration of surgical scheduling standards.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".