886. Impact of Type of Surgical Management on the Incidence of Recurrent Surgical Site Infections Following Hip and Knee replacements in Calgary, Alberta
Bibliographic record
Abstract
Abstract Background Recurrent surgical site infections (SSIs) are associated with decreased quality of life for patients and increased economic burden to healthcare systems. Positive cultures at reimplantation and patient co-morbidities have been shown to increase the risk of recurrent SSI in hip and knee surgical site infections. Two-stage exchange has been considered for the most appropriate surgical management for these SSI’s, however, it is unclear whether the type of revision arthroplasty and pathogen of the first SSI impacts recurrence rates. Methods A retrospective review of prospectively collected data on all complex SSIs following primary hip and knee arthroplasties between April 1 2012 and March 31, 2019, in Calgary, Alberta was performed. Patients were followed for two years post-index arthroplasty to determine initial management of first complex SSI (Debridement, antibiotics and implant retention (DAIR) vs DAIR+liner exchange vs one-stage vs two-stage), rate of recurrent complex SSI, and microbiological data for first and subsequent SSI’s. Results Of the 142 complex SSIs, 95 (66.9%) were managed with DAIR and liner exchange, 25 (17.6%) were managed with DAIR, 13 (9.1%) with one-stage and 8 (5.6%) with two-stage procedures. The recurrence rate was 19/95 (20%) for DAIR and liner, 8/25 (32%) for DAIR alone, 2/13 (15%) with one stage, and 3/8 (37.5%) with two-stage. There was no significant difference in recurrence rates of complex SSI when stratified by surgical management. Of the pathogens, Staphylococcus aureus (S.aureus) (including methicillin-resistant S. aureus (MRSA)) accounted for 35.2% of total first SSI and 50% of recurrences. A significantly higher proportion of S.aureus infections (including MRSA) ended up with a recurrent infection compared to all other pathogens (p=0.045). Of the 32 recurrences, 28.1% were due to the same pathogen as the initial SSI. Conclusion S.aureus was the most common pathogen causing initial and recurrent SSIs. This reinforces that S.aureus complex SSIs would likely benefit from early recognition and aggressive treatment. Recurrence of SSI was not impacted by type of revision arthroplasty. This study is limited by a small sample size. These findings contribute to the paucity of literature in this area and suggest a need for expansion to larger populations. Disclosures All Authors: No reported disclosures
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".