Hospital environmental influences and the rate of periprosthetic joint infections at a Canadian tertiary center: a retrospective chart review
Bibliographic record
Abstract
Background: As the demand for total joint arthroplasty is expected to increase substantially in the coming years, the reported incidence of periprosthetic joint infections (PJI) after total joint arthroplasty is also expected to increase. This study investigated both patient factors and hospital factors and their relation to rates of infection for total hip arthroplasty (THA) and total knee arthroplasty (TKA). To the authors’ knowledge, this is the first paper to investigate rates of hand washing and carpet removal to PJIs. Methods: Traditional sample size calculations based on effect sizes or differences were not applicable in this observational, retrospective study. The annual rate of irrigation and debridement (I&D) at our institution was calculated. Hospital environmental influences for carpet removal and hand hygiene were obtained from hospital archives. Patient risk factors were obtained from the electronic patient charting system (PCS). Results: The average rate of I&D for THA was 2.8% and TKA was 1.9%. Hospital environmental influences (carpet removal and hand hygiene) were not associated with the rates of I&D. Conclusions: Despite rates of hand hygiene at our institution being reported as having a greater than 90% success rate, we did not find any association between successful hand hygiene practices and rates of PJI. Our study revealed that the rate of infection for THA at our institution was nearly two to three times higher than what was reported in the literature, and we believe poor patient selection played a factor. Level of Evidence: Level III.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".