Risk factors for surgical site infection after kidney and pancreas transplantation
Bibliographic record
Abstract
OBJECTIVE: To evaluate the incidence of surgical site infection (SSI) in a cohort of pancreas transplant recipients and assess predisposing risk factors for SSI DESIGN: Retrospective cohort study SETTING: Single transplant center in CanadaPatientsPatients who underwent any simultaneous pancreas and kidney (SPK) or pancreas after kidney (PAK) transplant procedures between January 2000 and December 2015 METHODS: In this retrospective cohort evaluation of SPK or PAK recipients, we assessed the incidence of SSI and risk factors associated with superficial, deep, and organ/space SSI. Multivariate logistic regression was used to identify independent risk factors for SSI in SPK and PAK recipients. RESULTS: In total, 445 adult transplant recipients were enrolled. The median age of these patients was 51 years (range, 19-71 years), and 64.9% were men. SSIs were documented in 108 patients (24.3%). Organ/space SSIs predominated (59 patients, 54.6%), followed by superficial SSIs (47 patients, 43.5%) and deep SSIs (3 patients, 2.8%). Factors predictive of SSIs in the multivariate analysis were cold pancreas ischemic time (odds ratio [OR], 1.002; P=.019) and SPK transplant (compared to PAK transplant recipients; OR, 2.38; P=.038). Patients with SSIs developed graft loss more frequently (OR, 16.99; P<.001). CONCLUSIONS: Organ/space SSIs remain a serious and common complication after SPK and PAK. Prolonged cold ischemic time and SPK transplant were the risk factors predictive of SSIs. Appropriate perioperative prophylaxis in high-risk patients targeting the potential pathogens producing SSIs in kidney and/or pancreas transplant recipients and a reduction in cold ischemia may prove beneficial in reducing these SSIs.
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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 | 0.000 | 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) | 0.000 | 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".