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Background: We developed a novel analytic tool for colorectal deep organ/space surgical site infections (C-OSI) prediction utilizing both institutional and extra-institutional American College of Surgeons-National Surgical Quality Improvement Program (ACS-NSQIP) data. Methods: Elective colorectal resections (2006-2014) were included. The primary end point was C-OSI rate. A Bayesian-Probit regression model with multiple imputation (BPMI) via Dirichlet process handled missing data. The baseline model for comparison was a multivariable logistic regression model (generalized linear model; GLM) with indicator parameters for missing data and stepwise variable selection. Out-of-sample performance was evaluated with receiver operating characteristic (ROC) analysis of 10-fold cross-validated samples. Results: Among 2,376 resections, C-OSI rate was 4.6% (n = 108). The BPMI model identified (n = 57; 56% sensitivity) of these patients, when set at a threshold leading to 80% specificity (approximately a 20% false alarm rate). The BPMI model produced an area under the curve (AUC) = 0.78 via 10-fold cross- validation demonstrating high predictive accuracy. In contrast, the traditional GLM approach produced an AUC = 0.71 and a corresponding sensitivity of 0.47 at 80% specificity, both of which were statstically significant differences. In addition, when the model was built utilizing extra-institutional data via inclusion of all (non-Mayo Clinic) patients in ACS-NSQIP, C-OSI prediction was less accurate with AUC = 0.74 and sensitivity of 0.47 (i.e., a 19% relative performance decrease) when applied to patients at our institution. Conclusions: Although the statistical methodology associated with the BPMI model provides advantages over conventional handling of missing data, the tool should be built with data specific to the individual institution to optimize performance. [ABSTRACT FROM AUTHOR]

Background: The present study aimed to analyze risk factors and management strategies for organ space infections (OSI) specifically after colonic resections. Methods: This was a retrospective analysis of all consecutive colonic resections performed between February 2012 and October 2017 in a single-center quality-improvement project. All OSIs were assessed prospectively by an independent national surveillance program ( www.swissnoso.ch ) and classified according to the U.S. Centers for Disease Control and Prevention (CDC) criteria (infection involves organ and spaces other than the incision), including anastomotic leaks. Risk factors for OSI were identified by univariable and multivariable analysis. Results: The study cohort included 1,263 patients (731 elective and 532 emergency colectomies). One hundred fifty-three patients (12%) were found to have an OSI, which occurred at median POD 8 [interquartile range 4-14]. Treatment strategies consisted of surgical management in 85 cases (56%), percutaneous drainage in 36 cases (24%), and antibiotic treatment alone in 32 patients (21%). Independent risk factors for OSI were emergency surgery (odds ratio [OR] 2.06; 95% confidence interval [CI] 1.35-3.16), operation duration >180 minutes (OR 2.10; 95% CI 1.29-3.40), and open surgery (OR 2.51; 95% CI 1.73-3.65). Conclusions: Organ space infections after colonic surgery were more frequent after open emergency surgery and occurred early in the post-operative course. Invasive management was required in 79% of cases. [ABSTRACT FROM AUTHOR]

Background: Reported incidence of surgical site infections (SSI) after colonic surgery varies widely. These variations depend not only on patient- and surgery-related parameters but are influenced by type and quality of follow-up. The aim of the study was to compare SSI assessed by two independent prospective surveillance systems, a national surveillance program based on recommendations of the National Healthcare Safety Network (Swissnoso) versus an international audit system, the ERAS® Interactive Audit System (EIAS; Encare, Stockholm, Sweden).Methods: Comparative study of a consecutive cohort of colonic resections at a single institution from September 2015 to March 2017. Independent prospective SSI monitoring was available from Swissnoso and EIAS. Inter-observer reliability was calculated using Cohen k. Sensitivity, specificity, and accuracy of EIAS in assessing SSI was compared with Swissnoso, considered as gold standard.Results: The final sample included 143 patients. Of these, 136 (95.1%) were classified into the same category by both systems, identifying 17 patients (12.5%) with SSI and 119 patients (87.5%) without SSI, respectively. Discrepant results were found for the remaining seven patients (4.9%) with four SSI categorization according to Swissnoso but not EIAS, and three SSI categorization in EIAS but not in Swissnoso; all miscategorized patients presented superficial SSI. Sensitivity, specificity, and accuracy of EIAS for SSI recording was 81%, 97.5%, and 95.1%, respectively. Inter-observer agreement was high (Cohen k value of 0.801, p < 0.001). Case-by-case analysis of discrepant findings revealed mainly discrepant interpretation of clinical symptoms and erroneous labeling of non-procedure-related infections.Conclusions: Surgical site infection recording by two independent systems showed high concordance and good inter-rater reliability. [ABSTRACT FROM AUTHOR]