Clinical prediction score for superficial surgical site infection after appendectomy in adults with complicated appendicitis

Autor: Pinit Noorit, Boonying Siribumrungwong, Ammarin Thakkinstian
Jazyk: angličtina
Rok vydání: 2018
Předmět:
Zdroj: World Journal of Emergency Surgery, Vol 13, Iss 1, Pp 1-7 (2018)
Druh dokumentu: article
ISSN: 1749-7922
DOI: 10.1186/s13017-018-0186-1
Popis: Abstract Background Superficial surgical site infection (SSI) is common after appendectomy. This study aims to determine a clinical prediction score for SSI after appendectomy in complicated appendicitis. Methods Data from randomized controlled trial of delayed versus primary wound closures in complicated appendicitis was used. Nineteen patient- and operative-related predictors were selected in the logit model. Clinical prediction score was then constructed using coefficients of significant predictors. Risk stratification was done by receiver operating characteristic (ROC) curve analysis. Bootstrap technique was used to internal validate the score. Results Among 607 patients, the SSI incidence was 8.7% (95% CI 6.4, 11.2). Four predictors were significantly associated with SSI, i.e., presence of diabetes, incisional length > 7 cm, fecal contamination, and operative time > 75 min with the odds ratio of 2.6 (95% CI 1.2, 5.9), 2.8 (1.5, 5.4), 3.6 (1.9, 6.8), and 3.4 (1.8, 6.5), respectively. Clinical prediction score ranged from 0 to 4.5 with its discrimination concordance (C) statistic of 0.74 (95% CI 0.66, 0.81). Risk stratification classified patients into very low, low, moderate, and high risk groups for SSI when none, one, two, and more than two risk factors were presented with positive likelihood ratio of 1.00, 1.45, 3.32, and 9.28, respectively. A bootstrap demonstrated well calibration and thus good internal validation. Conclusions Diabetes, incisional length, fecal contamination, and operative time could be used to predict SSI with acceptable discrimination. This clinical risk prediction should be useful in prediction of SSI. However, external validation should be performed. Trial registration ClinicalTrials.gov (ID NCT01659983), registered August 8, 2012
Databáze: Directory of Open Access Journals
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