How likely is septic shock to develop in a patient with Fournier's gangrene? A risk prediction model based on a 7-year retrospective study. (11th August 2022)

• Record Type: Journal Article
• Authors: Yang, Yang; Wang, Li-Chun; Yu, Xin-Yang; Zhang, Xiao-Fei; Yang, Zhong-Qing; Zheng, Yang-Zi; Jiang, Bin-Yan; Chen, Lei
• Is Part Of: Gastroenterology report. Volume 10(2022)
• Publication Date: 2022-08-11
• Subjects: Fournier's gangrene -- sepsis -- septic shock -- nomogram -- risk prediction; Gastroenterology -- Periodicals; 616.33
• DOI: 10.1093/gastro/goac038
• Languages: English
• ISSNs: 2052-0034

Abstract

Abstract: Background: Fournier's gangrene (FG) is a rare life-threatening form of necrotizing fasciitis. The risk factors for septic shock in patients with FG are unclear. This study aimed to identify potential risk factors and develop a prediction model for septic shock in patients with FG. Methods: This retrospective cohort study included patients who were treated for FG between May 2013 and May 2020 at the Sixth Affiliated Hospital, Sun Yat-sen University (Guangzhou, China). The patients were divided into a septic shock group and a non-septic shock group. An L1-penalized logistic regression model was used to detect the main effect of important factors and a penalized Quadratic Discriminant Analysis method was used to identify possible interaction effects between different factors. The selected main factors and interactions were used to obtain a logistic regression model based on the Bayesian information criterion. Results: A total of 113 patients with FG were enrolled and allocated to the septic shock group ( n = 24) or non-septic shock group ( n = 89). The best model selected identified by backward logistic regression based on Bayesian information criterion selected temperature, platelets, total bilirubin (TBIL) level, and pneumatosis on pelvic computed tomography/magnetic resonance images as the main linear effect and Na + × TBIL as the interaction effect. The area under the ROC curve of the probability of FG with septic shock by our model was 0.84 (95% confidence interval, 0.78–0.95). The Harrell's concordance index for the nomogram was 0.864 (95% confidence interval, 0.78–0.95). Conclusion: We have developed a prediction model for evaluation of the risk of septic shock in patients with FG that could assist clinicians in identifying critically ill patients with FG and prevent them from reaching a crisis state.