Ze Zhang,1 Haotian Zhao,2 Zhiyang Zhang,1 Lijing Jia,1 Ling Long,1 You Fu,1 Quansheng Du1 

1Department of Intensive Care Unit, Hebei General Hospital, Shijiazhuang, Hebei, People’s Republic of China; 2Department of Ultrasound, Hebei General Hospital, Shijiazhuang, Hebei, People’s Republic of China

Correspondence: Quansheng Du, Department of Intensive Care Unit, Hebei General Hospital, Shijiazhuang, 050000, Hebei, People’s Republic of China, Email duquansheng@hebmu.edu.cn

Background: Acute respiratory distress syndrome (ARDS) is a severe form of organ dysfunction and a common postoperative complication. This study aims to develop a predictive model for ARDS in postoperative patients with gastrointestinal perforation to facilitate early detection and effective prevention.
Methods: In this single-center retrospective study, clinical data were collected from postoperative patients with gastrointestinal perforation admitted to the ICU in Hebei Provincial People’s Hospital from October 2017 to May 2024. Univariate analysis and multifactorial logistic regression analysis were used to determine the independent risk factors for developing ARDS. Nomograms were developed to show predictive models, and the discrimination, calibration, and clinical usefulness of the models were assessed using the C-index, calibration plots, and decision curve analysis (DCA).
Results: Two hundred patients were ultimately included for analysis. In the development cohort, 38 (27.1%) of 140 patients developed ARDS, and in the internal validation cohort, 13 (21.7%) of 60 patients developed ARDS. The multivariate logistic regression analysis revealed the site of perforation (OR = 0.164, P = 0.006), the duration of surgery (OR = 0.986, P = 0.008), BMI (OR = 1.197, P = 0.015), SOFA (OR = 1.443, P = 0.001), lactate (OR = 1.500, P = 0.017), and albumin (OR = 0.889, P = 0.007) as the independent risk factors for ARDS development. The area under the curve (AUC) was 0.921 (95% CI: 0.869, 0.973) for the development cohort and 0.894 (95% CI: 0.809, 0.978) for the validation cohort. The calibration curve and decision curve analysis (DCA) demonstrate that the nomogram possesses good predictive value and clinical practicability.
Conclusion: Our research introduced a nomogram that integrates six independent risk factors, facilitating the precise prediction of ARDS risk in postoperative patients following gastrointestinal perforation.

Keywords: gastrointestinal perforation, acute respiratory distress syndrome, prediction model, nomogram