Analysis of death related risk factors in intensive care unit after gastrointestinal perforation
10.3760/cma.j.cn115396-20240528-00161
- VernacularTitle:消化道穿孔术后重症监护室患者的死亡相关危险因素分析
- Author:
Heihei LI
1
;
Yongjie WU
;
Jifang LIANG
;
Haipeng SHI
;
Ning MA
Author Information
1. 山西白求恩医院（山西医学科学院 同济山西医院），山西医科大学第三医院重症医学科，太原 030032
- Keywords:
Peptic ulcer perforation;
Intensive care unit;
Death;
Risk factor
- From:
International Journal of Surgery
2024;51(9):597-604
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the mortality-related factors affecting patients with gastrointestinal perforation who are transferred to the intensive care unit (ICU) and to establish a prediction model, and to evaluate the predictive performance of the model.Methods:A retrospective analysis was performed on the medical records of 306 patients who underwent gastrointestinal perforation surgery in Shanxi Bethune Hospital (Shanxi Academy of Medical Sciences) from January 2021 to January 2024 and were transferred to intensive care unit after surgery, including 176 males and 130 females, aged from 28 to 92 years with the average of (66.07±16.03) years. According to the prognosis, patients were divided into survival group ( n=264) and death group ( n=42). Clinical characteristics of the two groups were compared, univariate and multivariate Logistic regression was used to analyze the risk factors of perioperative death, and the related risk factors were selected to establish a nomogram prediction model, the subject work curve was drawn, and the area under the curve (AUC) was calculated. Evaluate its predictive effectiveness; The calibration chart and clinical decision curve were further used to evaluate the prediction accuracy and clinical application value of the model. Results:Clinical data analysis showed that age, white blood cell count, procalcitonin, lactic acid level, preoperative shock, preoperative underlying diseases (cerebral infarction, hormone history), intraoperative blood loss, postoperative lung infection in the death group were higher than those in the survival group ( P<0.05), and hemoglobin was lower than those in the survival group ( P<0.05). Multivariate Logistic regression analysis showed age ( OR=1.422, 95% CI: 1.205-1.680, P<0.001), hemoglobin ( OR=0.945, 95% CI: 0.904-0.987, P=0.012), white blood cell count ( OR=1.832, 95% CI: 1.341-2.501, P<0.001), procalcitonin ( OR=1.099, 95% CI: 1.012-1.192, P=0.024), lactic acid level ( OR=16.435, 95% CI: 3.729-72.425, P<0.001), reoperative shock ( OR=172.358, 95% CI: 13.059-2274.773, P<0.001), intraoperative blood loss ( OR=1.041, 95% CI: 1.017-1.065, P=0.001) and postoperative pulmonary infection ( OR=38.670, 95% CI: 3.449-433.553, P=0.003) was an independent risk factor for perioperative death in intensive care patients after DTP. Based on the screened independent risk factors ( P<0.05), a nomogram model was established and receiver operating characteristic (ROC) curve was drawn. The model area under the curve was 0.985. The accurate graph shows that the predicted results of the model are in good agreement with the actual clinical results, and the analysis of clinical decision curve indicates that the model has high clinical prediction value. Conclusion:Age>71.5 years, hemoglobin< 109 g/L, white blood cell count>17.9×10 9/L, procalcitonin>6.225 ng/mL, lactate level>2.25 mmol/L, preoperative shock, intraoperative blood loss>45 mL and postoperative pulmonary infection are independent risk factors for perioperative death in intensive care patients after DTP.
