Xinsuo Zhuang1, Fumei Chen1, Qian Zhou1, Yuanrun Zhu1, Xiaofeng Yang2. 1. Emergency and Trauma Center, The International Medical Center, The First Affiliated Hospital, Zhejiang University School of Medicine, 1367 West Wenyi Rd.Zhejiang Province, Hangzhou, 310058, China. 2. Emergency and Trauma Center, The International Medical Center, The First Affiliated Hospital, Zhejiang University School of Medicine, 1367 West Wenyi Rd.Zhejiang Province, Hangzhou, 310058, China. zjcswk@zju.edu.cn.
Abstract
BACKGROUND: Acute mesenteric ischemia (AMI) is a life-threatening condition. However, there is no accurate method to predict intestinal necrosis in AMI patients that may facilitate early surgical intervention. This study thus aimed to explore a simple and accurate model to predict intestinal necrosis in patients with AMI. METHODS: A single-center retrospective study was performed on the data of 132 AMI patients treated between October 2011 and June 2020. The patients were divided into the intestinal necrosis and non-intestinal necrosis groups. The clinical characteristics and laboratory data were analyzed by univariate analysis, and the variables with statistical significance were further analyzed by multivariate logistic regression analysis. The independent predictors of intestinal necrosis were determined and a logistic prediction model was established. Finally, the accuracy, sensitivity, and specificity of the model in predicting intestinal necrosis were evaluated. RESULTS: Univariate analysis showed that white blood cell (WBC) count, blood urea nitrogen (BUN) level, neutrophil ratio, prothrombin time (PT), and LnD-dimer were associated with intestinal necrosis. According to logistic regression multivariate analysis, WBC count, BUN level and LnD-dimer were independent predictors of intestinal necrosis. These parameters were used to establish a clinical prediction model of intestinal necrosis (CPMIN) as follows: model score = 0.349 × BUN (mmol/L) + 0.109 × WBC × 109 (109/L) + 0.394 × LnD - Dimer (ug/L) - 7.883. The area under the receiver operating characteristics (ROC) curve of the model was 0.889 (95% confidence interval: 0.833-0.944). Model scores greater than - 0.1992 predicted the onset of intestinal necrosis. The accuracy, specificity, and sensitivity of the model were 82.6%, 78.2%, and 88.3%, respectively. The proportion of intestinal necrosis in the high-risk patient group (CPMIN score ≥ - 0.1992) was much greater than that in the low-risk patient group (CPMIN score < - 0.1992; 82.7% vs. 15.0%, p < 0.001). CONCLUSION: The CPMIN can effectively predict intestinal necrosis and guide early surgical intervention to improve patient prognosis. Patients with AMI who are classified as high-risk should be promptly treated with surgery to avoid the potential complications caused by delayed operation. Patients classified as low-risk group can receive non-surgical treatment. This model may help to lower the morbidity and mortality from AMI. However, this model's accuracy should be validated by larger sample size studies in the future.
BACKGROUND: Acute mesenteric ischemia (AMI) is a life-threatening condition. However, there is no accurate method to predict intestinal necrosis in AMIpatients that may facilitate early surgical intervention. This study thus aimed to explore a simple and accurate model to predict intestinal necrosis in patients with AMI. METHODS: A single-center retrospective study was performed on the data of 132 AMIpatients treated between October 2011 and June 2020. The patients were divided into the intestinal necrosis and non-intestinal necrosis groups. The clinical characteristics and laboratory data were analyzed by univariate analysis, and the variables with statistical significance were further analyzed by multivariate logistic regression analysis. The independent predictors of intestinal necrosis were determined and a logistic prediction model was established. Finally, the accuracy, sensitivity, and specificity of the model in predicting intestinal necrosis were evaluated. RESULTS: Univariate analysis showed that white blood cell (WBC) count, blood ureanitrogen (BUN) level, neutrophil ratio, prothrombin time (PT), and LnD-dimer were associated with intestinal necrosis. According to logistic regression multivariate analysis, WBC count, BUN level and LnD-dimer were independent predictors of intestinal necrosis. These parameters were used to establish a clinical prediction model of intestinal necrosis (CPMIN) as follows: model score = 0.349 × BUN (mmol/L) + 0.109 × WBC × 109 (109/L) + 0.394 × LnD - Dimer (ug/L) - 7.883. The area under the receiver operating characteristics (ROC) curve of the model was 0.889 (95% confidence interval: 0.833-0.944). Model scores greater than - 0.1992 predicted the onset of intestinal necrosis. The accuracy, specificity, and sensitivity of the model were 82.6%, 78.2%, and 88.3%, respectively. The proportion of intestinal necrosis in the high-risk patient group (CPMIN score ≥ - 0.1992) was much greater than that in the low-risk patient group (CPMIN score < - 0.1992; 82.7% vs. 15.0%, p < 0.001). CONCLUSION: The CPMIN can effectively predict intestinal necrosis and guide early surgical intervention to improve patient prognosis. Patients with AMI who are classified as high-risk should be promptly treated with surgery to avoid the potential complications caused by delayed operation. Patients classified as low-risk group can receive non-surgical treatment. This model may help to lower the morbidity and mortality from AMI. However, this model's accuracy should be validated by larger sample size studies in the future.