Abstract：
BACKGROUND: The goal of this study is to look into the factors that lead to death in patients with necrotizing soft tissue infections（NSTIs） in the intensive care unit and create a mortality risk model.
METHODS: The clinical data of 106 patients with necrotizing soft tissue infections admitted to intensive care unit(ICU) of the First Affiliated Hospital of Wenzhou Medical University between January 2008 and December 2021 were retrospectively analyzed. Univariate analysis and multivariate analysis were performed to evaluate the risk factors impacting patient mortality. The regression coefficient in binary logistic regression analysis was converted into the item score in the model, and then the model score of each patient was calculated. Finally, an ROC curve was constructed to evaluate the efficiency of the model for predicting mortality. Thirteen patients with NSTIs admitted to ICU between January 2022 and November 2022 were used to validate the model.
RESULTS: The death group had 44 patients, while the survival group had 62 patients. The overall mortality was 41.5%. Binary logistic regression analysis showed that risk factors for mortality were age≥ 60 years(OR:4.419; 95%CI:1.093-17.862; P = 0.037), creatinine ≥ 132μmol/L(OR:11.166; 95%CI:2.234-55.816; P = 0.003), creatine kinase ≥ 1104 U/L(OR:4.019; 95%CI:1.134-14.250; P = 0.031), prothrombin time ≥ 24.4 s(OR:11.589; 95%CI:2.510-53.506; P = 0.002), and invasive mechanical ventilation (OR:17.404; 95%CI:4.586-66.052; P＜0.000). The AUC of the model for predicting mortality was 0.940 (95% CI:0.894-0.986). When the cut-off value for the model was 4 points, the sensitivity was 95.5% and the specificity was 83.9%.
CONCLUSIONS: The death risk model in this study for NSTIs patients in the intensive care unit shows high sensitivity and specificity. Patients with a score of ≥ 4 points have a higher risk of mortality.
METHODS: The clinical data of 106 patients with necrotizing soft tissue infections admitted to intensive care unit(ICU) of the First Affiliated Hospital of Wenzhou Medical University between January 2008 and December 2021 were retrospectively analyzed. Univariate analysis and multivariate analysis were performed to evaluate the risk factors impacting patient mortality. The regression coefficient in binary logistic regression analysis was converted into the item score in the model, and then the model score of each patient was calculated. Finally, an ROC curve was constructed to evaluate the efficiency of the model for predicting mortality. Thirteen patients with NSTIs admitted to ICU between January 2022 and November 2022 were used to validate the model.
RESULTS: The death group had 44 patients, while the survival group had 62 patients. The overall mortality was 41.5%. Binary logistic regression analysis showed that risk factors for mortality were age≥ 60 years(OR:4.419; 95%CI:1.093-17.862; P = 0.037), creatinine ≥ 132μmol/L(OR:11.166; 95%CI:2.234-55.816; P = 0.003), creatine kinase ≥ 1104 U/L(OR:4.019; 95%CI:1.134-14.250; P = 0.031), prothrombin time ≥ 24.4 s(OR:11.589; 95%CI:2.510-53.506; P = 0.002), and invasive mechanical ventilation (OR:17.404; 95%CI:4.586-66.052; P＜0.000). The AUC of the model for predicting mortality was 0.940 (95% CI:0.894-0.986). When the cut-off value for the model was 4 points, the sensitivity was 95.5% and the specificity was 83.9%.
CONCLUSIONS: The death risk model in this study for NSTIs patients in the intensive care unit shows high sensitivity and specificity. Patients with a score of ≥ 4 points have a higher risk of mortality.
摘要：
背景：本研究的目的是研究导致重症监护病房坏死性软组织感染（NSTIs）患者死亡的因素，并建立死亡风险模型。
方法：回顾性分析2008年1月至2021年12月温州医科大学附属第一医院重症监护病房（ICU）收治的106例坏死性软组织感染患者的临床资料。进行单因素分析和多因素分析以评估影响患者死亡率的危险因素。二元logistic回归分析中的回归系数转化为模型中的项目得分,然后计算每个患者的模型评分。最后,构建ROC曲线评价模型预测死亡率的效率.2022年1月至2022年11月期间入住ICU的13例NSTIs患者用于验证该模型。
结果：死亡组有44例患者，而生存组有62例患者。总死亡率为41.5%。二元logistic回归分析显示,死亡的危险因素为年龄≥60岁(OR:4.419;95CI:1.093~17.862;P=0.037),肌酐≥132μmol/L(OR:11.166;95CI:2.234-55.816;P=0.003),肌酸激酶≥1104U/L（OR：4.019;95CI：1.134-14.250;P=0.031），凝血酶原时间≥24.4s（OR：11.589;95CI：2.510-53.506;P=0.002），有创机械通气（OR：17.404；95CI：4.586～66.052；P＜0.000）。预测死亡率的模型的AUC为0.940(95%CI:0.894-0.986)。当模型的截止值为4点时，敏感性为95.5%,特异性为83.9%.
结论：本研究中针对重症监护病房NSTIs患者的死亡风险模型显示出较高的敏感性和特异性。评分≥4分的患者死亡风险较高。
方法：回顾性分析2008年1月至2021年12月温州医科大学附属第一医院重症监护病房（ICU）收治的106例坏死性软组织感染患者的临床资料。进行单因素分析和多因素分析以评估影响患者死亡率的危险因素。二元logistic回归分析中的回归系数转化为模型中的项目得分,然后计算每个患者的模型评分。最后,构建ROC曲线评价模型预测死亡率的效率.2022年1月至2022年11月期间入住ICU的13例NSTIs患者用于验证该模型。
结果：死亡组有44例患者，而生存组有62例患者。总死亡率为41.5%。二元logistic回归分析显示,死亡的危险因素为年龄≥60岁(OR:4.419;95CI:1.093~17.862;P=0.037),肌酐≥132μmol/L(OR:11.166;95CI:2.234-55.816;P=0.003),肌酸激酶≥1104U/L（OR：4.019;95CI：1.134-14.250;P=0.031），凝血酶原时间≥24.4s（OR：11.589;95CI：2.510-53.506;P=0.002），有创机械通气（OR：17.404；95CI：4.586～66.052；P＜0.000）。预测死亡率的模型的AUC为0.940(95%CI:0.894-0.986)。当模型的截止值为4点时，敏感性为95.5%,特异性为83.9%.
结论：本研究中针对重症监护病房NSTIs患者的死亡风险模型显示出较高的敏感性和特异性。评分≥4分的患者死亡风险较高。
