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  • Title: [Establishment and validation of a risk prediction model for disseminated intravascular coagulation patients with electrical burns].
    Author: Li Q, Ba T, Cao SJ, Chen Q, Zhou B, Yan ZQ, Hou ZH, Wang LF.
    Journal: Zhonghua Shao Shang Yu Chuang Mian Xiu Fu Za Zhi; 2023 Aug 20; 39(8):738-745. PubMed ID: 37805784.
    Abstract:
    Objective: To establish and validate a risk prediction model of disseminated intravascular coagulation (DIC) by the screening independent risk factors for the occurrence of DIC in patients with electrical burns. Methods: The retrospective case series study was conducted. The clinical data of 218 electrical burn patients admitted to Baogang Hospital of Inner Mongolia from January 2015 to January 2023 who met the inclusion criteria were collected, including 198 males and 20 females, with the age of (38±14) years. The patients were divided into DIC group and non DIC group based on whether they were diagnosed with DIC during the treatment period. The following data of patients of two groups were collected and compared, including age, gender, total burn area, full-thickness burn area, injury voltage, whether osteofascial compartment syndrome occurred within 1 day after injury, duration of stay in burn intensive care unit, total length of hospital stay, whether combined with inhalation injury and multiple injuries, whether shock occurred upon admission, the abbreviated burn severity index score, and the acute physiology and chronic health evaluation Ⅱ score. The laboratory examination data of the patients within 24 hours after admission were also collected, including blood routine indexes: white blood cell count (WBC), hemoglobin level, platelet count (PLT), and neutrophil count; coagulation indexes: activated partial thromboplastin time (APTT), prothrombin time, thrombin time, and levels of D-dimer and fibrinogen (FIB); blood biochemistry indexes: aspartic transaminase, alanine transaminase, direct bilirubin, total bilirubin, total protein, albumin, blood glucose, creatinine, and urea nitrogen; blood gas analysis indexes: blood pH value, arterial partial pressure of oxygen, arterial partial pressure of carbon dioxide, bicarbonate, and base excess; and cardiac zymogram indexes: levels of myoglobin, troponin, lactate dehydrogenase, creatine kinase (CK), and α-hydroxybutyrate dehydrogenase. Data were statistically analyzed with chi-square test, Fisher's exact probability test, independent sample t test, and Mann-Whitney U test. For the variables with statistically significant differences in single factor analysis, the least absolute value selection and shrinkage operator (LASSO) regression was used to reduce the dimension, and the predictive factors for DIC in 218 patients with electrical burns were screened. The above-mentioned predictors were included in multivariate logistic regression analysis to find out the independent risk factors for DIC in 218 patients with electrical burns, and to draw the prediction model nomograms. The performance of the prediction model was evaluated by the receiver operating characteristic (ROC) curve and the area under the ROC curve, and the prediction model was validated by the calibration curve and clinical decision curve analysis (DCA). Results: Compared with those in non DIC group, the total burn area, full-thickness burn area, total length of hospital stay, and the proportions of high voltage caused injury, occurrence of osteofascial compartment syndrome within 1 day after injury, combination of inhalation injury, and occurrence of shock upon admission of patients in DIC group were significantly increased/prolonged (with Z values of -2.53, -4.65, and -2.10, respectively, with χ2 values of 11.46, 16.00, 7.98, and 18.93, respectively, P<0.05). Compared with those in non DIC group, the APTT, level of D-dimer, myoglobin, WBC, PLT, and levels of FIB, total bilirubin, and CK of patients within 24 hours after admission in DIC group were significantly prolonged/increased (with Z values of -2.02, -4.51, and -3.82, respectively, with t values of -3.84, -2.34, -2.77, -2.70, and -2.61, respectively), and the level of total protein and blood pH value were significantly reduced (t=-2.85, Z=-2.03), P<0.05. LASSO regression analysis was carried out for the above 17 indicators with statistically significant differences. The results showed that injury voltage, the occurrence of shock upon admission, the occurrence of osteofascial compartment syndrome within 1 day after injury, and levels of D-dimer and total protein within 24 hours after admission were predictive factors for the occurrence of DIC in 218 patients with electrical burns (with regression coefficients of 0.24, 0.52, 0.35, 0.13, and -0.001, respectively). Multivariate logistic regression analysis showed that injury voltage, the occurrence of shock upon admission, the occurrence of osteofascial compartment syndrome within 1 day after injury, and D-dimer level within 24 hours after admission were independent risk factors for DIC in 218 patients with electrical burns (with odds ratios of 3.33, 4.24, 2.68, and 1.38, respectively, with 95% confidence intervals of 1.43-7.79, 1.78-10.07, 1.17-6.13, and 1.19-1.61, respectively, P<0.05). Based on the aforementioned four independent risk factors, the nomogram of prediction model for evaluating the probability of DIC in patients was drawn. The area under the ROC curve of prediction model was 0.88, and the 95% confidence interval was 0.82-0.95, indicating that the model had good predictive ability; the curve of prediction model tended to be near the ideal curve, indicating that the model had a high calibration degree; the clinical DCA of prediction model showed that the threshold probability of patients ranged from 4% to 97%, indicating that the model had good predictive ability. Conclusions: The injury voltage, the occurrence of shock upon admission, the occurrence of osteofascial compartment syndrome within 1 day after injury, and D-dimer level within 24 hours after admission are independent risk factors for the occurrence of DIC in patients with electrical burns. The prediction model established based on the above indicators can provide early warning for the occurrence of DIC in these patients. 目的： 通过筛选电烧伤患者发生弥散性血管内凝血（DIC）的独立危险因素，建立发生DIC风险预测模型并进行验证。 方法： 采用回顾性病例系列研究方法。收集2015年1月—2023年1月内蒙古包钢医院收治的符合入选标准的218例电烧伤患者临床资料，其中男198例、女20例，年龄（38±14）岁。按照治疗期间是否被诊断为DIC，将患者分为DIC组和非DIC组。收集并比较2组患者一般临床资料，包括年龄、性别、烧伤总面积、Ⅲ度烧伤面积、致伤电压、伤后1 d内是否发生骨筋膜室综合征、烧伤重症监护病房停留时间、总住院时间，是否合并吸入性损伤、多发伤和入院时是否发生休克，简明烧伤严重指数评分与急性生理学和慢性健康状况评价Ⅱ评分；患者入院24 h内的实验室检测指标资料，包括血常规指标：白细胞计数（WBC）、血红蛋白水平、血小板计数（PLT）、中性粒细胞计数，凝血指标：活化部分凝血活酶时间（APTT）、凝血酶原时间、凝血酶时间、D-二聚体水平、纤维蛋白原（FIB）水平，血生化指标：天冬氨酸转氨酶、丙氨酸转氨酶、直接胆红素、总胆红素、总蛋白、白蛋白、血糖、肌酐、尿素氮的水平，血气分析指标：血pH值、动脉血氧分压、动脉血二氧化碳分压、碳酸氢根、碱剩余，心肌酶谱指标：肌红蛋白、肌钙蛋白、乳酸脱氢酶、肌酸激酶和α-羟丁酸脱氢酶的水平。对数据行χ2检验、Fisher确切概率法检验、独立样本t检验、Mann-Whitney U检验。对单因素分析差异有统计学意义的变量采用最小绝对值压缩和选择算法（LASSO）回归进行降维处理，筛选218例电烧伤患者发生DIC的预测因子。将前述预测因子纳入多因素logistic回归分析，寻找218例电烧伤患者发生DIC的独立危险因素并绘制预测模型列线图。通过受试者操作特征（ROC）曲线和ROC曲线下面积评估预测模型性能，采用校准曲线和临床决策曲线分析法（DCA）对预测模型进行验证。 结果： 与非DIC组相比，DIC组患者烧伤总面积、Ⅲ度烧伤面积、总住院时间以及高压致伤、伤后1 d内发生骨筋膜室综合征、合并吸入性损伤、入院时发生休克的比例均显著增大/延长（Z值分别为-2.53、-4.65、-2.10，χ2值分别为11.46、16.00、7.98、18.93，P<0.05）。与非DIC组相比，DIC组患者入院24 h内的APTT、D-二聚体水平、肌红蛋白、WBC、PLT以及FIB、总胆红素、肌酸激酶水平均显著延长/升高（Z值分别为-2.02、-4.51、-3.82，t值分别为-3.84、-2.34、-2.77、-2.70、-2.61），总蛋白水平、血pH值均显著降低（t=-2.85、Z=-2.03），P<0.05。对前述17个差异有统计学意义的指标行LASSO回归分析，结果显示致伤电压、入院时发生休克、伤后1 d内发生骨筋膜室综合征以及入院24 h内的D-二聚体水平与总蛋白水平为218例电烧伤患者发生DIC的预测因子（回归系数分别为0.24、0.52、0.35、0.13、-0.001）。多因素logistic回归分析显示，致伤电压、入院时发生休克、伤后1 d内发生骨筋膜室综合征和入院24 h内的D-二聚体水平是218例电烧伤患者发生DIC的独立危险因素（比值比分别为3.33、4.24、2.68、1.38，95%置信区间分别为1.43~7.79、1.78~10.07、1.17~6.13、1.19~1.61，P<0.05）。根据前述4个独立危险因素绘制可评估患者发生DIC概率的预测模型列线图。预测模型的ROC曲线下面积为0.88，95%置信区间为0.82~0.95，提示该模型预测能力较好；预测模型曲线趋近于理想曲线，提示该模型有较高校准度；预测模型的临床DCA显示，患者阈值概率在4%~97%范围内，提示该模型预测能力较好。 结论： 致伤电压、入院时发生休克、伤后1 d内发生骨筋膜室综合征、入院24 h内的D-二聚体水平是电烧伤患者发生DIC的独立危险因素，基于以上指标建立的预测模型可为该类患者是否发生DIC提供早期预警。.
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