Ren H T, Chen H Q, Han C M
Department of Burns, the Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009, China.
Department of Nursing, the Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009, China.
Zhonghua Shao Shang Za Zhi. 2021 Apr 20;37(4):333-339. doi: 10.3760/cma.j.cn501120-20200301-00109.
To establish a predictive model for acute respiratory distress syndrome (ARDS) in critical burn patients with the screened independent risk factors, and to validate its predictive value. Totally 131 critical burn patients (101 males and 30 females, aged 18-84 years) who met the inclusion criteria were admitted to the Department of Burns of the Second Affiliated Hospital of Zhejiang University School of Medicine from January 2018 to December 2019. A retrospective case-control study was conducted. The patients were divided into ARDS group (54 cases) and non-ARDS group (77 cases) according to whether ARDS occurred or not. The statistics of patients in the two groups were recorded including the gender, age, burn index, combination of inhalation injury, smoking history, delayed resuscitation, indwelling nasogastric tube, and complication of sepsis, and the data were statistically analyzed with independent sample test, chi-square test, and Fisher's exact probability test. The multivariate logistic regression analysis was performed on the indicators with statistically significant differences between the two groups to screen the independent risk factors for developing ARDS in critical burn patients, and the corresponding nomograph prediction model for the risk of ARDS in critical burn patients was established. The risk scores for patients developing ARDS were therefore obtained based on the above-mentioned nomograph, and the corresponding receiver operating characteristic (ROC) curve was drawn to calculate the area under the curve. The internal validation of the above-mentioned ARDS prediction model was performed using the Bootstrap method, and the area under the ROC curve was calculated for modeling group (79 cases) and validation group (52 cases), respectively. A calibration curve was drawn to assess the predictive conformity of the above-mentioned ARDS prediction model for the occurrence of ARDS in critical burn patients. The burn index, proportion of combination of inhalation injury, and proportion of complication of sepsis of patients were significantly higher in ARDS group than in non-ARDS group (=0.36, =33.78, 49.92, <0.01). The gender, age, smoking history, delayed resuscitation, and indwelling nasogastric tube of patients in ARDS group were close to those in non-ARDS group (>0.05). The multivariate logistic regression analysis showed that the burn index, combination of inhalation injury, and complication of sepsis were the independent risk factors for developing ARDS in critical burn patients (odds ratio=1.05, 15.33, 5.02, 95% confidence interval=1.01-1.10, 2.65-88.42, 1.28-19.71, <0.05 or <0.01). The overall area under the ROC curve of the above-mentioned ARDS prediction model was 0.92 (95% confidence interval=0.88-0.97), and the area under the ROC curve was 0.95 and 0.91 (95% confidence interval=0.90-1.00, 0.86-0.97) for validation group and modeling group, respectively. When applying the above-mentioned ARDS prediction model for ARDS incidence prediction, there might be some risk of overestimating ARDS incidence when the prediction probability was <35.0% or >85.0%, and some risk of underestimating ARDS incidence when the prediction probability was 35.0%-85.0%. The burn index, inhalation injury, and sepsis are the independent risk factors for the occurrence of ARDS in critical burn patients. The risk prediction model for ARDS based on these three indicators has good predictive ability for ARDS in critical burn patients.
利用筛选出的独立危险因素建立重症烧伤患者急性呼吸窘迫综合征(ARDS)的预测模型,并验证其预测价值。2018年1月至2019年12月,浙江大学医学院附属第二医院烧伤科收治了131例符合纳入标准的重症烧伤患者(男101例,女30例,年龄18 - 84岁)。进行回顾性病例对照研究。根据是否发生ARDS将患者分为ARDS组(54例)和非ARDS组(77例)。记录两组患者的性别、年龄、烧伤指数、吸入性损伤合并情况、吸烟史、延迟复苏、留置鼻胃管以及脓毒症并发症等情况,并采用独立样本t检验、卡方检验和Fisher确切概率检验进行统计学分析。对两组间差异有统计学意义的指标进行多因素logistic回归分析,筛选重症烧伤患者发生ARDS的独立危险因素,并建立相应的重症烧伤患者ARDS风险列线图预测模型。据此得到患者发生ARDS的风险评分,并绘制相应的受试者工作特征(ROC)曲线计算曲线下面积。采用Bootstrap法对上述ARDS预测模型进行内部验证,并分别计算建模组(79例)和验证组(52例)的ROC曲线下面积。绘制校准曲线以评估上述ARDS预测模型对重症烧伤患者ARDS发生的预测一致性。ARDS组患者的烧伤指数、吸入性损伤合并比例和脓毒症并发症比例均显著高于非ARDS组(=0.36,=33.78,49.92,<0.01)。ARDS组患者的性别、年龄、吸烟史、延迟复苏和留置鼻胃管情况与非ARDS组相近(>0.05)。多因素logistic回归分析显示,烧伤指数、吸入性损伤合并情况和脓毒症并发症是重症烧伤患者发生ARDS的独立危险因素(比值比=1.05,15.33,5.02,95%置信区间=1.01 - 1.10,2.65 - 88.42,1.28 - 19.71,<0.0