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Article Navigation >  CHINESE JOURNAL OF BURNS AND WOUNDS  >  > Accepted Manuscript
Jiang Shengpan,Gao Xiaoqing,Tan Yiqing.Establishment and validation of a risk prediction model for severe burn patients complicated with pulmonary embolism[J].Chin J Burns Wounds,2024,40(12):1-8.DOI: 10.3760/cma.j.cn501225-20240122-00028.
Citation: Jiang Shengpan,Gao Xiaoqing,Tan Yiqing.Establishment and validation of a risk prediction model for severe burn patients complicated with pulmonary embolism[J].Chin J Burns Wounds,2024,40(12):1-8.DOI: 10.3760/cma.j.cn501225-20240122-00028.
shu

Establishment and validation of a risk prediction model for pulmonary embolism in severe burn patients

doi: 10.3760/cma.j.cn501225-20240122-00028
  • 1.

    Department of Interventional Radiology, Tongren Hospital of Wuhan UniversityWuhan Third Hospital, Wuhan430060, China

  • 2.

    Department of Clinical Laboratory, Tongren Hospital of Wuhan UniversityWuhan Third Hospital, Wuhan430060, China

Funds:

Project of Hubei Provincial Health Commission from 2019 to 2020 WJ2019F004

Hubei Province Knowledge Innovation Project (Natural Science and Technology Fund) in 2019 2019CFC917

Scientific Research Program of Wuhan Health and Family Planning Commission WX16D13

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  • Corresponding author: Tan Yiqing, Email: tanyiqing72@163.com
  • Received Date: 2024-01-22
    Available Online: 2024-12-12
    Abstract
  •   Objective  To screen the risk factors risk factors for pulmonary embolism in severe burn patients, based on which, a risk prediction model was established and validated.  Methods  This study was a retrospective case series study. The clinical data of 267 severe burn patients who met the inclusion criteria and were admitted to the Department of Burns of Wuhan Third Hospital from March 2021 to March 2023 were collected, including 159 males and 108 females, aged 18-82 years. The patients were divided into pulmonary embolism group (26 cases) and non-pulmonary embolism group (241 cases) according to whether they were complicated with pulmonary embolism. The following data of patients in the 2 groups were collected and compared, including gender, age, body mass index, bedtime during treatment, cause of burn, albumin level on admission, combination of chronic obstructive pulmonary disease (COPD), combination of diabetes mellitus, combination of hypertension, combination of inhalation injury, and the abbreviated burn severity index (ABSI) on admission. The indicators with statistically significant differences between the two groups were conducted with univariate and multivariate logistic regression analyses to identify the independent risk factors for pulmonary embolism in 267 severe burn patients. Based on these findings, a nomogram prediction model was constructed. The performance of the prediction model was evaluated by the receiver operating characteristic (ROC) curve, while its validation was conducted through calibration curve and clinical decision curve analysis.  Results  The proportions of beyond 60 years old, bedtime during treatment beyond 7 days, combination of COPD, and combination of diabetes (with χ2 values of 7.75, 29.15, 29.86, and 5.94, respectively), and ABSI score on admission (t=6.01) of patients in pulmonary embolism group were higher than those of non-pulmonary embolism group (P<0.05). There were no statistically significant differences in the other indicators between the two groups of patients (P>0.05). The univariate logistic regression analysis showed that, age, bedtime during treatment, combination of COPD, combination of diabetes, and ABSI score on admission were the risk factors for pulmonary embolism in severe burn patients (with odds ratios of 3.40, 14.87, 17.78, 2.80, and 1.88, respectively, 95% confidence intervals of 1.38-8.39, 4.34-50.98, 4.63-68.22, 1.19-6.58, and 1.47-2.41, respectively, P<0.05). The multivariate logistic regression analysis showed that, bedtime during treatment beyond 7 days, combination of COPD, and high ABSI score on admission were the independent risk factors for pulmonary embolism in severe burn patients (with odds ratios of 11.02, 30.82, and 1.86, respectively, 95% confidence intervals of 2.76-43.98, 3.55-267.33, and 1.38-2.50, respectively, P<0.05). Based on the three aforementioned independent risk factors, a nomogram prediction model for the risk of pulmonary embolism in severe burn patients was constructed. The ROC curve of prediction model showed that, the area under the ROC curve was 0.91 (with 95% confidence interval of 0.82-0.99). When the optimal cut-off value of 25% was taken, the sensitivity and specificity of prediction model was 84.6% and 93.4%, respectively. The calibration curve showed that, the calibration curve of prediction model was around the ideal curve, with a consistency index of 0.80 in Cox regression (with 95% confidence interval of 0.74-0.87). The clinical decision curve showed that the threshold probability value of the prediction model was in the range of 1% to 98%, with net return rate over 0.  Conclusions  The independent risk factors for pulmonary embolism in severe burn patients include bedtime during treatment beyond 7 days, combination of COPD, and high ABSI score on admission. The nomogram prediction model constructed based on this has a good ability to predict pulmonary embolism in severe burn patients.

     

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