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Volume 39 Issue 8
Aug.  2023
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Article Navigation >  CHINESE JOURNAL OF BURNS AND WOUNDS  > 2023  >  39(8): 738-745
Li Q,Ba T,Cao SJ,et al.Establishment and validation of a risk prediction model for disseminated intravascular coagulation patients with electrical burns[J].Chin J Burns Wounds,2023,39(8):738-745.DOI: 10.3760/cma.j.cn501225-20230419-00132.
Citation: Li Q,Ba T,Cao SJ,et al.Establishment and validation of a risk prediction model for disseminated intravascular coagulation patients with electrical burns[J].Chin J Burns Wounds,2023,39(8):738-745.DOI: 10.3760/cma.j.cn501225-20230419-00132.
shu

Establishment and validation of a risk prediction model for disseminated intravascular coagulation patients with electrical burns

doi: 10.3760/cma.j.cn501225-20230419-00132

  • Department of Burn Surgery, Baogang Hospital of Inner Mongolia, Burn Medical Institute of Inner Mongolia, Baotou 014010, China

Funds:

Inner Mongolia Natural Science Foundation 2021MS08066, 2020MS03022

Major Disease Prevention and Control Technology Action Plan 2018-ZX-01S-001

Scientific and Research Project of Metallurgical Safety and Health Branch of the Chinese Society for Metals JKWS201832, JKWS202033

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    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 χ 2 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.

     

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