• J H Fan, Y F Sun, G S Wu, K A Wang, J Wei, and Y Sun.
• Burn Institute of PLA, Department of Burn Surgery, the First Affiliated Hospital, Naval Medical University, Shanghai 200433, China.
• Zhonghua Shao Shang Za Zhi. 2020 Jan 20; 36 (1): 42-47.

AbstractObjective: To investigate the predictive value of the joint prediction model based on the modified systemic inflammatory response syndrome (SIRS) score (hereinafter referred to as the joint prediction model) for the mortality risk of patients with large area burns within 24 hours after admission. Methods: The clinical data of 158 patients [111 males, 47 females, aged 40 (28, 50) years] admitted to the Department of Burn Surgery of the First Affiliated Hospital of Naval Medical University from January 2005 to January 2018, conforming to the study criteria, were analyzed retrospectively by the method of case-control study. The age, gender, total burn area, full-thickness burn area, injury cause, with or without inhalation injury, severity of inhalation injury, and tracheotomy condition of patients were recorded, and the modified SIRS score and the modified Baux score of patients were calculated. According to the final outcome, all patients were divided into survival group (n=123) and death group (n=35). The clinical data of patients between two groups, except for modified Baux score, were compared by chi-square test or Mann-Whitney U test to screen the death-related factors of patients. The indexes with statistically significant difference between the two groups were included in the multivariate logistic regression analysis to screen the independent risk factors related to the death of patients, and the prediction model was constructed by combining the modified SIRS score. The receiver's operating characteristic curves of the modified SIRS score, the modified Baux score, and the joint prediction model of 158 patients were drawn to analyze their ability to predict death of patients. The area under curve (AUC) of the receiver's operating characteristic and the sensitivity and specificity of optimal threshold were calculated, and the quality of AUC of the three prediction indexes was compared with Jonckheere-Terpstra test. Results: (1) There were statistically significant differences between the two groups in the modified SIRS score, age, total burn area, full-thickness burn area, severity of inhalation injury, with or without inhalation injury, and tracheotomy condition of patients (Z=-4.356, -3.568, -5.291, -6.052, -4.720, χ(2)=12.967, 19.692, P<0.01). (2) The modified SIRS score, age, full-thickness burn area were the independent risk factors for the death of patients with large area burn (odds ratio=2.699, 1.069, 1.029, 95% confidence interval=1.447-5.033, 1.029-1.109, 1.005-1.054, P<0.05). (3) The AUC of modified SIRS score, the joint prediction model, and the modified Baux score for predicting death of 158 patients within 24 hours after admission were 0.730, 0.879, and 0.895 respectively (95% confidence interval=0.653-0.797, 0.818-0.926, 0.836-0.938, P<0.01). The sensitivities of the three optimal threshold values to death prediction were 54.3%, 91.4%, and 82.9% respectively, while the specificities were 81.3%, 76.4%, and 84.6% respectively. The AUC quality of the joint prediction model was similar to that of the modified Baux score (95% confidence interval=-0.057-0.088, P>0.05), and both of them were significantly better than that of the modified SIRS score (95% confidence interval=0.072-0.259, 0.023-0.276, P<0.05 or P<0.01). Conclusions: Both the joint prediction model and the modified Baux score are considered to be good to predict the death rate of patients with large area burns at early stage after admission. However, the joint prediction model has better clinical practice value due to its advantage of simple scoring and easier access to data acquisition.

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