• Yiran Wang, Chenghao Cai, Zhikang Zhu, Deqing Duan, Wanting Xu, Tao Shen, Xingang Wang, Qinglian Xu, Hongyan Zhang, and Chunmao Han.
• Department of Burns & Wound Care Center, the Second Affiliated Hospital of Zhejiang University College of Medicine, Hangzhou, China; The Key Laboratory of the Diagnosis and Treatment of Severe Trauma and Burn of Zhejiang Province, Hangzhou, China; Center of Clinical Epidemiology & Biostatistics, Department of Scientific Research, the Second Affiliated Hospital of Zhejiang University College of Medicine, Hangzhou, China.
• Burns. 2024 Jun 1; 50 (5): 127712851277-1285.

BackgroundSeveral models predicting mortality risk of burn patients have been proposed. However, models that consider all such patients may not well predict the mortality of patients with extensive burns.MethodThis retrospective multicentre study recruited patients with extensive burns (≥ 50% of the total body surface area [TBSA]) treated in three hospitals of Eastern China from 1 January 2016 to 30 June 2022. The performances of six predictive models were assessed by drawing receiver operating characteristic (ROC) and calibration curves. Potential predictors were sought via "least absolute shrinkage and selection operator" regression. Multivariate logistic regression was employed to construct a predictive model for patients with burns to ≥ 50% of the TBSA. A nomogram was prepared and the performance thereof assessed by reference to the ROC, calibration, and decision curves.ResultA total of 465 eligible patients with burns to ≥ 50% TBSA were included, of whom 139 (29.9%) died. The FLAMES model exhibited the largest area under the ROC curve (AUC) (0.875), followed by the models of Zhou et al. (0.853) and the ABSI model (0.802). The calibration curve of the Zhou et al. model fitted well; those of the other models significantly overestimated the mortality risk. The new nomogram includes four variables: age, the %TBSA burned, the area of full-thickness burns, and blood lactate. The AUCs (training set 0.889; internal validation set 0.934; external validation set 0.890) and calibration curves showed that the nomogram exhibited an excellent discriminative capacity and that the predictions were very accurate.ConclusionFor patients with burns to ≥ 50％of the TBSA, the Zhou et al. and FLAMES models demonstrate relatively high predictive ability for mortality. The new nomogram is sensitive, specific, and accurate, and will aid rapid clinical decision-making.Copyright © 2024 Elsevier Ltd and International Society of Burns Injuries. All rights reserved.

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