Guangzhou Red Cross Hospital of Jinan University, Guangzhou, China.
Medicine (Baltimore). 2024 Nov 29;103(48):e40709. doi: 10.1097/MD.0000000000040709.
Sepsis is a common and severe complication in burn patients and remains one of the leading causes of mortality. This retrospective study aimed to develop a predictive model for the risk of in-hospital sepsis among burn patients treated at Guangzhou Red Cross Hospital between January 2022 and January 2024, with the goal of improving clinical outcomes through early prevention based on risk stratification. A total of 302 eligible patients were randomly divided into training and validation cohorts in a 7:3 ratio for model development and validation, respectively. Predictive factors were initially selected using LASSO regression, followed by logistic regression analysis to establish the prediction model and construct a nomogram. The final model incorporated 4 independent predictors: burn area (odds ratio [OR] = 1.043, 95% confidence interval [CI]: 1.026-1.062/1%), hemoglobin (OR = 0.968, 95% CI: 0.954-0.980/1 g/L), diabetes (OR = 10.91, 95% CI: 2.563-56.62), and potassium (OR = 3.091, 95% CI: 1.635-6.064/1 mmol/L). The areas under the receiver operating characteristic curve were 0.875 and 0.861 for the training and validation cohorts, with Youden indexes of 0.634 and 0.600, respectively. The calibration curve and decision curve analysis demonstrated good predictive accuracy and clinical utility of the model. These findings suggest that our developed model exhibits robust predictive performance for the risk of in-hospital sepsis in burn patients, and early prevention strategies based on risk stratification may potentially improve clinical outcomes.
脓毒症是烧伤患者常见且严重的并发症，仍然是导致死亡的主要原因之一。本回顾性研究旨在为 2022 年 1 月至 2024 年 1 月在广州市红十字会医院接受治疗的烧伤患者住院期间发生脓毒症的风险开发预测模型，目的是通过基于风险分层的早期预防来改善临床结局。总共纳入 302 名符合条件的患者，随机分为训练集和验证集，比例为 7:3，用于模型开发和验证。使用 LASSO 回归初步选择预测因素，然后进行 logistic 回归分析，以建立预测模型并构建列线图。最终模型纳入 4 个独立预测因素：烧伤面积（比值比 [OR] = 1.043，95%置信区间 [CI]：1.026-1.062/1%）、血红蛋白（OR = 0.968，95% CI：0.954-0.980/1 g/L）、糖尿病（OR = 10.91，95% CI：2.563-56.62）和钾（OR = 3.091，95% CI：1.635-6.064/1 mmol/L）。训练集和验证集的受试者工作特征曲线下面积分别为 0.875 和 0.861，约登指数分别为 0.634 和 0.600。校准曲线和决策曲线分析表明该模型具有良好的预测准确性和临床实用性。这些发现表明，我们开发的模型对烧伤患者住院期间发生脓毒症的风险具有稳健的预测性能，基于风险分层的早期预防策略可能潜在改善临床结局。
