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Development and validation of a mortality risk model for pediatric sepsis

机译:儿童败血症死亡率风险模型的开发和验证

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Pediatric sepsis is a burdensome public health problem. Assessing the mortality risk of pediatric sepsis patients, offering effective treatment guidance, and improving prognosis to reduce mortality rates, are crucial. We extracted data derived from electronic medical records of pediatric sepsis patients that were collected during the first 24 hours after admission to the pediatric intensive care unit (PICU) of the Hunan Children's hospital from January 2012 to June 2014. A total of 788 children were randomly divided into a training (592, 75%) and validation group (196, 25%). The risk factors for mortality among these patients were identified by conducting multivariate logistic regression in the training group. Based on the established logistic regression equation, the logit probabilities for all patients (in both groups) were calculated to verify the model's internal and external validities. According to the training group, 6 variables (brain natriuretic peptide, albumin, total bilirubin, D-dimer, lactate levels, and mechanical ventilation in 24 hours) were included in the final logistic regression model. The areas under the curves of the model were 0.854 (0.826, 0.881) and 0.844 (0.816, 0.873) in the training and validation groups, respectively. The Mortality Risk Model for Pediatric Sepsis we established in this study showed acceptable accuracy to predict the mortality risk in pediatric sepsis patients.
机译:小儿败血症是一个繁重的公共卫生问题。评估小儿败血症患者的死亡风险,提供有效的治疗指导并改善预后以降低死亡率是至关重要的。我们从2012年1月至2014年6月湖南省儿童医院儿科重症监护室(PICU)入院后最初24小时内收集的小儿败血症患者的电子病历中提取了数据。随机抽取了788名儿童分为培训(592,75%)和验证组(196,25%)。通过在训练组中进行多元logistic回归确定这些患者中的死亡危险因素。基于已建立的逻辑回归方程,计算所有患者(两组)的对数概率,以验证模型的内部和外部有效性。根据训练组,最终的logistic回归模型包括6个变量(脑钠肽,白蛋白,总胆红素,D-二聚体,乳酸水平和24小时机械通气)。在训练和验证组中,模型曲线下的面积分别为0.854(0.826,0.881)和0.844(0.816,0.873)。我们在这项研究中建立的小儿败血症死亡率风险模型显示出可接受的准确性,可以预测小儿败血症患者的死亡风险。

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