Risk factor analysis and prediction model construction for severe adenovirus pneumonia in children.

IF 3.2 3区 医学 Q1 PEDIATRICS
Yaowen Liang, Jinhuan Wu, Gang Chen, Yuchen Du, Yi Yan, Shuqin Xie, Wenxian Qian, Apeng Chen, Changhua Yi, Man Tian
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引用次数: 0

Abstract

Background: Severe adenovirus pneumonia in children has a high mortality rate, but research on risk prediction models is lacking. Such models are essential as they allow individualized predictions and assess whether children will likely progress to severe disease.

Methods: A retrospective analysis was performed on children with adenovirus pneumonia who were hospitalized at the Children's Hospital of Nanjing Medical University from January 2017 to March 2024. The patients were grouped according to clinical factors, and the groups were compared using Ridge regression and multiple logistic regression to identify risk factors associated with severe adenovirus pneumonia. A prediction model was constructed, and its value in clinical application was evaluated.

Results: 699 patients were included in the study, with 284 in the severe group and 415 in the general group. Through the screening of 44 variables, the final risk factors for severe adenovirus pneumonia in children as the levels of neutrophils (OR = 1.086, 95% CI: 1.054‒1.119, P < 0.001), D-dimer (OR = 1.005, 95% CI: 1.003‒1.007, P < 0.001), fibrinogen degradation products (OR = 1.341, 95% CI: 1.034‒1.738, P = 0.027), B cells (OR = 1.076, 95%CI: 1.046‒1.107, P < 0.001), and lactate dehydrogenase (OR = 1.008, 95% CI: 1.005‒1.011, P < 0.001). The value of the area under the receiver operating characteristic curve was 0.974, the 95% CI was 0.963-0.985, and the P-value of the Hosmer-Lemeshow test was 0.547 (P > 0.05), indicating that the model had strong predictive power.

Conclusion: In this study, the clinical variables of children with adenovirus pneumonia were retrospectively analyzed to identify risk factors for severe disease. A prediction model for severe disease was constructed and evaluated, showing good application value.

儿童重症腺病毒肺炎的风险因素分析和预测模型构建。
背景:儿童重症腺病毒肺炎的死亡率很高,但却缺乏对风险预测模型的研究。这种模型非常重要,因为它可以进行个性化预测,评估儿童是否有可能发展成重症:对2017年1月至2024年3月在南京医科大学附属儿童医院住院治疗的腺病毒肺炎患儿进行回顾性分析。根据临床因素对患者进行分组,并使用岭回归和多元逻辑回归对各组进行比较,以确定与重症腺病毒肺炎相关的风险因素。构建了一个预测模型,并评估了其临床应用价值:研究共纳入 699 名患者,其中重症组 284 人,普通组 415 人。通过对44个变量的筛选,儿童重症腺病毒肺炎的最终危险因素为中性粒细胞水平(OR = 1.086,95% CI:1.054-1.119,P 0.05),表明该模型具有较强的预测能力:本研究对腺病毒肺炎患儿的临床变量进行了回顾性分析,以确定重症的风险因素。结论:本研究对腺病毒肺炎患儿的临床变量进行了回顾性分析,以确定重症的风险因素,并构建了重症预测模型进行评估,结果显示该模型具有良好的应用价值。
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来源期刊
CiteScore
6.10
自引率
13.90%
发文量
192
审稿时长
6-12 weeks
期刊介绍: Italian Journal of Pediatrics is an open access peer-reviewed journal that includes all aspects of pediatric medicine. The journal also covers health service and public health research that addresses primary care issues. The journal provides a high-quality forum for pediatricians and other healthcare professionals to report and discuss up-to-the-minute research and expert reviews in the field of pediatric medicine. The journal will continue to develop the range of articles published to enable this invaluable resource to stay at the forefront of the field. Italian Journal of Pediatrics, which commenced in 1975 as Rivista Italiana di Pediatria, provides a high-quality forum for pediatricians and other healthcare professionals to report and discuss up-to-the-minute research and expert reviews in the field of pediatric medicine. The journal will continue to develop the range of articles published to enable this invaluable resource to stay at the forefront of the field.
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