Wollny Krista, Pitt Tona, Brenner Darren, Metcalfe Amy
Alberta Children's Hospital Research Institute, Calgary, AB, Canada.
Faculty of Nursing, University of Calgary, Calgary, AB, Canada.
Pediatr Res. 2022 Dec;92(6):1780-1786. doi: 10.1038/s41390-022-02008-9. Epub 2022 Mar 17.
Respiratory syncytial virus (RSV) is the most common cause of lower respiratory tract infections in children. This study aimed to predict the prolonged length of stay in children admitted to hospital with RSV.
Children aged <2 years with RSV in the National Inpatient Sample (NIS) were included in the analyses. The primary outcome was prolonged length of stay (≥90th percentile). Logistic regression models were developed using data from 2016; internal validation was completed using a bootstrapped sample. Data from 2017 were used to validate out-of-sample discrimination and calibration of the models.
The sample included 9589 children; 1054 had prolonged length of stay (≥7 days). Children who were younger, transferred from another hospital, and required intubation during admission had a higher risk of prolonged length of stay. The prediction model included age, transport, intubation, comorbidities, hospital location, and teaching status. The area under the receiver operating characteristic curve was 0.73, demonstrating good predictive ability. The model performed similarly in external validation.
Variables that predict the prolonged length of stay for RSV include younger age, transport, intubation, comorbidities, hospital location, and teaching status. This can be used to predict children who will have a prolonged length of stay when hospitalized for RSV.
There are no recommended treatments for RSV; medical care involves supportive treatment such as oxygen delivery, hydration, and antipyretics. The clinical course is difficult to predict, partially attributable to the supportive nature of care and the sparsity of evidence-based therapies for this population. A prediction model was developed, demonstrating variables that predict prolonged length of stay in RSV hospitalizations, including age, interhospital transport, intubation, comorbidities, hospital location, and teaching status. The model was developed with a sample size of 9589 that is representative of all hospitalizations in the United States.
呼吸道合胞病毒（RSV）是儿童下呼吸道感染最常见的病因。本研究旨在预测因RSV入院儿童的住院时间延长情况。
分析纳入了国家住院患者样本（NIS）中年龄小于2岁的RSV患儿。主要结局为住院时间延长（≥第90百分位数）。使用2016年的数据建立逻辑回归模型；通过自抽样样本完成内部验证。2017年的数据用于验证模型的样本外区分度和校准情况。
样本包括9589名儿童；1054名儿童住院时间延长（≥7天）。年龄较小、从其他医院转来以及住院期间需要插管的儿童住院时间延长的风险更高。预测模型包括年龄、转运、插管、合并症、医院位置和教学状态。受试者工作特征曲线下面积为0.73，表明具有良好的预测能力。该模型在外部验证中的表现相似。
预测RSV住院时间延长的变量包括年龄较小、转运、插管、合并症、医院位置和教学状态。这可用于预测因RSV住院时住院时间会延长的儿童。
目前尚无针对RSV的推荐治疗方法；医疗护理包括支持性治疗，如给氧、补液和使用退烧药。临床病程难以预测，部分原因是护理的支持性性质以及针对该人群的循证疗法较少。开发了一个预测模型，展示了预测RSV住院时间延长的变量，包括年龄、医院间转运、插管、合并症、医院位置和教学状态。该模型是基于9589个样本量开发的，代表了美国所有住院病例。
