Division of Pediatric Critical Care Medicine, Department of Pediatrics, Lucile Packard Children's Hospital, Palo Alto, CA, USA.
Department of Biomedical Data Science, Stanford University School of Medicine, Palo Alto, CA, USA.
J Asthma. 2023 May;60(5):960-968. doi: 10.1080/02770903.2022.2111686. Epub 2022 Sep 21.
Severe asthma exacerbations account for a large share of asthma morbidity, mortality, and costs. Here, we aim to identify early predictive factors associated with pediatric intensive care unit (PICU) admission.
We performed a retrospective observational study of 5,185 emergency department (ED) encounters at a large children's hospital, including 86 (1.7%) resulting in PICU admission between 10/1/2015 and 8/7/2018 with ICD9/ICD10 codes for "asthma," "bronchospasm," or "wheezing." Vital signs and demographic information were obtained from electronic health record data and analyzed for each encounter. Predictive factors were identified using adjusted regression models, and our primary outcome was PICU admission.
Higher mean heart rates (HRs) and respiratory rates (RRs), and lower SpO2 within the first hour of ED presentation were independently associated with PICU admission. Odds of PICU admission increased 70% for each 10 beats/min higher HR, 125% for each 10 breaths/min higher RR, and 34% for each 5% lower SpO2. A binary predictive index using 1-h vitals yielded OR 13.4 (95% CI 8.1-22.1) for PICU admission, area under receiver operator characteristic (AUROC) curve 0.84 and overall accuracy of 80.1%. Results were largely unchanged (AUROC 0.84-0.88) after adjusting for surrogates of asthma severity and initial ED management. In combination with a secondary standardized clinical asthma distress score, positive predictive value increased by sevenfold (6.1%-46%).
A predictive index using HR, RR, and SpO2 within the first hour of ED presentation accurately predicted PICU admission in this cohort. Automated vital signs trend analysis may help identify vulnerable patients quickly upon presentation.
严重哮喘发作在哮喘发病率、死亡率和医疗费用中占很大比例。本研究旨在确定与儿科重症监护病房(PICU)入院相关的早期预测因素。
我们对一家大型儿童医院的 5185 例急诊科(ED)就诊进行了回顾性观察性研究,其中 10/1/2015 至 8/7/2018 期间有 86 例(1.7%)因 ICD9/ICD10 编码为“哮喘”、“支气管痉挛”或“喘息”而导致 PICU 入院。从电子健康记录数据中获取生命体征和人口统计学信息,并对每个就诊进行分析。使用调整后的回归模型确定预测因素,主要结局为 PICU 入院。
ED 就诊最初 1 小时内平均心率(HR)和呼吸频率(RR)较高,SpO2 较低与 PICU 入院独立相关。HR 每增加 10 次/分钟,RR 每增加 10 次/分钟,SpO2 每降低 5%,PICU 入院的可能性分别增加 70%、125%和 34%。使用 1 小时生命体征的二元预测指标,PICU 入院的 OR 为 13.4(95%CI 8.1-22.1),接受者操作特征(ROC)曲线下面积(AUROC)为 0.84,总准确率为 80.1%。调整哮喘严重程度和初始 ED 管理的替代指标后,结果基本不变(AUROC 0.84-0.88)。与二级标准化临床哮喘窘迫评分相结合,阳性预测值增加了七倍(6.1%-46%)。
该研究使用 ED 就诊最初 1 小时内的 HR、RR 和 SpO2 构建的预测指标可准确预测该队列中 PICU 入院情况。自动生命体征趋势分析可能有助于在就诊时快速识别脆弱患者。