Department of Pediatrics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA.
Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA.
J Pediatric Infect Dis Soc. 2023 Aug 31;12(8):451-458. doi: 10.1093/jpids/piad054.
Unwarranted variation in disposition decisions exist among children with pneumonia. We validated three prognostic models for predicting pneumonia severity among children in the emergency department (ED) and hospital.
We performed a two-center, prospective study of children 6 months to <18 years presenting to the ED with pneumonia from January 2014 to May 2019. We evaluated three previously developed disease-specific prognostic models which use demographic, clinical, and diagnostic predictor variables, with each model estimating risk for Very Severe (mechanical ventilation or shock), Severe (ICU without very severe features), and Moderate/Mild (Hospitalization without severe features or ED discharge) pneumonia. Predictive accuracy was measured using discrimination (concordance or c-statistic) and re-calibration.
There were 1088 children included in one or more of the three models. Median age was 3.6 years and the majority of children were male (53.7%) and identified as non-Hispanic White (63.7%). The distribution for the ordinal severity outcome was mild or moderate (79.1%), severe (15.9%), and very severe (4.9%). The three models each demonstrated excellent discrimination (C-statistic range across models [0.786-0.803]) with no appreciable degradation in predictive accuracy from the derivation cohort.
All three prognostic models accurately identified risk for three clinically meaningful levels of pneumonia severity and demonstrated very good predictive performance. Physiologic variables contributed the most to model prediction. Application of these objective tools may help standardize and improve disposition and other management decisions for children with pneumonia.
儿童肺炎处置决策存在不必要的差异。我们验证了三种预测儿童急诊科和医院肺炎严重程度的预后模型。
我们进行了一项为期 2 年的前瞻性研究，研究对象为 2014 年 1 月至 2019 年 5 月期间因肺炎到急诊科就诊的 6 个月至<18 岁的儿童。我们评估了三种以前开发的疾病特异性预后模型，这些模型使用人口统计学、临床和诊断预测变量，每个模型都估计了非常严重（机械通气或休克）、严重（无非常严重特征的 ICU）和中度/轻度（无严重特征的住院或急诊科出院）肺炎的风险。预测准确性通过辨别力（一致性或 c 统计量）和再校准来衡量。
有 1088 名儿童参与了一个或多个三个模型。中位数年龄为 3.6 岁，大多数儿童为男性（53.7%），非西班牙裔白人（63.7%）。有序严重程度结果的分布为轻度或中度（79.1%）、重度（15.9%）和非常严重（4.9%）。三个模型的辨别力均非常出色（模型之间的 C 统计量范围为[0.786-0.803]），从推导队列中没有明显的预测准确性下降。
所有三种预后模型都能准确识别三种临床有意义的肺炎严重程度风险，并表现出非常好的预测性能。生理变量对模型预测的贡献最大。这些客观工具的应用可能有助于标准化和改善儿童肺炎的处置和其他管理决策。
