Liu Gangtie, Wang Guanglei, Yang Zhan, Liu Guangfu, Ma Haijun, Lv Yong, Ma Feiyan, Zhu Weiwei
Department of Pediatrics, Jinan Central Hospital, Shandong University, Jinan, People's Republic of China.
Department of Pediatrics, Taian Maternity and Child Health Care Hospital, Taian, People's Republic of China.
Infect Drug Resist. 2022 Oct 31;15:6343-6355. doi: 10.2147/IDR.S387890. eCollection 2022.
Early diagnosis of pneumonia (RMPP) is challenging because of the lack of practical diagnostic imaging tools. Lung ultrasound (LUS) is an emerging tool for diagnosing childhood pneumonia. Hence, we evaluated the role of a nomogram combining LUS findings, clinical features, and laboratory indices in the early prediction of RMPP in children.
We retrospectively analyzed 225 children with pneumonia (MPP) admitted to our hospital between Dec 2018 and Aug 2021. Logistic regression analysis incorporated LUS findings and clinical predictors into the nomogram. Ninety patients hospitalized from Sep 2021 to Dec 2021 were used for external validation of the prediction model. Receiver operating characteristics (ROC) and calibration curves were used to evaluate the performance of the nomogram in the early diagnosis of RMPP.
Ultimately, Consolidation size /BSA (odds ratio (OR) 1.015, 95% confidence interval (CI) 1.536-2.446), Pleural Effusion (OR 3.551, 95% CI 1.921-15.600), LDH (OR 1.044, 95% CI 1.006-1. 021) and CRP (OR 3.293, 95% CI 1.019-1.098) were independent risk factors for the development of RMPP. The prediction model was represented visually as a nomogram. The area under the ROC curve for the predictive nomogram was 0.955 (95% CI 0.919-0.978) in the training cohort and 0.916 (95% CI 0.838-0.964) in the validation cohort. The calibration curve is close to the diagonal.
This is the first-time lung ultrasound was added to the predicted nomogram, which can more comprehensively assess the condition and more accurately predict the occurrence of RMPP early. Therefore, this nomogram can be widely used in the early diagnosis of RMPP, especially in primary care hospitals.
由于缺乏实用的诊断成像工具,肺炎支原体肺炎(RMPP)的早期诊断具有挑战性。肺部超声(LUS)是一种新兴的儿童肺炎诊断工具。因此,我们评估了一种结合LUS检查结果、临床特征和实验室指标的列线图在儿童RMPP早期预测中的作用。
我们回顾性分析了2018年12月至2021年8月期间我院收治的225例肺炎支原体肺炎(MPP)患儿。逻辑回归分析将LUS检查结果和临床预测因素纳入列线图。2021年9月至2021年12月住院的90例患者用于预测模型的外部验证。采用受试者工作特征(ROC)曲线和校准曲线评估列线图在RMPP早期诊断中的性能。
最终,实变面积/体表面积(比值比(OR)1.015,95%置信区间(CI)1.536 - 2.446)、胸腔积液(OR 3.551,95% CI 1.921 - 15.600)、乳酸脱氢酶(LDH,OR 1.044,95% CI 1.006 - 1.021)和C反应蛋白(CRP,OR 3.293,95% CI 1.019 - 1.098)是RMPP发生的独立危险因素。预测模型以列线图的形式直观呈现。预测列线图在训练队列中的ROC曲线下面积为0.955(95% CI 0.919 - 0.978),在验证队列中为0.916(95% CI 0.838 - 0.964)。校准曲线接近对角线。
这是首次将肺部超声添加到预测列线图中,其能够更全面地评估病情,并更准确地早期预测RMPP的发生。因此,该列线图可广泛应用于RMPP的早期诊断,尤其是在基层医院。