Clinical features and risk factors analysis for poor outcomes of severe community-acquired pneumonia in children: a nomogram prediction model

Frontiers in Pediatrics

Pediatrics

Yujie Liu¹  Changjing Xu²  Xuemei Tao²  Xuping Yang²  Yilan Huang²  Chao Hou³  Junlong Zhu⁴  Liya Fu⁵  Wanlong Zhu⁵ 

[1] Department of Geriatric Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, China;Department of Pharmacy, The Affiliated Hospital of Southwest Medical University, Luzhou, China;Department of Ultrasound, The Affiliated Hospital of Southwest Medical University, Luzhou, China;Department of Vascular Surgery, The Affiliated Hospital of Southwest Medical University, Luzhou, China;School of Pharmacy, Southwest Medical University, Luzhou, China;

关键词: severe community-acquired pneumonia;    children;    risk factor;    nomogram;    predictive model;   

DOI  :  10.3389/fped.2023.1194186

 received in 2023-03-26, accepted in 2023-09-07,  发布年份 2023

来源: Frontiers

【 摘 要 】

BackgroundPneumonia remains the leading cause of death among children aged 1–59 months. The early prediction of poor outcomes (PO) is of critical concern. This study aimed to explore the risk factors relating to PO in severe community-acquired pneumonia (SCAP) and build a PO-predictive nomogram model for children with SCAP.MethodsWe retrospectively identified 300 Chinese pediatric patients diagnosed with SCAP who were hospitalized in the Affiliated Hospital of Southwest Medical University from August 1, 2018, to October 31, 2021. Children were divided into the PO and the non-PO groups. The occurrence of PO was designated as the dependent variable. Univariate and multivariate logistic regression analyses were used to identify the risk factors of PO. A nomogram model was constructed from the multivariate logistic regression analysis and internally validated for model discrimination and calibration. The performance of the nomogram was estimated using the concordance index (C-index).ResultsAccording to the efficacy evaluation criteria, 56 of 300 children demonstrated PO. The multivariate logistic regression analysis resulted in the following independent risk factors for PO: co-morbidity (OR: 8.032, 95% CI: 3.556–18.140, P < 0.0001), requiring invasive mechanical ventilation (IMV) (OR: 7.081, 95% CI: 2.250–22.282, P = 0.001), and ALB < 35 g/L (OR: 3.203, 95% CI: 1.151–8.912, P = 0.026). Results of the internal validation confirmed that the model provided good discrimination (concordance index [C-index], 0.876 [95% CI: 0.828–0.925]). The calibration plots in the nomogram model were of high quality.ConclusionThe nomogram facilitated accurate prediction of PO in children diagnosed with SCAP and could be helpful for clinical decision-making.

【 授权许可】

Unknown   
© 2023 Xu, Tao, Zhu, Hou, Liu, Fu, Zhu, Yang and Huang.