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

Abstract Background: Early prediction of poor outcomes (PO) is of great significance to the improvement of the longterm prognosis of children with a diagnosis of severe community-acquired pneumonia (SCAP).The study aimed to explore the risk factors for PO of SCAP in children. We further aimed to develop and validate a PO-predictive nomogram model for SCAP in children. Methods: A population-based, retrospective case-control study was conducted in children with a diagnosis of SCAP who were hospitalized in our hospital from August 1, 2018 to October 31, 2021. Based on the occurrence of poor outcomes (PO), children were divided into PO and the non-PO groups. The multivariate logistic regression model was used to construct the nomogram model. Results: A total of 300 children with a diagnosis of SCAP were included, and 56 children had PO. The results of multivariate logistic regression analysis revealed that the possible independent risk factors for PO were comorbidity and invasive mechanical ventilation (IMV). In internal validation, the model displayed good discrimination with a C-index of 0.866 (95% CI: 0.772~0.960) and high quality of calibration plots in the nomogram model was noted. Conclusions: The nomogram model presented good discrimination and calibration in estimating the risk of PO among pediatric patients with a diagnosis of SCAP.