Objective  To establish a nomogram prediction model and analysis the risk factors for poor outcome (PO) in children with asthma combined with severe community-acquired pneumonia (As-SCAP) to provide personalized treatment references for clinics.

Methods  A total of 109 As-SCAP children diagnosed from September 2019 to September 2023 in the department of pediatrics of Qingdao Municipal Hospital were retrospectively collected and divided into PO and non-PO groups according to whether PO occurred during hospitalization. Use Logistic regression analysis to determine the independent risk factors for PO, and construct a nomogram predictive model based on the regression coefficients. Receiver operating characteristic curve (ROC), calibration curve and clinical decision curve were used to evaluate the predictive ability, calibration ability and clinical net benefit of the nomogram model.

Results  The incidence of PO was 27.52%. Asthma attacks in recent 3 months, psychiatric symptoms, septic shock, and haemoglobin (Hb)<90 g·L^-1, neutrophil-to-lymphocyte ratio (NLR)≥3.5 and serum albumin (ALB)<30 g·L^-1 were independent risk factors of PO. ROC analysis showed that the nomogram model exhibits good discrimination[AUC=0.912, 95%CI(0.856, 0.967)]; The calibration curve showed that the predicted probability of the model was consistent with the actual probability, the decision curve showed that the model has a good net benefit.

Conclusion  Risk factors such as asthma exacerbation in the last 3 months, associated psychiatric symptoms, the presence of septic shock, Hb<90 g·L^-1, ALB<30 g·L^-1, NLR≥3.5 and anaemia in children with As-SCAP suggested a possible poor prognosis. The study constructed a nomogram model to predict the risk of PO in children with As-SCAP, which can help clinicians to identify high-risk patients and taking timely interventions to improve the prognosis.

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