ArticleJournal of inflammation research2026
A Novel Nomogram Integrating Clinical, Radiological, and Immunological Indicators for Early Prediction of Severe
Article in Journal of inflammation research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Objective: This study aimed to develop a preliminary nomogram model for early prediction of severe Methods: A retrospective analysis was conducted on children with MPP, classifying them into general MPP (GMPP) and severe MPP (SMPP) groups. The risk factors for SMPP were identified using Logistic Stepwise Regression Analysis, followed by Multivariate Regression Analysis to construct the nomogram model. The model's discrimination was evaluated using the receiver operating characteristic (ROC) curve and area under the curve (AUC), its calibration with a calibration curve, and the results were visualized using the Hosmer-Lemeshow goodness-of-fit test. Results: No statistically significant differences were observed in gender or age between the two groups (all Conclusion: Fever duration, pulmonary consolidation, CD64, and LDH are independent risk factors for SMPP in children. The nomogram integrating these four factors shows good preliminary predictive performance but requires external validation in larger, multi-center cohorts before clinical application.
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