Abstract
OBJECTIVE: This study investigates the relationship between immune inflammation indicators and rotaviral-induced diarrhea in children under five years old. METHODS: This retrospective cohort study included 439 children with diarrhea between January 2022 and December 2023. Clinical and laboratory data were retrospectively collected. The least absolute shrinkage and selection operator (LASSO), univariate, and multivariate logistic regression analyses were used to identify the risk factors in the training cohort, which were used to develop a nomogram model. The accuracy of the nomogram was assessed using a calibration plot. Finally, Decision curve analysis was used to examine the clinical utility of the nomogram, and internal validation was performed in the training set. RESULTS: Among the 439 children, 120 developed rotaviral-induced diarrhea, with a prevalence rate of 27.33%. The systemic inflammatory response index (SIRI), lymphocyte-to-monocyte ratio (LMR), neutrophil-to-albumin ratio (NAR), and C-reactive protein-to-albumin ratio (CAR) were identified as independent predictors of rotaviral diarrhea in the training cohort. A nomogram model was established using multivariable logistic analysis, with an AUC of 0.795 (95% CI, 0.743-0.848) in the training set and 0.787 (95% CI, 0.694-0.879) in the validation set. Calibration curves indicated strong agreement between the predicted and actual probabilities. Decision curve analysis demonstrated substantial net benefits of the nomogram model for predicting the risk of rotaviral diarrhea in these children. CONCLUSION: This study confirms that the immune inflammation indicators SIRI, LMR, NAR, and CAR predict the risk of rotaviral diarrhea in children under five years old. The nomogram model developed using these indicators demonstrates excellent predictive capability for the risk of rotaviral diarrhea.