A simple nomogram for assessing the risk of IgA vasculitis nephritis in IgA vasculitis Asian pediatric patients.

A nomogram for assessing the risk of IgA vasculitis nephritis (originally termed Henoch-Schönlein purpura nephritis, HSPN) in IgA vasculitis (originally termed Henoch-Schönlein purpura, HSP) pediatric patients can effectively improve early diagnosis and prognosis of IgA vasculitis nephritis. However, currently, no nomogram is available. 246 IgA vasculitis and 142 IgA vasculitis nephritis Asian pediatric patients confirmed by renal biopsy were enrolled. Univariate and multivariate logistic regressions were performed to identify the independent risk factors and construct a series of predictive models. The receiver operating characteristic curve, calibration plot, decision curve analysis, net reclassification index and integrated discrimination index were used to screen the best model. Stratification analysis was applied to optimize model's clinical utility. An external validation set was introduced to verify the predictive efficiency. The final predictive model was converted to nomogram for visual use. We identified age, duration of rash (Dor), D-dimer and IgG as independent risk factors and constructed four models as follows: AIDD (Age + IgG + Dor + D-dimer), AIDi (Age + IgG + D-dimer), AIDo (Age + IgG + Dor) and ADD (Age + Dor + D-dimer), which achieved the receiver operator characteristic curve (AUROC) of 0.931, 0.920, 0.856 and 0.907, respectively. Finally, AIDi model with an AUROC of 0.956 and 0.897 in internal and external validating sets was proposed as a novel predictive model. In stratification analysis by gender and histological grade, the AUROC of AIDi was 0.949 in female, 0.926 in male, 0.933 in mild histological grades and 0.939 in severe histological grades, respectively. AIDi nomogram is an effective and visual tool for assessing the risk of nephritis in IgA vasculitis Asian pediatric patients, regardless of IgA vasculitis nephritis histological grades and gender.

Risk of Mycoplasma pneumoniae-related hepatitis in MP pneumonia pediatric patients: a predictive model construction and assessment.

BACKGROUND: A predictive model for risk of Mycoplasma pneumoniae (MP)-related hepatitis in MP pneumonia pediatric patients can improve treatment selection and therapeutic effect. However, currently, no predictive model is available. METHODS: Three hundred seventy-four pneumonia pediatric patients with/without serologically-confirmed MP infection and ninety-three health controls were enrolled. Logistic regressions were performed to identify the determinant variables and develop predictive model. Predictive performance and optimal diagnostic threshold were evaluated using area under the receiver operating characteristic curve (AUROC). Stratification analysis by age and MP-IgM titer was used to optimize model's clinical utility. An external validation set, including 84 MP pneumonia pediatric patients, was used to verify the predictive efficiency. After univariate analysis to screen significant variables, monocyte count (MO), erythrocyte distribution width (RDW) and platelet count (PLT) were identified as independent predictors in multivariate analysis. RESULTS: We constructed MRP model: MO [^109/L] × 4 + RDW [%] - PLT [^109/L] × 0.01. MRP achieved an AUROC of 0.754 and the sensitivity and specificity at cut-off value 10.44 were 71.72 and 61.00 %, respectively in predicting MP-related hepatitis from MP pneumonia. These results were verified by the external validation set, whereas it merely achieved an AUROC of 0.540 in pneumonia without MP infection. The AUROC of MRP was 0.812 and 0.787 in infants and toddlers (0-36 months) and low MP-IgM titer subgroup (1:160-1:320), respectively. It can achieve an AUROC of 0.804 in infants and toddler with low MP-IgM titer subgroup. CONCLUSIONS: MRP is an effective predictive model for risk of MP-related hepatitis in MP pneumonia pediatric patients, especially infants and toddlers with low MP-IgM titer.