Development and validation of a clinical prediction model for gastrointestinal hemorrhage in pediatric IgA vasculitis

To develop and internally validate a preliminary clinical prediction model for incident gastrointestinal hemorrhage (GH) occurring after admission in children with IgA vasculitis (IgAV), with continuous laboratory predictors retained in original scale to maximize predictive information.

Single-center retrospective cohort including 662 pediatric IgAV patients (2016-2022). The primary derivation cohort comprised 599 patients without overt bleeding on admission, among whom 126 (21.0%) developed delayed-onset GH ≥ 24 h post-admission. Eight admission-based predictors were selected for the Primary Continuous Model (PCM): abdominal pain, vomiting, neutrophil count, eosinophil count, mean platelet volume, albumin, complement C3, and IgA. D-dimer was excluded from the PCM because restricted cubic spline analysis demonstrated a significant non-linear, threshold-dependent relationship rather than a linear association with GH risk (P for non-linearity = 0.032); it was subsequently incorporated into the Simplified Bedside Score (SBS) via its clinically established dichotomous cutoff of 210 µg/L. Multivariable logistic regression with Enter method was performed. Internal validation included 1000-bootstrap resampling, Hosmer-Lemeshow calibration assessment, and decision curve analysis. A simplified dichotomized nine-point bedside scoring system was derived post hoc for clinical triage.

The primary eight-variable continuous model achieved an apparent AUC of 0.790 (95% CI: 0.748-0.832) and a bootstrap optimism-corrected AUC of 0.763. Calibration was excellent (Hosmer-Lemeshow P = 0.917). Five predictors demonstrated independent association with delayed-onset GH (P < 0.05): abdominal pain, vomiting, neutrophil count, MPV, and C3. The simplified dichotomized bedside scoring system yielded a corrected AUC of 0.779, with sensitivity of 77.0% and specificity of 70.2%. Restricted to clinically significant overt severe GH (n = 102), the corrected AUC increased to 0.801.

This admission-based preliminary prediction model achieves moderate discrimination for post-admission GH in pediatric IgAV. The primary continuous model preserves predictive information, while a simplified dichotomized scoring system facilitates bedside triage. In conclusion, this admission-based model preserves substantial predictive information and provides a validated baseline framework; we now propose and open this simplified dichotomized scoring system for external validation across international multicenter pediatric cohorts.