Frontiers in immunology
Transcriptomics-guided serum podoplanin and interpretable machine learning for early risk stratification of necrotizing enterocolitis in preterm infants
By Peng H, Liu X, Li Y and 6 others.
Abstract
Background
To evaluate podoplanin (PDPN) as a circulating biomarker for early necrotizing enterocolitis (NEC) risk stratification and to determine whether an interpretable machine-learning framework integrating PDPN with prediagnostic clinical and inflammatory variables could improve individualized risk estimation.
Methods
PDPN expression was examined in two public NEC intestinal transcriptomic datasets. Serum PDPN was then measured by enzyme-linked immunosorbent assay in a nested case-control cohort of 132 preterm infants (66 with NEC and 66 gestational-age- and birth-weight-matched controls). All candidate predictors were obtained before NEC onset in cases and before the matched reference time in controls. Restricted cubic spline, receiver operating characteristic, precision-recall, LASSO, multivariable logistic regression, 11 machine-learning algorithms, SHAP, and nomogram analyses were performed.