Immune and inflammatory features associated with pyroptosis- and myocardial fibrosis-related genes in HFpEF: a machine learning study.

Heart failure with preserved ejection fraction (HFpEF) is a heterogeneous syndrome marked by inflammation, immune dysregulation, and myocardial fibrosis. Whether pyroptosis intersects with fibrotic remodeling in HFpEF remains uncertain. Two murine cardiac transcriptomic datasets were integrated after batch correction and intersected with curated pyroptosis- and myocardial fibrosis-related gene sets. Functional enrichment, univariate logistic regression, support vector machine-recursive feature elimination (SVM-RFE), and least absolute shrinkage and selection operator (LASSO) regression were used for feature selection. Complete separation in the ordinary three-gene logistic fit prompted refitting with Firth bias-reduced logistic regression. Performance was assessed by apparent area under the curve (AUC), stratified bootstrap optimism correction, and repeated nested cross-validation; the panel was re-estimated in a human left-ventricular dataset for exploratory replication. Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) estimated immune-cell fractions, and expression was examined in a high-fat diet (HFD)/N