ESC Congress 2026 Abstract · Oct 26, 2026
Clonal hematopoiesis of indeterminate potential and stress hyperglycemia ratio among patients with STEMI---from a prospective cohort study
By Xue L, Zhao X, Dong W et al.
Background and aim: ST-elevation myocardial infarction (STEMI) remains a major cause of mortality despite advances in reperfusion therapy, underscoring the need for improved risk stratification. This study investigated the interplay between clonal hematopoiesis of indeterminate potential (CHIP), a marker of age-related inflammation1, and stress hyperglycemia ratio (SHR), an indicator of acute metabolic stress2, in STEMI patients undergoing primary percutaneous coronary intervention. Methods: In a prospective cohort, we performed deep targeted sequencing to detect CHIP mutations (variant allele frequency ≥2%) and calculated SHR from admission glucose and HbA1c. Results: We found that CHIP, particularly mutations in TET2, was significantly more prevalent in non-survivors. The adverse prognostic impact of CHIP was critically dependent on SHR levels. In patients with lower SHR (<1.414), CHIP was independently associated with increased all-cause mortality (adjusted hazard ratio [HR] = 1.70 for any-CHIP). Conversely, this association was absent in patients with higher SHR (≥1.414). Furthermore, elevated SHR itself was an independent risk factor for mortality, specifically in patients harboring common-CHIP or TET2 mutations (HR=1.84 and 1.83, respectively). Conclusion: These results demonstrate that stress hyperglycemia modifies the mortality risk conferred by CHIP, with CHIP's effect being most pronounced in the context of lower acute glycemic stress. Our findings reveal a novel interaction between a somatic mutation-driven aging process and acute metabolic dysregulation, identifying a high-risk phenotype. This integrated approach paves the way for personalized risk assessment and suggests potential therapeutic targets for mitigating inflammation and metabolic stress in vulnerable STEMI populations.The distributions of CHIP mutationsCox regression analyses of CHIP prevalence