Letter: Optimizing Emergency Revascularization Decisions Through DVFFR and Phenotyping

Abstract

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References

Wang

, et al. Latent class analysis identifies distinct patient phenotypes associated with mistaken treatment decisions and adverse outcomes in coronary artery disease. Angiology. 2026;77(7):857-867.

Rahoual

Zeitouni

Charpentier

, et al. Phenotyping coronary plaque by computed tomography in premature coronary artery disease. Eur Heart J Cardiovasc Imaging. 2024;25(2):257-266. doi:10.1093/ehjci/jead212

Koo

Yang

Jung

, et al. Artificial intelligence-enabled quantitative coronary plaque and hemodynamic analysis for predicting acute coronary syndrome. JACC Cardiovasc Imaging. 2024;17(9):1062-1076. doi:10.1016/j.jcmg.2024.03.015

Wang

, et al. Prognostic significance of computed tomography-derived fractional flow reserve for long-term outcomes in individuals with coronary artery disease. J Am Heart Assoc. 2025;14(2):e037988. doi:10.1161/JAHA.124.037988