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Latent Class Analysis Identifies Distinct Patient Phenotypes Associated With Mistaken Treatment Decisions and Adverse Outcomes in Coronary Artery Disease.

Angiology - 1 Aug 2026

Qi Jing, Wang Zhiqiang, Ma Xiaoteng, Wang Zhijian, Li Yueping, Yang Lixia, Shi Dongmei, Zhou Yujie

Abstract excerpt

This study aimed to identify patient characteristics linked to mistaken treatments and major adverse cardiovascular events (MACE) in percutaneous coronary intervention (PCI) for coronary artery disease (CAD) using deep learning-based fractional flow reserve (DEEPVESSEL-FFR, DVFFR). A retrospective cohort of 3,840 PCI patients was analyzed using latent class analysis (LCA) based on eight factors. Mistaken...

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Identifiers

PMID: 40682405
DOI: 10.1177/00033197251350182
PMCID: PMC13291419

Genes

CAD

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026.

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