Latent Class Analysis Identifies Distinct Patient Phenotypes Associated With Mistaken Treatment Decisions and Adverse Outcomes in Coronary Artery Disease.
Article in Angiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it
What it found
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2 · The registry
The trial behind it
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5 · Who and what money
Authors and funding
8 authors.
Jing QiDepartment of Cardiology, Beijing Anzhen Hospital, Capital Medical University, Beijing Key Laboratory of Precision Medicine of Coronary Atherosclerotic Disease, Clinical Center for Coronary Heart Disease, Beijing Institute of Heart Lung and Blood Vessel Disease, Capital Medical University, Beijing, China.
Zhiqiang WangDepartment of Cardiology, Beijing Anzhen Hospital, Capital Medical University, Beijing Key Laboratory of Precision Medicine of Coronary Atherosclerotic Disease, Clinical Center for Coronary Heart Disease, Beijing Institute of Heart Lung and Blood Vessel Disease, Capital Medical University, Beijing, China.
Xiaoteng MaDepartment of Cardiology, Beijing Anzhen Hospital, Capital Medical University, Beijing Key Laboratory of Precision Medicine of Coronary Atherosclerotic Disease, Clinical Center for Coronary Heart Disease, Beijing Institute of Heart Lung and Blood Vessel Disease, Capital Medical University, Beijing, China.ORCID 0000-0003-4806-6458
Zhijian WangDepartment of Cardiology, Beijing Anzhen Hospital, Capital Medical University, Beijing Key Laboratory of Precision Medicine of Coronary Atherosclerotic Disease, Clinical Center for Coronary Heart Disease, Beijing Institute of Heart Lung and Blood Vessel Disease, Capital Medical University, Beijing, China.ORCID 0000-0002-7516-7038
Yueping LiDepartment of Cardiology, Beijing Anzhen Hospital, Capital Medical University, Beijing Key Laboratory of Precision Medicine of Coronary Atherosclerotic Disease, Clinical Center for Coronary Heart Disease, Beijing Institute of Heart Lung and Blood Vessel Disease, Capital Medical University, Beijing, China.
Lixia YangDepartment of Cardiology, Beijing Anzhen Hospital, Capital Medical University, Beijing Key Laboratory of Precision Medicine of Coronary Atherosclerotic Disease, Clinical Center for Coronary Heart Disease, Beijing Institute of Heart Lung and Blood Vessel Disease, Capital Medical University, Beijing, China.ORCID 0000-0002-9795-0373
Dongmei ShiDepartment of Cardiology, Beijing Anzhen Hospital, Capital Medical University, Beijing Key Laboratory of Precision Medicine of Coronary Atherosclerotic Disease, Clinical Center for Coronary Heart Disease, Beijing Institute of Heart Lung and Blood Vessel Disease, Capital Medical University, Beijing, China.
Yujie ZhouDepartment of Cardiology, Beijing Anzhen Hospital, Capital Medical University, Beijing Key Laboratory of Precision Medicine of Coronary Atherosclerotic Disease, Clinical Center for Coronary Heart Disease, Beijing Institute of Heart Lung and Blood Vessel Disease, Capital Medical University, Beijing, China.ORCID 0000-0002-9545-1984
Funding
No grant is acknowledged in the PubMed record.
6 · The paper itself
Abstract
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 treatment was defined as negative DVFFR patients undergoing revascularization or positive DVFFR patients not receiving it. MACE included all-cause mortality, rehospitalization for unstable angina, and non-fatal myocardial infarction. Patients were classified into comorbidities (Class 1), smoking-drinking (Class 2), and relatively healthy (Class 3) groups. Mistaken treatment was highest in Class 2 (15.4% vs. 6.7%,
Indexed as
Clinical Decision-MakingCoronary Artery DiseaseFractional Flow Reserve, MyocardialPercutaneous Coronary InterventionAgedComorbidityFemaleHumansLatent Class AnalysisMaleMiddle AgedPhenotypePredictive Value of TestsRetrospective StudiesRisk AssessmentRisk Factorscomputed tomography angiographycoronary artery diseaseDEEPVESSEL-FFRfractional flow reservelatent class analysismistaken treatment
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.
Latent Class Analysis Identifies Distinct Patient Phenotypes Associated With Mistaken Treatment Decisions and Adverse Outcomes in Coronary Artery Disease. · full record | OpenQuestion