{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T15:07:03Z","timestamp":1784214423482,"version":"3.55.0"},"reference-count":33,"publisher":"SAGE Publications","issue":"7","license":[{"start":{"date-parts":[[2025,7,19]],"date-time":"2025-07-19T00:00:00Z","timestamp":1752883200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2025,7,19]],"date-time":"2025-07-19T00:00:00Z","timestamp":1752883200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2022YFC3602500"],"award-info":[{"award-number":["2022YFC3602500"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Angiology"],"published-print":{"date-parts":[[2026,8]]},"abstract":"<jats:p>\n                    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%,\n                    <jats:italic toggle=\"yes\">P<\/jats:italic>\n                    \u2009&lt;\u2009.001), while MACE was highest in Class 1 (7.0% vs. 4.8%,\n                    <jats:italic toggle=\"yes\">P<\/jats:italic>\n                    \u2009&lt;\u2009.001). Adjusted analyses showed increased mistaken treatment risk in Class 1 (OR 1.96; 95% CI 1.49\u20132.57) and Class 2 (OR 1.69; 95% CI 1.28\u20132.25) compared with Class 3. Class 1 also had higher MACE risk (HR 1.53; 95% CI 1.10\u20132.12). In conclusion, comorbidities and smoking-drinking classes had higher mistaken treatment and MACE risks compared with the relatively healthy class.\n                  <\/jats:p>","DOI":"10.1177\/00033197251350182","type":"journal-article","created":{"date-parts":[[2025,7,19]],"date-time":"2025-07-19T08:16:09Z","timestamp":1752912969000},"page":"857-867","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":2,"title":["Latent Class Analysis Identifies Distinct Patient Phenotypes Associated With Mistaken Treatment Decisions and Adverse Outcomes in Coronary Artery Disease"],"prefix":"10.1177","volume":"77","author":[{"given":"Jing","family":"Qi","sequence":"first","affiliation":[{"name":"Department 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 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