Joris Holtrop, Carl-Emil Lim, Alicia Uijl, Peter Ueda, Tomas Jernberg, Manon G van der Meer, Pim van der Harst, Adriaan O Kraaijeveld, Jan-Willem Balder, Steven H J Hageman, Frank L J Visseren, Jannick A N Dorresteijn
{"title":"鉴定冠状动脉疾病患者的临床表型簇。","authors":"Joris Holtrop, Carl-Emil Lim, Alicia Uijl, Peter Ueda, Tomas Jernberg, Manon G van der Meer, Pim van der Harst, Adriaan O Kraaijeveld, Jan-Willem Balder, Steven H J Hageman, Frank L J Visseren, Jannick A N Dorresteijn","doi":"10.1136/heartjnl-2025-325740","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Guideline recommendations for the prevention of cardiovascular (CV) events in patients with coronary artery disease (CAD) are predominantly one-size-fits-all. Clinically identifiable phenotypes needing specific considerations might exist. The purpose of this study is to identify such clinical phenotypic clusters in patients with CAD and assess their relationship with the risk of recurrent CV events.</p><p><strong>Methods: </strong>Unsupervised machine learning through latent class analysis was performed in patients with CAD from the Swedish Web-System for Enhancement and Development of Evidence-Based Care in Heart Disease Evaluated According to Recommended Therapies (SWEDEHEART) registry (n=88 894) and Utrecht Cardiovascular Cohort-Second Manifestations of Arterial Disease (UCC-SMART) cohort (n=5506). Characteristics for clustering were based on availability, missingness and clinical relevance. Clustering was performed in SWEDEHEART and validated in UCC-SMART. Association between clusters and the composite of myocardial infarction, stroke or CV death was assessed using Cox proportional hazard models.</p><p><strong>Results: </strong>Four phenotypes could be distinguished: cluster 1 (38%, n=33 777) of predominantly younger males with increased body mass index, blood pressure and C-reactive protein, cluster 2 (21%, n=18 775) of smokers with few traditional risk factors, cluster 3 (30%, n=26 501) of older patients with few comorbidities and cluster 4 (11%, n=9841) of patients with multimorbidity. Compared with cluster 1, cluster 4 was at the highest risk (HR 4.38 95% CI (4.01 to 4.78)), followed by cluster 3 (HR 1.78 (1.70 to 1.85)), and cluster 2 (HR 0.97 (0.88 to 1.07)). Validation in UCC-SMART yielded similar results.</p><p><strong>Conclusion: </strong>Four distinct and reproducible phenotypes, with differences in the risk of recurrent CV events, were identified among patients with CAD. These may be relevant in practice and warrant research into specific pathophysiology and differences in treatment effects.</p>","PeriodicalId":12835,"journal":{"name":"Heart","volume":" ","pages":""},"PeriodicalIF":5.1000,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Identifying clinical phenotype clusters in patients with coronary artery disease.\",\"authors\":\"Joris Holtrop, Carl-Emil Lim, Alicia Uijl, Peter Ueda, Tomas Jernberg, Manon G van der Meer, Pim van der Harst, Adriaan O Kraaijeveld, Jan-Willem Balder, Steven H J Hageman, Frank L J Visseren, Jannick A N Dorresteijn\",\"doi\":\"10.1136/heartjnl-2025-325740\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Guideline recommendations for the prevention of cardiovascular (CV) events in patients with coronary artery disease (CAD) are predominantly one-size-fits-all. Clinically identifiable phenotypes needing specific considerations might exist. The purpose of this study is to identify such clinical phenotypic clusters in patients with CAD and assess their relationship with the risk of recurrent CV events.</p><p><strong>Methods: </strong>Unsupervised machine learning through latent class analysis was performed in patients with CAD from the Swedish Web-System for Enhancement and Development of Evidence-Based Care in Heart Disease Evaluated According to Recommended Therapies (SWEDEHEART) registry (n=88 894) and Utrecht Cardiovascular Cohort-Second Manifestations of Arterial Disease (UCC-SMART) cohort (n=5506). Characteristics for clustering were based on availability, missingness and clinical relevance. Clustering was performed in SWEDEHEART and validated in UCC-SMART. Association between clusters and the composite of myocardial infarction, stroke or CV death was assessed using Cox proportional hazard models.</p><p><strong>Results: </strong>Four phenotypes could be distinguished: cluster 1 (38%, n=33 777) of predominantly younger males with increased body mass index, blood pressure and C-reactive protein, cluster 2 (21%, n=18 775) of smokers with few traditional risk factors, cluster 3 (30%, n=26 501) of older patients with few comorbidities and cluster 4 (11%, n=9841) of patients with multimorbidity. Compared with cluster 1, cluster 4 was at the highest risk (HR 4.38 95% CI (4.01 to 4.78)), followed by cluster 3 (HR 1.78 (1.70 to 1.85)), and cluster 2 (HR 0.97 (0.88 to 1.07)). Validation in UCC-SMART yielded similar results.</p><p><strong>Conclusion: </strong>Four distinct and reproducible phenotypes, with differences in the risk of recurrent CV events, were identified among patients with CAD. These may be relevant in practice and warrant research into specific pathophysiology and differences in treatment effects.</p>\",\"PeriodicalId\":12835,\"journal\":{\"name\":\"Heart\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":5.1000,\"publicationDate\":\"2025-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Heart\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1136/heartjnl-2025-325740\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CARDIAC & CARDIOVASCULAR SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Heart","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1136/heartjnl-2025-325740","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
Identifying clinical phenotype clusters in patients with coronary artery disease.
Background: Guideline recommendations for the prevention of cardiovascular (CV) events in patients with coronary artery disease (CAD) are predominantly one-size-fits-all. Clinically identifiable phenotypes needing specific considerations might exist. The purpose of this study is to identify such clinical phenotypic clusters in patients with CAD and assess their relationship with the risk of recurrent CV events.
Methods: Unsupervised machine learning through latent class analysis was performed in patients with CAD from the Swedish Web-System for Enhancement and Development of Evidence-Based Care in Heart Disease Evaluated According to Recommended Therapies (SWEDEHEART) registry (n=88 894) and Utrecht Cardiovascular Cohort-Second Manifestations of Arterial Disease (UCC-SMART) cohort (n=5506). Characteristics for clustering were based on availability, missingness and clinical relevance. Clustering was performed in SWEDEHEART and validated in UCC-SMART. Association between clusters and the composite of myocardial infarction, stroke or CV death was assessed using Cox proportional hazard models.
Results: Four phenotypes could be distinguished: cluster 1 (38%, n=33 777) of predominantly younger males with increased body mass index, blood pressure and C-reactive protein, cluster 2 (21%, n=18 775) of smokers with few traditional risk factors, cluster 3 (30%, n=26 501) of older patients with few comorbidities and cluster 4 (11%, n=9841) of patients with multimorbidity. Compared with cluster 1, cluster 4 was at the highest risk (HR 4.38 95% CI (4.01 to 4.78)), followed by cluster 3 (HR 1.78 (1.70 to 1.85)), and cluster 2 (HR 0.97 (0.88 to 1.07)). Validation in UCC-SMART yielded similar results.
Conclusion: Four distinct and reproducible phenotypes, with differences in the risk of recurrent CV events, were identified among patients with CAD. These may be relevant in practice and warrant research into specific pathophysiology and differences in treatment effects.
期刊介绍：
Heart is an international peer reviewed journal that keeps cardiologists up to date with important research advances in cardiovascular disease. New scientific developments are highlighted in editorials and put in context with concise review articles. There is one free Editor’s Choice article in each issue, with open access options available to authors for all articles. Education in Heart articles provide a comprehensive, continuously updated, cardiology curriculum.
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