{"title":"Diabetes Phenotypes in Patients Presenting a Myocardial Infarction: Progress Towards Precision Medicine?","authors":"Christelle Lacqua, Arnaud Barbou, Marianne Zeller, Ludwig Serge Aho Glele, Héloïse Adam, Florence Bichat, Jean-Michel Petit, Yves Cottin, Mathieu Boulin","doi":"10.3390/jpm15090444","DOIUrl":null,"url":null,"abstract":"<p><p><b>Background/Objectives</b>: Despite advances in personalized medicine, diabetes classification and management have remained widely unchanged for decades. The aims of the present study were to determine profiles of patients with type 2 diabetes at the time of their myocardial infarction and to assess 1-year cardiovascular events. <b>Methods</b>: All type 2 diabetic patients admitted for myocardial infarction in our Coronary Intensive Care Unit between 1 April 2021 and 30 June 2023 were included in this retrospective study. To identify patient profiles, we performed a data-driven cluster analysis based on the <i>k</i>-means method according to six characteristics considered as the most relevant in the literature (age at diabetes diagnosis, body mass index, glycated hemoglobin, glutamate decarboxylase antibodies, insulin resistance and beta-cell function). Cox multivariate models were used to identify predictors of 1-year cardiovascular event- and major adverse cardiovascular event-free survivals. <b>Results:</b> This study included 250 patients with a median age of 71 years. Our cluster repartition was as follows: 46% patients presented a severe insulin-deficient diabetes, 3% a severe insulin-resistant diabetes, 16% a mild obesity-related diabetes, 33% a mild age-related diabetes, and 2% patients suffered from a severe autoimmune diabetes. In multivariate analyses, the only independent factor for both longer cardiovascular event- and major adverse cardiovascular event-free survival was a higher glomerular function rate (hazard ratio of 0.97 and 0.98 per 1 mL/mn/1.73 m<sup>2</sup>; <i>p</i> = 0.01 and <i>p</i> = 0.03, respectively). <b>Conclusions</b>: This study suggests that the severe insulin-deficient diabetes and mild age-related diabetes pathophysiological phenotypes, easily estimated using insulin resistance and beta-cell function as well as age at diabetes diagnosis, body mass index, and glycated hemoglobin, were more frequent among diabetic patients at the time of their myocardial infarction. In daily clinical practice, caution is needed for patients with a low glomerular function rate, as this was associated with shorter cardiovascular event- and major adverse cardiovascular event-free survival at 1-year.</p>","PeriodicalId":16722,"journal":{"name":"Journal of Personalized Medicine","volume":"15 9","pages":""},"PeriodicalIF":3.0000,"publicationDate":"2025-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12470935/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Personalized Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3390/jpm15090444","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0
Abstract
Background/Objectives: Despite advances in personalized medicine, diabetes classification and management have remained widely unchanged for decades. The aims of the present study were to determine profiles of patients with type 2 diabetes at the time of their myocardial infarction and to assess 1-year cardiovascular events. Methods: All type 2 diabetic patients admitted for myocardial infarction in our Coronary Intensive Care Unit between 1 April 2021 and 30 June 2023 were included in this retrospective study. To identify patient profiles, we performed a data-driven cluster analysis based on the k-means method according to six characteristics considered as the most relevant in the literature (age at diabetes diagnosis, body mass index, glycated hemoglobin, glutamate decarboxylase antibodies, insulin resistance and beta-cell function). Cox multivariate models were used to identify predictors of 1-year cardiovascular event- and major adverse cardiovascular event-free survivals. Results: This study included 250 patients with a median age of 71 years. Our cluster repartition was as follows: 46% patients presented a severe insulin-deficient diabetes, 3% a severe insulin-resistant diabetes, 16% a mild obesity-related diabetes, 33% a mild age-related diabetes, and 2% patients suffered from a severe autoimmune diabetes. In multivariate analyses, the only independent factor for both longer cardiovascular event- and major adverse cardiovascular event-free survival was a higher glomerular function rate (hazard ratio of 0.97 and 0.98 per 1 mL/mn/1.73 m2; p = 0.01 and p = 0.03, respectively). Conclusions: This study suggests that the severe insulin-deficient diabetes and mild age-related diabetes pathophysiological phenotypes, easily estimated using insulin resistance and beta-cell function as well as age at diabetes diagnosis, body mass index, and glycated hemoglobin, were more frequent among diabetic patients at the time of their myocardial infarction. In daily clinical practice, caution is needed for patients with a low glomerular function rate, as this was associated with shorter cardiovascular event- and major adverse cardiovascular event-free survival at 1-year.
期刊介绍:
Journal of Personalized Medicine (JPM; ISSN 2075-4426) is an international, open access journal aimed at bringing all aspects of personalized medicine to one platform. JPM publishes cutting edge, innovative preclinical and translational scientific research and technologies related to personalized medicine (e.g., pharmacogenomics/proteomics, systems biology). JPM recognizes that personalized medicine—the assessment of genetic, environmental and host factors that cause variability of individuals—is a challenging, transdisciplinary topic that requires discussions from a range of experts. For a comprehensive perspective of personalized medicine, JPM aims to integrate expertise from the molecular and translational sciences, therapeutics and diagnostics, as well as discussions of regulatory, social, ethical and policy aspects. We provide a forum to bring together academic and clinical researchers, biotechnology, diagnostic and pharmaceutical companies, health professionals, regulatory and ethical experts, and government and regulatory authorities.