{"title":"心肌梗死患者的糖尿病表型:精准医学的进展?","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":"{\"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}","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
摘要
背景/目的:尽管个性化医疗取得了进步,但几十年来糖尿病的分类和管理基本没有改变。本研究的目的是确定2型糖尿病患者发生心肌梗死时的概况,并评估1年内的心血管事件。方法:所有在2021年4月1日至2023年6月30日期间在我们的冠状动脉重症监护病房因心肌梗死入院的2型糖尿病患者纳入了这项回顾性研究。为了确定患者概况,我们根据文献中最相关的六个特征(糖尿病诊断年龄、体重指数、糖化血红蛋白、谷氨酸脱羧酶抗体、胰岛素抵抗和β细胞功能),基于k-means方法进行了数据驱动的聚类分析。Cox多变量模型用于确定1年心血管事件和主要不良心血管事件无生存率的预测因子。结果:本研究纳入了250例患者,中位年龄为71岁。我们的聚类重新划分如下:46%的患者表现为严重胰岛素缺乏型糖尿病,3%表现为严重胰岛素抵抗型糖尿病,16%表现为轻度肥胖相关糖尿病,33%表现为轻度年龄相关糖尿病,2%表现为严重自身免疫性糖尿病。在多变量分析中,延长心血管事件和无主要不良心血管事件生存期的唯一独立因素是较高的肾小球功能率(风险比分别为0.97和0.98 /1 mL/mn/1.73 m2; p = 0.01和p = 0.03)。结论:本研究提示,重度胰岛素缺乏型糖尿病和轻度年龄相关性糖尿病病理生理表型在糖尿病患者心肌梗死时更为常见,这些表型可通过胰岛素抵抗、β细胞功能、糖尿病诊断年龄、体重指数、糖化血红蛋白等指标来判断。在日常临床实践中,需要谨慎对待肾小球功能率低的患者,因为这与较短的心血管事件和1年无主要不良心血管事件生存期相关。
Diabetes Phenotypes in Patients Presenting a Myocardial Infarction: Progress Towards Precision Medicine?
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.