{"title":"基线甘油三酯-葡萄糖、体重指数、左心房舒张末期内径和肌酐是冠心病患者经皮冠状动脉介入治疗后肺动脉高压的独立预测指标。","authors":"Li Xie, Shilin Fu, Yuzheng Xu, Litong Ran, Jing Luo, Rongsheng Rao, Jianfei Chen, Shi-Zhu Bian, Dehui Qian","doi":"10.1080/17520363.2024.2422807","DOIUrl":null,"url":null,"abstract":"<p><p><b>Aim:</b> To identify the predictive role of triglyceride-glucose (TyG) index in pulmonary hypertension (PH) in coronary artery disease (CAD) patients after percutaneous coronary intervention (PCI) treatment.<b>Methods:</b> Blood biomarkers have been measured at the cross-section of entrance. The baseline and followed-up echocardiography have been performed at both cross-sections.<b>Results:</b> The incidence of PH was 8.91%. The baseline myoglobin (MYO), was significantly higher among PH patients (<i>p</i> < 0.001). In the univariate regression, body mass index (BMI <i>p</i> = 0.020), left atria end-diastolic internal diameter (LAD, <i>p</i> = 0.083), creatinine (Cr, <i>p</i> = 0.005), triglyceride (TG, <i>p</i> < 0.001), high-density lipoprotein cholesterol (HDL-C, <i>p</i> = 0.056) and TyG index (<i>p</i> = 0.002) were potential predictors for PH. Finally, the adjusted COX regression indicated that BMI (<i>p</i> = 0.001), LAD (<i>p</i> = 0.030), Cr(<i>p</i> = 0.005) and TyG index (<i>p</i> = 0.002) were independent predictors of the onset of PH.<b>Conclusion:</b> Baseline TyG index, BMI, LAD, Cr level were independent predictors for PH in CAD patients after PCI treatment.</p>","PeriodicalId":9182,"journal":{"name":"Biomarkers in medicine","volume":" ","pages":"1-11"},"PeriodicalIF":1.9000,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Baseline triglyceride-glucose, body mass index, end-diastolic internal diameter of the left atria and creatinine are independent predictors for pulmonary hypertension in coronary artery disease patients after percutaneous coronary intervention treatments.\",\"authors\":\"Li Xie, Shilin Fu, Yuzheng Xu, Litong Ran, Jing Luo, Rongsheng Rao, Jianfei Chen, Shi-Zhu Bian, Dehui Qian\",\"doi\":\"10.1080/17520363.2024.2422807\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p><b>Aim:</b> To identify the predictive role of triglyceride-glucose (TyG) index in pulmonary hypertension (PH) in coronary artery disease (CAD) patients after percutaneous coronary intervention (PCI) treatment.<b>Methods:</b> Blood biomarkers have been measured at the cross-section of entrance. The baseline and followed-up echocardiography have been performed at both cross-sections.<b>Results:</b> The incidence of PH was 8.91%. The baseline myoglobin (MYO), was significantly higher among PH patients (<i>p</i> < 0.001). In the univariate regression, body mass index (BMI <i>p</i> = 0.020), left atria end-diastolic internal diameter (LAD, <i>p</i> = 0.083), creatinine (Cr, <i>p</i> = 0.005), triglyceride (TG, <i>p</i> < 0.001), high-density lipoprotein cholesterol (HDL-C, <i>p</i> = 0.056) and TyG index (<i>p</i> = 0.002) were potential predictors for PH. Finally, the adjusted COX regression indicated that BMI (<i>p</i> = 0.001), LAD (<i>p</i> = 0.030), Cr(<i>p</i> = 0.005) and TyG index (<i>p</i> = 0.002) were independent predictors of the onset of PH.<b>Conclusion:</b> Baseline TyG index, BMI, LAD, Cr level were independent predictors for PH in CAD patients after PCI treatment.</p>\",\"PeriodicalId\":9182,\"journal\":{\"name\":\"Biomarkers in medicine\",\"volume\":\" \",\"pages\":\"1-11\"},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2024-11-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Biomarkers in medicine\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1080/17520363.2024.2422807\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MEDICINE, RESEARCH & EXPERIMENTAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biomarkers in medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/17520363.2024.2422807","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MEDICINE, RESEARCH & EXPERIMENTAL","Score":null,"Total":0}
Baseline triglyceride-glucose, body mass index, end-diastolic internal diameter of the left atria and creatinine are independent predictors for pulmonary hypertension in coronary artery disease patients after percutaneous coronary intervention treatments.
Aim: To identify the predictive role of triglyceride-glucose (TyG) index in pulmonary hypertension (PH) in coronary artery disease (CAD) patients after percutaneous coronary intervention (PCI) treatment.Methods: Blood biomarkers have been measured at the cross-section of entrance. The baseline and followed-up echocardiography have been performed at both cross-sections.Results: The incidence of PH was 8.91%. The baseline myoglobin (MYO), was significantly higher among PH patients (p < 0.001). In the univariate regression, body mass index (BMI p = 0.020), left atria end-diastolic internal diameter (LAD, p = 0.083), creatinine (Cr, p = 0.005), triglyceride (TG, p < 0.001), high-density lipoprotein cholesterol (HDL-C, p = 0.056) and TyG index (p = 0.002) were potential predictors for PH. Finally, the adjusted COX regression indicated that BMI (p = 0.001), LAD (p = 0.030), Cr(p = 0.005) and TyG index (p = 0.002) were independent predictors of the onset of PH.Conclusion: Baseline TyG index, BMI, LAD, Cr level were independent predictors for PH in CAD patients after PCI treatment.
期刊介绍:
Biomarkers are physical, functional or biochemical indicators of physiological or disease processes. These key indicators can provide vital information in determining disease prognosis, in predicting of response to therapies, adverse events and drug interactions, and in establishing baseline risk. The explosion of interest in biomarker research is driving the development of new predictive, diagnostic and prognostic products in modern medical practice, and biomarkers are also playing an increasingly important role in the discovery and development of new drugs. For the full utility of biomarkers to be realized, we require greater understanding of disease mechanisms, and the interplay between disease mechanisms, therapeutic interventions and the proposed biomarkers. However, in attempting to evaluate the pros and cons of biomarkers systematically, we are moving into new, challenging territory.
Biomarkers in Medicine (ISSN 1752-0363) is a peer-reviewed, rapid publication journal delivering commentary and analysis on the advances in our understanding of biomarkers and their potential and actual applications in medicine. The journal facilitates translation of our research knowledge into the clinic to increase the effectiveness of medical practice.
As the scientific rationale and regulatory acceptance for biomarkers in medicine and in drug development become more fully established, Biomarkers in Medicine provides the platform for all players in this increasingly vital area to communicate and debate all issues relating to the potential utility and applications.
Each issue includes a diversity of content to provide rounded coverage for the research professional. Articles include Guest Editorials, Interviews, Reviews, Research Articles, Perspectives, Priority Paper Evaluations, Special Reports, Case Reports, Conference Reports and Company Profiles. Review coverage is divided into themed sections according to area of therapeutic utility with some issues including themed sections on an area of topical interest.
Biomarkers in Medicine provides a platform for commentary and debate for all professionals with an interest in the identification of biomarkers, elucidation of their role and formalization and approval of their application in modern medicine. The audience for Biomarkers in Medicine includes academic and industrial researchers, clinicians, pathologists, clinical chemists and regulatory professionals.