{"title":"估计脉搏波速度(ePWV)与体重指数(BMI)相结合对新诊断糖尿病的预测价值。","authors":"","doi":"10.1016/j.rceng.2024.07.001","DOIUrl":null,"url":null,"abstract":"<div><h3>Purpose</h3><div>Estimated pulse wave velocity (ePWV) and body mass index (BMI) are significant predictors of new-onset diabetes. This study aims to evaluate the impact and predictive value of combining ePWV and BMI on the incidence of new-onset diabetes.</div></div><div><h3>Methods</h3><div>A secondary analysis was conducted on a cohort study by Rich Healthcare (China), involving 211,833 eligible participants. Logistic regression analysis identified factors influencing diabetes occurrence, while ROC curve analysis assessed the predictive value of ePWV, BMI, and their combination for new-onset diabetes.</div></div><div><h3>Results</h3><div>Over a mean follow-up period of 3.12 years, 3,000 men (1.41%) and 1,174 women (0.55%) were diagnosed with diabetes. Logistic regression revealed that BMI, triglycerides, alanine aminotransferase, blood urea nitrogen, creatinine clearance rate, ePWV, and family history of diabetes are high-risk factors for new-onset diabetes. The combination of ePWV and BMI provided a higher area under the ROC curve (0.822) compared to ePWV or BMI alone.</div></div><div><h3>Conclusion</h3><div>Elevated levels of ePWV and BMI are independent risk factors for new-onset diabetes. Combining these measures enhances predictive accuracy compared to using either indicator alone.</div></div>","PeriodicalId":94354,"journal":{"name":"Revista clinica espanola","volume":"224 8","pages":"Pages 503-509"},"PeriodicalIF":0.0000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The predictive value of estimated pulse wave velocity (ePWV) combined with BMI for newly diagnosed diabetes\",\"authors\":\"\",\"doi\":\"10.1016/j.rceng.2024.07.001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Purpose</h3><div>Estimated pulse wave velocity (ePWV) and body mass index (BMI) are significant predictors of new-onset diabetes. This study aims to evaluate the impact and predictive value of combining ePWV and BMI on the incidence of new-onset diabetes.</div></div><div><h3>Methods</h3><div>A secondary analysis was conducted on a cohort study by Rich Healthcare (China), involving 211,833 eligible participants. Logistic regression analysis identified factors influencing diabetes occurrence, while ROC curve analysis assessed the predictive value of ePWV, BMI, and their combination for new-onset diabetes.</div></div><div><h3>Results</h3><div>Over a mean follow-up period of 3.12 years, 3,000 men (1.41%) and 1,174 women (0.55%) were diagnosed with diabetes. Logistic regression revealed that BMI, triglycerides, alanine aminotransferase, blood urea nitrogen, creatinine clearance rate, ePWV, and family history of diabetes are high-risk factors for new-onset diabetes. The combination of ePWV and BMI provided a higher area under the ROC curve (0.822) compared to ePWV or BMI alone.</div></div><div><h3>Conclusion</h3><div>Elevated levels of ePWV and BMI are independent risk factors for new-onset diabetes. Combining these measures enhances predictive accuracy compared to using either indicator alone.</div></div>\",\"PeriodicalId\":94354,\"journal\":{\"name\":\"Revista clinica espanola\",\"volume\":\"224 8\",\"pages\":\"Pages 503-509\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Revista clinica espanola\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2254887424000912\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Revista clinica espanola","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2254887424000912","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The predictive value of estimated pulse wave velocity (ePWV) combined with BMI for newly diagnosed diabetes
Purpose
Estimated pulse wave velocity (ePWV) and body mass index (BMI) are significant predictors of new-onset diabetes. This study aims to evaluate the impact and predictive value of combining ePWV and BMI on the incidence of new-onset diabetes.
Methods
A secondary analysis was conducted on a cohort study by Rich Healthcare (China), involving 211,833 eligible participants. Logistic regression analysis identified factors influencing diabetes occurrence, while ROC curve analysis assessed the predictive value of ePWV, BMI, and their combination for new-onset diabetes.
Results
Over a mean follow-up period of 3.12 years, 3,000 men (1.41%) and 1,174 women (0.55%) were diagnosed with diabetes. Logistic regression revealed that BMI, triglycerides, alanine aminotransferase, blood urea nitrogen, creatinine clearance rate, ePWV, and family history of diabetes are high-risk factors for new-onset diabetes. The combination of ePWV and BMI provided a higher area under the ROC curve (0.822) compared to ePWV or BMI alone.
Conclusion
Elevated levels of ePWV and BMI are independent risk factors for new-onset diabetes. Combining these measures enhances predictive accuracy compared to using either indicator alone.