{"title":"Predicting hypertension in type 2 diabetes mellitus: Insights from a nomogram model.","authors":"Jie Liu, Nan Zhang, Tong Liu","doi":"10.4239/wjd.v16.i7.107501","DOIUrl":null,"url":null,"abstract":"<p><p>The prevalence of type 2 diabetes mellitus (T2DM) is rising, with hypertension as a common comorbidity that significantly increases cardiovascular and microvascular risks. Accurate prediction of hypertension in T2DM is essential for early intervention and personalized management. In this editorial, we comment on a recent retrospective study by Zhao <i>et al</i>, which developed a nomogram model using a large cohort of 26850 patients to predict hypertension risk in patients with T2DM. The model incorporated key independent risk factors, including age, body mass index, duration of diabetes, low-density lipoprotein cholesterol and urine protein levels, demonstrating promising discriminative power and predictive accuracy in internal validation. However, its external applicability requires further confirmation. This editorial discusses the clinical value and limitations of the predictive model, highlighting the unfavorable impact of hypertension on T2DM patients. Future research should evaluate the potential contribution of other risk factors to enhance risk prediction and improve the management of T2DM comorbidities.</p>","PeriodicalId":48607,"journal":{"name":"World Journal of Diabetes","volume":"16 7","pages":"107501"},"PeriodicalIF":4.6000,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12278073/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"World Journal of Diabetes","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.4239/wjd.v16.i7.107501","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
引用次数: 0
Abstract
The prevalence of type 2 diabetes mellitus (T2DM) is rising, with hypertension as a common comorbidity that significantly increases cardiovascular and microvascular risks. Accurate prediction of hypertension in T2DM is essential for early intervention and personalized management. In this editorial, we comment on a recent retrospective study by Zhao et al, which developed a nomogram model using a large cohort of 26850 patients to predict hypertension risk in patients with T2DM. The model incorporated key independent risk factors, including age, body mass index, duration of diabetes, low-density lipoprotein cholesterol and urine protein levels, demonstrating promising discriminative power and predictive accuracy in internal validation. However, its external applicability requires further confirmation. This editorial discusses the clinical value and limitations of the predictive model, highlighting the unfavorable impact of hypertension on T2DM patients. Future research should evaluate the potential contribution of other risk factors to enhance risk prediction and improve the management of T2DM comorbidities.
期刊介绍:
The WJD is a high-quality, peer reviewed, open-access journal. The primary task of WJD is to rapidly publish high-quality original articles, reviews, editorials, and case reports in the field of diabetes. In order to promote productive academic communication, the peer review process for the WJD is transparent; to this end, all published manuscripts are accompanied by the anonymized reviewers’ comments as well as the authors’ responses. The primary aims of the WJD are to improve diagnostic, therapeutic and preventive modalities and the skills of clinicians and to guide clinical practice in diabetes. Scope: Diabetes Complications, Experimental Diabetes Mellitus, Type 1 Diabetes Mellitus, Type 2 Diabetes Mellitus, Diabetes, Gestational, Diabetic Angiopathies, Diabetic Cardiomyopathies, Diabetic Coma, Diabetic Ketoacidosis, Diabetic Nephropathies, Diabetic Neuropathies, Donohue Syndrome, Fetal Macrosomia, and Prediabetic State.