ArticleDiabetology & metabolic syndrome2013
Predictive models for type 2 diabetes onset in middle-aged subjects with the metabolic syndrome.
Article in Diabetology & metabolic syndrome, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.
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Who cites it
9 citing papers in PubMed, 2 syntheses or guidelines pooled it, 15 citations in OpenAlex.
- Machine learning and artificial intelligence in type 2 diabetes prediction: a comprehensive 33-year bibliometric and literature analysis.Frontiers in digital health · 2025Pooled it
- Evidence of a Bi-Directional Relationship between Arterial Stiffness and Diabetes: A Systematic Review and Meta-Analysis of Cohort Studies.Current diabetes reviews · 2025Pooled it
- Atherogenic index of plasma and its 5-year changes associated with type 2 diabetes risk: a 10-Year cohort study.Cardiovascular diabetology · 2025Article
- Article
- Development and Validation of a Machine Learning Model Using Administrative Health Data to Predict Onset of Type 2 Diabetes.JAMA network open · 2021Article
- Predicting long-term type 2 diabetes with support vector machine using oral glucose tolerance test.PloS one · 2019Article
- Machine Learning and Data Mining Methods in Diabetes Research.Computational and structural biotechnology journal · 2017Review
- Patient Characteristics are not Associated with Clinically Important Differential Response to Dapagliflozin: a Staged Analysis of Phase 3 Data.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2014Article
- The effect of short-term intensive insulin therapy in newly-diagnosed Type-2 diabetic patients.Pakistan journal of medical sciencesArticle
Corrections and comments
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Authors and funding
10 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo investigate the predictive value of different biomarkers for the incidence of type 2 diabetes mellitus (T2DM) in subjects with metabolic syndrome.
methodsA prospective study of 525 non-diabetic, middle-aged Lithuanian men and women with metabolic syndrome but without overt atherosclerotic diseases during a follow-up period of two to four years. We used logistic regression to develop predictive models for incident cases and to investigate the association between various markers and the onset of T2DM.
resultsFasting plasma glucose (FPG), body mass index (BMI), and glycosylated haemoglobin can be used to predict diabetes onset with a high level of accuracy and each was shown to have a cumulative predictive value. The estimated area under the receiver-operating characteristic curve (AUC) for this combination was 0.92. The oral glucose tolerance test (OGTT) did not show cumulative predictive value. Additionally, progression to diabetes was associated with high values of aortic pulse-wave velocity (aPWV).
conclusionT2DM onset in middle-aged metabolic syndrome subjects can be predicted with remarkable accuracy using the combination of FPG, BMI, and HbA1c, and is related to elevated aPWV measurements.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.