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Modelling of OGTT c...
Modelling of OGTT curve identifies 1 h plasma glucose level as a strong predictor of incident type 2 diabetes: results from two prospective cohorts
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Alyass, Akram (author)
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- Almgren, Peter (author)
- Lund University,Lunds universitet,Genomik, diabetes och endokrinologi,Forskargrupper vid Lunds universitet,Genomics, Diabetes and Endocrinology,Lund University Research Groups
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- Åkerlund, Mikael (author)
- Lund University,Lunds universitet,Genomik, diabetes och endokrinologi,Forskargrupper vid Lunds universitet,Genomics, Diabetes and Endocrinology,Lund University Research Groups
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Dushoff, Jonathan (author)
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Isomaa, Bo (author)
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- Nilsson, Peter (author)
- Lund University,Lunds universitet,Internmedicin - epidemiologi,Forskargrupper vid Lunds universitet,Internal Medicine - Epidemiology,Lund University Research Groups
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Tuomi, Tiinamaija (author)
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- Lyssenko, Valeriya (author)
- Lund University,Lunds universitet,Genomik, diabetes och endokrinologi,Forskargrupper vid Lunds universitet,Genomics, Diabetes and Endocrinology,Lund University Research Groups
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- Groop, Leif (author)
- Lund University,Lunds universitet,Genomik, diabetes och endokrinologi,Forskargrupper vid Lunds universitet,Genomics, Diabetes and Endocrinology,Lund University Research Groups
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Meyre, David (author)
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(creator_code:org_t)
- 2014-10-08
- 2015
- English.
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In: Diabetologia. - : Springer Science and Business Media LLC. - 1432-0428 .- 0012-186X. ; 58:1, s. 87-97
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Abstract
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- Aims/hypothesis The relevance of the OGTT in predicting type 2 diabetes is unclear. We assessed the performance of 14 OGTT glucose traits in type 2 diabetes prediction. Methods We studied 2,603 and 2,386 Europeans from the Botnia study and Malmo Prevention Project (MPP) cohorts with baseline OGTT data. Over a follow-up period of 4.94 years and 23.5 years, 155 (5.95%) and 467 (19.57%) participants, respectively, developed type 2 diabetes. The main outcome was incident type 2 diabetes. Results One-hour plasma glucose (1h-PG) was a fair/good predictor of incident type 2 diabetes in the Botnia study and MPP (AUC for receiver operating characteristic [AUC(ROC)] 0.80 [0.77, 0.84] and 0.70 [0.68, 0.73]). 1h-PG alone outperformed the prediction model of multiple clinical risk factors (age, sex, BMI, family history of type 2 diabetes) in the Botnia study and MPP (AUC(ROC) 0.75 [0.72, 0.79] and 0.67 [0.64, 0.70]). The same clinical risk factors added to 1h-PG modestly increased prediction for incident type 2 diabetes (Botnia, AUC(ROC) 0.83 [0.80, 0.86]; MPP, AUC(ROC) 0.74 [0.72, 0.77]). 1h-PG also outperformed HbA(1c) in predicting type 2 diabetes in the Botnia cohort. A 1h-PG value of 8.9 mmol/l and 8.4 mmol/l was the optimal cut-point for initial screening and selection of high-risk individuals in the Botnia study and MPP, respectively, and represented 30% and 37% of all participants in these cohorts. High-risk individuals had a substantially increased risk of incident type 2 diabetes (OR 8.0 [5.5, 11.6] and 3.8 [3.1, 4.7]) and captured 75% and 62% of all incident type 2 diabetes in the Botnia study and MPP. Conclusions/interpretation1h-PG is a valuable prediction tool for identifying adults at risk for future type 2 diabetes.
Subject headings
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Endokrinologi och diabetes (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Endocrinology and Diabetes (hsv//eng)
Keyword
- Incident type 2 diabetes
- Mathematical modelling
- One-hour post-OGTT
- plasma glucose
- Oral glucose tolerance test
- Prevention
Publication and Content Type
- art (subject category)
- ref (subject category)
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- By the author/editor
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Alyass, Akram
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Almgren, Peter
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Åkerlund, Mikael
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Dushoff, Jonatha ...
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Isomaa, Bo
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Nilsson, Peter
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Tuomi, Tiinamaij ...
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Lyssenko, Valeri ...
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Groop, Leif
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Meyre, David
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- About the subject
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- MEDICAL AND HEALTH SCIENCES
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MEDICAL AND HEAL ...
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and Clinical Medicin ...
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and Endocrinology an ...
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Diabetologia
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Lund University