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Diabetologia. 2012 Apr;55(4):959-66. doi: 10.1007/s00125-011-2432-x. Epub 2012 Jan 10.

Detection of impaired glucose regulation and/or type 2 diabetes mellitus, using primary care electronic data, in a multiethnic UK community setting.

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Department of Health Sciences, University of Leicester, Leicester, UK.



The aim of this study was to develop and validate a score for detecting the glycaemic categories of impaired glucose regulation (IGR) and type 2 diabetes using the WHO 2011 diagnostic criteria.


We used data from 6,390 individuals aged 40-75 years from a multiethnic population based screening study. We developed a logistic regression model for predicting IGR and type 2 diabetes (diagnosed using OGTT or HbA(1c) ≥ 6.5% [48 mmol/mol]) from data which are routinely stored in primary care. We developed the score by summing the β coefficients. We externally validated the score using data from 3,225 participants aged 40-75 years screened as part of another study.


The score includes age, ethnicity, sex, family history of diabetes, antihypertensive therapy and BMI. Fifty per cent of a population would need to be invited for testing to detect type 2 diabetes mellitus on OGTT with 80% sensitivity; this is slightly raised to 54% that need to be invited if using HbA(1c). Inviting the top 10% for testing, 9% of these would have type 2 diabetes mellitus using an OGTT (positive predictive value [PPV] 8.9% [95% CI 5.8%,12.8%]), 26% would have IGR (PPV 25.9% [95% CI 20.9%, 31.4%]). Using HbA(1c) increases the PPV to 19% for type 2 diabetes mellitus (PPV 18.6% [95% CI 14.2%, 23.7%]) and 28% for an HbA(1c) between 6.0% and 6.4% (PPV 28.3% [95% CI 23.1%, 34.0%]).


The score can be used to reliably identify those with undiagnosed IGR and type 2 diabetes in multiethnic populations. This is the first score developed taking into account HbA(1c) in the diagnosis of type 2 diabetes.

[Indexed for MEDLINE]

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