Literature DB >> 14693976

The performance of a risk score as a screening test for undiagnosed hyperglycemia in ethnic minority groups: data from the 1999 health survey for England.

Annemieke M W Spijkerman1, Matthew F Yuyun, Simon J Griffin, Jacqueline M Dekker, Giel Nijpels, Nicholas J Wareham.   

Abstract

OBJECTIVE: To assess the performance of the Cambridge Risk Score (CRS) to predict undiagnosed hyperglycemia in Caribbean and South Asian people living in the U.K. RESEARCH DESIGN AND METHODS: The CRS uses routinely available data from primary care records to identify people at high risk for undiagnosed type 2 diabetes. The sensitivity, specificity, and area under the receiver operator characteristic (ROC) curve for the CRS cut point of 0.199 were 77, 72, and 80% (95% CI 68-91), respectively. The risk score was calculated for 248 Caribbean and 555 South Asian participants aged 40-75 years in the 1999 Health Survey for England. Undiagnosed hyperglycemia was considered present if fasting plasma glucose was >/=7.0 mmol/l or HbA(1c) was >/=6.5%. Sensitivity, specificity, and predictive values were calculated for various cut points of the risk score, and ROC curves were constructed.
RESULTS: The area under the ROC curve was 67% (59-76) and 72% (67-78) for Caribbeans and South Asians, respectively. The optimal cut point in Caribbean participants was 0.236, sensitivity was 63% (46-77), and specificity was 63% (56-69). In the South Asian population, the optimal cut point was and 0.127, sensitivity was 69% (60-78), and specificity was 64% (60-69).
CONCLUSIONS: The CRS, using routinely available data, can be used in a strategy to detect undiagnosed hyperglycemia in Caribbean and South Asian populations. The existence of ethnic group-specific cut points must be further established in future studies.

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Year:  2004        PMID: 14693976     DOI: 10.2337/diacare.27.1.116

Source DB:  PubMed          Journal:  Diabetes Care        ISSN: 0149-5992            Impact factor:   19.112


  27 in total

1.  Different type 2 diabetes risk assessments predict dissimilar numbers at 'high risk': a retrospective analysis of diabetes risk-assessment tools.

Authors:  Benjamin J Gray; Richard M Bracken; Daniel Turner; Kerry Morgan; Michael Thomas; Sally P Williams; Meurig Williams; Sam Rice; Jeffrey W Stephens
Journal:  Br J Gen Pract       Date:  2015-11-05       Impact factor: 5.386

2.  Screening score for early detection of cardio-metabolic risk in Indian adults.

Authors:  Deepa Pandit-Agrawal; Anuradha Khadilkar; Shashi Chiplonkar; Vaman Khadilkar; Vivek Patwardhan
Journal:  Int J Public Health       Date:  2017-06-21       Impact factor: 3.380

3.  Performance of Indian Diabetes Risk Score (IDRS) as screening tool for diabetes in an urban slum.

Authors:  Puja Dudeja; Gurpreet Singh; Tukaram Gadekar; Sandip Mukherji
Journal:  Med J Armed Forces India       Date:  2016-10-18

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

Authors:  L J Gray; M J Davies; S Hiles; N A Taub; D R Webb; B T Srinivasan; K Khunti
Journal:  Diabetologia       Date:  2012-01-10       Impact factor: 10.122

5.  Diabetes prevalence and its risk factors in urban Pondicherry.

Authors:  Sanjay Kumar Gupta; Zile Singh; Anil J Purty; Mohan Vishwanathan
Journal:  Int J Diabetes Dev Ctries       Date:  2009-10

6.  Random plasma glucose in serendipitous screening for glucose intolerance: screening for impaired glucose tolerance study 2.

Authors:  David C Ziemer; Paul Kolm; Jovonne K Foster; William S Weintraub; Viola Vaccarino; Mary K Rhee; Rincy M Varughese; Circe W Tsui; David D Koch; Jennifer G Twombly; K M Venkat Narayan; Lawrence S Phillips
Journal:  J Gen Intern Med       Date:  2008-03-12       Impact factor: 5.128

7.  Age, BMI, and race are less important than random plasma glucose in identifying risk of glucose intolerance: the Screening for Impaired Glucose Tolerance Study (SIGT 5).

Authors:  David C Ziemer; Paul Kolm; William S Weintraub; Viola Vaccarino; Mary K Rhee; Jane M Caudle; Jade M Irving; David D Koch; K M Venkat Narayan; Lawrence S Phillips
Journal:  Diabetes Care       Date:  2008-02-29       Impact factor: 19.112

8.  Impact of an informed choice invitation on uptake of screening for diabetes in primary care (DICISION): trial protocol.

Authors:  Eleanor Mann; A Toby Prevost; Simon Griffin; Ian Kellar; Stephen Sutton; Michael Parker; Simon Sanderson; Ann Louise Kinmonth; Theresa M Marteau
Journal:  BMC Public Health       Date:  2009-02-20       Impact factor: 3.295

9.  The ADDITION-Cambridge trial protocol: a cluster -- randomised controlled trial of screening for type 2 diabetes and intensive treatment for screen-detected patients.

Authors:  Justin B Echouffo-Tcheugui; Rebecca K Simmons; Kate M Williams; Roslyn S Barling; A Toby Prevost; Ann Louise Kinmonth; Nicholas J Wareham; Simon J Griffin
Journal:  BMC Public Health       Date:  2009-05-12       Impact factor: 3.295

10.  Validation of a type 2 diabetes screening tool in rural Honduras.

Authors:  Evan C Milton; William H Herman; Allison E Aiello; Kris R Danielson; Milton O Mendoza-Avelarez; John D Piette
Journal:  Diabetes Care       Date:  2009-11-16       Impact factor: 19.112

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