A simple clinical score for type 2 diabetes mellitus screening in the Canary Islands

León, Antonio Cabrera de; Coello, Santiago Domínguez; Pérez, María del Cristo Rodríguez; Medina, Marta Batista; González, Delia Almeida; Díaz, Buenaventura Brito; Fuentes, Mireya; Aguirre‐Jaime, Armando

doi:10.1016/j.diabres.2007.10.022

Cited by 29 publications

(27 citation statements)

References 25 publications

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“…The predictive performance and discriminative ability of this simple tool is highly comparable to those diabetes risk scores that are composed of different sets of clinical variables 11 13 14 17 18. The AUC of DRL generated by CART analysis in our study is similar to those in Indian (AUC 0.73),18 Thai (AUC 0.74)12 and Danish (AUC 0.76)14 studies.…”

Section: Discussionsupporting

confidence: 64%

“…However, those diabetes risk scores included at least four variables and also required medical information. Even higher AUC (Germany 0.84; USA 0.85; UK 0.80; USA 0.82, Spain 0.83 for men, 0.87 for women; and middle east 0.83) have been reported if more risk factors are included, such as smoking, alcohol consumption and biochemical tests 11 17 19 23. It is well known that the more variables included in the prediction tool, the less applicable it is to the general population.…”

Section: Discussionmentioning

confidence: 99%

“…However, currently available screening tools for identifying individuals at high risk of type 2 diabetes can be invasive, costly and time consuming 11–18. Furthermore, most diabetes risk scores have been developed in western populations,11 13–15 17 19 20 south Asian12 18 21 22 and Arab populations23 with application in clinical practice/primary care services 15 17–19. Such predicting tools are lacking in the Chinese population.…”

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confidence: 99%

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A quick self-assessment tool to identify individuals at high risk of type 2 diabetes in the Chinese general population

Xie

et al. 2009

Journal of Epidemiology & Community Health

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Background Currently available tools for identifying individuals at high risk of type 2 diabetes can be invasive, costly and time consuming. This study aims to develop and validate a self-assessment tool for identifying individuals at high risk of type 2 diabetes in the Chinese general population. Methods A cross-sectional survey was conducted from 2000 to 2001 in a nationally representative sample of 15 540 Chinese adults aged 35e74 years. The diabetes risk level (DRL) was assessed by classification and regression tree (CART) analysis using four predictors: age, body mass index, waistehip ratio (WHR) and waist circumference (WC). Results The significant predictors for type 2 diabetes were WHR and age for women and WC and age for men. The categories generated by CART analysis stratified women into eight DRL and men into five DRL. The prevalence of type 2 diabetes increased with the increase in DRL in both women and men. A DRL of 6 or greater predicted type 2 diabetes status with a sensitivity of 0.61 (95% CI 0.55 to 0.67), a specificity of 0.71 (95% CI 0.70 to 0.73) in women, and a DRL of 3 or greater predicted type 2 diabetes status with a sensitivity of 0.59 (95% CI 0.52 to 0.65) and a specificity of 0.63 (95% CI 0.62 to 0.65) in men. Conclusions This study demonstrates that application of the DRL has identified a substantial proportion of individuals with type 2 diabetes in the Chinese general population. It suggests that there is a great potential for applying the self-assessment tool in healthcare-limited settings.The rising prevalence of type 2 diabetes has a become major public health problem worldwide, and it has been predicted to affect 366 million people by the year 2030, of which at least 40 million people would be from China alone.

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Section: Discussionsupporting

confidence: 64%

Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

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A quick self-assessment tool to identify individuals at high risk of type 2 diabetes in the Chinese general population

Xie

et al. 2009

Journal of Epidemiology & Community Health

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“…Risk score values ranged from 0-20. The risk of developing type 2 diabetes within ten years was stratified into different scores; low risk (<7), slightly elevated risk (7)(8)(9)(10)(11), moderately elevated risk (12)(13)(14), high risk (15)(16)(17)(18)(19)(20) and very high risk (>20).…”

Section: Exclusion Criteriamentioning

confidence: 99%

“…The challenges encountered are to identify these high risk individuals and encourage them to modify their life styles. Measuring blood glucose is an invasive method and as a tool for identifying these high risk individuals are relatively costly and labor intensive [12][13][14]. Measuring blood glucose only provides information about current glycaemic status.…”

Section: Introductionmentioning

confidence: 99%

Assessment of risk of developing diabetes mellitus among local government employees in Onitsha, south-eastern Nigeria

Agu¹,

Agu²,

Nnaji³

2015

Epidemiol Rep

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Background: Diabetes is of growing global concern with a knowledge gap on how best to assess individuals on their risk of developing Diabetes Mellitus. Objective: The aim of this study is to identify individuals with high risk of developing Diabetes Mellitus using a simple scoring system so as to contribute to the knowledge in the prevention of Diabetes Mellitus.Methodology: A pre-tested self-administered questionnaire survey was carried out during the period 1

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Survey of diabetes risk assessment tools: concepts, structure and performance

Thoopputra

Newby

Schneider

et al. 2012

Diabetes Metabolism Res

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The objective of this study is to review the effectiveness and limitations of existing diabetes risk screening tools to assess the need for further developing of such tools. An electronic search of the EMBASE, MEDLINE, and Cochrane library supplemented by a manual search was performed from 1995-2010. The search retrieved a total of 2168 articles reporting diabetes risk assessment tools which, after culling, produced 41 tools developed in 22 countries, with the majority (n = 26) developed in North America and Europe. All are short questionnaires of 2-16 questions incorporating common variables including age, gender, waist circumference, BMI, family history of diabetes, history of hypertension or antihypertensive medications. While scoring format and cut-offs point are diverse between questionnaires, overall accuracy value range of 40-97%, 24-86% and 62-87% were reported for sensitivity, specificity and receiver operating characteristic curve respectively. In summary, there is a trend of increasing availability of diabetes prediction tools with the existing risk assessment tools being generally a short questionnaire aiming for ease of use in clinical practice. The overall performance of existing tools showed moderate to high accuracy in their predictive performance. However, further detailed comparison of existing questionnaires is needed to evaluate whether they can serve adequately as diabetes risk assessment tool in clinical practice.

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A simple clinical score for type 2 diabetes mellitus screening in the Canary Islands

Cited by 29 publications

References 25 publications

A quick self-assessment tool to identify individuals at high risk of type 2 diabetes in the Chinese general population

A quick self-assessment tool to identify individuals at high risk of type 2 diabetes in the Chinese general population

Assessment of risk of developing diabetes mellitus among local government employees in Onitsha, south-eastern Nigeria

Survey of diabetes risk assessment tools: concepts, structure and performance

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