Development and validation of the type 2 diabetes mellitus 10-year risk score prediction models from survey data

Author(s):  
Gregor Stiglic ◽  
Fei Wang ◽  
Aziz Sheikh ◽  
Leona Cilar
2021 ◽  
Vol 24 ◽  
pp. 157-166
Author(s):  
Wilailuck Tuntayothin ◽  
Stephen John Kerr ◽  
Chanchana Boonyakrai ◽  
Suwasin Udomkarnjananun ◽  
Sumitra Chukaew ◽  
...  

Author(s):  
Rocío Barrios-Rodríguez ◽  
Esther García-Esquinas ◽  
Beatriz Pérez-Gómez ◽  
Gemma Castaño-Vinyals ◽  
Javier Llorca ◽  
...  

Author(s):  
VENKATESAN S. ◽  
SUSILA S. ◽  
SUTHANTHIRAN S. ◽  
MADHUSUDHAN S. ◽  
PAARI N.

Objective: To identify and prevent the vulnerable prediabetic population becoming diabetic patients in the future using the Indian Diabetic Risk Score (IDRS) and to evaluate the performance of the IDRS questionnaire for detecting prediabetes and predicting the risk of Type 2 Diabetes Mellitus in Chidambaram rural Indian population. Methods: A cross-sectional descriptive study was carried out among patients attending a master health check-up of RMMCH hospital located at Chidambaram. The IDRS was calculated by using four simple measures of age, family history of diabetes, physical activity, and waist measurement. The relevant blood test, like Fasting plasma glucose (FBS), Glycated hemoglobin (HbA1C) test, were observed for identifying prediabetes. Subjects were classified as Normoglycemic, prediabetics, and diabetics based on the questionnaire and diagnostic criteria of the Indian Council of Medical Research (ICMR) guidelines. Results: In the study, sensitivity and specificity of IDRS score were found to be 84.21% and 63.4% respectively for detecting prediabetes in community with the positive predictive value of 51.6% and negative predictive value of 89.6% and prevalence of prediabetes in the Chidambaram rural population is 31.6% among the 60 participants. Conclusion: The Indian diabetic risk score questionnaire designed by Ma­dras diabetic research federation is a useful screening tool to identify unknown type 2 diabetes mellitus. The question­naire is a reliable, valuable, and easy to use screening tool which can be used in a primary care setup. 


2016 ◽  
Vol 14 (1) ◽  
pp. 47-54 ◽  
Author(s):  
Benjamin J Gray ◽  
Jeffrey W Stephens ◽  
Daniel Turner ◽  
Michael Thomas ◽  
Sally P Williams ◽  
...  

This study examined the relationship between cardiorespiratory fitness determined by a non-exercise testing method for estimating fitness and predicted risk of developing type 2 diabetes mellitus using five risk assessments/questionnaires (Leicester Diabetes Risk Score, QDiabetes, Cambridge Risk Score, Finnish Diabetes Risk Score and American Diabetes Association Diabetes Risk Test). Retrospective analysis was performed on 330 female individuals with no prior diagnosis of cardiovascular disease or type 2 diabetes mellitus who participated in the Prosiect Sir Gâr workplace initiative in Carmarthenshire, South Wales. Non-exercise testing method for estimating fitness (expressed as metabolic equivalents) was calculated using a validated algorithm, and females were grouped accordingly into fitness quintiles <6.8 metabolic equivalents (Quintile 1), 6.8–7.6 metabolic equivalents (Quintile 2), 7.6–8.6 metabolic equivalents (Quintile 3), 8.6–9.5 metabolic equivalents (Quintile 4), >9.5 metabolic equivalents (Quintile 5). Body mass index, waist circumference, and HbA1c all decreased between increasing non-exercise testing method for estimating fitness quintiles ( p < 0.05), as did risk prediction scores in each of the five assessments/questionnaires ( p < 0.05). The proportion of females in Quintile 1 predicted at ‘high risk’ was between 20.9% and 81.4%, depending on diabetes risk assessment used, compared to none of the females in Quintile 5. A calculated non-exercise testing method for estimating fitness <6.8 metabolic equivalents could help to identify females at ‘high risk’ of developing type 2 diabetes mellitus as predicted using five risk assessments/questionnaires.


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