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Development and validation of prediabetes risk score for predicting prediabetes among Indonesian adults in primary care: Cross-sectional diagnostic study

OBJECTIVE: To develop and validate a risk score model for recognizing prediabetes among Indonesian adults in primary care. METHODS: This was a cross-sectional diagnostic study. After excluding subjects with diabetes from Indonesian National Basic Health Survey (INBHS) data set, 21,720 subjects who h...

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Autores principales: Fujiati, Isti Ilmiati, Damanik, Harun Alrasyid, Bachtiar, Adang, Nurdin, Andi Armyn, Ward, Paul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Akadémiai Kiadó 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5598131/
https://www.ncbi.nlm.nih.gov/pubmed/28932501
http://dx.doi.org/10.1556/1646.9.2017.2.18
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author Fujiati, Isti Ilmiati
Damanik, Harun Alrasyid
Bachtiar, Adang
Nurdin, Andi Armyn
Ward, Paul
author_facet Fujiati, Isti Ilmiati
Damanik, Harun Alrasyid
Bachtiar, Adang
Nurdin, Andi Armyn
Ward, Paul
author_sort Fujiati, Isti Ilmiati
collection PubMed
description OBJECTIVE: To develop and validate a risk score model for recognizing prediabetes among Indonesian adults in primary care. METHODS: This was a cross-sectional diagnostic study. After excluding subjects with diabetes from Indonesian National Basic Health Survey (INBHS) data set, 21,720 subjects who have completed fasting plasma glucose test and aged >18 years were selected for development stage. About 6,933 subjects were selected randomly from INBHS for validation stage in different diagnostic criteria of prediabetes-based random plasma glucose. Logistic regression was used to determine significant diagnostic variable and the receiver operating characteristic analysis was used to calculate area under the curve (AUC), cutoff point, sensitivity, specificity, and predictive values. RESULTS: Age, sex, education level, family history of diabetes, smoking habit, physical activity, body mass index, and hypertension were significant variables for Indonesian Prediabetes Risk Score (INA-PRISC). The scoring range from 0 to 24, the AUC was 0.623 (95% CI 0.616–0.631) and cutoff point of 12 yielded sensitivity/specificity (50.03%/67.19%, respectively). The validation study showed the AUC was 0.646 (95% CI 0.623–0.669) and cutoff point of 12 yielded sensitivity/specificity (55.11%/65.81%, respectively). CONCLUSION: INA-PRISC, which consists of eight demographical and clinical variables, is a valid and a simple prediabetes risk score in primary care.
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spelling pubmed-55981312017-09-20 Development and validation of prediabetes risk score for predicting prediabetes among Indonesian adults in primary care: Cross-sectional diagnostic study Fujiati, Isti Ilmiati Damanik, Harun Alrasyid Bachtiar, Adang Nurdin, Andi Armyn Ward, Paul Interv Med Appl Sci Original Paper OBJECTIVE: To develop and validate a risk score model for recognizing prediabetes among Indonesian adults in primary care. METHODS: This was a cross-sectional diagnostic study. After excluding subjects with diabetes from Indonesian National Basic Health Survey (INBHS) data set, 21,720 subjects who have completed fasting plasma glucose test and aged >18 years were selected for development stage. About 6,933 subjects were selected randomly from INBHS for validation stage in different diagnostic criteria of prediabetes-based random plasma glucose. Logistic regression was used to determine significant diagnostic variable and the receiver operating characteristic analysis was used to calculate area under the curve (AUC), cutoff point, sensitivity, specificity, and predictive values. RESULTS: Age, sex, education level, family history of diabetes, smoking habit, physical activity, body mass index, and hypertension were significant variables for Indonesian Prediabetes Risk Score (INA-PRISC). The scoring range from 0 to 24, the AUC was 0.623 (95% CI 0.616–0.631) and cutoff point of 12 yielded sensitivity/specificity (50.03%/67.19%, respectively). The validation study showed the AUC was 0.646 (95% CI 0.623–0.669) and cutoff point of 12 yielded sensitivity/specificity (55.11%/65.81%, respectively). CONCLUSION: INA-PRISC, which consists of eight demographical and clinical variables, is a valid and a simple prediabetes risk score in primary care. Akadémiai Kiadó 2017-06-15 2017-06 /pmc/articles/PMC5598131/ /pubmed/28932501 http://dx.doi.org/10.1556/1646.9.2017.2.18 Text en © 2017 The Author(s) http://creativecommons.org/licenses/by-nc/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium for non-commercial purposes, provided the original author and source are credited.
spellingShingle Original Paper
Fujiati, Isti Ilmiati
Damanik, Harun Alrasyid
Bachtiar, Adang
Nurdin, Andi Armyn
Ward, Paul
Development and validation of prediabetes risk score for predicting prediabetes among Indonesian adults in primary care: Cross-sectional diagnostic study
title Development and validation of prediabetes risk score for predicting prediabetes among Indonesian adults in primary care: Cross-sectional diagnostic study
title_full Development and validation of prediabetes risk score for predicting prediabetes among Indonesian adults in primary care: Cross-sectional diagnostic study
title_fullStr Development and validation of prediabetes risk score for predicting prediabetes among Indonesian adults in primary care: Cross-sectional diagnostic study
title_full_unstemmed Development and validation of prediabetes risk score for predicting prediabetes among Indonesian adults in primary care: Cross-sectional diagnostic study
title_short Development and validation of prediabetes risk score for predicting prediabetes among Indonesian adults in primary care: Cross-sectional diagnostic study
title_sort development and validation of prediabetes risk score for predicting prediabetes among indonesian adults in primary care: cross-sectional diagnostic study
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5598131/
https://www.ncbi.nlm.nih.gov/pubmed/28932501
http://dx.doi.org/10.1556/1646.9.2017.2.18
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