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Prediction model for high glycated hemoglobin concentration among ethnic Chinese in Taiwan

BACKGROUND: This study aimed to construct a prediction model to identify subjects with high glycated hemoglobin (HbA1c) levels by incorporating anthropometric, lifestyle, clinical, and biochemical information in a large cross-sectional ethnic Chinese population in Taiwan from a health checkup center...

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Autores principales: Chien, Kuo-Liong, Lin, Hung-Ju, Lee, Bai-Chin, Hsu, Hsiu-Ching, Chen, Ming-Fong
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2955643/
https://www.ncbi.nlm.nih.gov/pubmed/20875098
http://dx.doi.org/10.1186/1475-2840-9-59
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author Chien, Kuo-Liong
Lin, Hung-Ju
Lee, Bai-Chin
Hsu, Hsiu-Ching
Chen, Ming-Fong
author_facet Chien, Kuo-Liong
Lin, Hung-Ju
Lee, Bai-Chin
Hsu, Hsiu-Ching
Chen, Ming-Fong
author_sort Chien, Kuo-Liong
collection PubMed
description BACKGROUND: This study aimed to construct a prediction model to identify subjects with high glycated hemoglobin (HbA1c) levels by incorporating anthropometric, lifestyle, clinical, and biochemical information in a large cross-sectional ethnic Chinese population in Taiwan from a health checkup center. METHODS: The prediction model was derived from multivariate logistic regression, and we evaluated the performance of the model in identifying the cases with high HbA1c levels (> = 7.0%). In total 17,773 participants (age > = 30 years) were recruited and 323 participants (1.8%) had high HbA1c levels. The study population was divided randomly into two parts, with 80% as the derivation data and 20% as the validation data. RESULTS: The point-based clinical model, including age (maximal 8 points), sex (1 point), family history (3 points), body mass index (2 points), waist circumference (4 points), and systolic blood pressure (3 points) reached an area under the receiver operating characteristic curve (AUC) of 0.723 (95% confidence interval, 0.677- 0.769) in the validation data. Adding biochemical measures such as triglycerides and HDL cholesterol improved the prediction power (AUC, 0.770 [0.723 - 0.817], P = < 0.001 compared with the clinical model). A cutoff point of 7 had a sensitivity of 0.76 to 0.96 and a specificity of 0.39 to 0.63 for the prediction model. CONCLUSIONS: A prediction model was constructed for the prevalent risk of high HbA1c, which could be useful in identifying high risk subjects for diabetes among ethnic Chinese in Taiwan.
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spelling pubmed-29556432010-10-16 Prediction model for high glycated hemoglobin concentration among ethnic Chinese in Taiwan Chien, Kuo-Liong Lin, Hung-Ju Lee, Bai-Chin Hsu, Hsiu-Ching Chen, Ming-Fong Cardiovasc Diabetol Original Investigation BACKGROUND: This study aimed to construct a prediction model to identify subjects with high glycated hemoglobin (HbA1c) levels by incorporating anthropometric, lifestyle, clinical, and biochemical information in a large cross-sectional ethnic Chinese population in Taiwan from a health checkup center. METHODS: The prediction model was derived from multivariate logistic regression, and we evaluated the performance of the model in identifying the cases with high HbA1c levels (> = 7.0%). In total 17,773 participants (age > = 30 years) were recruited and 323 participants (1.8%) had high HbA1c levels. The study population was divided randomly into two parts, with 80% as the derivation data and 20% as the validation data. RESULTS: The point-based clinical model, including age (maximal 8 points), sex (1 point), family history (3 points), body mass index (2 points), waist circumference (4 points), and systolic blood pressure (3 points) reached an area under the receiver operating characteristic curve (AUC) of 0.723 (95% confidence interval, 0.677- 0.769) in the validation data. Adding biochemical measures such as triglycerides and HDL cholesterol improved the prediction power (AUC, 0.770 [0.723 - 0.817], P = < 0.001 compared with the clinical model). A cutoff point of 7 had a sensitivity of 0.76 to 0.96 and a specificity of 0.39 to 0.63 for the prediction model. CONCLUSIONS: A prediction model was constructed for the prevalent risk of high HbA1c, which could be useful in identifying high risk subjects for diabetes among ethnic Chinese in Taiwan. BioMed Central 2010-09-27 /pmc/articles/PMC2955643/ /pubmed/20875098 http://dx.doi.org/10.1186/1475-2840-9-59 Text en Copyright ©2010 Chien et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Investigation
Chien, Kuo-Liong
Lin, Hung-Ju
Lee, Bai-Chin
Hsu, Hsiu-Ching
Chen, Ming-Fong
Prediction model for high glycated hemoglobin concentration among ethnic Chinese in Taiwan
title Prediction model for high glycated hemoglobin concentration among ethnic Chinese in Taiwan
title_full Prediction model for high glycated hemoglobin concentration among ethnic Chinese in Taiwan
title_fullStr Prediction model for high glycated hemoglobin concentration among ethnic Chinese in Taiwan
title_full_unstemmed Prediction model for high glycated hemoglobin concentration among ethnic Chinese in Taiwan
title_short Prediction model for high glycated hemoglobin concentration among ethnic Chinese in Taiwan
title_sort prediction model for high glycated hemoglobin concentration among ethnic chinese in taiwan
topic Original Investigation
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2955643/
https://www.ncbi.nlm.nih.gov/pubmed/20875098
http://dx.doi.org/10.1186/1475-2840-9-59
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