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Predicting Changes in Cardiovascular Risk Factors in Type 2 Diabetes in the Post-UKPDS Era: Longitudinal Analysis of the Swedish National Diabetes Register

The aim of the current study was to provide updated time-path equations for risk factors of type-2-diabetes-related cardiovascular complications for application in risk calculators and health economic models. Observational data from the Swedish National Diabetes Register were analysed using Generali...

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Autores principales: Ahmad Kiadaliri, Aliasghar, Clarke, Philip M., Gerdtham, Ulf-G., Nilsson, Peter, Eliasson, Björn, Gudbjörnsdottir, Soffia, Steen Carlsson, Katarina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3647571/
https://www.ncbi.nlm.nih.gov/pubmed/23671860
http://dx.doi.org/10.1155/2013/241347
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author Ahmad Kiadaliri, Aliasghar
Clarke, Philip M.
Gerdtham, Ulf-G.
Nilsson, Peter
Eliasson, Björn
Gudbjörnsdottir, Soffia
Steen Carlsson, Katarina
author_facet Ahmad Kiadaliri, Aliasghar
Clarke, Philip M.
Gerdtham, Ulf-G.
Nilsson, Peter
Eliasson, Björn
Gudbjörnsdottir, Soffia
Steen Carlsson, Katarina
author_sort Ahmad Kiadaliri, Aliasghar
collection PubMed
description The aim of the current study was to provide updated time-path equations for risk factors of type-2-diabetes-related cardiovascular complications for application in risk calculators and health economic models. Observational data from the Swedish National Diabetes Register were analysed using Generalized Method of Moments estimation for dynamic panel models (N = 5,043, aged 25–70 years at diagnosis in 2001–2004). Validation was performed using persons diagnosed in 2005 (n = 414). Results were compared with the UKPDS outcome model. The value of the risk factor in the previous year was the main predictor of the current value of the risk factor. People with high (low) values of risk factor in the year of diagnosis experienced a decreasing (increasing) trend over time. BMI was associated with elevations in all risk factors, while older age at diagnosis and being female generally corresponded to lower levels of risk factors. Updated time-path equations predicted risk factors more precisely than UKPDS outcome model equations in a Swedish population. Findings indicate new time paths for cardiovascular risk factors in the post-UKPDS era. The validation analysis confirmed the importance of updating the equations as new data become available; otherwise, the results of health economic analyses may be biased.
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spelling pubmed-36475712013-05-13 Predicting Changes in Cardiovascular Risk Factors in Type 2 Diabetes in the Post-UKPDS Era: Longitudinal Analysis of the Swedish National Diabetes Register Ahmad Kiadaliri, Aliasghar Clarke, Philip M. Gerdtham, Ulf-G. Nilsson, Peter Eliasson, Björn Gudbjörnsdottir, Soffia Steen Carlsson, Katarina J Diabetes Res Research Article The aim of the current study was to provide updated time-path equations for risk factors of type-2-diabetes-related cardiovascular complications for application in risk calculators and health economic models. Observational data from the Swedish National Diabetes Register were analysed using Generalized Method of Moments estimation for dynamic panel models (N = 5,043, aged 25–70 years at diagnosis in 2001–2004). Validation was performed using persons diagnosed in 2005 (n = 414). Results were compared with the UKPDS outcome model. The value of the risk factor in the previous year was the main predictor of the current value of the risk factor. People with high (low) values of risk factor in the year of diagnosis experienced a decreasing (increasing) trend over time. BMI was associated with elevations in all risk factors, while older age at diagnosis and being female generally corresponded to lower levels of risk factors. Updated time-path equations predicted risk factors more precisely than UKPDS outcome model equations in a Swedish population. Findings indicate new time paths for cardiovascular risk factors in the post-UKPDS era. The validation analysis confirmed the importance of updating the equations as new data become available; otherwise, the results of health economic analyses may be biased. Hindawi Publishing Corporation 2013 2013-02-28 /pmc/articles/PMC3647571/ /pubmed/23671860 http://dx.doi.org/10.1155/2013/241347 Text en Copyright © 2013 Aliasghar Ahmad Kiadaliri et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Ahmad Kiadaliri, Aliasghar
Clarke, Philip M.
Gerdtham, Ulf-G.
Nilsson, Peter
Eliasson, Björn
Gudbjörnsdottir, Soffia
Steen Carlsson, Katarina
Predicting Changes in Cardiovascular Risk Factors in Type 2 Diabetes in the Post-UKPDS Era: Longitudinal Analysis of the Swedish National Diabetes Register
title Predicting Changes in Cardiovascular Risk Factors in Type 2 Diabetes in the Post-UKPDS Era: Longitudinal Analysis of the Swedish National Diabetes Register
title_full Predicting Changes in Cardiovascular Risk Factors in Type 2 Diabetes in the Post-UKPDS Era: Longitudinal Analysis of the Swedish National Diabetes Register
title_fullStr Predicting Changes in Cardiovascular Risk Factors in Type 2 Diabetes in the Post-UKPDS Era: Longitudinal Analysis of the Swedish National Diabetes Register
title_full_unstemmed Predicting Changes in Cardiovascular Risk Factors in Type 2 Diabetes in the Post-UKPDS Era: Longitudinal Analysis of the Swedish National Diabetes Register
title_short Predicting Changes in Cardiovascular Risk Factors in Type 2 Diabetes in the Post-UKPDS Era: Longitudinal Analysis of the Swedish National Diabetes Register
title_sort predicting changes in cardiovascular risk factors in type 2 diabetes in the post-ukpds era: longitudinal analysis of the swedish national diabetes register
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3647571/
https://www.ncbi.nlm.nih.gov/pubmed/23671860
http://dx.doi.org/10.1155/2013/241347
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