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Cardiovascular risk prediction in type 2 diabetes: a comparison of 22 risk scores in primary care settings

AIMS/HYPOTHESIS: We aimed to compare the performance of risk prediction scores for CVD (i.e., coronary heart disease and stroke), and a broader definition of CVD including atrial fibrillation and heart failure (CVD+), in individuals with type 2 diabetes. METHODS: Scores were identified through a lit...

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Autores principales: Dziopa, Katarzyna, Asselbergs, Folkert W., Gratton, Jasmine, Chaturvedi, Nishi, Schmidt, Amand F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8894164/
https://www.ncbi.nlm.nih.gov/pubmed/35032176
http://dx.doi.org/10.1007/s00125-021-05640-y
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author Dziopa, Katarzyna
Asselbergs, Folkert W.
Gratton, Jasmine
Chaturvedi, Nishi
Schmidt, Amand F.
author_facet Dziopa, Katarzyna
Asselbergs, Folkert W.
Gratton, Jasmine
Chaturvedi, Nishi
Schmidt, Amand F.
author_sort Dziopa, Katarzyna
collection PubMed
description AIMS/HYPOTHESIS: We aimed to compare the performance of risk prediction scores for CVD (i.e., coronary heart disease and stroke), and a broader definition of CVD including atrial fibrillation and heart failure (CVD+), in individuals with type 2 diabetes. METHODS: Scores were identified through a literature review and were included irrespective of the type of predicted cardiovascular outcome or the inclusion of individuals with type 2 diabetes. Performance was assessed in a contemporary, representative sample of 168,871 UK-based individuals with type 2 diabetes (age ≥18 years without pre-existing CVD+). Missing observations were addressed using multiple imputation. RESULTS: We evaluated 22 scores: 13 derived in the general population and nine in individuals with type 2 diabetes. The Systemic Coronary Risk Evaluation (SCORE) CVD rule derived in the general population performed best for both CVD (C statistic 0.67 [95% CI 0.67, 0.67]) and CVD+ (C statistic 0.69 [95% CI 0.69, 0.70]). The C statistic of the remaining scores ranged from 0.62 to 0.67 for CVD, and from 0.64 to 0.69 for CVD+. Calibration slopes (1 indicates perfect calibration) ranged from 0.38 (95% CI 0.37, 0.39) to 0.74 (95% CI 0.72, 0.76) for CVD, and from 0.41 (95% CI 0.40, 0.42) to 0.88 (95% CI 0.86, 0.90) for CVD+. A simple recalibration process considerably improved the performance of the scores, with calibration slopes now ranging between 0.96 and 1.04 for CVD. Scores with more predictors did not outperform scores with fewer predictors: for CVD+, QRISK3 (19 variables) had a C statistic of 0.68 (95% CI 0.68, 0.69), compared with SCORE CVD (six variables) which had a C statistic of 0.69 (95% CI 0.69, 0.70). Scores specific to individuals with diabetes did not discriminate better than scores derived in the general population: the UK Prospective Diabetes Study (UKPDS) scores performed significantly worse than SCORE CVD (p value <0.001). CONCLUSIONS/INTERPRETATION: CVD risk prediction scores could not accurately identify individuals with type 2 diabetes who experienced a CVD event in the 10 years of follow-up. All 22 evaluated models had a comparable and modest discriminative ability. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains peer-reviewed but unedited supplementary material available at 10.1007/s00125-021-05640-y.
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spelling pubmed-88941642022-03-08 Cardiovascular risk prediction in type 2 diabetes: a comparison of 22 risk scores in primary care settings Dziopa, Katarzyna Asselbergs, Folkert W. Gratton, Jasmine Chaturvedi, Nishi Schmidt, Amand F. Diabetologia Article AIMS/HYPOTHESIS: We aimed to compare the performance of risk prediction scores for CVD (i.e., coronary heart disease and stroke), and a broader definition of CVD including atrial fibrillation and heart failure (CVD+), in individuals with type 2 diabetes. METHODS: Scores were identified through a literature review and were included irrespective of the type of predicted cardiovascular outcome or the inclusion of individuals with type 2 diabetes. Performance was assessed in a contemporary, representative sample of 168,871 UK-based individuals with type 2 diabetes (age ≥18 years without pre-existing CVD+). Missing observations were addressed using multiple imputation. RESULTS: We evaluated 22 scores: 13 derived in the general population and nine in individuals with type 2 diabetes. The Systemic Coronary Risk Evaluation (SCORE) CVD rule derived in the general population performed best for both CVD (C statistic 0.67 [95% CI 0.67, 0.67]) and CVD+ (C statistic 0.69 [95% CI 0.69, 0.70]). The C statistic of the remaining scores ranged from 0.62 to 0.67 for CVD, and from 0.64 to 0.69 for CVD+. Calibration slopes (1 indicates perfect calibration) ranged from 0.38 (95% CI 0.37, 0.39) to 0.74 (95% CI 0.72, 0.76) for CVD, and from 0.41 (95% CI 0.40, 0.42) to 0.88 (95% CI 0.86, 0.90) for CVD+. A simple recalibration process considerably improved the performance of the scores, with calibration slopes now ranging between 0.96 and 1.04 for CVD. Scores with more predictors did not outperform scores with fewer predictors: for CVD+, QRISK3 (19 variables) had a C statistic of 0.68 (95% CI 0.68, 0.69), compared with SCORE CVD (six variables) which had a C statistic of 0.69 (95% CI 0.69, 0.70). Scores specific to individuals with diabetes did not discriminate better than scores derived in the general population: the UK Prospective Diabetes Study (UKPDS) scores performed significantly worse than SCORE CVD (p value <0.001). CONCLUSIONS/INTERPRETATION: CVD risk prediction scores could not accurately identify individuals with type 2 diabetes who experienced a CVD event in the 10 years of follow-up. All 22 evaluated models had a comparable and modest discriminative ability. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains peer-reviewed but unedited supplementary material available at 10.1007/s00125-021-05640-y. Springer Berlin Heidelberg 2022-01-15 2022 /pmc/articles/PMC8894164/ /pubmed/35032176 http://dx.doi.org/10.1007/s00125-021-05640-y Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Dziopa, Katarzyna
Asselbergs, Folkert W.
Gratton, Jasmine
Chaturvedi, Nishi
Schmidt, Amand F.
Cardiovascular risk prediction in type 2 diabetes: a comparison of 22 risk scores in primary care settings
title Cardiovascular risk prediction in type 2 diabetes: a comparison of 22 risk scores in primary care settings
title_full Cardiovascular risk prediction in type 2 diabetes: a comparison of 22 risk scores in primary care settings
title_fullStr Cardiovascular risk prediction in type 2 diabetes: a comparison of 22 risk scores in primary care settings
title_full_unstemmed Cardiovascular risk prediction in type 2 diabetes: a comparison of 22 risk scores in primary care settings
title_short Cardiovascular risk prediction in type 2 diabetes: a comparison of 22 risk scores in primary care settings
title_sort cardiovascular risk prediction in type 2 diabetes: a comparison of 22 risk scores in primary care settings
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8894164/
https://www.ncbi.nlm.nih.gov/pubmed/35032176
http://dx.doi.org/10.1007/s00125-021-05640-y
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