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Predictive scores for identifying patients with type 2 diabetes mellitus at risk of acute myocardial infarction and sudden cardiac death

Lee, S; Zhou, J; Guo, CL; Wong, WT; Liu, T; Wong, ICK; Jeevaratnam, K; ... Tse, G; + view all (2021) Predictive scores for identifying patients with type 2 diabetes mellitus at risk of acute myocardial infarction and sudden cardiac death. Endocrinology, Diabetes & Metabolism , Article e00240. 10.1002/edm2.240. (In press). Green open access

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Abstract

Introduction: The present study evaluated the application of incorporating non‐linear J/U‐shaped relationships between mean HbA1c and cholesterol levels into risk scores for predicting acute myocardial infarction (AMI) and non‐AMI‐related sudden cardiac death (SCD) respectively, amongst patients with type 2 diabetes mellitus. / Methods: This was a territory‐wide cohort study of patients with type 2 diabetes mellitus above the age 40 and free from prior AMI and SCD, with or without prescriptions of anti‐diabetic agents between January 1st, 2009 to December 31st, 2009 at government‐funded hospitals and clinics in Hong Kong. Patients recruited were followed up until 31 December 2019 or their date of death. Risk scores were developed for predicting incident AMI and non‐AMI‐related SCD. The performance of conditional inference survival forest (CISF) model compared to that of random survival forests (RSF) model and multivariate Cox model. / Results: This study included 261 308 patients (age = 66.0 ± 11.8 years old, male = 47.6%, follow‐up duration = 3552 ± 1201 days, diabetes duration = 4.77 ± 2.29 years). Mean HbA1c and low high‐density lipoprotein‐cholesterol (HDL‐C) were significant predictors of AMI on multivariate Cox regression. Mean HbA1c was linearly associated with AMI, whilst HDL‐C was inversely associated with AMI. Mean HbA1c and total cholesterol were significant multivariate predictors with a J‐shaped relationship with non‐AMI‐related SCD. The AMI and SCD risk scores had an area under the curve (AUC) of 0.666 (95% confidence interval (CI) = [0.662, 0.669]) and 0.677 (95% CI = [0.673, 0.682]), respectively. CISF significantly improves prediction performance of both outcomes compared to RSF and multivariate Cox models. / Conclusion: A holistic combination of demographic, clinical and laboratory indices can be used for the risk stratification of patients with type 2 diabetes mellitus for AMI and SCD.

Type: Article
Title: Predictive scores for identifying patients with type 2 diabetes mellitus at risk of acute myocardial infarction and sudden cardiac death
Open access status: An open access version is available from UCL Discovery
DOI: 10.1002/edm2.240
Publisher version: https://doi.org/10.1002/edm2.240
Language: English
Additional information: Copyright © 2021 The Authors. Endocrinology, Diabetes & Metabolism published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > UCL School of Pharmacy
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > UCL School of Pharmacy > Practice and Policy
URI: https://discovery.ucl.ac.uk/id/eprint/10123260
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