Why the study?
Cardiovascular risk varies widely in diabetes mellitus, challenging the approach of treating it simply as a CVD equivalent and necessitating an evaluation of CVD risk scores.
What is the evidence and clinical utility of cardiovascular disease risk models and scores in patients with diabetes mellitus?
What is the evidence and clinical utility of cardiovascular disease risk models and scores in patients with diabetes mellitus?
Current cardiovascular risk models for patients with diabetes mellitus lack adequate external validation and often exhibit moderate discrimination and poor calibration, highlighting the need for further research before universal clinical application.
DM as CVD equivalent guides preventive strategies; leaves open whether refined noninvasive scores improve outcomes in contemporary cohorts.
Diabetes mellitus (DM) is an established risk factor for atherosclerotic cardiovascular disease (CVD), and patients with DM are at a two to four-fold higher cardiovascular risk, including myocardial infraction, unstable angina, stroke, and heart failure. All of the above have arisen interest in CVD preventive strategies by the use of non-invasive methods, such as risk scores. The most common approach is to consider DM as a CVD equivalent and, therefore, to treat patients with DM in a similar way to those who required secondary CVD prevention. However, this approach has been disputed as all patients with DM do not have the same risk for CVD, and since other potentially important factors within the context of DM, such as DM duration, presence of albuminuria, and comorbidities, should be taken into consideration. Thus, the second and third approach is the application of risk models that were either developed initially for the general population or designed specifically for patients with DM, respectively. This review summarizes the evidence and implications for clinical practice regarding these scores. Up to date, several models that can be applied to the diabetic population have been proposed. However, only a few meet the minimum requirement of adequate external validation. In addition, moderate discrimination and poor calibration, which might lead to inaccurate risk estimations in populations with different characteristics, have been reported. Therefore, future research is needed before recommending a specific risk model for universal clinical practice in the management of diabetes.
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Kostopoulos et al. (2020) studied this question.
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