Existing cardiovascular risk prediction tools primarily assess traditional risk factors and fail to incorporate pregnancy-related indicators to adequately capture long-term risk in women with a history of gestational diabetes.
Do existing cardiovascular risk assessment tools adequately capture the long-term cardiovascular risk in women with a history of gestational diabetes?
Existing cardiovascular risk prediction tools frequently used in women with a history of gestational diabetes do not incorporate pregnancy-related indicators, highlighting the need for adapted risk models for this population.
Gestational Diabetes Mellitus (GDM) is a glucose intolerance diagnosed during pregnancy and is associated with an increased risk of developing cardiovascular disease (CVD) later in life. Despite this well-established link, it remains unclear how effectively existing CVD risk assessment tools account for the unique risks faced by women with a history of GDM. This scoping review aims to systematically explore the literature to examine how CVD risk prediction tools have been applied to this population and whether they adequately capture their long-term risk. A comprehensive search was conducted across multiple databases, including Medline (via Ovid), Embase (via Ovid), Scopus, PubMed, PsycINFO, CINAHL, along with grey literature from Google Scholar. The overall search was conducted from the database’s inception date to January 28, 2026. A total of 508 studies underwent title and abstract screening, with 18 selected for full-text data extraction. Three reviewers independently screened studies and extracted data, ensuring consistency and reliability. A PRISMA flow diagram was used to illustrate the study selection process. Among the identified CVD risk prediction tools, the Framingham risk score (FRS) 10-year estimator was one of the most frequently applied in 7 (38.9%) of the included studies. This was followed by the ASCVD-Pooled Cohort risk equations (ASCVD-PCE) risk calculator and Framingham-30 years risk lipid-based calculator with 5 (27.8%) and 4 (22.2%). Despite their widespread use, these tools primarily assess traditional cardiovascular risk factors and do not incorporate pregnancy-related indicators, which are significant predictors of future CVD risk in women with a history of GDM. This scoping review underscores the need for the development or adaptation of risk prediction models that specifically address the long-term cardiovascular risk profile of this population.
Wonde et al. (Fri,) conducted a review in Gestational Diabetes Mellitus (n=3,099,466). Cardiovascular risk assessment tools (e.g., Framingham risk score, ASCVD-PCE) was evaluated on Application and type of CVD risk prediction tools used. Existing cardiovascular risk prediction tools primarily assess traditional risk factors and fail to incorporate pregnancy-related indicators to adequately capture long-term risk in women with a history of gestational diabetes.