The value of pregnancy-related factors in the prediction of cardiovascular disease: a systematic review

Abstract

Aims

Pregnancy-related factors are associated with an increased risk of cardiovascular disease (CVD) and may help identify women at high cardiovascular risk. This study aims to provide an overview of prediction models for CVD which included pregnancy-related factors and to evaluate the impact of these factors on model performance.

Methods

PubMed and Embase were systematically searched until March 2023 for studies reporting on the development or validation of prediction models for CVD which included pregnancy-related factors. Data extraction was performed using the CHARMS checklist. Risk of bias was assessed using PROBAST.

Results

Seven studies were included. C-indices ranged between 0.63 and 0.79. Adding pregnancy-related factors resulted in improved C-index in four studies, ranging from 0.0033 (95 % confidence interval [CI]: 0.0022–0.0051) to 0.004 (95 % CI: 0.002–0.006). Net reclassification improvement (NRI) for events was improved in two studies, ranging from 0.01 (95 % CI: 0.003–0.02) to 0.038 (95 % CI: 0.003–0.074). NRI for non-events was improved in three studies, ranging from 0.002 (95 % CI: 0.0001–0.005) to 0.02 (95 % CI: 0.001–0.04). Two studies showed both low risk of bias and low concern regarding applicability. Subgroup analyses by age in three studies indicated larger improvements in model performance in younger women.

Conclusion

Addition of pregnancy-related factors results in limited improvements in performance of CVD prediction models, with relatively larger improvements in younger women.