Predicting adverse cardiac events using DEVI and CARPREG-I score in pregnant with valvular heart disease: External validation study from MPAC registry.

Abstract

Background: While numerous risk assessment tools exist for pregnant women with valvular heart disease (VHD), validation studies assessing their performance in diverse settings are few. Such validation is crucial before applying these tools routinely in clinical practice.

Objectives: To validate and establish the clinical utility of two risk stratification tools - DEVI (VHD-specific tool) and CARPREG-I in predicting adverse cardiac events in pregnant women with VHD.

Methods: This cohort study involved consecutive pregnancies complicated with VHD enrolled in the prospective Medical College Pregnancy and Cardiac (MPAC) registry from July 2016 to December 2019. Individual risk for adverse composite cardiac events was calculated using DEVI and CARPREG-I models. Performance was assessed through discrimination and calibration characteristics. Clinical utility was evaluated with decision curve analysis.

Results: Of the 1029 pregnancies, 609 had VHD. Mitral regurgitation (67.2 %; 409/609) was most common; 11.5 % (70/609) experienced at least one component of the composite outcome. The area under the receiver operating characteristic curve was 0.747, with 95 % confidence intervals (CI) (0.685-0.809) for DEVI and 0.705 (95%CI 0.646-0.765) for CARPREG-I models. Calibration plots suggested that the DEVI score overestimates risk at higher probabilities, while the CARPREG-I score underestimates risk at most probabilities. Decision curve analysis demonstrated that both models were useful across predicted probability thresholds between 10 % and 60 %.

Conclusion: In this external validation study in pregnant women with VHD, both DEVI and CARPREG-I scores showed good discriminative ability and clinical utility across various probabilities. However, both models need recalibration to improve the agreement between the predicted and observed events.