A prediction model of echocardiographic variables to screen for potentially correctable shunts in adult ASD-PAH patients.

Background: Atrial septal defect (ASD) is a prevalent congenital heart condition in adults that leads to pulmonary hypertension (PAH) and right heart failure if left untreated. During a routine follow-up of adult ASD-PAH patients, the suitability of shunt closure depends on the invasive right heart catheterization (RHC).Nevertheless, performing RHC at every follow-up is impractical and may be harmful. The present retrospective cross-sectional study was designed to investigate which echocardiographic variables are related to pulmonary vascular resistance (PVR) in adult ASD-PAH patients and proposed a model using these variables to screen for patients with a correctable shunt.

Methods: A total of 530 adult ASD-PAH patients with pulmonary arterial systolic pressure (PASP) of ≥60 mmHg measured using transthoracic echocardiogram (TTE) were included in the study. All RHCs were performed within 3 months after TTE. The correctable shunt was defined as PVR ≤3 wood units (WU). Multivariate regressions were performed utilizing echocardiographic variables. A scoring system was constructed based on the predictors of PVR ≤3 WU using multivariate logistic regression analysis. The scoring system was then examined using a receiver operating characteristic (ROC) analysis. In addition, clinical utility of the model was determined based on decision curve analysis and a calibration curve was used to evaluate model conformity.

Results: Estimated pulmonary arterial systolic pressure, velocity through the pulmonary valve, tricuspid annulus early diastolic velocity, and maximum defect dimension were identified as independent predictors. The area under the ROC curve of the predictive value in the model was 0.905 [95% confidence interval (CI): 0.878-0.931, sensitivity: 84.3%, specificity: 83.6%]. The net benefit of the model was notable in terms of a wide-range probability threshold in decision curve analysis, indicating that the prediction model had good clinical applicability. The model's calibration curve was close to an ideal diagonal line, showing good predictive accuracy between the actual and predictive probabilities.

Conclusion: The study model was demonstrated to be valuable in predicting adult ASD-PAH patients with a correctable shunt, which may help clinicians to make appropriate treatment decision for follow-up patients.