ArticleJournal of the Chinese Medical Association : JCMA2025
A prediction model of echocardiographic variables to screen for potentially correctable shunts in adult atrial septal defect-pulmonary hypertension patients.
Article in Journal of the Chinese Medical Association : JCMA, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundAtrial 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 were associated with pulmonary vascular resistance (PVR) in adult ASD-PAH patients and propose a model using these variables to screen for patients with a correctable shunt.
methodsA 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). Multivariable regressions were performed utilizing echocardiographic variables. A scoring system was constructed based on the predictors of PVR ≤3 WU using multivariable 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.
resultsEstimated PASP, 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% 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.
conclusionThe study provided a valuable model in predicting adult ASD-PAH patients with a correctable shunt, which may help clinicians to make appropriate treatment decision for follow-up patients.
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