An improved echocardiographic rejection-surveillance strategy following pediatric heart transplantation

Background: The unique demands of cardiac transplantation in infancy have led to non-invasive rejection-surveillance strategies. ECHO-A is a multiparametric, two-dimensionally guided, M-mode analysis algorithm that assigns an empirically derived score for deviations of recipient parameters to age-adjusted, population-based normal values. A cumulative ECHO-A score ≥4 is highly predictive of endomyocardial biopsy Grade ≥3 and of cellular rejection. Methods: This study determined whether modifying ECHO-A to score for deviations of recipient parameters from the recipient's baseline would improve the predictive power of ECHO-A. We reanalyzed 701 consecutive echocardiograms of 18 pediatric cardiac transplant recipients (median age at transplantation, 142 days) and based scoring on significant (Z score ≥1) deviation from the patients' baseline means (ECHO-B). Results: Eight episodes of treated rejection occurred during the first year after transplantation (median, 1.4 years). Approximately 10% (72) of the analyses had ECHO-A scores ≥4 that were not associated with treated rejection and were considered false positives. We identified parameters that contributed to the false-positive evaluations and calculated patient-specific baseline mean ± standard deviation. The ECHO-B, in comparison with ECHO-A, decreased the number of false positives from 72 to 10, increased specificity from 90% to 99%, and increased the positive predictive value about 4-fold (10% to 44%). With treated rejection episodes, ECHO-B increased ECHO-A scores in 7 of 8 recipients and increased the mean score from 6 to 8. Conclusions: An analysis algorithm based on change from baseline improved the positive predictive power without reducing the negative predictive value of multiparametric quantitative analyses of echocardiograms following pediatric heart transplantation. Copyright (C) 2000 International Society for Heart and Lung Transplantation.