A score including age, diastolic dysfunction ≥ grade II, apical sparing, and interventricular septum thickness diagnosed ATTR-CA with 91% sensitivity and 83% specificity.
Does a clinical and echocardiographic prediction model accurately diagnose ATTR-CA?
A simple diagnostic score using age and three echocardiographic parameters (diastolic dysfunction, apical sparing, septum thickness) provides excellent accuracy for identifying ATTR-CA.
Tasa de eventos absoluta: 0% vs 0%
Abstract Background Cardiac amyloidosis by transthyretin (ATTR-CA) presents diagnostic challenges despite advanced diagnostic modalities. Identifying primary diagnostic predictors using accessible tools like electrocardiogram (ECG) and transthoracic echocardiography (TTE) is essential for early recognition. Purpose This study aimed to assess primary electrocardiographic and echocardiographic diagnostic predictors of ATTR-CA through a prediction model. Methods Data from the REACT-SP registry, involving patients diagnosed with ATTR CA. Electrocardiographic and echocardiographic parameters were evaluated, and statistical analyses were conducted to identify predictive variables associated with ATTR-CA diagnosis. Binary regression analysis, both univariate and multivariate. ROC curve analysis and Youden index were realized. A p 0.05 was considered statistically significant for all analyses. After regression analysis the final model for the score was: -7.5 + (age x 0.03) + (diastolic dysfunction x 1.33) + (apical sparing x 1.5) + (septum x 0.4). Results 755 patients were included, with male predominance and a median age of 65 years. Low voltage and pseudoinfarction pattern were common ECG changes, while apical sparing and specific echocardiographic parameters were noted. Multivariate analysis identified age OR 1.031 (1.008-1.053); p = 0.007, interventricular septum (IVS) thickness OR 1.449 (1.273-1.650); p 0.001, presence of apical sparing OR 4.450 (2.302-8.602), p 0.001, and diastolic dysfunction (DD) ≥ grade II OR 3.801 (1.979-7.299); p 0.001 as significant predictors of ATTR-CA diagnosis. The area under the curve of the new score for diagnosis of amyloidosis was 0.940 (0.933-0.946), p = 0.001 with a sensitivity of 91% and specificity of 83% when the resultant value of the Youden index analysis was -0.0513. Conclusions This study validates ECG and TTE changes as key predictors of ATTR-CA diagnosis in a large, multicenter sample. Echocardiographic parameters like presence of apical sparing, DD grade ≥II and IVS thickness demonstrated good predictive power. Regarding other parameters only age was found like a diagnostic predictor. The proposed scoring model had excellent performance for the diagnosis of ATTR-CA.Baseline characteristics
Morales et al. (Sat,) reported a other. A score including age, diastolic dysfunction ≥ grade II, apical sparing, and interventricular septum thickness diagnosed ATTR-CA with 91% sensitivity and 83% specificity.