Assessment of potential transthyretin amyloid cardiomyopathy cases in the Brazilian public health system using a machine learning model.

OBJECTIVES: To identify and describe the profile of potential transthyretin cardiac amyloidosis (ATTR-CM) cases in the Brazilian public health system (SUS), using a predictive machine learning (ML) model. METHODS: This was a retrospective descriptive database study that aimed to estimate the frequency of potential ATTR-CM cases in the Brazilian public health system using a supervised ML model, from January 2015 to December 2021. To build the model, a list of ICD-10 codes and procedures potentially related with ATTR-CM was created based on literature review and validated by experts. RESULTS: From 2015 to 2021, the ML model classified 262 hereditary ATTR-CM (hATTR-CM) and 1,581 wild-type ATTR-CM (wtATTR-CM) potential cases. Overall, the median age of hATTR-CM and wtATTR-CM patients was 66.8 and 59.9 years, respectively. The ICD-10 codes most presented as hATTR-CM and wtATTR-CM were related to heart failure and arrythmias. Regarding the therapeutic itinerary, 13% and 5% of hATTR-CM and wtATTR-CM received treatment with tafamidis meglumine, respectively, while 0% and 29% of hATTR-CM and wtATTR-CM were referred to heart transplant. CONCLUSION: Our findings may be useful to support the development of health guidelines and policies to improve diagnosis, treatment, and to cover unmet medical needs of patients with ATTR-CM in Brazil.

Electrocardiography scar quantification correlates with scar size of hypertrophic cardiomyopathy seen by multidetector computed tomography.

BACKGROUND: Hypertrophic cardiomyopathy (HCM), a genetically transmitted disease, is the most common genetic cardiovascular disease. Current strategies to stratify risk are expensive and concentrated in wealthy centers. Twelve-lead electrocardiography (ECG) is inexpensive, universally available, and can be readily used for Selvester QRS scoring, which estimates scar size. This study aimed to establish the relation between ECG scar quantification and myocardial fibrosis (extent of myocardial delayed enhancement) in multidetector computed tomography (MDCT). HYPOTHESIS: There is a significant association between ECG scar quantification and the extent of myocardial delayed enhancement in MDCT. METHODS: Seventy-five patients with HCM underwent a routine clinical evaluation and echocardiography, 12-lead ECG, and MDCT study. Patients with and without an implantable cardioverter-defibrillator were included. RESULTS: The estimated Selvester QRS score of myocardial fibrosis was correlated significantly (R = 0.70; P < 0.01) with the quantified MDCT fibrosis. Compared with MDCT, the QRS score had 84.8% sensitivity and 88.8% specificity. Myocardial fibrosis was present in 88% of these patients with HCM (fibrotic mass, 9.87 ±10.8 g) comprising 5.66% ±6.16% of the total myocardial mass seen on the MDCT images. The Selvester QRS score reliably predicted the fibrotic mass in 76% of patients, which estimated 8.44% ±7.39% of the total myocardial mass. CONCLUSIONS: The Selvester QRS score provides reliable quantification of myocardial fibrosis and was well correlated with MDCT in patients with HCM.