Predictors of Fabry disease in patients with hypertrophic cardiomyopathy: How to guide the diagnostic strategy?

Azevedo, Olga; Marques, Nuno; Reis, Liliana; Cruz, Inês; Craveiro, N; Antunes, Hugo; Lourenço, Carolina; Gomes, Renata; Guerreiro, Rui Azevedo; Faria, Ricardo; Sá, Fernando Montenegro; Lima, Rui; Gaspar, Paulo; Faria, Rui P. V.; Miltenberger-Miltényi, Gábriel; Sousa, Nuno; Cunha, Damião

doi:10.1016/j.ahj.2020.04.006

Cited by 9 publications

(14 citation statements)

References 45 publications

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“…Hypertrophic cardiomyopathy (HCM) is the main cardiac manifestation of FD [ 25 ]. FD has been diagnosed in 0.9% of the patients with HCM [ 29 , 30 ] and, being a treatable disease, it should be systematically ruled out in all patients with HCM, either by targeted FD screening or by a wider HCM gene panel including the GLA gene [ 29 ]. Basal inferolateral LGE and bifascicular block were identified as the most powerful predictors of FD in patients with HCM; therefore, in their presence, a targeted FD screening should be performed, while in their absence, an HCM gene panel would be the most appropriate next step in the etiological study of HCM [ 29 ].…”

Section: Cardiac Manifestations Of Fdmentioning

confidence: 99%

“…Some of these mutations are very common and, despite their widespread distribution around the world, they occur in large clusters in specific geographical areas, such as the IVS4+919G>A mutation in Taiwan, the p.N215S mutation in the United Kingdom, and the p.F113L mutation in the Portuguese region of Guimarães. Indeed, a founder effect has already been documented for the IVS4+919G>A mutation in Southern China [ 162 ] and the p.F113L mutation in the Portuguese region of Guimarães [ 4 , 29 ].…”

Section: Late-onset Phenotypes With Predominant Cardiac Involvement (“Cardiac Variants”)mentioning

confidence: 99%

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Fabry Disease and the Heart: A Comprehensive Review

Azevedo

Cordeiro

Gago

et al. 2021

IJMS

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Fabry disease (FD) is an X-linked lysosomal storage disorder caused by mutations of the GLA gene that result in a deficiency of the enzymatic activity of α-galactosidase A and consequent accumulation of glycosphingolipids in body fluids and lysosomes of the cells throughout the body. GB3 accumulation occurs in virtually all cardiac cells (cardiomyocytes, conduction system cells, fibroblasts, and endothelial and smooth muscle vascular cells), ultimately leading to ventricular hypertrophy and fibrosis, heart failure, valve disease, angina, dysrhythmias, cardiac conduction abnormalities, and sudden death. Despite available therapies and supportive treatment, cardiac involvement carries a major prognostic impact, representing the main cause of death in FD. In the last years, knowledge has substantially evolved on the pathophysiological mechanisms leading to cardiac damage, the natural history of cardiac manifestations, the late-onset phenotypes with predominant cardiac involvement, the early markers of cardiac damage, the role of multimodality cardiac imaging on the diagnosis, management and follow-up of Fabry patients, and the cardiac efficacy of available therapies. Herein, we provide a comprehensive and integrated review on the cardiac involvement of FD, at the pathophysiological, anatomopathological, laboratory, imaging, and clinical levels, as well as on the diagnosis and management of cardiac manifestations, their supportive treatment, and the cardiac efficacy of specific therapies, such as enzyme replacement therapy and migalastat.

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Section: Cardiac Manifestations Of Fdmentioning

confidence: 99%

Section: Late-onset Phenotypes With Predominant Cardiac Involvement (“Cardiac Variants”)mentioning

confidence: 99%

Fabry Disease and the Heart: A Comprehensive Review

Azevedo

Cordeiro

Gago

et al. 2021

IJMS

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“…Согласно Azevedo O, et al, гипертрофия миокарда с наличием бифасцикулярной блокады на ХМЭКГ и участками контрастирования в отсроченную фазу на МРТ в базальном сегменте нижнебоковой стенки ЛЖ являются характерными признаками БФ, а их отсутствие позволяет исключить у пациента данный диагноз с точностью 95,8% [23].…”

Section: мнение по проблемеunclassified

Red flags to diagnose infiltrative cardiomyopathies

et al. 2023

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Infiltrative cardiomyopathies are a group of diseases characterized by the deposition of abnormal substances in heart tissues, which leads to thickening of the walls or dilation of chambers with a secondary decrease in wall thickness and the development of diastolic, less often systolic, ventricular dysfunction. Most often, these are progressive diseases that, in the absence of adequate therapy, have an unfavorable prognosis. Clinical manifestations of infiltrative cardiac diseases are variable, which often leads to diagnostic difficulties and errors. In most cases, specific laboratory and morphological tests are required to confirm or clarify the diagnosis. Early diagnosis is critical to initiating therapy and improving patient prognosis. This article provides characteristic signs and symptoms, the so-called "red flags", making it possible to suspect infiltrative cardiomyopathies, diagnose them at an early stage and start life-saving therapy.

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“…As abnormal loading conditions, such as hypertension and valvular disease are also quite common, the distinction between LVH that is sufficiently explained by these conditions and ULVH requires further investigation (3,4). Early detection of ULVH is essential to initiate targeted treatment, for instance in AFD and cardiac amyloidosis, for risk stratification of sarcomeric ULVH and for family screening (3,(5)(6)(7)(8)(9)(10)(11). As AFD and cardiac amyloidosis are rare and therefore difficult to detect, the imperative to recognize them largely depends on availability of specific therapeutic workflows (11,17,20).…”

Section: Unexplained Lvhmentioning

confidence: 99%

“…ULVH is an important cause of sudden cardiac death and is caused by autosomal dominant genetic mutations in genes encoding proteins of the cardiac sarcomere in 40-60% of patients (5)(6)(7). Some ULVH cases are explained by a variety of rare, genetic, and non-genetic etiologies that may produce isolated or syndromic LVH, such as cardiac amyloidosis in an estimated 5-10% and Anderson-Fabry's Disease (AFD) in 0.5-1% of cases (3,(8)(9)(10)(11). These specific etiologies are also referred to as phenocopies.…”

Section: Introductionmentioning

confidence: 99%

Automatic Identification of Patients With Unexplained Left Ventricular Hypertrophy in Electronic Health Record Data to Improve Targeted Treatment and Family Screening

Sammani

Jansen

Vries

et al. 2022

Front. Cardiovasc. Med.

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BackgroundUnexplained Left Ventricular Hypertrophy (ULVH) may be caused by genetic and non-genetic etiologies (e.g., sarcomere variants, cardiac amyloid, or Anderson-Fabry's disease). Identification of ULVH patients allows for early targeted treatment and family screening.AimTo automatically identify patients with ULVH in electronic health record (EHR) data using two computer methods: text-mining and machine learning (ML).MethodsAdults with echocardiographic measurement of interventricular septum thickness (IVSt) were included. A text-mining algorithm was developed to identify patients with ULVH. An ML algorithm including a variety of clinical, ECG and echocardiographic data was trained and tested in an 80/20% split. Clinical diagnosis of ULVH was considered the gold standard. Misclassifications were reviewed by an experienced cardiologist. Sensitivity, specificity, positive, and negative likelihood ratios (LHR+ and LHR–) of both text-mining and ML were reported.ResultsIn total, 26,954 subjects (median age 61 years, 55% male) were included. ULVH was diagnosed in 204/26,954 (0.8%) patients, of which 56 had amyloidosis and two Anderson-Fabry Disease. Text-mining flagged 8,192 patients with possible ULVH, of whom 159 were true positives (sensitivity, specificity, LHR+, and LHR– of 0.78, 0.67, 2.36, and 0.33). Machine learning resulted in a sensitivity, specificity, LHR+, and LHR– of 0.32, 0.99, 32, and 0.68, respectively. Pivotal variables included IVSt, systolic blood pressure, and age.ConclusionsAutomatic identification of patients with ULVH is possible with both Text-mining and ML. Text-mining may be a comprehensive scaffold but can be less specific than machine learning. Deployment of either method depends on existing infrastructures and clinical applications.

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Predictors of Fabry disease in patients with hypertrophic cardiomyopathy: How to guide the diagnostic strategy?

Cited by 9 publications

References 45 publications

Fabry Disease and the Heart: A Comprehensive Review

Fabry Disease and the Heart: A Comprehensive Review

Red flags to diagnose infiltrative cardiomyopathies

Automatic Identification of Patients With Unexplained Left Ventricular Hypertrophy in Electronic Health Record Data to Improve Targeted Treatment and Family Screening

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