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Detection and Diagnosis of Cardiac Amyloidosis in Egypt
Mohamed Abdelghany1, Magdy Abdelhamid1, Adel Allam2
1Department of Cardiology, Faculty of Medicine, Cairo University, Cairo, Egypt.
Abstract:
Cardiac amyloidosis is a life-threatening disease that occurs when amyloid proteins, most commonly immunoglobulin light chain or transthyretin, mutate or become unstable, misfold, deposit as amyloid fibrils, and accumulate in the myocardium. Early diagnosis of cardiac amyloidosis is hindered by insufficient awareness, specifically regarding clinical red flags and diagnostic pathways. Cardiac amyloidosis diagnosis comprises two important phases, clinical suspicion (phase one) followed by definitive diagnosis (phase two). Each phase is associated with specific clinical techniques. For example, clinical features, electrocardiography, echocardiography, and cardiac magnetic resonance imaging serve to raise suspicion of cardiac amyloidosis and facilitate early diagnosis, whereas laboratory tests (i.e., blood or urine electrophoresis with immunofixation), biopsy, scintigraphy-based nuclear imaging, and genetic testing provide a definitive diagnosis of cardiac amyloidosis. In Egypt, both the lack of cardiac amyloidosis awareness amongst healthcare providers and the unavailability of clinical expertise for the use of diagnostic techniques must be overcome to improve the prognosis of cardiac amyloidosis in the region. Previously published diagnostic algorithms for cardiac amyloidosis have amalgamated techniques that can raise clinical suspicions of cardiac amyloidosis with those that definitively diagnose cardiac amyloidosis. Though such algorithms have been successful in developed countries, diagnostic tools like echocardiography, scintigraphy, and cardiac magnetic resonance imaging are not ubiquitously available across Egyptian facilities. This review presents the current state of knowledge regarding cardiac amyloidosis in Egypt and outlines a new diagnostic algorithm which leverages regional nuclear imaging expertise. Importantly, the proposed diagnostic algorithm guides accurate amyloid-typing to mitigate misdiagnosis and erroneous treatment selection and improve the cardiac amyloidosis diagnostic accuracy in Egypt.
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