Development and validation of a smartphone based app to support the differential diagnosis in patients with primary left ventricular hypertrophy

INTRODUCTION: Patients presenting with primary Left Ventricular Hypertrophy (LVH) suffers from a diagnostic delay quantified in years. They are often misdiagnosed because of both physician-related and disease-related reasons including fragmented knowledge among different specialties and rarity of the conditions. PURPOSE: We developed and validate a free digital support tool in the form of an App to provide support and to guide the physician in the differential diagnostic process of patients presenting with primary LVH. METHODS: We studied 210 consecutively genotyped patients (54±21 years, 118 (56% males) referred to our center for the suspicion of primary LVH. A systematic literature analysis was conducted to classify disease specific red-flags (RFs) associated with sarcomeric and non sarcomeric hypertrophic cardiomyopathy (HCM). RFs were categorized into two subgroups: extremely specific RFs (features only described associated to the given disease) and specific RF (characteristics typical for the disease but also associated with other conditions). Pre-specified RF were categorized into four domains: family history; signs/symptoms; electrocardiography and imaging. The outcome of the digital support tool was categorized as follows: (a) most likely diagnosis (if contemplated age range for the condition, at least 1 extremely specific RFs or more than 1 specific RF were satisfied); (b) possible diagnosis (if contemplated age range for the condition, 1 specific RF were satisfied); (c) less likely diagnosis (outside age range for disease and no RF selected). RESULTS: Of the 210 patients, 84 (40%) were diagnosed with sarcomeric HCM, 56 (27%) with TTR amyloidosis, 44 (21%) with Fabry disease (FD), 7 (4%) with a mitochondrial disease, 4 (2%) with Pompe disease, 4 (2%) with PRKAG2 cardiomyopathy, 3 (1%) with Noonan, 3 (1%) with Friederich's Ataxia, 3 (1%) with LEOPARD and 2 (1%) with Danon disease. A total of 942 RFs has been identified in the cohort, of which 327 were extremely specific RFs (41 from family history; 107 from signs/symptoms; 111 from electrocardiography and 113 from imaging sections). Non-sarcomeric causes of HCM were the most prevalent in ages <1yo and >55yo. One-hundred-ninety-five patients (92%) were correctly categorized in the most likely and possible diagnosis section. The App proved to be sensible for sarcomeric HCM, FD (0.99 and 0.91, NPV 0.98 and 0.83) and extremely capable in the identification of rare causes of LVH (Danon, Friederich's ataxia, LEOPARD, Pompe, Noonan and PRKAG2 diseases). By design, specificity was not high, in particular for sarcomeric HCM and FD. CONCLUSIONS: The present free digital support tool in the form of an App proved to be extremely sensible in providing the support to the screening of different causes of primary LVH in patients presenting with a HCM phenotype. Further external and multicenter validation is warranted. FUNDING ACKNOWLEDGEMENT: Type of funding sources: Private company. Main funding source(s): Amicus therapeutics