Development and validation of a smartphone based app to guide the differential diagnosis in patients with primary left ventricular hypertrophy: the Thick Heart App

Abstract 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 712 patients with definitive diagnosis of sarcomeric HCM or one of its genocopies (414 (58%) males, 48±24 years) referred to four tertiary centers in Europe. Pre-specified RF were categorized into five domains: family history; signs/symptoms; electrocardiography, echocardiographic and laboratory. Each patient’s characteristics were inserted by two independent and blind investigators on the App of the digital support tool. The possible diagnostic outcome was categorized as follows: (a) most likely diagnosis (age range for the condition, at least 1 extremely specific RFs or >1 specific RF; (b) possible diagnosis (age range, 1 specific RF); (c) less likely diagnosis (outside age range, no RF selected). Results Ris were common in patients presenting with a genotyped HCM (2568 RFs, 3.5 per patient). RF on physical examination was associated with non sarcomeric aetiology (318/319 physical examination RF identified in non-sarcomeric HCM), whereas 68% of RF associated with sarcomeric HCM were derived from accurate ECG and echocardiography analysis. Sarcomeric HCM, TTR-amyloidosis, Danon and PRKAG2 cardiomyopathy relied extensively on ECG and echocardiographic systematic analyisis (68%, 69%, 67% and 69% respectively). In contrast, AFD, Friederich’s ataxia, Noonan syndrome with multiple lentiges (NSML), mitochondrial, Pompe and Noonan cardiomyopathy presented red flags potentially identifiable in the general practioner setting by anamnesis, physical examination and routine laboratory (57%, 59%, 52%, 57%, 57% and 58% respectively) in the vast majority of case. A total of 697/712 (97.8%) 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 validation of an App based 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.