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Abstract Background Early diagnosis is of substantial benefit for patients with Pompe disease. Yet underdiagnosing and substantial diagnostic delay are still frequent and the determinants of this are unknown. This study is the first to systematically investigate the diagnostic odyssey in Pompe disease from patients', parents', and physicians' perspectives. Methods Patients with infantile or late onset Pompe disease, their parents as well as their metabolic experts were invited to fill in respective surveys. The survey addressed perceived disease symptoms at onset and during the course of the disease, specialties of involved physicians, activities of patient‐initiated search for diagnosis and the perceived impact of time to diagnosis on outcome. Results of experts' and patients'/parents' surveys were compared and expressed by descriptive statistics. Results and Discussion We collected data on 15 males and 17 females including 9 infantile and 23 late onset Pompe patients. All received the correct diagnosis at a metabolic or musculoskeletal expert center. Patients with direct referral to the expert center had the lowest diagnostic delay, while patients who were seen by several physicians, received the correct diagnosis after 44%‐200% longer delay. The proportion of direct referral varied strongly between pediatricians (57%) and other disciplines (18%‐36%). Conclusion Our study highlights a substantially larger diagnostic delay in Pompe patients that are not directly referred to expert centers for diagnostic work. Our findings may be used to develop more successful strategies for early diagnosis. Synopsis Diagnostic delay in Pompe disease is substantial particularly in patients that are not directly referred to expert centers for diagnostic workup, so facilitating direct referral may be a new strategy for early diagnosis.

Abstract Introduction: The interest in Expert systems has increased in the medical area. Some of them are employed even for diagnosis. With the variability of transcatheter prostheses, the most appropriate choice can be complex. This scenario reveals an enabling environment for the use of an Expert system. The goal of the study was to develop an Expert system based on artificial intelligence for supporting the transcatheter aortic prosthesis selection. Methods: The system was developed on Expert SINTA. The rules were created according to anatomical parameters indicated by the manufacturing company. Annular aortic diameter, aortic area, aortic perimeter, ascending aorta diameter and Valsalva sinus diameter were considered. After performing system accuracy tests, it was applied in a retrospective cohort of 22 patients with submitted to the CoreValve prosthesis implantation. Then, the system indications were compared to the real heart team decisions. Results: For 10 (45.4%) of the 22 patients there was no concordance between the Expert system and the heart team. In all cases with discordance, the software was right in the indication. Then, the patients were stratified in two groups (same indication vs. divergent indication). The baseline characteristics did not show any significant difference. Mortality, stroke, acute myocardial infarction, atrial fibrillation, atrioventricular block, aortic regurgitation and prosthesis leak did not present differences. Therefore, the maximum aortic gradient in the post-procedure period was higher in the Divergent Indication group (23.9 mmHg vs. 11.9 mmHg, P=0.03), and the mean aortic gradient showed a similar trend. Conclusion: The utilization of the Expert system was accurate, showing good potential in the support of medical decision. Patients with divergent indication presented high post-procedure aortic gradients and, even without clinical repercussion, these parameters, when elevated, can lead to early prosthesis dysfunction and the necessity of reoperation.