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Glycogen Storage Disease: Expert Opinion on Clinical Diagnosis Revisited after Molecular Testing.

Rafael de MarchiTatiele NalinFernanda Sperb-LudwigFranciele Cabral PinheiroIda Vanessa Doederlein SchwartzCarlos Eduardo Steiner
Published in: Genes (2023)
This study sought to analyze whether an accurate diagnosis of the type and subtype of hepatic Glycogen Storage Diseases (GSDs) could be performed based on general clinical and biochemical aspects via comparing the proposed diagnostic hypotheses with the molecular results. Twelve physicians with experience in hepatic GSDs reviewed 45 real cases comprising a standardized summary of clinical and laboratory data. There was no relation between the hit rate and the time since graduation, the time of experience in GSD, and the number of patients treated during their careers. The average assertiveness was 47%, with GSD Ia and Ib being the best-identified types, while no expert correctly identified GSD IXc. Underage investigation for later manifestations, incomplete clinical description, and complementary analysis, the overvaluation of a specific clinical finding ("false positive") or the discarding of the diagnosis in the absence of it ("false negative"), as well as the lack of knowledge of the rarest GSD types, may have impacted the accuracy of the assessment. This study emphasized that characteristics considered as determinants in identifying the specific types or subtypes of GSD are not exclusive, thus becoming factors that may have induced the evaluators to misdiagnose.
Keyphrases
  • healthcare
  • primary care
  • machine learning
  • big data
  • high resolution
  • endothelial cells
  • data analysis