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Diagnostic errors in uncommon conditions: a systematic review of case reports of diagnostic errors.

Yukinori HaradaTakashi WatariHiroyuki NaganoTomoharu SuzukiKotaro KunitomoChristine E MacBrayneTetsuro AitaKosuke IshizukaMika MaebashiTaku HaradaTetsu SakamotoShusaku TomiyamaTaro Shimizu
Published in: Diagnosis (Berlin, Germany) (2023)
Excluding three cases in that commonality could not be classified, 560 cases were classified into four categories: typical presentations of common diseases (60, 10.7 %), atypical presentations of common diseases (35, 6.2 %), typical presentations of uncommon diseases (276, 49.3 %), and atypical presentations of uncommon diseases (189, 33.8 %). The most important DEER taxonomy was "Failure/delay in considering the diagnosis" among the four categories, whereas the most important RDC and GDP taxonomies varied with the categories. Case reports can be a useful data source for research on the diagnostic errors of uncommon diseases with or without atypical presentations.
Keyphrases
  • patient safety
  • adverse drug
  • machine learning
  • drug induced