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Man versus machine? Acquired long QT syndrome in a patient with anorexia nervosa.

Tomio TranMichael BrunnquellPhilip S MehlerMori J Krantz
Published in: Annals of noninvasive electrocardiology : the official journal of the International Society for Holter and Noninvasive Electrocardiology, Inc (2019)
Computer-generated Bazett-corrected QT (QTcB) algorithms are common in clinical practice and can rapidly identify repolarization abnormalities, but accuracy is variable. This report highlights marked rate-corrected QT (QTc) interval prolongation not detected by the computer algorithm. A 26-year-old woman with anorexia nervosa was admitted with severe hypokalemia and ventricular ectopy. Computer-generated QTcB was 485 ms, while manual adjudication yielded a QTcB of 657 ms and a Fridericia-corrected QT (QTcF) interval of 626 ms using digital calipers. Computer-generated QTc intervals may aid in clinical decision-making. However, accuracy is variable, particularly in the setting of ectopy, and requires manual verification.
Keyphrases
  • anorexia nervosa
  • deep learning
  • drug induced
  • mass spectrometry
  • multiple sclerosis
  • ms ms
  • machine learning
  • clinical practice
  • decision making
  • case report
  • heart failure
  • left ventricular
  • early onset
  • atrial fibrillation