Login / Signup

Algorithms for the Identification of Anthrax Meningitis During a Mass Casualty Event Based on a Systematic Review of Systemic Anthrax From 1880 Through 2018.

Sophie BinneyMarissa K PersonRita M TraxlerRachel CookWilliam A BowerKatherine Hendricks
Published in: Clinical infectious diseases : an official publication of the Infectious Diseases Society of America (2022)
Our study confirms prior research suggesting quick and reliable assessment of patients for anthrax meningitis is possible based on the presence or absence of certain symptoms and signs. A single algorithm was adequate; however, if we assumed low-resource diagnostic testing was feasible for some patients, pairing algorithms improved specificity. Pairing algorithms with differing symptoms and signs minimized the proportion of patients requiring additional diagnostics.
Keyphrases
  • end stage renal disease
  • machine learning
  • chronic kidney disease
  • ejection fraction
  • prognostic factors
  • deep learning
  • patient reported outcomes
  • patient reported