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Rethinking ME/CFS Diagnostic Reference Intervals via Machine Learning, and the Utility of Activin B for Defining Symptom Severity

Authors
  • lidbury, brett a.
  • kita, badia
  • richardson, alice m.
  • lewis, donald p.
  • privitera, edwina
  • hayward, susan
  • de kretser, david
  • hedger, mark
Publication Date
Jul 19, 2019
Source
MDPI
Keywords
Language
English
License
Green
External links

Abstract

62% when compared via weighted standing time (WST) severity classes. A closer analysis revealed that the inclusion of activin B to the panel of pathology markers improved the prediction of mild to moderate ME/CFS cases. Applying correct WST class prediction from RFA modelling, new reference intervals were calculated for activin B and associated pathology markers, where 24-h urinary creatinine clearance, serum urea and serum activin B showed the best potential as diagnostic markers. While the serum activin B results remained statistically significant for the new participant cohorts, activin B was found to also have utility in enhancing the prediction of symptom severity, as represented by WST class.

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