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Asthma Detection Research Based on Voice Signal Processing and Machine Learning
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Asthma diagnosis: into the fourth dimension.

Ran Wang1,2, Clare S Murray1,2, Stephen J Fowler1,2

  • 1Division of Infection, Immunity and Respiratory Medicine, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.

Thorax
|January 28, 2021
PubMed
Summary
This summary is machine-generated.

Asthma diagnosis is challenging due to its variability. Considering circadian rhythms and time of day in diagnostic tests can improve accuracy for this common respiratory condition.

Keywords:
asthmaasthma guidelines

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Area of Science:

  • Respiratory Medicine
  • Chronobiology
  • Diagnostic Accuracy

Background:

  • Asthma is a prevalent chronic respiratory disease in the UK with significant misdiagnosis rates.
  • Inconsistent national guidelines and limited data on diagnostic algorithms complicate accurate asthma diagnosis.
  • Asthma exhibits significant diurnal, day-to-day, and seasonal variability, impacting clinical presentation and pathogenesis.

Purpose of the Study:

  • To review the biological mechanisms of circadian rhythms in asthma.
  • To highlight the importance of time, or the 'fourth dimension,' in asthma diagnosis.
  • To address the challenges posed by asthma's inherent variability to diagnostic accuracy.

Main Methods:

  • Review of biological mechanisms underlying circadian rhythms in asthma.
  • Analysis of existing asthma diagnostic tools and their performance considering diurnal variation.
  • Discussion of novel strategies and the role of home monitoring and digital apps.

Main Results:

  • Established asthma diagnostic tools show diurnal variation, but standardized timing is often lacking.
  • Fixed cut-off values for diagnostic tests may reduce accuracy due to diurnal variability.
  • The impact of testing during asymptomatic periods on diagnostic sensitivity remains unclear.

Conclusions:

  • Circadian variability is a critical, yet often overlooked, factor in asthma diagnosis.
  • Standardization of diagnostic processes must incorporate consideration of circadian rhythms.
  • Novel approaches are needed to integrate temporal dynamics into asthma diagnostic strategies for improved accuracy.