Sleep Medicine Reviews
Volume 13, Issue 5 , Pages 333-343, October 2009

Understanding sleep-disordered breathing through mathematical modelling

  • Tero Aittokallio

      Affiliations

    • Biomathematics Research Group, Department of Mathematics, University of Turku, FI-20014 Turku, Finland
    • Sleep Research Unit, Department of Physiology, University of Turku, FI-20520 Turku, Finland
    • Corresponding Author InformationCorresponding author. Department of Mathematics, University of Turku, FI-20014 Turku, Finland. Tel.: +358 2 333 6030; fax: +358 2 333 6595.
  • ,
  • Arho Virkki

      Affiliations

    • Biomathematics Research Group, Department of Mathematics, University of Turku, FI-20014 Turku, Finland
    • Sleep Research Unit, Department of Physiology, University of Turku, FI-20520 Turku, Finland
  • ,
  • Olli Polo

      Affiliations

    • Sleep Research Unit, Department of Physiology, University of Turku, FI-20520 Turku, Finland
    • Department of Pulmonary Medicine, Tampere University Hospital, FI-33521 Tampere, Finland

Summary 

Recent studies have uncovered high prevalence of undiagnosed sleep-disordered breathing, and its linkage to metabolic or cardiovascular disorders which represent increasing health hazard. However, the mechanistic links behind these disorders as well as their contribution to the experimental observations and treatment responses remain poorly understood. Therefore, the screening of clinical measurements still relies upon relatively simple diagnostic features, such as signal averages or event frequencies, which may represent suboptimal or surrogate markers of the underlying abnormality. Consequently, most patients are being treated with general therapies regardless of the cause of their key dysfunction. Combining experimental measurements with mathematical modelling has the potential to provide mechanistic insights into the individual factors underlying the disease progression, which may finally enable tailored treatment alternatives for each patient. This review depicts a number of modelling approaches to elucidate sleep-related dysfunctions of the human respiratory system, and how these models are being used to translate the measurements first into new ideas and then into testable hypotheses. Such model-based investigations can provide systematic strategies towards better understanding, predicting or even preventing these dysfunctions. Along with the brief description of the modelling approaches, we discuss their relative merits and potential implications especially for clinical research.

Keywords: Sleep-disordered breathing, Obstructive sleep apnea, Flow limitation, Transcutaneous carbon dioxide, Non-invasive measurement, Mathematical modelling, Predictive modelling, Metabolic disorder, Vascular impairment

Abbreviations: AHI, apnea–hypopnea index, CO2, carbon dioxide, CPAP, continuous positive airway pressure, EtCO2, end-tidal partial pressure of CO2, HbA1c, glycosylated hemoglobin A1c, HDL-C, high-density lipoprotein cholesterol, IMT, carotid artery intima–media thickness, NMD, nitroglycerin-mediated dilatation, O2, oxygen, ODI, oxyhemoglobin desaturation index, OSAS, obstructive sleep apnea syndrome, PaCO2, arterial partial pressure of CO2, SaO2, oxyhemoglobin saturation, SDB, sleep-disordered breathing, TcCO2, transcutaneous partial pressure of CO2

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PII: S1087-0792(08)00110-X

doi:10.1016/j.smrv.2008.09.008

Sleep Medicine Reviews
Volume 13, Issue 5 , Pages 333-343, October 2009