Sleep · 2018
Estimation of adaptive ventilation success and failure using polysomnogram and outpatient therapy biomarkers.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Gunn Stacey, Naik Sreelatha, Bianchi Matt Travis, Thomas Robert Joseph
Аннотация
STUDY OBJECTIVES: Adaptive servo-ventilation (ASV) devices provide anticyclic pressure support for the treatment of central and/or complex sleep apnea, including heart failure patients. Variability in responses in the clinic and negative clinical trials motivated assessment of standard and novel signal biomarkers for ASV efficacy.
METHODS: Multiple clinical databases were queried to assess potential signal biomarkers of ASV effectiveness, including the following: (1) attended laboratory adaptive ventilation titrations: 108, of which 66 had mainstream ETCO2 measurements; (2) AirView data in 98 participants, (3) complete data, from diagnostic polysomnogram (PSG) through review and prospective analysis of on-therapy data using SleepyHead freeware in 44 participants; and (4) hemodynamic data in the form of beat-to-beat blood pressure during ASV titration, using a Finometer in five participants.
RESULTS: Signal biomarkers of reduced ASV efficacy were noted as follows: (1) an arousal index which markedly exceeded the respiratory event index during positive pressure titration; (2) persistent pressure cycling during long-term ASV therapy, visible in online review systems or reviewing data using freeware; (3) the ASV-associated pressure cycling induced arousals, sleep fragmentation, and blood pressure surges; and (4) elevated ratios of 95th percentile to median tidal volume, minute ventilation, and respiratory rate were associated with pressure cycling. High intraclass coefficients (>0.8) for machine apnea-hypopnea index and other extractable metrics were consistent with stability of patterns over multiple nights of use. Global clinical outcomes correlated negatively with pressure cycling.
CONCLUSIONS: Potential polysomnographic- and device-related signal biomarkers of ASV efficacy are described and may allow improved estimation of therapeutic effectiveness of adaptive ventilation.
METHODS: Multiple clinical databases were queried to assess potential signal biomarkers of ASV effectiveness, including the following: (1) attended laboratory adaptive ventilation titrations: 108, of which 66 had mainstream ETCO2 measurements; (2) AirView data in 98 participants, (3) complete data, from diagnostic polysomnogram (PSG) through review and prospective analysis of on-therapy data using SleepyHead freeware in 44 participants; and (4) hemodynamic data in the form of beat-to-beat blood pressure during ASV titration, using a Finometer in five participants.
RESULTS: Signal biomarkers of reduced ASV efficacy were noted as follows: (1) an arousal index which markedly exceeded the respiratory event index during positive pressure titration; (2) persistent pressure cycling during long-term ASV therapy, visible in online review systems or reviewing data using freeware; (3) the ASV-associated pressure cycling induced arousals, sleep fragmentation, and blood pressure surges; and (4) elevated ratios of 95th percentile to median tidal volume, minute ventilation, and respiratory rate were associated with pressure cycling. High intraclass coefficients (>0.8) for machine apnea-hypopnea index and other extractable metrics were consistent with stability of patterns over multiple nights of use. Global clinical outcomes correlated negatively with pressure cycling.
CONCLUSIONS: Potential polysomnographic- and device-related signal biomarkers of ASV efficacy are described and may allow improved estimation of therapeutic effectiveness of adaptive ventilation.