BACKGROUND: Continuous positive airway pressure (CPAP) is considered the treatment of choice for obstructive sleep apnea (OSA), and studies have shown that there is a correlation between patient adherence and treatment outcomes. Newer CPAP machines can track adherence, hours of use, mask leak, and residual apnea-hypopnea index (AHI). Such data provide a strong platform to examine OSA outcomes in a chronic disease management model. However, there are no standards for capturing CPAP adherence data, scoring flow signals, or measuring mask leak, or for how clinicians should use these data. METHODS: American Thoracic Society (ATS) committee members were invited, based on their expertise in OSA and CPAP monitoring. Their conclusions were based on both empirical evidence identified by a comprehensive literature review and clinical experience. RESULTS: CPAP usage can be reliably determined from CPAP tracking systems, but the residual events (apnea/hypopnea) and leak data are not as easy to interpret as CPAP usage and the definitions of these parameters differ among CPAP manufacturers. Nonetheless, ends of the spectrum (very high or low values for residual events or mask leak) appear to be clinically meaningful. CONCLUSIONS: Providers need to understand how to interpret CPAP adherence tracking data. CPAP tracking systems are able to reliably track CPAP adherence. Nomenclature on the CPAP adherence tracking reports needs to be standardized between manufacturers and AHIFlow should be used to describe residual events. Studies should be performed examining the usefulness of the CPAP tracking systems and how these systems affect OSA outcomes.
BACKGROUND: Continuous positive airway pressure (CPAP) is considered the treatment of choice for obstructive sleep apnea (OSA), and studies have shown that there is a correlation between patient adherence and treatment outcomes. Newer CPAP machines can track adherence, hours of use, mask leak, and residual apnea-hypopnea index (AHI). Such data provide a strong platform to examine OSA outcomes in a chronic disease management model. However, there are no standards for capturing CPAP adherence data, scoring flow signals, or measuring mask leak, or for how clinicians should use these data. METHODS: American Thoracic Society (ATS) committee members were invited, based on their expertise in OSA and CPAP monitoring. Their conclusions were based on both empirical evidence identified by a comprehensive literature review and clinical experience. RESULTS: CPAP usage can be reliably determined from CPAP tracking systems, but the residual events (apnea/hypopnea) and leak data are not as easy to interpret as CPAP usage and the definitions of these parameters differ among CPAP manufacturers. Nonetheless, ends of the spectrum (very high or low values for residual events or mask leak) appear to be clinically meaningful. CONCLUSIONS: Providers need to understand how to interpret CPAP adherence tracking data. CPAP tracking systems are able to reliably track CPAP adherence. Nomenclature on the CPAP adherence tracking reports needs to be standardized between manufacturers and AHIFlow should be used to describe residual events. Studies should be performed examining the usefulness of the CPAP tracking systems and how these systems affect OSA outcomes.
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