Abstract

Abstract BACKGROUND Sleep hypoventilation complicates a range of neurological and respiratory conditions. However, robust definitions are based mainly on expert consensus, and clinically significant thresholds remain unclear. This study thus aims to provide a descriptive analysis of capnography results in a large clinical cohort of patients referred for overnight polysomnography (PSG). METHODS Retrospective clinical audit of overnight in-lab PSGs, between Jan 2015 and June 2023, at a tertiary hospital housing the State-wide referral centre for chronic domiciliary ventilation. Diagnostic PSGs with transcutaneous CO2 (PTcCO2) monitoring and without supplemental oxygen were included. The following data will be extracted from each PSG: Patient demographics: -Primary and secondary clinical diagnoses -PTcCO2 values (e.g. Mean, Minimum and Maximum PTcCO2 in Wake, Sleep, NREM and REM) -Sleep fragmentation measures -Sleep macro-architecture measures -AHI -SpO2 values Data analysis will be performed with IBM SPSS Statistics software, version 26 (Armonk, NY: IBM Corp) PROGRESS TO DATE 525 PSGs meeting initial criteria have been identified. Currently processing PSG data files to extract parameters and complete exploratory data cleaning and analysis. INTENDED OUTCOME AND IMPACT We aim to explore and clarify: -Differences in patterns of hypoventilation between different diagnostic groups. -Relationships between awake hypoventilation, sleep hypoventilation and REM-isolated hypoventilation. -Effects of applying differing criteria for hypoventilation available in the literature. -Relationships between measures of sleep fragmentation, AHI, SpO2 and hypoventilation parameters. The results of this study will also support and inform future research into associations between severity, duration and patterns of hypoventilation and clinically significant outcomes including morbidity and mortality.

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