Comparison of apnoea-hypopnoea index and oxygen desaturation index when identifying obstructive sleep apnoea using type-4 sleep studies

Chamara V Senaratna; Adrian Lowe; Jennifer L Perret; Caroline Lodge; Gayan Bowatte; Michael J Abramson; Bruce R Thompson; Garun Hamilton; Shyamali C Dharmage

doi:10.1111/jsr.12804

Comparison of apnoea-hypopnoea index and oxygen desaturation index when identifying obstructive sleep apnoea using type-4 sleep studies

J Sleep Res. 2019 Oct;28(5):e12804. doi: 10.1111/jsr.12804. Epub 2018 Dec 18.

Authors

Chamara V Senaratna^{1

2}, Adrian Lowe¹, Jennifer L Perret^{1

3}, Caroline Lodge¹, Gayan Bowatte¹, Michael J Abramson⁴, Bruce R Thompson⁵, Garun Hamilton^{6

7}, Shyamali C Dharmage¹

Affiliations

¹ Allergy & Lung Health, Melbourne School of Population & Global Health, The University of Melbourne, Melbourne, Australia.
² University of Sri Jayewardenepura, Nugegoda, Sri Lanka.
³ Institute for Breathing and Sleep (IBAS), Heidelberg/Melbourne, Australia.
⁴ School of Public Health & Preventive Medicine, Monash University, Melbourne, Australia.
⁵ Department of Respiratory Medicine, Alfred Health, Central Clinical School, Monash University, Melbourne, Australia.
⁶ School of Clinical Sciences, Monash University, Clayton, Australia.
⁷ Department of Lung and Sleep, Monash Health, Clayton, Australia.

PMID: 30565351
DOI: 10.1111/jsr.12804

Abstract

The concordance of different indices from type-4 sleep studies in diagnosing and categorising the severity of obstructive sleep apnoea is not known. This is a critical gap as type-4 sleep studies are used to diagnose obstructive sleep apnoea in some settings. Therefore, we aimed to determine the concordance between flow-based apnoea-hypopnoea index (AHI_flow50% ) and oxygen desaturation index (ODI_3% ) by measuring them concurrently. Using a random sub-sample of 296 from a population-based cohort who underwent two-channel type-4 sleep studies, we assessed the concordance between AHI_flow50% and ODI_3% . We compared the prevalence of obstructive sleep apnoea of various severities as identified by the two methods, and determined their concordance using coefficient Kappa(κ). Participants were aged (mean ± SD) 53 ± 0.9 years (48% male). The body mass index was 28.8 ± 5.2 kg m^-2 and neck circumference was 37.4 ± 3.9 cm. The median AHI_flow50% was 5 (inter-quartile range 2, 10) and median ODI_3% was 9 (inter-quartile range 4, 15). The obstructive sleep apnoea prevalence reported using AHI_flow50% was significantly lower than that reported using ODI_3% at all severity thresholds. Although 90% of those with moderate-severe obstructive sleep apnoea classified using AHI_flow50% were identified by using ODI_3% , only 46% of those with moderate-severe obstructive sleep apnoea classified using ODI_3% were identified by AHI_flow50% . The overall concordance between AHI_flow50% and ODI_3% in diagnosing and classifying the severity of obstructive sleep apnoea was only fair (κ = 0.32), better for males (κ = 0.42 [95% confidence interval 0.32-0.57] versus 0.22 [95% confidence interval 0.09-0.31]), and lowest for those with a body mass index ≥ 35 (κ = 0.11). In conclusion, ODI_3% and AHI_flow50% from type-4 sleep studies are at least moderately discordant. Until further evidence is available, the use of ODI_3% as the measure of choice for type-4 sleep studies is recommended cautiously.

Keywords: agreement; home sleep studies; home sleep-testing; oxygen desaturation index; portable.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Female
Humans
Male
Middle Aged
Oxygen / metabolism*
Oxygen Consumption / physiology*
Polysomnography / methods*
Sleep Apnea, Obstructive / diagnosis*
Sleep Apnea, Obstructive / physiopathology
Sleep Stages / physiology*

Substances

Oxygen