ADVERTISEMENT

Upcoming Website Maintenance Notification

On Sunday October 20th, 2019 from 5:00 am cst to 8:00 am cst there will be approximately 3 hours of scheduled downtime while we make upgrades to our servers. During this time-window the JCSM website will be unavailable. Thank you for your patience.

gears

Issue Navigator

Volume 15 No. 08
Earn CME
Accepted Papers





Commentary
Free

Diving Deeper: Rethinking AHI as the Primary Measure of OSA Severity

Christopher M. Cielo, DO, MS; Ignacio E. Tapia, MD, MS
Division of Pulmonary Medicine/Sleep Center, Children’s Hospital of Philadelphia, Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania

ABSTRACT

Citation:

Cielo CM, Tapia IE. Diving deeper: rethinking AHI as the primary measure of OSA severity. J Clin Sleep Med. 2019;15(8):1075–1076.


More than most diagnostic tools used in medicine, polysomnography includes a wealth of simultaneously-obtained physiologic data, including objective measures of sleep state and arousal, airflow, and gas exchange. For decades, the diagnosis and severity of obstructive sleep apnea (OSA) has been largely determined from the numeric calculation of the number of discreet obstructive and mixed apneas and hypopneas per hour of sleep.1 Clinically, the apnea-hypopnea index (AHI) provides cutpoints that can be used to establish the diagnosis and severity of OSA and evaluate treatment effect. In research, it allows for comparison across institutions and has been the primary outcome of innumerable trials in OSA research.2 One of the most common and debilitating symptoms of OSA in adults is excessive daytime sleepiness (EDS). Objectively, EDS can be evaluated by mean sleep latency on Multiple Sleep Latency Testing (MSLT). However, there is significant variability in the degree to which EDS relates to OSA severity as determined by AHI.3 Clinically, this provides challenges for clinicians who reduce the AHI through OSA treatment and researchers using AHI as an endpoint for therapy.

In the study by Kainulainen et al published in this issue of Journal of Clinical Sleep Medicine, the investigators assessed the correlation between EDS and novel polysomnographic parameters, including obstruction duration, desaturation duration, desaturation severity, and obstructive severity.4 Compared with AHI or oxygen desaturation index, the authors found a stronger correlation between EDS and these newer measures, which incorporate the severity of individual apneas, hypopneas, and desaturations. Specifically, increased desaturation severity, obstruction severity, and percent sleep time with saturation below 90% conferred a significantly greater risk of daytime sleepiness than AHI across the cohort of adults referred for sleep-disordered breathing and daytime sleepiness. While it is useful to have a single measure to assess OSA severity, the physiologic data acquired during polysomnography is underutilized by doing so. Importantly, the analysis used highly objective data, including full polysomnography and MSLT, in a large cohort of participants, allowing for analysis based on severity of both OSA (by AHI) and EDS (by mean sleep latency). Although novel, these measures could be scalable and used even with more limited evaluation like home sleep apnea testing.

Despite its weaknesses, AHI has been a robust endpoint in both the diagnosis and treatment of OSA across the spectrum of disease that is easily calculated by software available worldwide. In the current study, the investigators included only patients who reported sleepiness on presentation. How these novel measures apply to patients with OSA who do not present with sleepiness is unclear. Whether these novel measures are related to cardiovascular or other long-term consequences of OSA also largely remains to be seen. Mujara-Murro and colleagues have previously shown that in a cohort of men with untreated OSA, adjusting AHI for obstructive event severity corelated better with mortality than conventional AHI.5 However, these measures need to be replicated in more diverse cohorts. Patients with OSA who present with EDS may be especially important to target, as they may be at significantly increased risk for worse cardiovascular outcomes.6 In patients with OSA, sleepiness may also be associated with inflammation and could be a marker of other comorbidities.7 If used as an outcome measure in patients with OSA who present with sleepiness, the change in these novel parameters following OSA treatment must be assessed prospectively. Interestingly, the correlations between these novel measures and sleepiness were stronger in younger patients, but overall the cohort was fairly old and male. Future studies including more patients who are young, female, and racially and ethnically diverse are needed.

Sleepiness is highly variable as a presenting symptom of OSA. Multinational studies of adults with moderate to severe OSA have identified multiple clinical subtypes, including some that present with excessive sleepiness.8 In children, the relationship between OSA severity and EDS is even less clear, as many younger children are more likely to present with irritability and hyperactivity.9 In patients with OSA, sleepiness may be related to a number of factors, including chronotype, sleep duration, and race. Similarly, the response to treatment is highly variable, with a substantial portion of adults still having EDS despite achieving a normal AHI with continuous positive airway pressure.10 As polysomnography software packages become more sophisticated and we move to more individualized approach to the management of OSA in patients with a variety of phenotypes, we should consider using newer metrics like those proposed in this study to offer more personalized approaches to the evaluation and treatment of OSA in both adults and children.

DISCLOSURE STATEMENT

Both authors have reviewed and approved the manuscript. Funding sources: NIH K23 HL135346 (NHLBI) and Parker B. Francis fellowship: Dr. Cielo; NIH K01 HL130719, R01 HL120909 Dr. Tapia. The authors report no conflicts of interest.

REFERENCES

1 

Berry RB, Albertario CL, Harding SM, et al; for the American Academy of Sleep Medicine. The AASM Manual for the Scoring of Sleep and Associated Events: Rules, Terminology, and Technical Specifications. Version 2.5. Darien, IL: American Academy of Sleep Medicine; 2018.

2 

Sleep-related breathing disorders in adults: recommendations for syndrome definition and measurement techniques in clinical research. The report of an American Academy of Sleep Medicine Task Force. Sleep. 1999;22(5):667–689. [PubMed]

3 

Roure N, Gomez S, Mediano O, et al. Daytime sleepiness and polysomnography in obstructive sleep apnea patients. Sleep Med. 2008;9(7):727–731. [PubMed]

4 

Kainulainen S, Töyräs J, Oksenberg A, et al. Severity of desaturations reflects OSA related daytime sleepiness better than AHI. J Clin Sleep Med. 2019;15(8):1135–1142

5 

Muraja-Murro A, Kulkas A, Hiltunen M, et al. Adjustment of apnea-hypopnea index with severity of obstruction events enhances detection of sleep apnea patients with the highest risk of severe health consequences. Sleep Breath. 2014;18(3):641–647. [PubMed]

6 

Mazzotti DR, Keenan BT, Lim DC, Gottlieb DJ, Kim J, Pack AI. Symptom subtypes of obstructive sleep apnea predict incidence of cardiovascular outcomes. Am J Respir Crit Care Med. 2019;Feb 15. [Epub ahead of print].

7 

Li Y, Vgontzas AN, Fernandez-Mendoza J, et al. Objective, but not subjective, sleepiness is associated with inflammation in sleep apnea. Sleep. 2017;40(2)

8 

Keenan BT, Kim J, Singh B, et al. Recognizable clinical subtypes of obstructive sleep apnea across international sleep centers: a cluster analysis. Sleep. 2018;41(3)

9 

Marcus CL, Brooks LJ, Draper KA, et al. Diagnosis and management of childhood obstructive sleep apnea syndrome. Pediatrics. 2012;130(3):e714–e755. [PubMed]

10 

Pepin JL, Viot-Blanc V, Escourrou P, et al. Prevalence of residual excessive sleepiness in CPAP-treated sleep apnoea patients: the French multicentre study. Eur Respir J. 2009;33(5):1062–1067. [PubMed]