Guide to Understanding Hypoxic Burden

Guide to Understanding Hypoxic Burden

What is Hypoxic Burden?

Hypoxic Burden (HB) is an alternative way to assess sleep apnea (Figure 1). It aims to better understand how much a patient is affected by their sleep apnea, and predict their risk for comorbid health issues and mortality [1]. HB takes into consideration:

  • The frequency of respiratory-related desaturation under a set SPO2 threshold, usually 88% or 90%, when desaturations are scored at 3% or 4% from baseline.  
  • The depth of the desaturation (how low they go).  
  • The duration of the desaturation (how long they last).

Figure 1: Example of hypoxic burden calculation for an individual respiratory event [7]. (A) The nasal cannula airflow and annotated respiratory events is shown. (B) The overlaid oxygen saturation signals (SpO2) associated with all respiratory events for one individual is shown. These signals were synchronized at the termination of respiratory events (time zero) and averaged to calculate the search window (the time between two peaks). The search window was used to calculate the hypoxic burden for individual events. That is, the area under saturation curve within the search window (C). The total hypoxic burden was defined as the sum of individual burdens divided by total sleep time. Resp. Event, respiratory event.

How is HB Calculated?

A detailed explanation of HB can be found in a 2022 publication by Martinez-Garcia and colleagues [1].

HB is defined as the total area under the oxygen saturation curve from a pre-event baseline oxygen desaturation. Total HB (%min/h) is defined as the sum of individual areas (%min) divided by total sleep time (h).

Why is HB Important?

HB provides additional information on how much a patient is impacted by their sleep apnea, regardless of their sleep apnea severity. While AHI, ODI, and T90 are the gold standard for assessing sleep apnea, these metrics have limitations, which include [1]:

  • No information on the duration and depth of respiratory events and their ensuing desaturations. 
  • Apnea and hypopnea have similar weight in the AHI calculation. 
  • Arbitrary threshold of 10s (9s-events can also be associated with significant oxygen desaturation).

Thus, two individuals with the same AHI may have vastly different symptoms and health outcomes due to differences in the characteristics of their desaturations.

Real Life HB Examples From Wesper User Data

Wesper Users 


Hypoxic Burden (%Min/Hr)

User 1



User 2



User 3



Table 1: Three Wesper user examples showing differences in HB. Despite having almost identical AHI scores, HB is different for each user. Based on clinical evidence, the severity of symptoms and the risk for comorbid health issues and mortality is highest for User 3.

Clinical Evidence for Including HB in Sleep Apnea Assessment

  • Incorporating the duration of respiratory events and their associated desaturation areas into the AHI could improve risk stratification (risk level) in patients with OSA [2].
  • Longer and deeper apneas and hypopneas elicit a larger cardiovascular response than shorter and milder events [3, 4, 5]
  • Detailed analysis of the oxygen desaturations and their morphology predicted the progression of mild to more severe OSA [6].
  • The association of OSA-specific HB with several cardiovascular outcomes, including cardiovascular mortality, major cardiovascular events, hypertension, stroke, heart failure, chronic kidney disease, have been assessed in past studies [7-11]. 
  • Risk of cardiovascular mortality is higher as HB increases. A high AHI but low HB was not associated with increased mortality, however a high HB with a low AHI was associated with increased mortality, demonstrating that HB is a better predictor of mortality than AHI.

Limitations with HB

Currently, there is no recommended scale to rate HB severity, which makes HB somewhat subjective for providers.

However, several studies have shown a linear relationship between HB and disease risk, and mortality (see examples below; [7, 9]).



  1. Martinez-Garcia MA, Sánchez-de-la-Torre M, White DP, Azarbarzin A. Hypoxic Burden in Obstructive Sleep Apnea: Present and Future. Arch Bronconeumol. 2023 Jan;59(1):36-43. English, Spanish. doi: 10.1016/j.arbres.2022.08.005. Epub 2022 Sep 5. PMID: 36115739.
  2. A. Muraja-Murro, A. Kulkas, M. Hiltunen, S. Kupari, T. Hukkanan, P. Tihonen, 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, 18 (2014), pp. 641-647
  3. Butler MP, Emch JT, Rueschman M, Sands SA, Shea SA, Wellman A, Redline S. Apnea-Hypopnea Event Duration Predicts Mortality in Men and Women in the Sleep Heart Health Study. Am J Respir Crit Care Med. 2019 Apr 1;199(7):903-912. doi: 10.1164/rccm.201804-0758OC. PMID: 30336691; PMCID: PMC6444651.
  4. Hietakoste S, Korkalainen H, Kainulainen S, Sillanmäki S, Nikkonen S, Myllymaa S, Duce B, Töyräs J, Leppänen T. Longer apneas and hypopneas are associated with greater ultra-short-term HRV in obstructive sleep apnea. Sci Rep. 2020 Dec 9;10(1):21556. doi: 10.1038/s41598-020-77780-x. PMID: 33298982; PMCID: PMC7726571.
  5. Azarbarzin A, Ostrowski M, Moussavi Z, Hanly P, Younes M. Contribution of arousal from sleep to postevent tachycardia in patients with obstructive sleep apnea. Sleep. 2013 Jun 1;36(6):881-9. doi: 10.5665/sleep.2716. PMID: 23729931; PMCID: PMC3649830.
  6. Karhu T, Myllymaa S, Nikkonen S, Mazzotti DR, Töyräs J, Leppänen T. Longer and Deeper Desaturations Are Associated With the Worsening of Mild Sleep Apnea: The Sleep Heart Health Study. Front Neurosci. 2021 Apr 28;15:657126. doi: 10.3389/fnins.2021.657126. PMID: 33994931; PMCID: PMC8113677.
  7. Azarbarzin A, Sands SA, Stone KL, Taranto-Montemurro L, Messineo L, Terrill PI, Ancoli-Israel S, Ensrud K, Purcell S, White DP, Redline S, Wellman A. The hypoxic burden of sleep apnoea predicts cardiovascular disease-related mortality: the Osteoporotic Fractures in Men Study and the Sleep Heart Health Study. Eur Heart J. 2019 Apr 7;40(14):1149-1157. doi: 10.1093/eurheartj/ehy624. Erratum in: Eur Heart J. 2019 Apr 7;40(14):1157. PMID: 30376054; PMCID: PMC6451769.
  8. Blanchard M, Gervès-Pinquié C, Feuilloy M, Le Vaillant M, Trzepizur W, Meslier N, Goupil F, Pigeanne T, Balusson F, Oger E, Sabil A, Girault JM, Gagnadoux F; ERMES study group. Hypoxic burden and heart rate variability predict stroke incidence in sleep apnoea. Eur Respir J. 2021 Mar 25;57(3):2004022. doi: 10.1183/13993003.04022-2020. PMID: 33214210.
  9. Azarbarzin A, Sands SA, Taranto-Montemurro L, Vena D, Sofer T, Kim SW, Stone KL, White DP, Wellman A, Redline S. The Sleep Apnea-Specific Hypoxic Burden Predicts Incident Heart Failure. Chest. 2020 Aug;158(2):739-750. doi: 10.1016/j.chest.2020.03.053. Epub 2020 Apr 13. PMID: 32298733; PMCID: PMC7417383.
  10. Kim JS, Azarbarzin A, Wang R, Djonlagic IE, Punjabi NM, Zee PC, Koo BB, Soliman EZ, Younes M, Redline S. Association of novel measures of sleep disturbances with blood pressure: the Multi-Ethnic Study of Atherosclerosis. Thorax. 2020 Jan;75(1):57-63. doi: 10.1136/thoraxjnl-2019-213533. Epub 2019 Aug 22. PMID: 31439722; PMCID: PMC8489982.
  11. Jackson CL, Umesi C, Gaston SA, Azarbarzin A, Lunyera J, McGrath JA, Jackson Ii WB, Diamantidis CJ, Boulware E, Lutsey PL, Redline S. Multiple, objectively measured sleep dimensions including hypoxic burden and chronic kidney disease: findings from the Multi-Ethnic Study of Atherosclerosis. Thorax. 2021 Jul;76(7):704-713. doi: 10.1136/thoraxjnl-2020-214713. Epub 2020 Dec 4. PMID: 33277428; PMCID: PMC8175452.

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