Understanding Hypoxic Burden: The Impact of Sleep Apnea
Chelsie Rohrscheib, Ph.D. Neuroscientist and Head Sleep Expert, Wesper
August 5, 2024
Obstructive Sleep Apnea (OSA) poses a significant health challenge, affecting millions worldwide and presenting a spectrum of severity. The conventional diagnostic tool, the apnea/hypopnea index (AHI), offers crucial insights into the presence of OSA by quantifying breathing disruptions during sleep. However, its reliance solely on frequency fails to capture the nuanced impact of OSA on individuals, leaving unanswered questions about varying symptomatology and associated health risks. This limitation underscores the need for complementary metrics that delve deeper into the physiological consequences of OSA. Enter the Hypoxic Burden (HB), an emerging concept that seeks to elucidate the true extent of OSA's impact by considering not only the frequency but also the depth and duration of respiratory-related desaturations.
While AHI provides a binary diagnosis, HB offers a nuanced understanding of OSA's physiological toll, potentially explaining why individuals with similar AHI scores experience vastly different symptoms and outcomes. By quantifying the cumulative burden of hypoxia during sleep, HB serves as a valuable adjunct to AHI, offering insights into sleep disruption, comorbid health conditions, and mortality risk. Through a comparison of three patients with matched AHIs but divergent HB scores, this study illustrates the differential impact of OSA on individuals, underscoring the importance of HB in guiding personalized treatment strategies. As the field of sleep medicine continues to evolve, integrating HB alongside AHI promises to enhance diagnostic accuracy, refine risk stratification, and optimize therapeutic interventions for individuals with OSA.
Background
The gold standard for obstructive sleep apnea (OSA) diagnosis is the apnea/hypopnea index (AHI), which calculates the average amount of times a patient has an apnea or hypopnea per hour. As per scoring guidelines in The American Association for Sleep Medicine for the Scoring of Sleep and Associated Events , an AHI of 5 or higher is considered positive for OSA.
While AHI can determine if a patient has OSA, it lacks vital information about how severely the patient is affected. Specifically, it cannot explain why some patients are more symptomatic or at a higher risk for comorbid health conditions, regardless of AHI.
Differences in outcomes are hypothesized to be due to several limitations in how AHI is calculated, including an inability to consider the duration and depth of respiratory events and their ensuing desaturations. Further, apneas and hypopneas have similar weight in the AHI calculation, and the arbitrary threshold of 10 seconds for respiratory events. Thus, two individuals with the same AHI may have vastly different symptoms and health outcomes due to differences in the characteristics of their desaturations.
An alternative to AHI, called Hypoxic Burden (HB), aims to better understand how much a patient is impacted by their OSA, and predicts their risk for sleep disruption, comorbid health conditions, 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. It further assesses the depth of the desaturation (how low they go) and the duration of the desaturation (how long they last).
HB is typically calculated as a percentage of minutes per hour of sleep time (%min/hr). While there is no severity rating scale for HB, clinical studies have shown that comorbidities and mortality increase with percentage. For example, a 2019 study by Azarbarzin and colleagues [2] found that patients with a HB of >88 (%min/hr) had a 15-year survival probability of only 65%, compared to an 82% survival probability for patients with an HB of <20 (%min/hr). Thus, similar scales may be used by providers to assess the impact of a patient’s sleep apnea, regardless of AHI.
Hypoxic burden exceeding 100% refers to a situation where an individual experiences hypoxia (oxygen deficiency) for more than 100% of a given time period. This can occur due to several factors:
1. Cumulative Effect
Hypoxic burden is often calculated as the integral of time spent below a certain oxygen saturation threshold over a period. For instance, if someone spends 50% of the time at 80% oxygen saturation and 50% at 100%, the average oxygen saturation may still be 90%, but the hypoxic burden can exceed 100% because of the cumulative impact of low oxygen levels.
2. Severity and Duration
The severity and duration of hypoxic episodes matter. Even brief episodes below a critical oxygen saturation level can significantly contribute to the overall hypoxic burden. For example, spending 10% of the time at 70% oxygen saturation is more detrimental than spending the same time at 90% saturation.
In summary, hypoxic burden exceeding 100% reflects the cumulative impact of time spent in hypoxic conditions, taking into account both the severity and duration of oxygen deficiency episodes. This concept is crucial in understanding the overall physiological stress due to oxygen deprivation in clinical and research settings.
Patient Example
Hypoxic Burden can be conceptually estimated from average desaturation area per event. For example, assume a subject has 20 events/hour and each event, on average, has a triangular-shaped desaturation area with an 8% height (desaturation depth) and a 0.5-minute base (desaturation duration). For this case, the desaturation area for each event is 2 %minute (area of the desaturation triangle= ½ × 0.5 minute × 8%). The total HB will be 40 %minute/hour (20 event/hour × 2 %minute/event).
Case Study
To further emphasize the usefulness of HB as a complimentary way to assess OSA, we compared three patients that underwent sleep apnea testing with Wesper, an FDA approved home sleep apnea test (HSAT). Each patient was matched for AHI (+/- 2), age (+/- 10 years) and gender (Table 1).
Table 1: Patient demographics and AHI
Patient |
Age |
Gender |
AHI |
1 |
74 |
Male |
14.7 |
2 |
70 |
Male |
13.1 |
3 |
80 |
Male |
14.3 |
Despite similar AHIs, the three patients had vastly different HB scores (Figure 2). Patient 1 had a much higher hypoxic burden than patient 2 and 3, demonstrating that patient 1 had desaturation events that were longer and reached lower depths, than patient 2 and 3. Thus, we can conclude that patient 3 is likely to be more symptomatic and at greater risk for comorbidities than patients 2 and 3.Â
Figure 1:
Differences in hypoxic burden for 3 different patients of similar demographics and similar AHI scores.
Further assessment of the patients’ Wesper sleep data showed marked differences in sleep quality. Patient 1 had the lowest total sleep time, the most awakenings, and rated their sleep quality the poorest on a scale of extremely good to extremely poor (Table 2).
Table 2: Sleep quality indicators
Patient |
Total Sleep Time |
Awakenings |
Subjective Sleep Quality |
1 |
5h 29m |
13 |
Extremely Poor |
2 |
6h 41m |
6 |
Fair |
3 |
7h 56m |
11 |
Good |
Conclusion
HB is a useful metric for evaluating a patient’s risk for OSA symptoms and comorbidities. Providers should use HB in combination with AHI to drive treatment, especially for treatments that require titrations, such as CPAP, oral appliance, and hypoglossal nerve stimulation. HB is also helpful for assessing patients with low AHIs, especially in cases where patients are borderline, yet experience severe symptoms, including sleep disruption.
ReferencesÂ
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.
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.