Home Sleep Apnea Testing for Obstructive Sleep Apnea

Abstract

Obstructive Sleep Apnea (OSA) is a major public health problem affecting almost one billion individuals worldwide. Ninety percent of patients with OSA are still undiagnosed. Although an attended polysomnography (PSG) testing is the gold standard to diagnose OSA, it is time-consuming and is associated with higher costs. The Home Sleep Apnea Testing (HSAT) is now available to diagnose OSA. Understanding the indications and limitations of HSAT is important to avoid misdiagnosis and improve patient outcomes.

Introduction

Obstructive Sleep Apnea (OSA) is a disorder characterized by recurrent collapse of the upper airway during sleep.¹ This repetitive process, over time, can result in a wide range of physiologic consequences involving the cardiovascular, pulmonary, and neurocognitive systems. Existing evidence also indicates that appropriate treatment of OSA reduces the risk of these consequences.² The increased prevalence of obesity and overall survival, which have accompanied advancements in healthcare, have contributed to the rise in OSA prevalence. The prevalence of OSA varies according to the severity cutoff used for diagnosis and the age of the population studied. Some reports have estimated that at least 20.2% of men and 10.0% of women are affected with moderate-severe OSA.³

Evaluation of OSA starts with exploring clinical symptoms, physical signs, and completion of validated questionnaires to help identify patients who may benefit from testing to confirm the diagnosis.¹ Overnight polysomnography (PSG) is still considered the gold standard test for confirming a diagnosis of OSA and other Sleep Disordered Breathing (SDB).⁴ Despite being the gold diagnostic test, a PSG may have limitations related to cost, long wait times, and lack of access. For this reason, several new technologies have been developed to assess for sleep apnea out-side of the sleep lab to accommodate demand and increase access to patients.^4,5

Basics of Obstructive Sleep Apnea Diagnostic Tests

A standard PSG involves data collection from seven or more channels including a limited Electroencephalogram (EEG), Electrooculography (EOG), Electromyogram (EMG), one lead Electrocardiogram (ECG), air flow channels (nasal pressure transducer and oronasal thermal flow sensor), respiratory effort (respiratory inductance plethysmography belts), and pulse oximeter.⁶

Using the respiratory derived data from different sensors, an Apnea-Hypopnea Index (AHI) can be calculated, which is the result of the total respiratory events (Apneas and Hypopneas) divided by Total Sleep Time (TST)¹ (Box 1). An apnea is scored when a reduction in respiratory flow signal equals or exceeds 90% of pre-event baseline and lasts more than 10 seconds. A hypopnea is scored when a 30% or more reduction in respiratory air flow lasts more than 10 seconds and is associated with a reduction in oxygen saturation of 3% (or 4% based on CMS criteria) from pre-event baseline and/or associated with an arousal.⁷ The AHI serves as a way to classify severity of OSA with AHI <5/hour being normal for adults, 5–15/hour indicating mild OSA, 15–30/hour for moderate OSA; while an AHI ≥30/hour reflecting severe disease.⁸

Box 1. Obstructive Sleep Apnea (OSA) severity based on Apnea/Hypopnea Index (AHI).

OSA Severity	AHI (events/hour)
Normal	<5
Mild	5 to <15
Moderate	15 to <30
Severe	≥30

Ref: Malhotra A, Ayappa I, Ayas N, et al. Metrics of sleep apnea severity: beyond the apneahypopnea index.

Sleep. Vol 44, Issue 7. March 2021

The calculation of AHI requires an accurate assessment of Total Sleep Time (TST), rather than total time in bed, which is derived from the EEG signal obtained in a polysomnogram. The quantification of TST is usually limited in most Home Sleep Apnea Tests as EEG signals are often not measured. For this reason, Monitoring Time (MT) is usually reported instead, which is usually obtained by subtracting periods of artifacts and wakefulness as determined by actigraphy, respiratory pattern, body position sensor or patient diary, from the Total Recording Time (TRT). When a HSAT is performed, OSA severity is sometimes expressed using the Respiratory Event Index (REI) which is the result of dividing the number of respiratory events (Apneas and Hypopneas) by the MT.⁸ Since EEG is not used to accurately estimate sleep time when MT is measured, it is usually longer than the TST and this can result in underestimation of OSA severity especially when the HSAT is performed on patients with low pretest probability for the disease. When HSAT is considered for evaluation of OSA, a careful patient selection is crucial to improve the utility of the test and reduce the rate of false negative results.¹⁰ A more detailed description of the suggested criteria for the use of HSAT will be discussed later in this review.

Classifications of Obstructive Sleep Apnea Testing

The first classification system for sleep apnea testing was introduced by the American Sleep Disorders Association, now the American Academy of Sleep Medicine (AASM) in 1994.⁹ This system suggested four types of sleep apnea testing as listed in Table 1.

Table 1.

American Academy of Sleep Medicine classification of sleep apnea diagnostic modalities

Test level	Description	Personnel	Parameters Measured
Type 1	Standard PSG performed in a sleep lab	Attended	EEG, EOG, chin EMG, ECG, airflow, respiratory effort and oxygen saturation
Type 2	Portable PSG	Unattended	Same as type 1
Type 3	Cardiorespiratory polygraphy	Unattended	4–6 signals, (two respiratory variables, oxygen saturation, and pulse or heart rate)
Type 4	1–2 signals	Unattended	Typically includes oxygen saturation or airflow

PSG: polysomnography; EEG: electroencephalography; EOG: electro-oculography; EMG: electromyography.

Reference: Portable Recording in the Assessment of Obstructive Sleep Apnea. Ferber R, Millman R, Coppola M et al. Sleep, Volume 17, Issue 4, June 1994, Pages 378–392.

Type 1 study includes the standard attended PSG, while the remaining types 2,3 and 4 include the portable techniques for testing. Type 2 sleep study uses the same equipment used in a standard PSG but without the supervision of a trained sleep technician. Although type 2 testing has been used experimentally in some clinical trials, many other studies have questioned the validity and reliability of the data collected by this home based PSGs, especially when a sophisticated device is being used by patients without supervision.¹⁰ Type 3 and type 4 studies represent the majority of home sleep apnea testing in clinical practice.

With the advancements in technology and innovations in home sleep apnea testing, it was noted that many new devices did not fit into these categories and hence the need for a more comprehensive categorization system. In 2011, the AASM issued a classification system based on sleep physiologic parameters measured during sleep. The proposed system relayed on the Sleep, Cardiovascular, Oximetry, Position, Effort, and Respiratory (SCOPER) parameters collected during testing.¹ In this classification, the ability to determine sleep and wakefulness in addition to sleep staging, has classified these devices to ones that use three or less EEG channels for sleep measurement and staging, to devices that uses sleep surrogates, like actigraphy, for sleep quantification. For cardiovascular monitoring, there are devices that used either the cardiac signal (one or more ECG leads) or vascular signal (peripheral arterial tonometry) to derive a respiratory event. Measurement of oxygen with a pulse oximetry was a requirement for the device to be included in this classification system. Ability to determine sleep position during sleep was used to define devices that used visual versus nonvisual measurement. For respiratory effort assessment, devices were graded from ones that used two Respiratory Inductance Plethysmography (RIP) belts (gold standard) versus one belt or other effort measures (including piezo belts). Lastly, for respiratory flow measurement, there were devices that used either nasal pressure or thermal sensors to detect flow, a combination of these sensors or used end-tidal CO2 as an indirect way to detect respiration.^13,2

There are currently many commercially available devices for home sleep apnea testing that use different combinations of sensors for detecting sleep apnea.

A direct comparison between these devices can be challenging due to the variability in the methods used in their validation studies and differences in the populations that were tested.

HSAT Utilizing Respiratory Flow and/or Effort Parameters

The most well established and studied method of HSAT includes the portable monitors of respiratory parameters that records a minimum of four signals. These usually consist of measurement of respiratory air flow, respiratory effort, oximetry, and pulse or heart rate.³ Respiratory airflow is usually measured using a nasal pressure transducer or an oronasal thermal airflow sensor. Quantification of airflow is possible with the nasal pressure sensors making it more reliable in detecting partial reduction in airflow as in the case of hypopneas. Thermal airflow sensors can detect apneas by using the difference of temperature between the inhaled and exhaled air in a respiratory cycle.⁴ Respiratory effort is measured by using Respiratory Inductance Plethysmography (RIP) which provides an estimate of changes in tidal volumes through a recording band around the chest and abdomen. RIP bands have an electrical wire that is arranged as a coil, changes in circumference during respiration results in changes in inductance or resistance which is used to estimate lung volumes. Dual RIP belts is also recommended by the AASM scoring manual for measurement of respiratory effort.⁵

Monitoring of heart rhythm can be derived from pulse oximetry. A more precise method for rhythm detection is through a signal lead ECG. Body position during sleep is sometimes determined by a 3D accelerometer sensor which can also provide an estimate of the sleep-wake state in some HSAT devices (Figure 1).

Figure 1.

HSAT device utilizing respiratory parameters (airflow and effort) for sleep apnea testing. Thoraco-abdominal RIP belts are used for respiratory effort detection. A nasal pressure transducer through a nasal cannula and oronasal thermal sensors are used for airflow detection. Pulse oximetry through a finger probe is used for oxygen saturation measurement and pulse wave generation.

Source: https://www.wsj.com/articles/SB10001424127887324715704578480883962087110

Peripheral Arterial Tonometry devices relay on detecting changes in blood volume in the peripheral arteries. It is well known that various respiratory events, apneas, and hypopneas, are associated with sympathetic activation during sleep. This activation results in vasoconstriction mediated by alpha receptors of vascular smooth muscles leading to reduction of blood flow in peripheral arteries.¹ A finger probe with a pneumo-optical sensor is used to continuously measure the digital arterial pulse wave volume. A pulse oximeter is integrated to the device system which also allows for oxygen saturation and heart rate measurements. A combination of a reduction in oxygen saturation, a decrease in PAT signal and an increase in heart rate help to identify reparatory events. Recent devices now also include an actigraphy which, along with PAT signal, has been used to determine sleep and wake time in addition to estimation of various stages of sleep, mainly non–rapid eye movement (NREM) sleep, and REM sleep, due to differences in sympathetic tone in each of these stages. A body position sensor and a microphone for snore detection has also been integrated in some devices allowing for more accurate evaluation of respiratory events⁸ (Figure 2).

Figure 2.

HSAT device with PAT measurement technology. A finger probe for PAT signal detection incorporates pulse oximetry and heart rate monitoring. An additional body position and snore sensor can be placed on the upper chest.

Source: https://sleeprightmckinney.com/comfortable-sleep-apnea-testingoption/

HSAT Utilizing Minimal Contact or Contactless Methods for Assessment of Respiration

Newer methods for assessing sleep-related breathing disorders by contactless techniques include recording and analysis of respiratory sounds (breathing, snoring, choking, gasping). A combined sensor that contains a microphone and a pressure transducer can be applied to the suprasternal notch that is used to calculate the respiratory flow, respiratory effort and snoring. Studies that compared this method to PSG have shown that this approach has high sensitivity and specificity for detecting apneas and hypopneas and can differentiate central from obstructive sleep apnea.^14,1

Recently, built-in-mobile microphones and sound analyzer applications have been used to detect sleep related breathing disorders, but these devices are still under research development and have not been approved yet as commercial devices in clinical practice.² Movement analysis is another approach that uses non-contact methods to detect sleep related breathing disorders. The movement of the chest and abdomen during respiration can be assessed with a biomotion sensor that uses a low-power radio frequency transceiver to detect respiratory events. One validation study for this method reported a sensitivity of 89% and a specificity of 92% for detecting clinically significant SDB (AHI>15).³ Although promising, many of these methods are still under development and further validation studies are still needed to be approved as medical devices.

Understanding Indications and Limitations of Home Sleep Apnea Tests

In 2017, the American Academy of Sleep Medicine (AASM) issued a position statement to address the acceptable clinical use of a home sleep apnea tests (HSAT).⁴ This statement highlighted the importance of using HSAT as a part of a more comprehensive sleep evaluation rather than a standalone test. With the current availability of numerous commercial HSAT devices, the statement emphasized that only a physician should make the decision that HSAT is appropriate for a patient based on history and examination findings. Diagnosis and treatment decisions should not rely completely on automaticity scored HSAT data and interpretation of raw data should be performed by a board-certified sleep medicine physician (Box 2).

Box 2. Advantages and disadvantages of HSAT.

Advantages:

• - Possible improved sleep in a patient preferred sleep environment in addition to less monitor leads.

• - An alternative testing method if PSG is difficult to perform (limited access, patient’s immobility)

• - Reduced study to study cost compared to PSG.

• - Number of tests performed are not limited by the capacity of the sleep lab as in PSG.

• - Reduce wait times for establishing diagnosis and initiating treatment.

Disadvantages/limitations:

• - Increased number of technically inadequate studies given the unattended nature of the study.

• - Possible underestimation of AHI and severity of OSA as accurate sleep time is not quantified in most HSAT.

• - Limited evaluation of non-obstructive sleep disordered breathing (central sleep apnea, significant hypoxemia or hypoventilation).

• - Not recommended for sleep apnea evaluation in patients with neuromuscular disease and respiratory muscle weakness, significant cardiopulmonary diseases, chronic opioid use and history of stroke.

• - Not recommended for patients who may require evaluation for comorbid non-respiratory sleep disorders (sleep related movements disorders, REM behavior disorder, parasomnias).

• - Negative or inadequate study with high clinical suspicion for OSA requires repeat testing

The most recent practice guideline by AASM for the diagnostic testing of OSA outlined the appropriate indications of HSAT. The guideline specified that a technically adequate HSAT device may be used for evaluation of OSA in medically uncomplicated patients with history and clinical findings suggesting at least moderate to high pre-test probability of the disease. Based on this, and to avoid false negative results, HSAT should not be used for routine testing or screening of general population or asymptomatic individuals.

In general, an attended polysomnography (PSG) rather than HSAT should be used for diagnosis of sleep disorders in patients with the following conditions:

1. Patients at increased risk of non-obstructive sleep disordered breathing including central sleep apnea, significant hypoxemia or hypoventilation. This also includes patients suspected of having obesity hypoventilation syndrome.

2. Patients presenting with symptoms of non-respiratory sleep disorders that require attended sleep evaluation like parasomnia and sleep related movements disorders.

3. Patients with medical conditions that may interfere with the accuracy of HSAT results (severe insomnia), or any environmental or personal factors (physical disability) that could affect the accuracy of HSAT data collection and interpretation.

4. Patients with Super Obesity (BMI > 40 or 50).

Specific medical conditions of important relevance that may predispose patients to non-obstructive sleep disordered breathing include significant cardiopulmonary diseases, neuromuscular disease resulting in respiratory muscle weakness, chronic opioid use and history of stroke. In certain cases of high clinical suspicion for OSA despite a negative or inconclusive HSAT result, a repeat testing with a full night polysomnogram (PSG) should be performed. ⁵ Figure 3 demonstrates a summary of the 2017 AASM guideline for the diagnostic testing of OSA in adults.

Figure 3.

The American Academy of Sleep Medicine clinical algorithm for the use of Home Sleep Apnea Tests in evaluation of obstructive sleep apnea.

Adapted from Kapur VK, Auckley DH, Chowdhuri S, Kuhlmann DC, Mehra R, Ramar K, Harrod CG. Clinical practice guideline for diagnostic testing for adult obstructive sleep apnea: an American Academy of Sleep Medicine clinical practice guideline. Journal of Clinical Sleep Medicine. Vol 13, Issue 3, March 2017, Pages 479–504.

Conclusion

The increasing prevalence and awareness of OSA in the last few decades have created an overwhelming demand for more accessible and efficient diagnostic testing. HSAT has offered an alternative for the long waiting times and limited availability of in lab polysomnograms. In order to make the most benefit of this technological advancement in diagnostic testing, clinicians should be aware of the limitations and common pitfalls when it comes to ordering and interpreting the results of these tests to avoid misdiagnosis and ultimately patient harm.