Obstructive sleep apnea syndrome (OSAS) is a common disorder characterized by the recurrent collapse of upper airway anatomy during sleep. This leads to a physiologic cascade of transient hypoxia, changes in intra-thoracic pressure, increased sympathetic output, and cortical arousals associated with excessive daytime sleepiness. It is estimated to occur in approximately 5% of the population. The incidence is reported to be higher (~20%) in patients with systemic hypertension. Several trials have indicated that treatment of OSAS can lead to reductions in hypertension and prehypertension.[3-5] The question then arises of how this is best accomplished. Diagnosis of obstructive sleep apnea (OSA) can be limited by availability, accessibility, and the cost of in-laboratory polysomnography: the gold standard for diagnosis. Further, many patients are uncomfortable with the concept of sleeping in a laboratory connected to a myriad of monitors.
In recent years, there has been a great amount of development of home sleep testing (HST) equipment. Currently, there are at least 16 different production models available for home testing. One of the challenges inherent in this is that there has not yet been an established standard of what types of channels should be recorded in a home sleep study. In 2007, the American Academy of Sleep Medicine (AASM) published clinical guidelines indicating that at minimum, devices record airflow, respiratory effort, and blood oxygenation. Most commercial devices replicate the equipment used in laboratory polysomnography (including nasal airflow, thermistor, respiratory effort, heart rate, body position, limited electroencephalography [EEG], and oximetry). The majority of these devices do not utilize EEG; as such, most home sleep studies are not able to discriminate whether a respiratory disturbance occurs during a period of wakefulness or sleep. As a result, the overall severity of OSA tends to be underestimated. Therefore, HST is best utilized for the detection of severe OSA rather than mild OSA. Further, home sleep studies are limited in their ability to recognize patterns of central sleep apnea (CSA) such as Cheyne-Stokes respiration. This is an important consideration in studying patients with comorbid heart failure or end-stage renal disease, wherein the risk of CSA is elevated.
In this issue of the journal, Gurbuhagavtula and colleagues present a study that validates a strategy to screen for severe OSAS in hypertensive outpatients, without the need for the cumbersome task of in-laboratory polysomnography. They looked at several clinical parameters and paired them with a straightforward HST device that measured unattended oximetry, chest and abdominal movement, and nasal airflow pressure. A real strength in their study is that they identified at least two potential models (one measuring neck circumference and obtaining a home sleep study, and another calculating a clinical risk score, multivariable apnea prediction score [MVAP] followed by HST) that had good predictive ability and could easily be translated into clinical practice by a non-sleep specialist caring for at-risk patients. Although the facial morphometrics score had slightly greater predictive ability, it is likely limited in practice based on technical expertise of providers.
It should also be noted that the authors used an autoscoring system built into the HST equipment to determine an unattended apnea-hypopnea index. This certainly has the advantage of ease of use, and allows the technology to be employed by a wide variety of providers, although the potential for increased error/misinterpretation is elevated. This is akin to using the automatic interpretation software built into electrocardiography machines. The AASM guidelines for out-of-office sleep testing encourage manual scoring/validation of all studies.
Looking forward, the results presented in this issue offer us evidence that checking a few straightforward clinical parameters coupled with a home sleep study, can reliably help identify patients at risk for severe OSAS. The clinical parameters recognized (measuring neck circumference, asking about snoring, apneas, and basic demographics) can easily be obtained. Further work is needed to look at the value of this type of screening tool in broader populations. In addition, as a field we must consider who is best suited to conduct these studies. Should they be completed and interpreted in-house by a generalist/nephrologist/cardiologist? Should this be referred to a sleep medicine specialist? Or, should it be outsourced to the growing market of independent sleep testing companies? Another practical consideration moving forward is how we approach patients who have a clinical screen suggestive of possible OSAS and have negative results on a home sleep study. We would propose that they likely would benefit from follow-up in-laboratory polysomnography. The strategy validated in this study has the potential to be an efficient and cost-effective way of screening for severe OSA in hypertensive patients. At the same time, we must keep in mind the limitations of most HST equipment: identifying mild OSA, identifying patterns of central sleep apnea, lack of sleep staging, and auto-scorer reliability.