Dreaming of a Better Sleep Study

Ashley Kita, MD, on behalf of the Sleep Disorders Committee

(See author’s disclosures at the end of this column.)

Otolaryngologists routinely make permanent surgical decisions based on information from one-night snapshots of sleep, known as sleep studies. Our patients choose to undergo procedures such as adenotonsillectomy, pharyngoplasty, or upper airway stimulation—all based on data collected during just one night in an unfamiliar environment. We can certainly examine patients in our clinics and suggest where the obstruction might be occurring, but we often leave the determination of whether it is clinically important to intervene to the results of sleep studies. Yet we know that sleep is inherently variable, influenced by countless factors that a single study cannot capture.

The First-Night Effect

The phenomenon known as the "first-night effect" represents one of the most fundamental limitations of in-laboratory polysomnography. Research shows that approximately 49% of patients sleep worse during their first night in a sleep laboratory, while another 21% sleep better—a "reverse first-night effect." Only about 30% sleep as they normally would at home.¹ A meta-analysis examining the first-night effect across all age groups found that it affects multiple sleep parameters, though importantly, it was only present on the first night of sleep and disappeared after several nights.²

The first-night effect has been seen in individuals with sleep-related breathing disorders, insomnia, movement and behavioral disorders, as well as healthy patients.³ This has underscored the importance of two consecutive nights of recordings, but this is rarely feasible given cost constraints and limited sleep laboratory availability. Thus, the variability with a single night of polysomnography is what we have come to accept.

Home Sleep Studies: Convenience at a Cost

Home sleep apnea testing (HSAT) has emerged as an attractive alternative to in-laboratory polysomnography, offering convenience, lower cost, and the comfort of sleeping in one's own environment. However, from a surgeon's perspective, HSAT introduces its own set of critical limitations that directly impact treatment planning.

The most significant limitation is HSAT's inability to measure total sleep time accurately. These devices measure total recording time rather than actual sleep time, potentially underestimating the apnea-hypopnea index (AHI) when patients spend significant time awake during the recording period. Studies comparing HSAT to polysomnography have documented systematic underestimation of OSA severity, with implications for both diagnosis and treatment planning.⁴

More problematic for surgical decision-making is HSAT's limited diagnostic scope. The American Academy of Sleep Medicine explicitly states that HSAT is designed for uncomplicated patients with moderate-to-high pretest probability of OSA.^5,6 These devices excel at detecting obstructive events but cannot reliably identify central sleep apnea, sleep-related hypoventilation, or conditions such as periodic limb movement disorder—all of which can significantly impact post-operative outcomes. This incomplete picture can lead to surgical failure when we address obstructive pathology while missing underlying central respiratory control issues. Furthermore, most HSATs do not measure sleep architecture or do so inaccurately, limiting our ability to assess the true impact of respiratory events on sleep quality and to offer treatment to many who would benefit.

Pediatric Sleep Studies: A Unique Challenge

Obtaining reliable sleep study data in children presents challenges that extend beyond the first-night effect. The American Academy of Pediatrics’ guidelines specifically exclude children from recommendations for portable polysomnography, citing the paucity of validation data in pediatric populations.⁷ This exclusion exists for good reason: young children frequently pull off monitoring leads, making home studies technically inadequate.

In-laboratory pediatric polysomnography requires specialized equipment, child-friendly environments, trained pediatric sleep technologists, and often the presence of a parent or caregiver throughout the night. Despite these accommodations, many children, particularly those under three years old or with developmental delays, find the experience difficult. Studies examining the psychological impact of pediatric polysomnography found that while most children tolerated the procedure, a substantial percentage demonstrated sleep patterns markedly different from their usual sleep at home.⁸

Recent investigations into contactless or low-contact diagnostic methods show promise for pediatric populations. Acoustic monitoring, movement analysis, and other non-invasive approaches are being developed and validated, though they have not yet achieved widespread clinical implementation.

The Site of Obstruction: A Critical Gap

Perhaps the most surgically relevant limitation of current sleep study technology is its inability to localize the anatomic site of upper airway obstruction. An AHI of 30 describes severe OSA, but it doesn't indicate whether the collapse occurs at the palatal level, the tongue base, the lateral pharyngeal walls, or multiple sites simultaneously. Yet this information is essential for selecting appropriate interventions.

Drug-induced sleep endoscopy (DISE) has revolutionized our approach to surgical planning for OSA. By visualizing the upper airway during sedation that mimics natural sleep, DISE enables direct observation of collapse patterns and obstruction sites. Studies have shown that DISE often changes the surgical management plan compared to what would have been recommended based on awake examination and polysomnography alone.^{9, 10} For patients being evaluated for upper airway stimulation, DISE is now a required component of the pre-operative workup, as complete concentric collapse at the palatal level represents a contraindication to this therapy.

However, DISE has its own limitations. It typically evaluates only non-REM sleep-equivalent states, as current sedation protocols cannot reliably reproduce REM sleep when OSA may be most severe. The depth of sedation must be carefully controlled—too light and obstruction may not manifest; too deep and excessive tongue base collapse may occur, which doesn't reflect natural sleep. There is also ongoing debate about how well drug-induced collapse patterns correlate with natural sleep, though studies using propofol with target-controlled infusion have shown reasonable concordance for non-REM sleep stages.¹¹

Confounding Variables

Beyond the structural limitations of sleep testing, numerous confounding variables can significantly alter polysomnography results. Sleep position is perhaps the most obvious: many patients have position-dependent OSA, with events occurring predominantly or exclusively in the supine position. If a patient spends most of their study night in lateral positions—perhaps because the polysomnography bed is narrow or because they're unconsciously avoiding the supine position in an unfamiliar environment while wearing multiple recording leads—the severity of their OSA may be substantially underestimated.

Alcohol consumption, sedative medications, and even over-the-counter sleep aids can profoundly impact upper airway collapsibility and the frequency of respiratory events. Benzodiazepines and opioids may exacerbate sleep-disordered breathing, while other medications may suppress REM sleep, altering the distribution of events across sleep stages. Current guidelines recommend that patients continue their usual medications on the night of polysomnography, but not all patients have a "usual" routine, as many have routines that vary.

The sleep environment itself introduces variables: different mattress firmness, room temperature, ambient noise, and light exposure all influence sleep quality and architecture. A patient who normally sleeps with their head elevated may be studied flat, or vice versa. These factors further compound the first-night effect.

What Surgeons Really Need: A Wish List for Sleep Diagnostics

As a surgeon planning upper airway interventions for OSA, my ideal sleep study would include several components:

Representative multi-night data: Aggregated data from multiple nights of typical sleep at home would be far better than a single-night snapshot. This would capture night-to-night variability, allow calculation of the average AHI, and identify worst-case scenarios (such as the severity of events during REM sleep in the supine position after alcohol consumption). This multi-night approach could document both the typical and worst patterns of obstruction. Furthermore, the ability to perform more frequent sleep monitoring in a home setting could allow us to better assess the effects of interventions over time and even allow those considering operative procedures to try other interventions first to see their effects on sleep. This could be a motivating factor for those losing weight with GLP1-agonists, prove the usefulness of an oral appliance, or encourage positionally indifferent patients to sleep more on their sides.

Reliable site-of-collapse information: Integration of anatomic localization data—whether from a wearable form of home sleep endoscopy, computational modeling, or advanced imaging—would be tremendously helpful. This information should reflect the dynamic nature of collapse across different sleep stages and positions, allowing for better patient counselling and surgical planning. Perhaps technology could even replace DISE.

Validated wearable integration: Consumer wearables now provide multi-night sleep data and are becoming increasingly accurate. Recent validation studies show that devices such as the Apple Watch Series 8 and Oura Ring can detect sleep versus wake with greater than 90% agreement compared to polysomnography, though their accuracy in distinguishing specific sleep stages remains more limited.^{12, 13, 14} We should be pursuing medical validation when compared with our current “gold standard” polysomnography to allow for integration of these devices into clinical decision-making. A patient's wearable data showing consistent oxygen desaturations across multiple weeks might provide more representative information than a single night of polysomnography.

Comprehensive phenotyping: Sleep-disordered breathing is heterogeneous. Some patients have predominantly anatomic collapse, others have impaired arousal responses, and still others demonstrate unstable ventilatory control. Our current diagnostic approach does not adequately phenotype patients, limiting our ability to match interventions to underlying pathophysiology. The ability of future technology to distinguish these categories is desired.

Rethinking Our Gold Standard

We often describe polysomnography as the gold standard for diagnosing OSA, but this designation deserves scrutiny. A gold standard should represent the most accurate and reliable method for diagnosis—yet polysomnography typically captures only one night of sleep in an artificial environment, cannot localize obstruction sites, and provides limited information about many factors that influence surgical outcomes.

Perhaps our true gold standard should be the average of several nights of typical sleep at home, captured with validated multi-night monitoring technology that accounts for position, sleep stage, and environmental factors. Such an approach may better represent the variability inherent in sleep-disordered breathing and provide surgeons with the representative data needed for informed decision-making.

Until that future arrives, we must acknowledge the limitations of our current diagnostic tools while working to improve them. This means understanding what a single polysomnography result can tell us to better counsel patients, while remaining open to integrating validated consumer technology into our diagnostic algorithms.

The gap between our current diagnostic approaches and the true dynamic nature of sleep-disordered breathing may not close quickly. But recognizing this gap—and its implications for surgical decision-making—is the first step toward better serving our patients with OSA.

Disclosures: This manuscript reflects the author’s clinical experience in otolaryngology and the management of obstructive sleep apnea. Although generative AI technology was used to assist with literature synthesis and initial drafting, all clinical insights are based on the authors’ professional expertise and judgment. The author has thoroughly reviewed, verified, and substantially revised all content, ensuring accuracy and clinical relevance. The author takes full responsibility for the integrity of the work and all medical opinions expressed herein.

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