This piece originally published in Sleep World Magazine
There’s a scene in Home Alone where Harry and Marv put their ears to the attic door to identify a loud sound. They are suddenly knocked to the floor as a large object crashes through the door. From his back, Marv eloquently states, "That was the sound of a tool chest. Falling down the stairs." Well, my sleep friends, we are Harry and Marv. And that tool chest? It's the tsunami of OSA patients heading toward us.
I’m not here to address the intricacies of evaluating, diagnosing, or treating OSA; I want to focus on finding it in the wild. This discussion is necessary because, despite all the news stories, research studies, and public awareness campaigns, OSA remains a condition where the gap between prevalence and diagnosis remains notably wide. This gap is not due to a lack of understanding of OSA's impact but rather the hurdles in its identification.
The reality is that the current process for screening OSA often depends on a sleep-deprived individual becoming frustrated with living like a zombie or a snorer receiving a nudge from their bed partner to seek medical advice or move to the couch. This is why we continue to hear that 8-year-old Frost & Sullivan statistic “80% of people with OSA are undiagnosed” shouted from the rooftops year after year. We just haven’t figured out how to move the needle.
As specialists in the field, the question we face isn't just about identifying OSA but about doing so in an efficient and scalable manner. The potential for improved screening methodologies is enhancing patient outcomes and adapting our approaches to the realities of modern healthcare systems and evolving patient expectations.
However, the future looks promising as consumer hardware, medical software powered by Artificial Intelligence, and data from alternative diagnostic tests are changing how we approach OSA screening. These advancements are technological upgrades and a new way of thinking that offers more personalized, accessible, and data-driven approaches. As we explore these innovations, we must understand what and how they work and their implications in the broader context of sleep medicine's future. Let's see how deep this rabbit hole goes.
The Rise of Wearables, Nearables, and Smart Mattresses
Wearables
Everyone these days is tracking their sleep. Even the barista at my local coffee shop shows me her sleep data for insights. With advancements in technology, sleep-tracking devices such as rings, bracelets, and headbands have become increasingly accurate, offering valuable insights into the wearer's sleep health. Their ease of use and continuous monitoring make them a convenient option for preliminary screening of obstructive sleep apnea (OSA), even if they may not match traditional sleep studies' precision. With the rich data they provide, these devices have become invaluable tools for monitoring sleep health. Let's all reserve judgment until the results of studies like these have been published.
Nearables
Nearables are like wearables that don't like to cuddle; when it's time to sleep, they want you to keep your distance. Devices like bedside monitors, smart home devices, and even your cell phone all qualify (yes, you should avoid cuddling with your phone at night!) By monitoring environmental factors and physiological signals, these devices can assess sleep quality and might even be able to screen for OSA without directly attaching to the body. The challenge lies in refining these technologies to ensure they offer reliable data that can be used in a clinical context.
Smart Mattresses
Considering what a typical mattress costs, it's hard to imagine a market for an even more advanced mattress. However, Smart Mattresses, including models that automatically elevate when snoring is detected, are on the rise (ba dum ching). These mattresses are embedded with sensors that can track a range of sleep metrics, potentially including indicators of OSA. The appeal is the integration of sleep monitoring into an object already central to the sleep experience, making the process as seamless as sleeping on a cloud. The accuracy and clinical relevance of data from smart mattresses are areas of ongoing development. Still, they promise a future where one's bed plays a crucial role in monitoring sleep health, including detecting the likelihood of OSA.
Author’s Prediction
The role of consumer hardware in OSA screening is expected to grow and evolve significantly in the coming years. As these technologies become more integrated with medical software and AI, they have the potential to revolutionize OSA screening, making it more accessible, patient-friendly, and a part of our daily lives. Our bedrooms could serve as the first line of defense in identifying and managing sleep disorders like OSA.
From EHR Analysis to AI-Powered Predictive Modeling
Retrospective EHR Sifting
The pendulum is swinging back. We had paper charts, where it didn't matter what anyone wrote because no one could read it anyway. Then we went to early (and sometimes current) Electronic Health Records, where you must click 17 times to confirm that the patient is not a smoker. And now, Artificial Intelligence (AI) and Machine Learning (ML) have revolutionized how EHRs are utilized in healthcare. In the context of OSA, AI algorithms can sift through vast EHR databases to identify undiagnosed cases. These algorithms analyze patterns in symptoms, diagnostic tests, and other health indicators that might have been overlooked. By correlating these data points with known OSA profiles, AI can flag individuals exhibiting potential signs of OSA but not formally diagnosed. This retrospective analysis is particularly valuable in uncovering cases in populations that might not typically present for sleep studies.
"Live" Guidance for Non-Sleep MDs
AI tools are increasingly being integrated into clinical software used by general practitioners, assisting non-sleep-specialized physicians during routine check-ups by providing real-time guidance on obstructive sleep apnea (OSA) risk assessment. With these tools, it's like having a sleep doctor standing behind every primary care physician, ready to assist. The AI system can analyze a patient's responses to general health questions, medical history, and physical examination findings, prompting the doctor to ask more in-depth sleep questions and ultimately consider OSA a differential diagnosis. This proactive approach enhances the likelihood of early detection and referral for specialized sleep studies, eventually leading to better patient outcomes.
Predictive Modeling Based on Current Health State
Without OSA, you can't spell . . . Nostradamus! (Wow, that was bad. Even for me). AI models are particularly adept at predictive analysis. By evaluating a patient's current state of health, including factors like weight, blood pressure, age, and family history, these models can predict the risk of developing OSA. The integration of machine learning algorithms with patient data enables the prediction of OSA even before symptoms become pronounced. This predictive capability is crucial for early intervention and can lead to improved patient outcomes.
Author’s Prediction
The potential of AI/ML in OSA screening is enormous. We can expect the development of more sophisticated models that can incorporate a broader range of data, including genetic information and lifestyle factors. These advancements could lead to personalized OSA risk assessments, more timely preventative measures, and tailored treatment plans. Furthermore, AI could revolutionize the continuous remote monitoring of patients, using medical and consumer technology to track sleep patterns and adjust treatment plans in real-time. The evolution of AI/ML will enhance the accuracy of OSA screening and transform the overall approach to sleep disorder management.
Molecular Insights and Advanced Imaging Techniques
Genetic, Blood, and Urine Testing
Someday, I’m going to walk into a doctor’s office, and they aren’t going to take some kind of fluid from me. No. No, they won’t. But that could be a good thing for OSA screening! Venturing into molecular diagnostics, genetic, blood, and urine testing offers a promising avenue for OSA screening. These tests could identify biomarkers associated with OSA, offering a glimpse into the body's internal workings. Imagine being able to predict the risk of OSA with a simple blood draw or urine test, much like checking the weather forecast. This approach could revolutionize early detection, enabling interventions before the condition exacerbates.
Cross-Sectional Imaging (CT/MRI)
Every go looking for your remote in your couch and find money? Well, what if OSA was that money? Cross-sectional imaging techniques such as CT and MRI scans provide a detailed view of the airway's structure. Like explorers mapping uncharted territories, these imaging modalities create internal maps of the throat and nasal passages. While these scans are typically used to assess traumatic injuries, inflammatory diseases, and some forms of cancer, they can potentially uncover the hidden anatomical contributors to OSA, prompting the non-sleep provider to look into OSA.
Nomogram
Using a nomogram in OSA assessment blends various patient factors into a comprehensive risk profile. It's like a finely tuned orchestra, where each instrument – or, in this case, clinical variable – contributes to the overall assessment. Or it can look like the guy’s back room in A Beautiful Mind. Either way, this tool simplifies the complex interplay of factors into a straightforward visual guide, aiding clinicians in evaluating the likelihood of OSA.
Author’s Prediction
In closing, as we explore the future of sleep medicine, it's clear that advancements in screening and assessment methods are on the horizon. Genetic, blood, and urine testing offer a promising avenue for OSA screening, potentially allowing us to predict the risk of OSA with a simple test, much like checking the weather forecast. Cross-sectional imaging techniques like CT and MRI scans are like explorers mapping uncharted territories in the airway, uncovering hidden anatomical contributors to OSA. Using a nomogram in OSA assessment is like a finely tuned orchestra, simplifying the complex interplay of factors into a visual guide for clinicians. With these tools and approaches, we're moving towards more efficient and effective ways of identifying and managing sleep disorders like OSA, bringing better sleep and health to all.
What’s Next?
As we come to the end of our exploration into the future of OSA screening, we find ourselves on unfamiliar ground, much like Kevin from Home Alone, who outsmarted burglars with creative traps. We're leading the way in developing innovative strategies to outsmart OSA in the rapidly evolving world of sleep medicine.
Evolving technology, AI-powered diagnostics, molecular insights, and advanced imaging techniques are turning points in approaching OSA screening. We're shifting from a reactive approach to a proactive strategy, detecting OSA before it progresses into serious health problems.
With each step, we're pushing the boundaries of what's possible in sleep medicine, improving wearables, integrating smart technology into our lives, and leveraging AI. Genetic, blood, urine testing, cross-sectional imaging, and nomograms offer exciting prospects. The future is bright and unpredictable (much like Kevin McCalister), but our commitment to improving lives remains constant. Keep the change, ya filthy animal.
