Clinical Research Achievements

We’ve just published our first preprint at Terra API Research! While reviewing the sleep literature, we identified a clear gap: almost no large-scale, global studies on year-round variation in sleep. Existing research suggested seasonal effects on sleep duration, but most studies were limited by small sample sizes, single-country focus, narrow latitude ranges, or subjective self-reports. We are in a unique position in that we have access to a large, diverse, and globally distributed data set, but we just had to find a way to tie nights to a location. The Terra API research team had a brilliant, collaborative, and innovative approach. We combined 185,000 anonymous, objectively measured nights of sleep from 697 individuals across 49 countries, with location data from activity sessions. Bayesian hierarchical models were applied to disentangle individual, country-level, and environmental effects. Key findings: - Sleep duration decreases consistently with increasing daylight (~4–5 minutes less per additional hour of daylight) - After accounting for individual and country baselines, calendar season explains surprisingly little - Despite vast differences in seasonal light exposure across latitudes, people at higher latitudes show no greater sensitivity to day-length changes - A large portion of the remaining variation appears at the country level — pointing to sociocultural factors playing a bigger role than latitude alone These results suggest that global sleep patterns are driven more by stable individual and national differences than by broad seasonal categories. This has real implications for interpreting seasonal effects in smaller, geographically limited studies and highlights the value of large-scale wearable data for circadian research. A massive thank you to the team, Faraaz Akhtar and Cameron Crawford. Looking forward to seeing what we can do next! Preprint link in comments. Curious to hear your thoughts: do you notice seasonal changes in your own sleep? #SleepResearch #WearableTechnology #BayesianModeling #GlobalHealth #CircadianRhythms #DataScience #TerraResearch

A large-scale study in Health Data Science (PMID: 40464054) found that poor sleep patterns were linked to 172 diseases, including dementia, Parkinson’s disease, diabetes, and kidney failure. Importantly, 92 of those diseases had more than 20% of their risk attributable to poor sleep traits, and in 42 conditions, risk at least doubled. While much prior research emphasized sleep duration, this work highlights the importance of sleep rhythm and regularity, showing that irregular bedtimes and disrupted circadian alignment may exert unique health effects. Qing Chen, PhD, co-lead author, noted: “Sleep regularity should be taken into consideration, or a number of diseases may be induced, even if sleep duration is adequate.” It is important to note that inadequate sleep is rarely an “isolated issue”. It can possibly be an indicator of chronic conditions. Practical steps can help: establishing a consistent bedtime, maintaining a cool and dark sleep environment, aligning with the day-night cycle, and seeking medical evaluation for persistent issues such as sleep apnea or insomnia. The study ultimately suggests that rhythm and regularity may matter even more than duration.

***Groundbreaking Sleep Study Reveals Unprecedented Insights into Sleep Patterns Across Age Groups*** I'm excited to share the results of a landmark sleep study presented at the recent Seville Sleep Conference. This collaborative effort between Stanford, UCSF, and Fullpower-AI has produced the largest-ever population-based assessment of sleep duration and architecture, analyzing over 7 million nights of sleep data. Key findings: • Sleep duration follows a U-shaped distribution across age groups, with middle-aged adults sleeping less than younger and older adults. • Deep sleep and REM sleep percentages decline with age, as expected. • Individuals with sleep apnea (AHI>5) show significantly reduced deep sleep across all age groups. Some highlights: • 20-25-year-olds: 431 minutes average sleep time, 15.9% deep sleep, 26% REM sleep • 50-55-year-olds: 413 minutes average sleep time, 14.3% deep sleep, 25.7% REM sleep • 80-85-year-olds: 420 minutes average sleep time, 13.1% deep sleep, 22.9% REM sleep This study provides crucial baseline data for understanding sleep patterns across the lifespan and the impact of sleep disorders. It underscores the importance of the 7-hour sleep recommendation and highlights how conditions like sleep apnea can significantly impact sleep quality. The scale and depth of this research, made possible by the Sleeptracker-AI platform, marks a significant advancement in sleep science. These findings will undoubtedly shape future research and clinical practice in sleep medicine. #SleepScience #HealthTech #AI #ResearchBreakthrough Citations: [1] https://sleeptracker.com [2] https://lnkd.in/gh_gshz3 [3] https://lnkd.in/g495VGwk [4] https://lnkd.in/g8patsXN [5] https://lnkd.in/g9c77TPj [6] https://lnkd.in/gjufJ2qC [7] https://lnkd.in/gTNtfnvh [8] https://lnkd.in/gNzvMJaa

"Imbalanced sleep increases mortality risk by 14–34%" Ungvari et al., (2025) systematically evaluates the relationship between sleep duration and all-cause mortality in adults, including sex specific differences. Key Points 1️⃣ Objective: Investigate how short (<7 hours) and long (≥9 hours) sleep durations impact all-cause mortality risk. Examine sex differences in these associations. Update and extend earlier meta analyses on sleep and mortality risk. 2️⃣ Methods: Included 79 cohort studies with adults aged 18+ and at least 1-year follow-up. Data pooled using random-effects meta-analysis. Subgroup analyses for men and women, and different sleep duration categories. Evaluated publication bias and used trial sequential analysis to test evidence robustness. 3️⃣ Main Findings: Short sleep duration (<7 h): Associated with a 14% increased risk of mortality (hazard ratio [HR] 1.14; 95% CI 1.10–1.18). Long sleep duration (≥9 h): Associated with a 34% increased mortality risk (HR 1.34; 95% CI 1.26–1.42). Both short and long sleep increased mortality risk for men and women, but long sleep had a stronger effect in women. Heterogeneity varied across studies, with stronger variability in long sleep results. Some evidence of publication bias in studies on long sleep and mortality, especially in men. 4️⃣ Biological and Health Implications: Chronic inadequate sleep accelerates biological aging. Insufficient sleep is linked to increased cardiovascular disease, cognitive decline, neurodegeneration , cancer risk, and metabolic disorders. Poor glymphatic clearance during sleep loss may promote Alzheimer’s pathology. Long sleep may reflect underlying health problems increasing mortality risk. 5️⃣ Sex Differences: Men showed slightly higher mortality risk connected with short sleep, potentially due to higher prevalence of risk factors like cardiovascular disease, sleep apnea, and lifestyle behaviours. Women had a more pronounced mortality risk associated with long sleep duration. 6️⃣ Public Health Significance: Sleep duration is a modifiable lifestyle factor linked to longevity. Emphasises importance of promoting healthy sleep habits as a public health priority. 7️⃣ Limitations & Future Directions: Many studies rely on self-reported sleep durations prone to bias. Variation in definitions for short and long sleep across studies. Residual confounding factors (e.g., socioeconomic status, pre-existing illnesses) could influence results. Calls for standardized sleep measurement and cause-specific mortality studies. ⚙️ Conclusion: The meta-analysis robustly confirms that sleep outside the recommended 7–8 hours per night (both short and long) significantly increases the risk of death, with different impacts by sex. Sleep duration is an important, modifiable factor for preventing premature death and supporting healthy aging.

Scientists have, for the first time, observed the brain’s self-cleaning system in real time during sleep. This process, known as the glymphatic system, helps remove waste products and toxins that accumulate throughout the day. During deep sleep, brain cells shrink slightly, allowing cerebrospinal fluid to flow more freely and flush out harmful proteins linked to neurological diseases. This cleansing activity is significantly more active during sleep than when we are awake. Studies show that poor sleep can disrupt this process, potentially increasing the risk of conditions like Alzheimer’s and other neurodegenerative disorders. The findings highlight why quality sleep is essential, not just for rest, but for maintaining long-term brain health and function. Understanding how the brain clears itself opens new possibilities for treating and preventing neurological diseases. It reinforces the idea that sleep is not a passive state, but a critical period of repair and maintenance. Prioritizing good sleep habits could be one of the simplest ways to protect your brain. Sources: Science Journal Nature Neuroscience National Institutes of Health (NIH) Journal of Neuroscience

Stanford University has unveiled a groundbreaking advancement in sleep research through the development of SleepFM, an advanced AI foundation model designed to leverage sleep data for forecasting future diseases. Sleep is intricately linked to brain, heart, respiratory, and metabolic health; however, traditional sleep studies, such as polysomnography (PSG), often face challenges in standardization and are underutilized. Researchers trained this AI model on approximately 585,000 hours of sleep recordings from around 65,000 individuals, utilizing various physiological signals including brain waves, heart rate, breathing, and muscle activity. Remarkably, from just one night of sleep, the model can predict 130 different health conditions. It excels in forecasting serious outcomes such as: - All-cause mortality - Dementia - Heart attack - Heart failure - Stroke - Chronic kidney disease - Atrial fibrillation The model either outperforms or matches specialized sleep-analysis tools and demonstrates effectiveness even on new datasets it was not specifically trained on. Key insight: Sleep possesses its own “language,” and large AI models can learn this language to facilitate early disease detection, scalable screening, and preventive healthcare. Bottom line: Your sleep patterns may indicate future disease risks long before symptoms manifest — and AI has the capability to decode this at scale. This research is published in Nature Medicine, titled "A multimodal sleep foundation model for disease prediction," available online since January 6, 2026. DOI: https://lnkd.in/gvWFAh6J

Scientists Capture Brain’s Self-Cleaning Process During Sleep in Real Time New research has provided the clearest view yet of how the brain cleans itself during sleep, revealing a dynamic process essential for long-term health. Using advanced ultrafast MRI technology, scientists have, for the first time, directly observed how fluids move through the brain while a person sleeps, offering critical insight into a function previously understood but never visualized in real time. The findings show that during sleep, the brain transitions into a different physiological state. While awake, blood flow is tightly regulated to support active neural processes. In contrast, sleep allows fluid movement to become more pronounced and less constrained. Water and cerebrospinal fluid begin to pulse and circulate more freely, creating a washing effect that helps remove metabolic waste accumulated during waking hours. This process is closely linked to the brain’s glymphatic system, which acts as a clearance mechanism for toxins, including proteins associated with neurodegenerative diseases. The enhanced fluid dynamics observed during sleep suggest that this system becomes significantly more active, effectively “taking out the trash” and maintaining neural health. The ability to observe these mechanisms directly represents a major technical and scientific milestone. It validates long-standing theories about the restorative function of sleep while providing measurable data on how and when these processes occur. This opens new avenues for studying sleep disorders and their connection to cognitive decline. The implications are substantial for both medicine and public health. Sleep is not merely restorative in a general sense; it is a critical maintenance cycle for the brain’s physical environment. Disruptions to this process could contribute to the buildup of harmful substances, potentially increasing the risk of conditions such as Alzheimer’s disease. As understanding deepens, sleep may become a central focus in preventative health strategies aimed at preserving cognitive function over time. I share daily insights with tens of thousands followers across defense, tech, and policy. If this topic resonates, I invite you to connect and continue the conversation. https://lnkd.in/gHPvUttw Keith King

Sleep – New study shows more than 850 million adults around the world are not getting enough sleep. Chronic #insomnia isn’t just a personal struggle - it’s a global health challenge. I’m proud to share new findings from a Resmed-sponsored recently published in Sleep Medicine Reviews. The study was conducted in collaboration with an international team of sleep scientists and clinicians via the #medXcloud group.    To our understanding, this is the first study to systematically estimate the global population prevalence of insomnia in adults by aggregating published prevalence data and applying standardized clinical definitions. 📊 Key findings:  * An estimated 852 million adults worldwide (16.2% of the adult population) experience clinically relevant insomnia.  * Nearly 415 million adults meet the criteria for severe insomnia.  * Insomnia is more prevalent in women across all age groups, with 18.9% of women affected vs. 13.4% of men.  * Insomnia is associated with a broad range of adverse outcomes, including:  Medical: cardiovascular disease, metabolic conditions, neurodegenerative disorders  * Mental health: depression, anxiety, chronic pain, substance misuse  * Quality of life: impaired functioning, poor well-being, and higher healthcare utilization  * Economic burden: increased payer costs, reduced workplace productivity, and elevated accident risk At Resmed, we believe sleep is not a luxury - it’s a biological necessity, on par with nutrition and physical activity. This study reinforces the urgent need for sleep health to be treated as a global public health priority. Thanks to our scientific colleagues at Resmed, Fatima Sert Kuniyoshi, PhD and Dr Leonie Maurer, as well as our academic partners around the world, we are strengthening the global case for sleep - and helping drive awareness with the data and evidence that is needed to improve lives. 📄 Read the full study: https://lnkd.in/gtJjDfPv #SleepHealth #Insomnia #PublicHealth #ClinicalResearch #GlobalHealth #EvidenceBased #Resmed #InvestinRest #DataDrivenChange