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	<title>pulse oximetry &#8211; Science</title>
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	<title>pulse oximetry &#8211; Science</title>
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		<title>Oxygen Surges During Sleep May Mark the Heart Risk Hiding in Central Sleep Apnea</title>
		<link>https://scienmag.com/oxygen-surges-during-sleep-may-mark-the-heart-risk-hiding-in-central-sleep-apnea/</link>
		
		<dc:creator><![CDATA[Ophelia Keating]]></dc:creator>
		<pubDate>Wed, 23 Sep 2026 23:08:35 +0000</pubDate>
				<category><![CDATA[Medicine]]></category>
		<category><![CDATA[cardiovascular outcomes]]></category>
		<category><![CDATA[central sleep apnea]]></category>
		<category><![CDATA[heart failure]]></category>
		<category><![CDATA[hypoxic burden]]></category>
		<category><![CDATA[intermittent hypoxia]]></category>
		<category><![CDATA[Oxidative stress]]></category>
		<category><![CDATA[oxygen overshoot burden]]></category>
		<category><![CDATA[oxygen saturation dynamics]]></category>
		<category><![CDATA[oxygen surges during sleep]]></category>
		<category><![CDATA[polysomnography]]></category>
		<category><![CDATA[pulse oximetry]]></category>
		<category><![CDATA[rebound oxygen in sleep apnea]]></category>
		<category><![CDATA[risk stratification]]></category>
		<category><![CDATA[sleep apnea and cardiovascular risk]]></category>
		<category><![CDATA[sleep apnea complications]]></category>
		<category><![CDATA[sleep cohort studies]]></category>
		<category><![CDATA[sleep disorder and heart health]]></category>
		<category><![CDATA[Sleep Heart Health Study]]></category>
		<category><![CDATA[sleep medicine and cardiovascular outcomes]]></category>
		<category><![CDATA[sleep study biomarkers]]></category>
		<category><![CDATA[sleep-disordered breathing]]></category>
		<category><![CDATA[sleep-related hypoxia]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=211114</guid>

					<description><![CDATA[A large cohort study finds that the cumulative rebound of oxygen saturation above baseline after breathing pauses, termed oxygen overshoot burden, independently predicts major adverse cardiovascular events in people with central sleep apnea but not obstructive sleep apnea.]]></description>
										<content:encoded><![CDATA[<p>For decades, sleep scientists have focused most of their attention on the drops in oxygen that punctuate the nights of people with sleep apnea. Now a large new analysis suggests that the other half of the story — the rebound, the surge of oxygen that floods back when breathing resumes — may be just as important, and perhaps more so, for identifying which patients are truly in cardiovascular danger. In a study published in the Journal of Clinical Sleep Medicine, researchers report that a measure they call oxygen overshoot burden, the cumulative amount by which blood oxygen saturation rises above a person&#8217;s stable baseline during sleep, is strongly linked to major adverse cardiovascular events in people with central sleep apnea, but not in those with the far more common obstructive form of the disorder.</p>
<p>The finding comes from a team led by Ali Azarbarzin of Brigham and Women&#8217;s Hospital and Harvard Medical School, working with colleagues at several institutions, including Atul Malhotra of the University of California, San Diego. The researchers pooled data from two of the most extensively characterized sleep cohorts in the world: the Sleep Heart Health Study, which enrolled community-dwelling adults with an average age of 64, and the Osteoporotic Fractures in Men Study, known as MrOS, which followed older men with an average age of 76. Together the analysis included 7,530 participants, roughly 47 percent of whom were men in the combined framing of the two cohorts, each of whom had undergone overnight polysomnography with continuous pulse oximetry.</p>
<p>The technical concept at the heart of the study is deceptively simple. Every apnea episode, whether central or obstructive, produces a fall in oxygen saturation followed by a recovery. Conventional metrics such as the apnea-hypopnea index count how often these events occur, and more recent work has quantified the hypoxic burden, meaning the cumulative depth and duration of the desaturations themselves. Oxygen overshoot burden flips the perspective: it measures the area under the curve of oxygen saturation above baseline, capturing how far and how long the blood oxygen climbs back — and sometimes beyond — after each event. The researchers computed this overshoot against two reference points, a stable baseline recorded during sleep and, in secondary analyses, a baseline recorded during quiet wakefulness, to confirm that the signal was not an artifact of how the baseline was chosen.</p>
<p>Over a median follow-up of nearly nine years — 8.92 years — the cohorts recorded 2,258 major adverse cardiovascular events, a composite that captures the kind of outcomes that matter most to patients: heart attacks, heart failure episodes, strokes, and cardiovascular death. When the team modeled oxygen overshoot burden as a continuous variable, they found that higher burden was associated with increased cardiovascular risk across the population, but the association was markedly stronger among individuals who exhibited any central apneas during their sleep studies. The interaction was statistically significant for both the sleep baseline and the wakefulness baseline calculations, with p values of 0.003 and 0.02 respectively, suggesting the finding is robust to how the reference point is defined.</p>
<p>The most striking results emerged when the researchers stratified participants by diagnosis and by overshoot burden. People with central sleep apnea whose oxygen overshoot burden was at or above the cohort median experienced a dramatically elevated rate of cardiovascular events: 54.6 percent of them suffered a major adverse cardiovascular event during follow-up, compared with 25.6 percent of controls. After adjustment for a comprehensive set of covariates, the hazard ratio was 1.45, with a 95 percent confidence interval of 1.16 to 1.82 and a p value of 0.001. In contrast, three other groups showed cardiovascular risk that was statistically comparable to the controls: patients with central sleep apnea but low overshoot burden, and patients with obstructive sleep apnea whether their overshoot burden was high or low.</p>
<p>That last contrast is what makes the study potentially paradigm-shifting. Obstructive sleep apnea, caused by the physical collapse of the upper airway, and central sleep apnea, in which the brain temporarily stops sending the signals that drive breathing, have long been lumped together in clinical scoring systems that count respiratory events without much regard to their mechanism. Yet the new data suggest that the cardiovascular consequences of the two disorders may travel along different physiological paths, and that the overshoot of oxygen after each pause in breathing may be a signature of the central form that carries particular danger. The result held up even after the researchers adjusted for the apnea-hypopnea index, the central apnea index, loop gain — a measure of the instability of the respiratory control system — and the hypoxic burden, indicating that oxygen overshoot captures risk information that these established metrics do not.</p>
<p>The biological rationale for the finding lies in oxidative stress. Repeated cycles of deoxygenation and reoxygenation, known as intermittent hypoxia followed by reoxygenation, are thought to generate reactive oxygen species in much the same way that reperfusion injury damages tissue after a blocked artery is reopened. Animal studies dating back to the early 1990s have shown that episodic hypoxia elevates blood pressure and drives inflammation and atherosclerosis, and human studies have documented oxidative stress, endothelial dysfunction, and vascular inflammation in sleep apnea patients. The overshoot may be the moment when this chemistry is most active: as oxygen floods back into blood that has just been depleted, the surge could catalyze the oxidative bursts that injure the vessel wall. Central sleep apnea, which is especially prevalent in patients with heart failure and is associated with unstable respiratory control and high loop gain, may produce particularly pronounced or repetitive overshoots, creating a vicious cycle in which the breathing disorder and the heart disease feed each other.</p>
<p>The clinical implications are substantial. Central sleep apnea has been a stubborn therapeutic problem: large randomized trials of adaptive servo-ventilation and continuous positive airway pressure in heart failure patients have produced mixed or sobering results, and the field has increasingly recognized that not all patients with the same diagnosis carry the same risk. By identifying a high-risk phenotype — central apnea with high oxygen overshoot — the study offers a potential tool for stratifying patients in future trials, and it raises the possibility that therapies aimed specifically at blunting the overshoot, whether through oxygen titration, ventilatory support, or phrenic nerve stimulation, could be tested in the patients most likely to benefit. Recent trials of nocturnal oxygen therapy and transvenous phrenic nerve stimulation are already probing this territory, and overshoot burden could become an endpoint or an enrollment criterion in the next generation of studies.</p>
<p>The authors are careful to note the limitations. The two cohorts are older and, in the case of MrOS, exclusively male, so the findings need validation in larger and more diverse populations. Pulse oximetry itself carries a known bias across skin pigmentation, a concern highlighted by prior research showing that oximeters can overestimate oxygen saturation in people with darker skin, which could affect the precision of overshoot measurements. The study is observational, so it demonstrates association rather than causation, and residual confounding cannot be fully excluded. Still, the size of the cohorts, the length of follow-up, the consistency of the signal across baseline definitions, and the specificity of the effect to central apnea make the result one of the most compelling pieces of evidence yet that the aftermath of each apnea — not just the event itself — shapes cardiovascular fate.</p>
<p>For patients and clinicians, the message is that the texture of sleep-disordered breathing matters, not merely its frequency. A night of breathing pauses that end in modest, controlled recoveries of oxygen appears very different from one in which each pause is followed by a dramatic rebound, and the difference may separate a benign pattern from a dangerous one. As the field moves toward physiological phenotyping of sleep apnea, oxygen overshoot burden joins hypoxic burden and loop gain in a growing toolkit of quantitative measures that promise to replace blunt event counts with a more precise picture of what is actually happening in the blood, the brainstem, and the heart. The next step, the researchers say, is validation — and, ultimately, interventional trials that test whether taming the overshoot can tame the risk.</p>
<p><strong>Subject of Research:</strong> Oxygen overshoot burden in central sleep apnea and its association with major adverse cardiovascular events</p>
<p><strong>Article Title:</strong> Oxygen overshoot burden of central sleep apnea and its association with cardiovascular outcomes</p>
<p><strong>Article References:</strong> Azarbarzin, A., McKane, S., Stone, K. L., Germany, R., Redline, S., &amp; Malhotra, A. (2026). Oxygen overshoot burden of central sleep apnea and its association with cardiovascular outcomes. <em>Journal of Clinical Sleep Medicine, 22</em>(1), Article 153. <a href="https://doi.org/10.1007/s44470-026-00161-0" rel="noopener noreferrer">https://doi.org/10.1007/s44470-026-00161-0</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.1007/s44470-026-00161-0" rel="noopener noreferrer">10.1007/s44470-026-00161-0</a></p>
<p><strong>Keywords:</strong> central sleep apnea, oxygen overshoot burden, cardiovascular outcomes, sleep-disordered breathing, oxidative stress, hypoxic burden, polysomnography, pulse oximetry, heart failure, intermittent hypoxia, risk stratification, Sleep Heart Health Study</p>
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		<post-id xmlns="com-wordpress:feed-additions:1">211114</post-id>	</item>
		<item>
		<title>India bears nearly a fifth of global infant deaths from congenital heart disease</title>
		<link>https://scienmag.com/india-bears-nearly-a-fifth-of-global-infant-deaths-from-congenital-heart-disease/</link>
		
		<dc:creator><![CDATA[Harold Sullivan]]></dc:creator>
		<pubDate>Sun, 20 Sep 2026 22:40:12 +0000</pubDate>
				<category><![CDATA[Technology and Engineering]]></category>
		<category><![CDATA[congenital heart disease]]></category>
		<category><![CDATA[Congenital heart disease in India]]></category>
		<category><![CDATA[economic burden]]></category>
		<category><![CDATA[economic impact of infant deaths]]></category>
		<category><![CDATA[global burden of congenital heart defects]]></category>
		<category><![CDATA[global burden of disease]]></category>
		<category><![CDATA[global comparison of infant mortality]]></category>
		<category><![CDATA[health inequity]]></category>
		<category><![CDATA[healthcare challenges in India]]></category>
		<category><![CDATA[healthcare disparities in India]]></category>
		<category><![CDATA[India]]></category>
		<category><![CDATA[India neonatal mortality rates]]></category>
		<category><![CDATA[infant mortality]]></category>
		<category><![CDATA[infant mortality from birth defects]]></category>
		<category><![CDATA[long-term effects of congenital heart defects]]></category>
		<category><![CDATA[neonatal care]]></category>
		<category><![CDATA[neonatal mortality]]></category>
		<category><![CDATA[newborn screening]]></category>
		<category><![CDATA[pediatric cardiology]]></category>
		<category><![CDATA[pediatric heart care in India]]></category>
		<category><![CDATA[pediatric research]]></category>
		<category><![CDATA[pulse oximetry]]></category>
		<category><![CDATA[survival rates of congenital heart defects]]></category>
		<category><![CDATA[trends in congenital heart disease]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=203612</guid>

					<description><![CDATA[A new 31-year analysis finds India accounted for about 18 percent of global congenital heart disease infant deaths, with mortality declining more slowly than worldwide rates and economic losses reaching an estimated 11.7 billion dollars in 2021.]]></description>
										<content:encoded><![CDATA[<p>Congenital heart defects, the most common birth anomalies worldwide, claim the lives of roughly 180,000 to 200,000 newborns in India every year, and a sweeping new analysis suggests the country is losing ground in the fight against a largely survivable condition. Using three decades of data from the Global Burden of Disease 2021 study, researchers have quantified for the first time how India&#8217;s progress on heart-related infant mortality has lagged behind the rest of the world, and what that failure costs the nation in economic terms.</p>
<p>The study, published in Pediatric Research by Ramesh Vidavalur of Cayuga Medical Center and Weill Cornell Medical College, Ramesh Agarwal of the All India Institute of Medical Sciences in New Delhi, and Vinod K. Bhutani of Stanford University School of Medicine, examined trends in congenital heart disease related infant and neonatal mortality in India from 1990 to 2021. The findings are stark: of the approximately 8.6 million infants worldwide who died from congenital heart defects over that 31-year period, about 1.5 million were Indian, representing roughly 18 percent of the entire global burden.</p>
<p>Congenital heart defects affect approximately 9 per 1,000 live births in India, a prevalence consistent with global estimates but applied to one of the world&#8217;s largest birth cohorts. Because most critical lesions manifest within the first days or weeks of life, congenital heart disease has become an increasingly visible share of India&#8217;s residual infant mortality as other causes, such as infections and prematurity complications, decline. Yet the analysis shows the country&#8217;s response has not kept pace.</p>
<p>Between 1990 and 2021, India&#8217;s congenital heart disease related neonatal mortality declined at an annual rate of just 1.5 percent, significantly slower than the global rate of 2.2 percent per year. That gap, compounded over three decades, means the relative weight of congenital heart disease within India&#8217;s infant mortality profile has grown even as absolute numbers of deaths have fallen.</p>
<p>The segmental analysis reveals a more troubling pattern beneath the long-term trend. Progress stagnated almost entirely between 2003 and 2013, a decade in which mortality reduction essentially flatlined. Only in recent years did the pace of decline recover, with a nearly threefold acceleration observed between 2019 and 2021. The researchers suggest this late acceleration may reflect expanding neonatal care infrastructure and growing recognition of critical congenital heart disease, but they caution that the gains remain fragile and unevenly distributed.</p>
<p>Indeed, subnational analysis identified substantial inequities in mortality reduction across Indian states. States with stronger health systems, better access to pediatric cardiac surgery, and more developed newborn screening programs achieved far greater declines than those where diagnosis is often delayed until infants arrive at referral centers in critical condition. Prior studies from South India have shown that transport delays alone dramatically worsen outcomes for newborns with heart disease, a problem concentrated in lower-income and rural regions.</p>
<p>The economic toll is enormous. Applying human capital and value of statistical life frameworks, the authors estimated that congenital heart disease related infant deaths cost India approximately 11.7 billion US dollars in lost economic value in 2021 alone, with a plausible range of 9 to 12 billion dollars. Each infant death from a treatable cardiac defect represents not only a family tragedy but also decades of lost productive capacity, underscoring that investment in early detection and surgical capacity is not merely a health priority but an economic one.</p>
<p>The contrast with high-income countries is instructive. In the United States, the rollout of mandatory pulse oximetry screening for critical congenital heart disease in newborn nurseries has been associated with measurable reductions in early infant cardiac deaths. Randomized and observational evidence has also shown that prenatal diagnosis substantially lowers the risk of death from cardiovascular collapse before planned surgery. India has validated pulse oximetry screening in its own newborn populations and issued national consensus guidelines on the timing of intervention, but implementation across public facilities remains patchy.</p>
<p>The authors argue that sustaining and accelerating the recent gains will require system-level reform on several fronts simultaneously: expanding pediatric cardiology and cardiac surgery training, improving service delivery in public healthcare facilities where most Indian children are treated, strengthening national surveillance so that the true burden is no longer obscured by sparse mortality data, and building longitudinal follow-up for children who survive initial interventions. Kerala&#8217;s population-based approach to congenital heart disease offers one domestic model of what coordinated, state-level planning can achieve.</p>
<p>As India pursues its sustainable development targets for child survival, the study makes clear that congenital heart disease is no longer a marginal contributor that can be deferred. With nearly one in five global deaths from these defects occurring in India, closing the gap between Indian and global rates of improvement could save tens of thousands of lives each year and unlock billions of dollars in economic value, provided the political will matches the scale of the problem.</p>
<p><strong>Subject of Research:</strong> Trends and economic impact of infant mortality from congenital heart disease in India, 1990–2021</p>
<p><strong>Article Title:</strong> Burden, trends and economic impact of infant mortality from congenital heart diseases in India, 1990–2021</p>
<p><strong>Article References:</strong> Vidavalur, R., Agarwal, R., &amp; Bhutani, V. K. (2026). Burden, trends and economic impact of infant mortality from congenital heart diseases in India, 1990–2021. <em>Pediatric Research</em>. <a href="https://doi.org/10.1038/s41390-026-05430-5" rel="noopener noreferrer">https://doi.org/10.1038/s41390-026-05430-5</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.1038/s41390-026-05430-5" rel="noopener noreferrer">10.1038/s41390-026-05430-5</a></p>
<p><strong>Keywords:</strong> congenital heart disease, infant mortality, neonatal mortality, India, Global Burden of Disease, pediatric cardiology, economic burden, newborn screening, health inequity, pulse oximetry, neonatal care, Pediatric Research</p>
]]></content:encoded>
					
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">203612</post-id>	</item>
		<item>
		<title>Night-Time Oxygen Dips Double Metabolic Syndrome Risk in Lean Adults</title>
		<link>https://scienmag.com/night-time-oxygen-dips-double-metabolic-syndrome-risk-in-lean-adults/</link>
		
		<dc:creator><![CDATA[Daisy Hatcher]]></dc:creator>
		<pubDate>Sun, 20 Sep 2026 21:53:58 +0000</pubDate>
				<category><![CDATA[Medicine]]></category>
		<category><![CDATA[abdominal obesity]]></category>
		<category><![CDATA[age-related differences in sleep-related health risks]]></category>
		<category><![CDATA[cardiometabolic risk]]></category>
		<category><![CDATA[connection between nighttime hypoxia and cardiovascular risk]]></category>
		<category><![CDATA[dyslipidemia]]></category>
		<category><![CDATA[hypertriglyceridemia]]></category>
		<category><![CDATA[impact of sleep apnea on metabolism]]></category>
		<category><![CDATA[Japanese adults]]></category>
		<category><![CDATA[Japanese cohort sleep study]]></category>
		<category><![CDATA[lean adults and metabolic health]]></category>
		<category><![CDATA[long-term effects of poor sleep breathing]]></category>
		<category><![CDATA[metabolic syndrome]]></category>
		<category><![CDATA[metabolic syndrome risk factors]]></category>
		<category><![CDATA[nocturnal intermittent hypoxia]]></category>
		<category><![CDATA[nocturnal oxygen desaturation]]></category>
		<category><![CDATA[obesity-independent metabolic disturbances]]></category>
		<category><![CDATA[obstructive sleep apnea]]></category>
		<category><![CDATA[oxygen desaturation index]]></category>
		<category><![CDATA[prevention of metabolic syndrome through sleep health]]></category>
		<category><![CDATA[prospective cohort]]></category>
		<category><![CDATA[pulse oximetry]]></category>
		<category><![CDATA[role of oxygen saturation in metabolic disease]]></category>
		<category><![CDATA[sleep-disordered breathing]]></category>
		<category><![CDATA[Toon Health Study]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=203288</guid>

					<description><![CDATA[A five-year Japanese cohort study finds that nocturnal oxygen desaturation roughly doubles the risk of developing metabolic syndrome in adults under 65, even without abdominal obesity.]]></description>
										<content:encoded><![CDATA[<p>A poor night&#8217;s breathing could quietly reshape your metabolism long before your waistline betrays you. A new prospective cohort study from Japan suggests that even in adults without abdominal obesity, repeated episodes of nocturnal oxygen desaturation—the hallmark of sleep-disordered breathing—roughly double the risk of developing metabolic syndrome within five years, but only in people under the age of 65. The findings, published in the International Journal of Obesity, challenge the long-standing assumption that the metabolic consequences of disrupted nighttime breathing are inseparable from excess body fat.</p>
<p>Metabolic syndrome is a cluster of interrelated risk factors—abdominal obesity, elevated triglycerides, low high-density lipoprotein cholesterol, high blood pressure, and elevated fasting glucose—that together markedly increase the likelihood of type 2 diabetes, cardiovascular disease, and stroke. Clinically, it is often treated as a condition of the overweight and sedentary, and screening strategies frequently hinge on waist circumference. Yet previous research, including a meta-analysis showing that obstructive sleep apnea predicts metabolic syndrome independently of obesity, has hinted that the airway and the metabolism are entangled in ways that body size alone cannot explain.</p>
<p>The new study, led by Yuko Kato of the Department of Public Health at Juntendo University Graduate School of Medicine, together with Ai Ikeda, Hadrien Charvat, Kiyohide Tomooka, Koutatsu Maruyama, Isao Saito, and senior author Takeshi Tanigawa, set out to disentangle that relationship. The team drew on participants of the Toon Health Study, an ongoing community-based cohort in Ehime, Japan, and focused on 647 adults who, at baseline, had neither metabolic syndrome nor abdominal obesity, defined by Japanese and Asia-Pacific criteria as a waist circumference below 90 centimeters in men and below 80 centimeters in women. This deliberately lean starting population allowed the researchers to isolate the effect of nighttime oxygen fluctuations from the confounding influence of central fat.</p>
<p>To quantify intermittent hypoxia—the recurring cycles of falling and recovering blood oxygen that occur when the upper airway collapses during sleep—the researchers used overnight pulse oximetry and calculated the 3% oxygen desaturation index, or ODI, the number of times per hour that blood oxygen saturation drops by at least 3%. A threshold of five desaturation events per hour separated participants into those with and without meaningful nocturnal intermittent hypoxia. The team then followed the cohort for a median of 5.0 years, reassessing metabolic syndrome and each of its components at the five-year follow-up survey using modified National Cholesterol Education Program Adult Treatment Panel III criteria adapted for Asian populations.</p>
<p>Because relatively rare outcomes and conventional logistic regression can inflate risk estimates, the investigators employed modified Poisson regression, a method that yields more directly interpretable risk ratios, with Firth-type penalization to stabilize estimates in the presence of sparse data. Critically, they stratified all analyses by age, comparing adults younger than 65 with those aged 65 and older—a decision grounded in prior evidence that the cardiovascular and metabolic hazards of sleep-disordered breathing appear to attenuate with advancing age, perhaps because older adults who survive with the condition represent a selected, more resilient population.</p>
<p>The results were striking in the younger stratum. Among adults under 65, those with a 3% ODI of five or higher had more than double the risk of developing metabolic syndrome over five years compared with their peers who breathed steadily through the night, with a risk ratio of 2.10 and a 95% confidence interval of 1.18 to 3.76. The pattern extended to individual components: nocturnal intermittent hypoxia conferred a 2.17-fold higher risk of newly developing abdominal obesity (95% CI 1.42–3.33), a 2.01-fold higher risk of low HDL cholesterol (95% CI 1.02–3.96), and a 2.41-fold higher risk of hypertriglyceridemia (95% CI 1.35–4.30). In the older age group, by contrast, no statistically significant association emerged between oxygen desaturation and incident metabolic syndrome or any of its components.</p>
<p>The component-level findings carry particular biological weight. Elevated triglycerides and reduced HDL cholesterol are the lipid fingerprints of metabolic dyslipidemia, and experimental work has long suggested a causal pathway: in lean mice, intermittent hypoxia alone induces hyperlipidemia, and in humans, nocturnal hypoxemia has been independently linked to dyslipidemia irrespective of obesity. Mechanistically, each cycle of desaturation and reoxygenation resembles ischemia-reperfusion injury at the tissue level, generating reactive oxygen species, activating inflammatory pathways, and stressing adipose tissue itself. Adipocytes respond by releasing pro-inflammatory cytokines and altered adipokine profiles, including disturbed leptin signaling, which in turn promotes hepatic very-low-density lipoprotein production and peripheral insulin resistance. Intermittent hypoxia also activates the sympathetic nervous system and the renin-angiotensin system, raising blood pressure and compounding cardiovascular strain.</p>
<p>Perhaps the most provocative result is the link between nighttime oxygen dips and the later emergence of abdominal obesity in people who began the study without it. This raises the question of directionality that has haunted the field for decades—the proverbial chicken-and-egg problem of whether visceral fat causes sleep apnea or sleep apnea cultivates visceral fat. By restricting the analysis to participants free of abdominal obesity at baseline, the study provides longitudinal support for the latter possibility: disordered nighttime breathing appears capable of initiating the central fat accumulation that defines the metabolic syndrome, rather than merely riding alongside it.</p>
<p>The age stratification adds an important nuance with clinical implications. If intermittent hypoxia accelerates metabolic deterioration primarily in midlife, then undiagnosed sleep-disordered breathing in younger, lean adults may represent a hidden reservoir of future cardiometabolic disease—one that current screening practices, which often target older or heavier patients, could easily miss. Pulse oximetry screening has known limitations, and the ODI is an imperfect proxy for full polysomnographic diagnosis, but the present findings suggest that a simple overnight oximetry measure may identify metabolically vulnerable individuals years before standard criteria flag them. Whether treating sleep-disordered breathing with continuous positive airway pressure can interrupt this trajectory remains debated; randomized evidence in metabolic syndrome has been mixed, and the authors note that earlier intervention, particularly in younger adults, may be where therapy has the greatest chance of altering risk.</p>
<p>The study&#8217;s strengths include its prospective design, its use of an objective physiological exposure measure rather than self-reported snoring, its rigorous adjudication of metabolic syndrome, and its focus on a population deliberately free of central adiposity. Limitations temper the conclusions: the cohort was community-based and Japanese, raising questions of generalizability to other ethnic groups in whom both obesity thresholds and sleep apnea prevalence differ; the five-year follow-up captured incident disease but not longer-term trajectories; and residual confounding by diet, alcohol, and detailed sleep habits cannot be excluded. The authors acknowledge support from JSPS KAKENHI grant 22H00496 and declare no competing interests. Still, the message is clear and increasingly well supported: the metabolic toll of ragged nighttime breathing does not require an expanded waistline to begin, and age is not merely a passive bystander but a decisive modifier of that risk. For millions of lean adults who snore, gasp, or desaturate nightly without knowing it, the oxygen monitor may see what the bathroom scale cannot.</p>
<p><strong>Subject of Research:</strong> Association of nocturnal intermittent hypoxia with incident metabolic syndrome in non-obese Japanese adults</p>
<p><strong>Article Title:</strong> Effects of nocturnal intermittent hypoxia on metabolic syndrome in Japanese adults without abdominal obesity</p>
<p><strong>Article References:</strong> Kato, Y., Ikeda, A., Charvat, H., Tomooka, K., Maruyama, K., Saito, I., &amp; Tanigawa, T. (2026). Effects of nocturnal intermittent hypoxia on metabolic syndrome in Japanese adults without abdominal obesity. <em>International Journal of Obesity</em>. <a href="https://doi.org/10.1038/s41366-026-02228-7" rel="noopener noreferrer">https://doi.org/10.1038/s41366-026-02228-7</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.1038/s41366-026-02228-7" rel="noopener noreferrer">10.1038/s41366-026-02228-7</a></p>
<p><strong>Keywords:</strong> nocturnal intermittent hypoxia, metabolic syndrome, oxygen desaturation index, obstructive sleep apnea, abdominal obesity, dyslipidemia, hypertriglyceridemia, prospective cohort, Japanese adults, Toon Health Study, cardiometabolic risk, pulse oximetry</p>
]]></content:encoded>
					
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">203288</post-id>	</item>
		<item>
		<title>Oxygen Overshoot in Sleep Apnea Traces Flags Cardiovascular Risk</title>
		<link>https://scienmag.com/oxygen-overshoot-in-sleep-apnea-traces-flags-cardiovascular-risk/</link>
		
		<dc:creator><![CDATA[Ophelia Keating]]></dc:creator>
		<pubDate>Sun, 20 Sep 2026 19:02:24 +0000</pubDate>
				<category><![CDATA[Medicine]]></category>
		<category><![CDATA[autonomic surges]]></category>
		<category><![CDATA[cardiovascular risk]]></category>
		<category><![CDATA[cardiovascular risk in sleep apnea]]></category>
		<category><![CDATA[central sleep apnea]]></category>
		<category><![CDATA[central sleep apnea biomarkers]]></category>
		<category><![CDATA[Cheyne-Stokes respiration]]></category>
		<category><![CDATA[hypoxic burden]]></category>
		<category><![CDATA[loop gain]]></category>
		<category><![CDATA[Oxidative stress]]></category>
		<category><![CDATA[oximetry metrics beyond apnea-hypopnea index]]></category>
		<category><![CDATA[oxygen overshoot]]></category>
		<category><![CDATA[pulse oximetry]]></category>
		<category><![CDATA[pulse oximetry in sleep studies]]></category>
		<category><![CDATA[Sleep apnea]]></category>
		<category><![CDATA[sleep apnea oxygen overshoot]]></category>
		<category><![CDATA[sleep disorder risk factors]]></category>
		<category><![CDATA[Sleep Heart Health Study]]></category>
		<category><![CDATA[sleep oxygen saturation analysis]]></category>
		<category><![CDATA[sleep research cardiovascular health]]></category>
		<category><![CDATA[sleep study biomarkers for heart disease]]></category>
		<category><![CDATA[sleep study prognostics]]></category>
		<category><![CDATA[sleep-related cardiovascular events]]></category>
		<category><![CDATA[ventilatory control]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=201448</guid>

					<description><![CDATA[A large cohort study links high oxygen overshoot burden in central sleep apnea to elevated cardiovascular risk, though experts caution the signal may mark unstable ventilatory and autonomic control rather than cause oxidative harm.]]></description>
										<content:encoded><![CDATA[<p>Sleep scientists have spent decades staring at the downward slopes of the overnight oximetry trace, counting the dips in blood oxygen that define sleep apnea. A new analysis argues that the most telling information may lie in the opposite direction: the moments when oxygen saturation climbs back and, in some patients, rises above the person&#8217;s own stable-sleep baseline before settling. This upward excursion, known as oxygen overshoot, is a familiar feature of Cheyne-Stokes respiration, the waxing-and-waning breathing pattern seen most often in central sleep apnea and heart failure. In a large community-based study, researchers have now quantified the cumulative burden of these overshoots and found that it identifies a subgroup of patients with central sleep apnea who face a dramatically elevated risk of major adverse cardiovascular events. The finding is generating excitement because it suggests that a routine pulse oximetry recording, already collected in every sleep laboratory, contains prognostic information that conventional metrics such as the apnea-hypopnea index have been missing.</p>
<p>The study, led by Azarbarzin and colleagues and published in the Journal of Clinical Sleep Medicine, drew on 7,530 participants from two well-established cohort studies, the Sleep Heart Health Study and the Osteoporotic Fractures in Men Study, known as MrOS. Over nearly nine years of follow-up, 2,258 major adverse cardiovascular events occurred in this population. The investigators computed an oxygen overshoot burden for each participant: the cumulative area under the oxygen saturation curve that lies above an individual&#8217;s stable-sleep baseline, normalized for total sleep time. This is a deliberately individualized measure. Rather than comparing every patient against a fixed cutoff, the analysis anchors the signal to each person&#8217;s own resting saturation during uneventful sleep, so that even small relative rises above the personal baseline accumulate into a meaningful summary of nightly physiological stress.</p>
<p>The headline result is striking. Among participants with central sleep apnea and high overshoot burden, 54.6 percent experienced a major adverse cardiovascular event during follow-up, compared with 25.6 percent of control participants, corresponding to an adjusted hazard ratio of 1.45. Crucially, central sleep apnea with low overshoot burden carried no elevated risk relative to controls, and no corresponding association appeared in obstructive sleep apnea. The relationship survived statistical adjustment for the apnea-hypopnea index, the central apnea index, hypoxic burden, and, in the MrOS cohort, an estimate of loop gain, the control-system parameter that describes how vigorously breathing responds to disturbances in blood gases. That specificity is intriguing: it suggests the overshoot signal is not merely a proxy for how often someone stops breathing, but may capture something distinct about the instability of their ventilatory control.</p>
<p>The authors and commentators have proposed an intuitive biological explanation rooted in oxidative stress. The cycle of desaturation and reoxygenation that characterizes sleep apnea resembles ischemia-reperfusion injury, and repeated swings are thought to generate reactive oxygen species, inflammation, and vascular damage. Hypoxic burden, which integrates the depth and duration of event-related desaturation, already predicts cardiovascular outcomes better than a simple count of respiratory events, lending weight to the idea that the shape of the oxygen trace carries mechanistic information. Extending that logic above the baseline line is tempting: if falling oxygen is harmful, perhaps overshooting oxygen is harmful too, and the cumulative area of overshoot might quantify a dose of oxidative injury delivered night after night.</p>
<p>Yet a careful reading of the physiology counsels caution before accepting that interpretation. Oxygen overshoot as measured here is a relative oximetry signal, not demonstrated hyperoxia. A rise in peripheral oxygen saturation above a person&#8217;s stable-sleep baseline does not establish an elevated arterial partial pressure of oxygen, nor does it demonstrate increased tissue oxygen exposure. The study provides no mechanistic pathway, no oxidative biomarker measurements, and no bench or animal evidence showing that this specific above-baseline signal causes oxidative injury. Evidence from the intermittent hypoxia and reoxygenation literature cannot simply be transferred to this different signal. Indeed, previous work in obstructive sleep apnea found that greater post-event saturation overshoot was associated with lower nocturnal glucose, a pattern that argues against harm and even hints at benefit. Treating the oxygen rise itself as the causal exposure is, for now, premature.</p>
<p>A more plausible reading is that the oximetric overshoot is the visible tail of a much larger ventilatory and autonomic response. When an apnea terminates, the accumulated carbon dioxide and chemoreflex drive produce a vigorous recovery breath; the resulting hypocapnia is a direct signature of unstable ventilatory control, which is precisely the physiology that generates central sleep apnea and Cheyne-Stokes respiration in the first place. Human studies of apnea have documented marked sympathetic nerve activation and blood pressure surges around the termination of each event, followed by vagal modulation tied to lung inflation during the recovery phase. These autonomic oscillations, repeated hundreds of times a night, offer a credible route to myocardial infarction, arrhythmia, and stroke that does not require a modest rise in saturation to be intrinsically toxic. On this view, overshoot burden is a marker of the force of each recovery, not a poison in its own right.</p>
<p>This interpretation also exposes an important analytical gap in the new study. Adjusting for event frequency and hypoxic burden does not establish that overshoot is independent of the severity of each respiratory event. A longer or more severe apnea accumulates more hypercapnia, more chemoreflex stimulation, more arousal-related and sympathetic activation, and a longer loss of the vagal restraint normally provided by lung inflation. Those stimuli can then generate a larger recovery breath and a larger oxygen overshoot, and desaturation depth alone does not fully represent them. Consistent with this, work in obstructive sleep apnea has shown that ventilatory burden, a measure of the effort expended against collapsed airways, predicts cardiovascular outcomes and explains much of the variation in hypoxic burden. Oxygen overshoot may play an analogous role in central sleep apnea, summarizing a hidden physiological load that conventional indices leave unmeasured, without being the injurious agent itself.</p>
<p>Residual cardiac confounding remains another live possibility. In older community cohorts, central sleep apnea and Cheyne-Stokes respiration often reflect underlying cardiac dysfunction, elevated left-sided filling pressures, and prolonged circulation time, rather than mediating the cardiovascular consequences of those conditions. Heart failure identified through self-report and clinical records may miss subclinical disease, so some of the apparent association between overshoot burden and events could reflect undiagnosed cardiac impairment that both destabilizes breathing control and drives outcomes. Adjustment for loop gain in one cohort helps address the ventilatory-instability pathway, but detailed cardiac phenotyping, with objective measures of structure and function, is still needed before the direction of the arrow can be declared with confidence.</p>
<p>Two further cautions temper clinical translation. The central sleep apnea subgroup comprised only 303 participants, so confidence intervals around the headline event proportions deserve as much attention as the proportions themselves, and the findings require replication in larger and more diverse samples. The demonstration that a subject-specific baseline outperformed a fixed threshold of saturation at or above 96 percent confirms that the result depends on small relative differences in the oximetry signal, which places a premium on signal quality and measurement precision. The cohorts were 88 percent White, and known differential pulse-oximeter error by skin pigmentation is relevant to any saturation-based metric, although its effect on an above-baseline area calculation is currently unknown and warrants direct study.</p>
<p>The path forward is clear enough. The next study should measure event duration, airflow, respiratory effort, carbon dioxide, arousals, and event-level autonomic responses alongside oximetry, with detailed cardiac phenotyping and representative recruitment, and then test whether oxygen overshoot adds prognostic information once those features are accounted for. Until that work is done, oxygen overshoot burden should be regarded as a promising risk marker, a way of reading the recovery half of the apnea cycle that standard metrics ignore, rather than a demonstrated oxidative mechanism or a validated treatment target. Even so, the study is a reminder that the familiar oximetry trace still holds unexploited information, and that the line above the dips may matter as much as the dips themselves.</p>
<p><strong>Subject of Research:</strong> Oxygen overshoot burden measured on overnight oximetry traces in central sleep apnea and its association with major adverse cardiovascular events.</p>
<p><strong>Article Title:</strong> Above the line: oxygen overshoot in the oximetry trace</p>
<p><strong>Article References:</strong> Manuel, A. R. G. (2026). Above the line: oxygen overshoot in the oximetry trace. <em>Journal of Clinical Sleep Medicine, 22</em>(1), Article 169. <a href="https://doi.org/10.1007/s44470-026-00183-8" rel="noopener noreferrer">https://doi.org/10.1007/s44470-026-00183-8</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.1007/s44470-026-00183-8" rel="noopener noreferrer">10.1007/s44470-026-00183-8</a></p>
<p><strong>Keywords:</strong> central sleep apnea, oxygen overshoot, pulse oximetry, Cheyne-Stokes respiration, cardiovascular risk, hypoxic burden, ventilatory control, autonomic surges, oxidative stress, Sleep Heart Health Study, loop gain, sleep apnea</p>
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		<post-id xmlns="com-wordpress:feed-additions:1">201448</post-id>	</item>
		<item>
		<title>Twelve-Minute Step Test Predicts Altitude Sickness Risk Through Machine Learning</title>
		<link>https://scienmag.com/twelve-minute-step-test-predicts-altitude-sickness-risk-through-machine-learning/</link>
		
		<dc:creator><![CDATA[Teresa Odom]]></dc:creator>
		<pubDate>Sun, 13 Sep 2026 02:32:38 +0000</pubDate>
				<category><![CDATA[Medicine]]></category>
		<category><![CDATA[acute mountain sickness]]></category>
		<category><![CDATA[acute mountain sickness early detection]]></category>
		<category><![CDATA[altitude sickness prediction]]></category>
		<category><![CDATA[Cardiorespiratory fitness]]></category>
		<category><![CDATA[high altitude]]></category>
		<category><![CDATA[high altitude illness risk assessment]]></category>
		<category><![CDATA[hypoxia]]></category>
		<category><![CDATA[hypoxia risk prediction tools]]></category>
		<category><![CDATA[K-means clustering]]></category>
		<category><![CDATA[Lake Louise Score]]></category>
		<category><![CDATA[low-cost screening for mountain sickness]]></category>
		<category><![CDATA[Machine learning]]></category>
		<category><![CDATA[machine learning in medical diagnosis]]></category>
		<category><![CDATA[oxygen saturation]]></category>
		<category><![CDATA[physiological response to exercise at altitude]]></category>
		<category><![CDATA[physiological screening]]></category>
		<category><![CDATA[predictive modeling for altitude adaptation]]></category>
		<category><![CDATA[pulse oximetry]]></category>
		<category><![CDATA[rapid altitude change health risk management]]></category>
		<category><![CDATA[rapid ascent]]></category>
		<category><![CDATA[remote health monitoring for mountain sickness]]></category>
		<category><![CDATA[step test]]></category>
		<category><![CDATA[travel health screening for high-altitude exposure]]></category>
		<category><![CDATA[twelve-minute step test]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=200872</guid>

					<description><![CDATA[A low-cost, twelve-minute step test combined with k-means clustering accurately stratified young adults into acute mountain sickness-susceptible and non-susceptible groups before rapid ascent to 3650 meters.]]></description>
										<content:encoded><![CDATA[<p>A simple twelve-minute step test, combined with a machine learning algorithm that most people could run on a laptop, may soon identify who is likely to develop acute mountain sickness before they ever set foot at high altitude. In a study published in <em>Physiological Reports</em>, researchers report that by measuring how healthy young adults respond to a standard low-altitude exercise challenge, they were able to sort them into two physiological groups that closely matched who went on to suffer from AMS after a rapid flight from near sea level to Lhasa, at 3650 meters. The findings point toward a practical, low-cost screening strategy for the growing millions of lowlanders who travel, work, or commute rapidly to elevations above 2500 meters.</p>
<p>Acute mountain sickness is far more than an inconvenience. Headache, dizziness, nausea, vomiting, and fatigue can degrade judgment and performance, and in severe cases the condition can progress to high-altitude cerebral edema or high-altitude pulmonary edema, both of which are life threatening. As modern transportation makes it possible to fly from Beijing to the Tibetan plateau in under five hours, the number of people exposed to sudden, severe hypoxia has risen sharply. Yet the tools available to predict who will fall ill remain frustratingly limited, often requiring hypoxic gas generators, hypobaric chambers, blood biomarkers, or expensive imaging equipment that is unrealistic for field deployment.</p>
<p>The research team, drawn from Tsinghua University and collaborating institutions, recruited 48 healthy low-altitude residents aged 18 to 31 years with no high-altitude exposure in the preceding year. After strict screening for cardiovascular disease, chronic respiratory conditions, hypertension, and medications affecting cardiopulmonary function, 44 participants completed the full protocol. At 50 meters above sea level, each volunteer performed a standardized step test involving three minutes of seated rest, five minutes of stepping at 22.5 steps per minute on a platform 35 centimeters high for women and 40 centimeters for men, and four minutes of seated recovery. Throughout the protocol, a finger-clip pulse oximeter continuously recorded heart rate and peripheral oxygen saturation, while investigators monitored pulse waveforms to discard any artifactual readings.</p>
<p>Days later, the same participants boarded a commercial flight from Beijing to Lhasa, followed by a bus transfer to an experimental base, with all arrivals synchronized between 14:00 and 15:00 to minimize travel-fatigue confounds. The following morning, 18 hours after arrival, researchers administered the Lake Louise Score, the widely used self-report instrument for AMS, under blinded conditions in an independent space. Nineteen of the 44 participants met the diagnostic criteria for AMS, defined as a score of 3 or greater with headache plus at least one additional symptom.</p>
<p>Back at low altitude, the physiological data told a clear story. Variables captured during exercise and recovery, including estimated maximal oxygen uptake, exercise oxygen saturation, recovery oxygen saturation, exercise heart rate, recovery heart rate, and a composite step index, were all significantly correlated with subsequent AMS severity. In contrast, resting heart rate and resting oxygen saturation showed no meaningful association. This distinction matters physiologically: a resting baseline rarely exposes hidden limitations in ventilatory or cardiovascular compensation, whereas the added oxygen demand of exercise can reveal subtle deficits in how efficiently the body shuttles and utilizes oxygen, mimicking in miniature the stress that sudden altitude exposure imposes.</p>
<p>To translate these observations into a classification framework, the researchers applied k-means clustering, an unsupervised machine learning algorithm that groups individuals based on similarity of features without requiring predefined labels. After standardizing the data and reducing dimensionality with principal component analysis, the team tested multiple combinations of physiological variables. The strongest and most accurate stratification emerged from four indicators: estimated VO2max, exercise oxygen saturation, recovery oxygen saturation, and the step index. This combination yielded a silhouette coefficient of 0.767, indicating a strong two-cluster structure, and achieved a within-cohort accuracy of 93.18 percent when evaluated against the actual Lake Louise classifications.</p>
<p>Perhaps most striking was the sensitivity of the approach. All 19 participants who developed AMS were assigned to the AMS-susceptible cluster, and none of the 22 participants in the non-susceptible cluster developed symptoms. The authors are careful to note that these figures represent within-cohort clustering performance rather than validated predictive accuracy in an independent sample, and that no false-negative assignments in a new cohort cannot be guaranteed. Nevertheless, the effect sizes separating the two clusters were substantial, with Cohen&#8217;s d values ranging from 0.99 for estimated VO2max to 1.75 for the step index, and the Lake Louise Score itself differed markedly between clusters.</p>
<p>The team went to considerable lengths to confirm the clustering was not an artifact. Bootstrap resampling across 3000 replicates produced a median Jaccard stability index of 0.803, well within the range considered stable. Alternative algorithms including fuzzy c-means, partitioning around medoids, Gaussian mixture models, spectral clustering, and Ward hierarchical clustering broadly reproduced the same partition. When estimated VO2max was deliberately perturbed with realistic measurement error, or excluded entirely, the core structure persisted with only modest degradation. Sex, which some prior studies have linked to AMS susceptibility, showed no significant association with cluster membership, and statistically removing sex-related differences in estimated fitness left every participant in their original cluster.</p>
<p>The most influential single variable turned out to be the step index, a simple composite derived from recovery heart rates and exercise duration. Though modest alone, it combined powerfully with exercise oxygenation measures to separate the two physiological phenotypes. The authors suggest this reflects the fundamental importance of cardiorespiratory reserve: people whose bodies recover quickly from submaximal exertion and who maintain oxygen saturation under load appear better equipped to handle the abrupt hypoxic burden of rapid ascent. Three participants classified as susceptible but who scored below the AMS threshold may represent individuals with genuinely compromised reserves or, alternatively, conservative symptom self-reporting that underestimated their true Lake Louise Scores.</p>
<p>The implications for public health and occupational medicine are considerable. Mountaineers, military personnel, railway and construction workers, pilgrims, and ordinary tourists all stand to benefit from a screening method that requires nothing more than a step platform, a pulse oximeter, and twelve minutes of time. Unlike hypoxic chamber tests or blood-based omics panels, the protocol is easily standardized and could plausibly be administered at worksites, travel clinics, or recruitment centers. The authors emphasize that the approach remains exploratory and requires validation in larger, more diverse cohorts spanning different ages, health statuses, ascent profiles, and altitude targets, and that severe outcomes such as high-altitude cerebral or pulmonary edema were not represented in this young, healthy sample. Still, the study demonstrates that meaningful physiological structure emerges from a test simple enough to be administered almost anywhere, offering a glimpse of a future in which altitude illness risk can be identified and mitigated before the first symptom ever appears.</p>
<p><strong>Subject of Research:</strong> Prediction of acute mountain sickness susceptibility using low-altitude step test data and unsupervised machine learning clustering</p>
<p><strong>Article Title:</strong> Clustering analysis of acute mountain sickness susceptibility among young adults during rapid ascent using low‐altitude step test data</p>
<p><strong>Article References:</strong> Clustering analysis of acute mountain sickness susceptibility among young adults during rapid ascent using low‐altitude step test data. (n.d.). <a href="https://doi.org/10.14814/phy2.71091" rel="noopener noreferrer">https://doi.org/10.14814/phy2.71091</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.14814/phy2.71091" rel="noopener noreferrer">10.14814/phy2.71091</a></p>
<p><strong>Keywords:</strong> acute mountain sickness, step test, k-means clustering, hypoxia, high altitude, machine learning, oxygen saturation, cardiorespiratory fitness, Lake Louise Score, rapid ascent, pulse oximetry, physiological screening</p>
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		<post-id xmlns="com-wordpress:feed-additions:1">200872</post-id>	</item>
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