Data-Driven Phenotyping of Central Disorders of Hypersomnolence With Unsupervised Clustering

Background and ObjectivesRecent studies fueled doubts as to whether all currently defined central disorders of hypersomnolence are stable entities, especially narcolepsy type 2 and idiopathic hypersomnia. New reliable biomarkers are needed, and the question arises of whether current diagnostic criteria of hypersomnolence disorders should be reassessed. The main aim of this data-driven observational study was to see whether data-driven algorithms would segregate narcolepsy type 1 and identify more reliable subgrouping of individuals without cataplexy with new clinical biomarkers.MethodsWe used agglomerative hierarchical clustering, an unsupervised machine learning algorithm, to identify distinct hypersomnolence clusters in the large-scale European Narcolepsy Network database. We included 97 variables, covering all aspects of central hypersomnolence disorders such as symptoms, demographics, objective and subjective sleep measures, and laboratory biomarkers. We specifically focused on subgrouping of patients without cataplexy. The number of clusters was chosen to be the minimal number for which patients without cataplexy were put in distinct groups.ResultsWe included 1,078 unmedicated adolescents and adults. Seven clusters were identified, of which 4 clusters included predominantly individuals with cataplexy. The 2 most distinct clusters consisted of 158 and 157 patients, were dominated by those without cataplexy, and among other variables, significantly differed in presence of sleep drunkenness, subjective difficulty awakening, and weekend-week sleep length difference. Patients formally diagnosed as having narcolepsy type 2 and idiopathic hypersomnia were evenly mixed in these 2 clusters.DiscussionUsing a data-driven approach in the largest study on central disorders of hypersomnolence to date, our study identified distinct patient subgroups within the central disorders of hypersomnolence population. Our results contest inclusion of sleep-onset REM periods in diagnostic criteria for people without cataplexy and provide promising new variables for reliable diagnostic categories that better resemble different patient phenotypes. Cluster-guided classification will result in a more solid hypersomnolence classification system that is less vulnerable to instability of single features

Positive airway pressure (PAP) treatment reduces glycated hemoglobin (HbA1c) levels in obstructive sleep apnea patients with concomitant weight loss: Longitudinal data from the ESADA

Patients with obstructive sleep apnea (OSA) are at increased risk of developing metabolic disease such as diabetes. The effects of positive airway pressure on glycemic control are contradictory. We therefore evaluated the change in glycated hemoglobin (HbA1c) in a large cohort of OSA patients after long-term treatment with positive airway pressure. HbA1c levels were assessed in a subsample of the European Sleep Apnea Database [n=1608] at baseline and at long-term follow up with positive airway pressure therapy (mean 378.9±423.0 days). In a regression analysis, treatment response was controlled for important confounders. Overall, HbA1c decreased from 5.98±1.01% to 5.93±0.98% (p=0.001). Patient subgroups with a more pronounced HbA1c response included patients with diabetes (−0.15±1.02, p=0.019), those with severe OSA baseline (−0.10±0.68, p=0.005), those with morbid obesity (−0.20±0.81, p<0.001). The strongest HbA1c reduction was observed in patients with a concomitant weight reduction >5 kilos (−0.38±0.99, p<0.001). In robust regression analysis, severe OSA (p=0.038) and morbid obesity (p=0.005) at baseline, and weight reduction >5 kilos (p<0.001) during follow up were independently associated with a reduction of HbA1c following PAP treatment. In contrast, PAP treatment alone without weight reduction was not associated with significant Hb1Ac reduction. In conclusion, positive airway pressure therapy is associated with HbA1c reduction in patients with severe OSA, in morbidly obese patients. and most obviously in those with significant weight lost during the follow-up. Our study underlines the importance to combine positive airway pressure use with adjustments in lifestyle to substantially modify metabolic complications in OSA

Arterial bicarbonate is associated with hypoxic burden and uncontrolled hypertension in obstructive sleep apnea - The ESADA cohort

Objective: Blood bicarbonate concentration plays an important role for obstructive sleep apnea (OSA) patients to maintain acid-base balance. We investigated the association between arterial standard bicarbonate ([HCO3-]) and nocturnal hypoxia as well as comorbid hypertension in OSA. Methods: A cross-sectional analysis of 3329 patients in the European Sleep Apnea Database (ESADA) was performed. Arterial blood gas analysis and lung function test were performed in conjunction with polysomnographic sleep studies. The 4% oxygen desaturation index (ODI), mean and minimum oxygen saturation (SpO2), and percentage of time with SpO2 below 90% (T90%) were used to reflect nocturnal hypoxic burden. Arterial hypertension was defined as a physician diagnosis of hypertension with ongoing antihypertensive medication. Hypertensive patients with SBP/DBP below or above 140/90 mmHg were classified as controlled-, uncontrolled hypertension, respectively. Results: The [HCO3-] level was normal in most patients (average 24.0 ± 2.5 mmol/L). ODI, T90% increased whereas mean and minimum SpO2 decreased across [HCO3-] tertiles (ANOVA, p = 0.030, <0.001, <0.001, and <0.001, respectively). [HCO3-] was independently associated with ODI, mean SpO2, minimum SpO2, and T90% after adjusting for confounders (β value [95%CI]: 1.21 [0.88–1.54], −0.16 [-0.20 to −0.11], −0.51 [-0.64 to −0.37], 1.76 [1.48–2.04], respectively, all p < 0.001). 1 mmol/L elevation of [HCO3-] was associated with a 4% increased odds of uncontrolled hypertension (OR: 1.04 [1.01–1.08], p = 0.013). Conclusion: We first demonstrated an independent association between [HCO3-] and nocturnal hypoxic burden as well as uncontrolled hypertension in OSA patients. Bicarbonate levels as an adjunctive measure provide insight into the pathophysiology of hypertension in OSA

Idling for Decades: A European Study on Risk Factors Associated with the Delay Before a Narcolepsy Diagnosis

Purpose: Narcolepsy type-1 (NT1) is a rare chronic neurological sleep disorder with excessive daytime sleepiness (EDS) as usual first and cataplexy as pathognomonic symptom. Shortening the NT1 diagnostic delay is the key to reduce disease burden and related low quality of life. Here we investigated the changes of diagnostic delay over the diagnostic years (1990–2018) and the factors associated with the delay in Europe. Patients and Methods: We analyzed 580 NT1 patients (male: 325, female: 255) from 12 European countries using the European Narcolepsy Network database. We combined machine learning and linear mixed-effect regression to identify factors associated with the delay. Results: The mean age at EDS onset and diagnosis of our patients was 20.9±11.8 (mean ± standard deviation) and 30.5±14.9 years old, respectively. Their mean and median diagnostic delay was 9.7±11.5 and 5.3 (interquartile range: 1.7−13.2 years) years, respectively. We did not find significant differences in the diagnostic delay over years in either the whole dataset or in individual countries, although the delay showed significant differences in various countries. The number of patients with short (≤2-year) and long (≥13-year) diagnostic delay equally increased over decades, suggesting that subgroups of NT1 patients with variable disease progression may co-exist. Younger age at cataplexy onset, longer interval between EDS and cataplexy onsets, lower cataplexy frequency, shorter duration of irresistible daytime sleep, lower daytime REM sleep propensity, and being female are associated with longer diagnostic delay. Conclusion: Our findings contrast the results of previous studies reporting shorter delay over time which is confounded by calendar year, because they characterized the changes in diagnostic delay over the symptom onset year. Our study indicates that new strategies such as increasing media attention/awareness and developing new biomarkers are needed to better detect EDS, cataplexy, and changes of nocturnal sleep in narcolepsy, in order to shorten the diagnostic interval

Neuroimaging of Narcolepsy and Primary Hypersomnias

Advances in neuroimaging open up the possibility for new powerful tools to be developed that potentially can be applied to clinical populations to improve the diagnosis of neurological disorders, including sleep disorders. At present, the diagnosis of narcolepsy and primary hypersomnias is largely limited to subjective assessments and objective measurements of behavior and sleep physiology. In this review, we focus on recent neuroimaging findings that provide insight into the neural basis of narcolepsy and the primary hypersomnias Kleine-Levin syndrome and idiopathic hypersomnia. We describe the role of neuroimaging in confirming previous genetic, neurochemical, and neurophysiological findings and highlight studies that permit a greater understanding of the symptoms of these sleep disorders. We conclude by considering some of the remaining challenges to overcome, the existing knowledge gaps, and the potential role for neuroimaging in understanding the pathogenesis and clinical features of narcolepsy and primary hypersomnias

Sleepiness at the time of testing impairs olfactory performance

We aimed to investigate the differential roles of hypocretin versus dopamine dysfunction versus excessive daytime sleepiness (EDS) in the development of hyposmia. Olfaction in patients with Parkinson disease, restless leg syndrome, narcolepsy with cataplexy, EDS, and healthy controls was compared

Sleep apnoea management in Europe during the COVID-19 pandemic – Data from the European Sleep Apnoea Database (ESADA)

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Sleep and cardiometabolic comorbidities in the obstructive sleep apnoea–COPD overlap syndrome: data from the European Sleep Apnoea Database

Aim The impact of obstructive sleep apnoea (OSA)–COPD overlap syndrome (OVS) on sleep quality and cardiovascular outcomes has not been fully explored. We aimed to compare clinical and polysomnographic characteristics of patients with OVS versus patients with OSA, and to explore pathophysiological links between OVS and comorbidities. Study design and methods This cross-sectional analysis initially included data from 5600 patients with OSA and lung function in the European Sleep Apnoea Database. Two subgroups of patients with OSA (n=1018) or OVS (n=509) were matched (2:1) based on sex, age, body mass index and apnoea–hypopnea index at baseline. Results After matching, patients with OVS had more severe hypoxia, lower sleep efficiency and presented with higher prevalences of arterial hypertension, ischaemic heart disease and heart failure compared with patients with OSA. OVS was associated with a significant decrease in sleep efficiency (mean difference (β) −3.0%, 95% CI −4.7 to −1.3) and in nocturnal mean peripheral oxyhaemoglobin saturation ( S pO 2 ) (β −1.1%, 95% CI −1.5 to −0.7). Further analysis revealed that a decrease in forced expiratory volume in 1 s and arterial oxygen tension was related to a decrease in sleep efficiency and in mean nocturnal S pO 2 . A COPD diagnosis increased the odds of having heart failure by 1.75 (95% CI 1.15–2.67) and systemic hypertension by 1.36 (95% CI 1.07–1.73). Nocturnal hypoxia was strongly associated with comorbidities; the mean nocturnal S pO 2 and T90 (increase in time below S pO 2 of 90%) were associated with increased odds of systemic hypertension, diabetes and heart failure but the oxygen desaturation index was only related to hypertension and diabetes. Conclusion Patients with OVS presented with more sleep-related hypoxia, a reduced sleep quality and a higher risk for heart failure and hypertension