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Journal of Clinical Medicine May 2024Repetitive episodes of apnea and hypopnea during sleep in patients with obstructive sleep apnea (OSA) are known to increase the risk of atherosclerosis. Underlying...
Repetitive episodes of apnea and hypopnea during sleep in patients with obstructive sleep apnea (OSA) are known to increase the risk of atherosclerosis. Underlying obesity and related disorders, such as insulin resistance, are indirectly related to the development of atherosclerosis. In addition, OSA is independently associated with insulin resistance; however, data regarding this relationship are scarce in Japanese populations. This study aimed to examine the relationship between the severity of OSA and insulin resistance in a Japanese population. We analyzed the data of consecutive patients who were referred for polysomnography under clinical suspicion of developing OSA and who did not have diabetes mellitus or any cardiovascular disease. Multiple regression analyses were performed to determine the relationship between the severity of OSA and insulin resistance. The data from a total of 483 consecutive patients were analyzed. The median apnea-hypopnea index (AHI) was 40.9/h (interquartile range: 26.5, 59.1) and the median homeostasis model assessment for insulin resistance (HOMA-IR) was 2.00 (interquartile range: 1.25, 3.50). Multiple regression analyses revealed that the AHI, the lowest oxyhemoglobin saturation (SO), and the percentage of time spent on SO < 90% were independently correlated with HOMA-IR (an adjusted R-squared value of 0.01278821, = 0.014; an adjusted R-squared value of -0.01481952, = 0.009; and an adjusted R-squared value of 0.018456581, = 0.003, respectively). The severity of OSA is associated with insulin resistance assessed by HOMA-IR in a Japanese population.
PubMed: 38892846
DOI: 10.3390/jcm13113135 -
Respiratory Research Jun 2024Sleep-disordered breathing (SDB) is a major comorbidity in idiopathic pulmonary fibrosis (IPF) and is associated with a poor outcome. There is a lack of knowledge...
Treating sleep-disordered breathing of idiopathic pulmonary fibrosis patients with CPAP and nocturnal oxygen treatment. A pilot study : Sleep-disordered breathing treatment in IPF.
INTRODUCTION
Sleep-disordered breathing (SDB) is a major comorbidity in idiopathic pulmonary fibrosis (IPF) and is associated with a poor outcome. There is a lack of knowledge regarding the impact of SDB treatment on IPF. We assessed at one year: (1) the effect of CPAP and/or nocturnal oxygen therapy on IPF regarding lung function, blood mediators, and quality of life; (2) adherence to SDB treatment and SDB changes.
METHODOLOGY
This is a prospective study of consecutive newly diagnosed IPF patients initiating anti-fibrotic treatment. Lung function, polysomnography, blood tests and quality of life questionnaires were performed at inclusion and after one year. Patients were classified as obstructive sleep apnoea (OSA), central sleep apnoea (CSA), and sleep-sustained hypoxemia (SSH). SDB therapy (CPAP and/or nocturnal oxygen therapy) was initiated if needed.
RESULTS
Fifty patients were enrolled (36% had OSA, 22% CSA, and 12% SSH). CPAP was started in 54% of patients and nocturnal oxygen therapy in 16%. At one-year, polysomnography found improved parameters, though 17% of patients had to add nocturnal oxygen therapy or CPAP, while 33% presented SDB onset at this second polysomnography. CPAP compliance at one year was 6.74 h/night (SD 0.74). After one year, matrix metalloproteinase-1 decreased in OSA and CSA (p = 0.029; p = 0.027), C-reactive protein in OSA (p = 0.045), and surfactant protein D in CSA group (p = 0.074). There was no significant change in lung function.
CONCLUSIONS
Treatment of SBD with CPAP and NOT can be well tolerated with a high compliance. IPF patients may exhibit SDB progression and require periodic re-assessment. Further studies to evaluate the impact of SDB treatment on lung function and serological mediators are needed.
Topics: Humans; Continuous Positive Airway Pressure; Female; Male; Idiopathic Pulmonary Fibrosis; Pilot Projects; Aged; Prospective Studies; Sleep Apnea Syndromes; Oxygen Inhalation Therapy; Middle Aged; Treatment Outcome; Polysomnography; Quality of Life
PubMed: 38890648
DOI: 10.1186/s12931-024-02871-6 -
Scientific Reports Jun 2024Previous studies on sleep state misperception have objectively evaluated sleep status in special environments using polysomnography. There is a paucity of data from...
Previous studies on sleep state misperception have objectively evaluated sleep status in special environments using polysomnography. There is a paucity of data from studies that evaluated habitual sleep status in home environments. The present study aimed to investigate sleep state misperception in the home environment of patients with chronic insomnia using a lumbar-worn actigraphy to identify sleep habits associated with sleep state misperception severity. Thirty-one patients and 42 healthy volunteers were included in the insomnia and non-insomnia group, respectively. Participants recorded subjective assessments in sleep diaries, objective assessments with an actigraphy worn for 14 days, and self-assessments using questionnaires. Both groups had similar objective sleep ratings; however, insomnia group had significantly worse subjective ratings (total sleep time, wake after sleep onset, and sleep onset latency). A significant correlation was found between subjective and objective total sleep time scores in non-insomnia group but not in insomnia group. Insomnia group had earlier bedtimes, significantly longer bedtimes, and impaired daytime functioning (Sheehan Disability Scale score); additionally, they underestimated their total sleep time, particularly with earlier bedtimes and longer laying durations. Monitoring the sleep status and habits of individuals in home environments could be instrumental in identifying key points for targeted interventions on sleep hygiene and cognitive behavioral therapy for insomnia.
Topics: Humans; Sleep Initiation and Maintenance Disorders; Male; Female; Middle Aged; Adult; Sleep; Actigraphy; Surveys and Questionnaires; Polysomnography; Sleep Quality; Habits
PubMed: 38886489
DOI: 10.1038/s41598-024-64355-3 -
Sleep Medicine Jun 2024This research work was performed: (1) To assess the accessibility of in-laboratory polysomnography for individuals with spinal cord injury (SCI); (2) to evaluate the...
OBJECTIVES
This research work was performed: (1) To assess the accessibility of in-laboratory polysomnography for individuals with spinal cord injury (SCI); (2) to evaluate the validity of four screening questionnaires for sleep-related breathing disorders (SRBDs); and (3) to assess the association between anthropometric features and apnea-hypopnea index (AHI).
METHODS
An Environmental scan (E-scan) was performed in the province of Ontario, where all sleep clinics were invited to complete the E-scan survey. Furthermore, a cross-sectional study was performed at a rehabilitation hospital (Canada), where consecutive adults with subacute/chronic (>1 month) SCI were recruited. Using a home-based screening sleep test (HBSST), the validity of the Berlin, STOP, Medical Outcomes Study Sleep Scale [MOS-SS], and STOP-Bang screening questionnaires was assessed. The association between AHI and three features (i.e., neck circumference, body mass index [BMI] and oropharynx opening as assessed using the Modified Mallampati classification [MMC]) was evaluated.
RESULTS
According to the E-scan, access to polysomnography is limited for the SCI population in Ontario. Of the 28 participants with SCI (11 females, 17 males; mean age: 54.9 years) included in the cross-sectional study, 32.1 % were diagnosed with moderate-to-severe SRBD. The performance of the questionnaires was considered insufficient for screening of individuals living with SCI. AHI was not associated with neck circumference, BMI, or MMC.
CONCLUSIONS
Those results suggest that the use of a HBSST could overcome the barriers for individuals with SCI to access diagnostic testing of SRBDs. The use of screening questionnaires and risk assessment for SRBDs in the SCI population is unreliable.
PubMed: 38885542
DOI: 10.1016/j.sleep.2024.06.011 -
MedRxiv : the Preprint Server For... Jun 2024Atrial fibrillation (AF) is often asymptomatic and thus under-observed. Given the high risks of stroke and heart failure among patients with AF, early prediction and...
BACKGROUND
Atrial fibrillation (AF) is often asymptomatic and thus under-observed. Given the high risks of stroke and heart failure among patients with AF, early prediction and effective management are crucial. Importantly, obstructive sleep apnea is highly prevalent among AF patients (60-90%); therefore, electrocardiogram (ECG) analysis from polysomnography (PSG), a standard diagnostic tool for subjects with suspected sleep apnea, presents a unique opportunity for the early prediction of AF. Our goal is to identify individuals at a high risk of developing AF in the future from a single-lead ECG recorded during standard PSGs.
METHODS
We analyzed 18,782 single-lead ECG recordings from 13,609 subjects at Massachusetts General Hospital, identifying AF presence using ICD-9/10 codes in medical records. Our dataset comprises 15,913 recordings without a medical record for AF and 2,056 recordings from patients who were first diagnosed with AF between 1 day to 15 years after the PSG recording. The PSG data were partitioned into training, validation, and test cohorts. In the first phase, a signal quality index (SQI) was calculated in 30-second windows and those with SQI 0.95 were removed. From each remaining window, 150 hand-crafted features were extracted from time, frequency, time-frequency domains, and phase-space reconstructions of the ECG. A compilation of 12 statistical features summarized these window-specific features per recording, resulting in 1,800 features. We then updated a pre-trained deep neural network and data from the PhysioNet Challenge 2021 using transfer-learning to discriminate between recordings with and without AF using the same Challenge data. The model was applied to the PSG ECGs in 16-second windows to generate the probability of AF for each window. From the resultant probability sequence, 13 statistical features were extracted. Subsequently, we trained a shallow neural network to predict future AF using the extracted ECG and probability features.
RESULTS
On the test set, our model demonstrated a sensitivity of 0.67, specificity of 0.81, and precision of 0.3 for predicting AF. Further, survival analysis for AF outcomes, using the log-rank test, revealed a hazard ratio of 8.36 (p-value of 1.93 × 10 ).
CONCLUSIONS
Our proposed ECG analysis method, utilizing overnight PSG data, shows promise in AF prediction despite a modest precision indicating the presence of false positive cases. This approach could potentially enable low-cost screening and proactive treatment for high-risk patients. Ongoing refinement, such as integrating additional physiological parameters could significantly reduce false positives, enhancing its clinical utility and accuracy.
PubMed: 38883765
DOI: 10.1101/2024.06.04.24308444 -
Nature and Science of Sleep 2024The COVID-19 pandemic affected the utilization of various healthcare services differentially. Sleep testing services utilization (STU), including Home Sleep Apnea...
PURPOSE
The COVID-19 pandemic affected the utilization of various healthcare services differentially. Sleep testing services utilization (STU), including Home Sleep Apnea Testing (HSAT) and Polysomnography (PSG), were uniquely affected. We assessed the effects of the pandemic on STU and its recovery using the Veterans Health Administration (VHA) data.
PATIENTS AND METHODS
A retrospective cohort study from the VHA between 01/2019 and 10/2023 of veterans with age ≥ 50. We extracted STU data using Current Procedural Terminology codes for five periods based on STU and vaccination status: pre-pandemic (Pre-Pan), pandemic sleep test moratorium (Pan-Mor), and pandemic pre-vaccination (Pan-Pre-Vax), vaccination (Pan-Vax), and postvaccination (Pan-Post-Vax). We compared STU between intervals (Pre-Pan as the reference).
RESULTS
Among 261,371 veterans (63.7±9.6 years, BMI 31.9±6.0 kg/m², 80% male), PSG utilization decreased significantly during Pan-Mor (-56%), Pan-Pre-Vax (-61%), Pan-Vax (-42%), and Pan-Post-Vax (-36%) periods all compared to Pre-Pan. HSAT utilization decreased significantly during the Pan-Mor (-59%) and Pan-Pre-Vax (-9%) phases compared to the Pre-Pan and subsequently increased during Pan-Vax (+6%) and Pan-Post-Vax (-1%) periods. Over 70% of STU transitioned to HSAT, and its usage surged five months after the vaccine Introduction.
CONCLUSION
Sleep testing services utilization recovered differentially during the pandemic (PSG vs HSAT), including a surge in HSAT utilization post-vaccination.
PubMed: 38882925
DOI: 10.2147/NSS.S456214 -
Nature and Science of Sleep 2024Obstructive sleep apnea (OSA) is a respiratory disorder characterized by chronic intermittent hypoxia and fragmented sleep, leading to inflammatory response and...
INTRODUCTION
Obstructive sleep apnea (OSA) is a respiratory disorder characterized by chronic intermittent hypoxia and fragmented sleep, leading to inflammatory response and oxidative stress. However, the differences in immune inflammatory response in OSA patients with different severity remain unclear.
PURPOSE
This study aims to examine the differences in peripheral blood immune cells and their risk factors in OSA patients.
PATIENTS AND METHODS
A total of 277 snoring patients from the Sleep Respiratory Disorder Monitoring Center of Zhongnan Hospital of Wuhan University were recruited in this study. According to the diagnosis and severity criteria of OSA, the included patients were further divided into simple snoring, mild, moderate, and severe groups. Peripheral blood immune cell counts including white blood cells, neutrophils, lymphocytes, monocytes, eosinophils, basophils, red blood cells, platelets, and polysomnography indicators were collected from the patients.
RESULTS
Compared with simple snoring patients, the OSA patients had increased circular monocyte and basophil count levels. In addition, correlation analysis results indicated that monocyte count was positively associated with chronic obstructive pulmonary disease (COPD), smoking, apnea-hypopnea index (AHI), the longest apnea duration, and Oxygen desaturation index (ODI), and negatively correlated with average SpO in snoring patients. Finally, multiple linear regression analysis revealed that AHI, COPD, smoking, and maximum heart rate were independent predictors of monocyte count.
CONCLUSION
OSA patients had a significant increase in their peripheral blood monocyte count. AHI, COPD, smoking, and maximum heart rate were risk factors for increased peripheral blood monocyte count in OSA patients. These findings suggest that peripheral blood monocytes can be considered an inflammatory biomarker of OSA.
PubMed: 38882924
DOI: 10.2147/NSS.S458098 -
Nature and Science of Sleep 2024This study aimed to evaluate nocturnal sleep structure and anxiety, depression, and fatigue in patients with narcolepsy type 1 (NT1).
PURPOSE
This study aimed to evaluate nocturnal sleep structure and anxiety, depression, and fatigue in patients with narcolepsy type 1 (NT1).
METHODS
Thirty NT1 patients and thirty-five healthy controls were enrolled and evaluated using the Epworth sleepiness scale (ESS), Generalized Anxiety Disorder-7, Patient Health Questionnaire-9, Fatigue Severity Scale (FSS), polysomnography, multiple sleep latency test, and brain function state monitoring. Statistical analyses were performed using SPSS Statistics for Windows, version 23.0. Benjamini-Hochberg correction was performed to control the false discovery rate.
RESULTS
Apart from typical clinical manifestations, patients with NT1 are prone to comorbidities such as nocturnal sleep disorders, anxiety, depression, and fatigue. Compared with the control group, patients with NT1 exhibited abnormal sleep structure, including increased total sleep time ( =0.007), decreased sleep efficiency ( =0.002), shortening of sleep onset latency ( <0.001), elevated wake after sleep onset ( =0.002), increased N1% ( =0.006), and reduced N2%, N3%, and REM% ( =0.007, <0.001, =0.013). Thirty-seven percent of patients had moderate to severe obstructive sleep apnea-hypopnea syndrome. And sixty percent of patients were complicated with REM sleep without atonia. Patients with NT1 displayed increased anxiety propensity ( <0.001), and increased brain fatigue ( =0.020) in brain function state monitoring. FSS scores were positively correlated with brain fatigue ( <0.001) and mean sleep latency was inversely correlated with FSS scores and brain fatigue ( =0.013, =0.029). Additionally, ESS scores and brain fatigue decreased after 3 months of therapy (=0.012, =0.030).
CONCLUSION
NT1 patients had abnormal nocturnal sleep structures, who showed increased anxiety, depression, and fatigue. Excessive daytime sleepiness and fatigue improved after 3 months of treatment with methylphenidate hydrochloride prolonged-release tablets in combination with venlafaxine.
PubMed: 38873239
DOI: 10.2147/NSS.S452665 -
PCN Reports : Psychiatry and Clinical... Sep 2023Nocturnal eating behavior in patients with sleep-related eating disorder (SRED) is difficult to control and can become chronic, causing weight gain and psychological...
BACKGROUND
Nocturnal eating behavior in patients with sleep-related eating disorder (SRED) is difficult to control and can become chronic, causing weight gain and psychological distress. Here, we report a case of SRED comorbid with major depressive disorder successfully treated by switching from brotizolam to suvorexant, that is, from a benzodiazepine to an orexin receptor antagonist.
CASE PRESENTATION
A 25-year-old woman complained of night snacking with partial/complete amnesia and sleepwalking for 1 year. She had a diagnosis of major depressive disorder at age 20 and was on paroxetine and brotizolam for depression and insomnia. At 24 years of age, she experienced her second depressive episode, then her amnestic nocturnal eating became prominent. Even after improvement in depressive symptoms, she experienced uncontrollable nocturnal eating episodes every 2 days, resulting in weight gain of over 10 kg. After a partial amnestic eating episode following an awakening from stage N2 sleep was confirmed through video polysomnography, she was diagnosed with SRED. Considering her strong desire to resolve involuntary eating, we instructed her to discontinue brotizolam and start suvorexant. Subsequently, her nocturnal eating completely disappeared. She experienced rebound insomnia, which improved within 1 month. She was then continued on 10 mg of suvorexant and has not experienced nocturnal eating for 2 years.
CONCLUSION
This case highlights the importance of discontinuing benzodiazepines in the treatment of SRED, but also suggests the potential benefit of orexin receptor antagonists in the treatment of SRED. The efficacy of orexin receptor antagonists in idiopathic SRED should be tested in future studies.
PubMed: 38867814
DOI: 10.1002/pcn5.123 -
Nature and Science of Sleep 2024Body-worn accelerometers are commonly used to estimate sleep duration in population-based studies. However, since accelerometry-based sleep/wake-scoring relies on...
PURPOSE
Body-worn accelerometers are commonly used to estimate sleep duration in population-based studies. However, since accelerometry-based sleep/wake-scoring relies on detecting body movements, the prediction of sleep duration remains a challenge. The aim was to develop and evaluate the performance of a machine learning (ML) model to predict accelerometry-based sleep duration and to explore if this prediction can be improved by adding skin temperature data, circadian rhythm based on the estimated midpoint of sleep, and cyclic time features to the model.
PATIENTS AND METHODS
Twenty-nine adults (17 females), mean (SD) age 40.2 (15.0) years (range 17-70) participated in the study. Overnight polysomnography (PSG) was recorded in a sleep laboratory or at home along with body movement by two accelerometers with an embedded skin temperature sensor (AX3, Axivity, UK) positioned at the low back and thigh. The PSG scoring of sleep/wake was used as ground truth for training the ML model.
RESULTS
Based on pure accelerometer data input to the ML model, the specificity and sensitivity for predicting sleep/wake was 0.52 (SD 0.24) and 0.95 (SD 0.03), respectively. Adding skin temperature data and contextual information to the ML model improved the specificity to 0.72 (SD 0.20), while sensitivity remained unchanged at 0.95 (SD 0.05). Correspondingly, sleep overestimation was reduced from 54 min (228 min, limits of agreement range [LoAR]) to 19 min (154 min LoAR).
CONCLUSION
An ML model can predict sleep/wake periods with excellent sensitivity and moderate specificity based on a dual-accelerometer set-up when adding skin temperature data and contextual information to the model.
PubMed: 38863481
DOI: 10.2147/NSS.S452799