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Journal of Global Health Dec 2023Unhealthy lifestyle and diet may contribute to the development of cardiovascular disease (CVD), but limited evidence exists regarding the association between sleep...
Interplay of sleep patterns and oxidative balance score on total cardiovascular disease risk: Insights from the National Health and Nutrition Examination Survey 2005-2018.
BACKGROUND
Unhealthy lifestyle and diet may contribute to the development of cardiovascular disease (CVD), but limited evidence exists regarding the association between sleep patterns, oxidative stress-related exposures to diet and lifestyle, and CVD risk.
METHODS
We analysed data from 10 212 adults in the National Health and Nutrition Examination Survey (NHANES) database (2005-2018). Self-report questionnaires were used to collect data on sleep duration, sleepiness, and trouble sleeping, classified into three categories: healthy, intermediate, and poor sleep patterns. Healthy sleep was defined as sleeping seven to nine hours per night with no self-reported sleepiness or trouble sleeping, while intermediate and poor sleep patterns indicated one and two to three sleep problems, respectively. The oxidative balance score (OBS) was calculated based on twenty oxidative stress-related exposures to dietary and lifestyle factors, with a higher score indicating greater antioxidant exposure. Survey-based multivariable-adjusted regression analysis was conducted to examine the association of sleep patterns or OBS alone and combined with the total and specific CVD risk.
RESULTS
Participants with poor sleep patterns had a higher likelihood of developing CVD (odds ratio (OR) = 1.76; 95% confidence interval (CI) = 1.26-2.45, P < 0.05), while an inverse association was found between OBS and CVD risk (quartile (Q) 4 vs Q1: OR = 0.67; 95% CI = 0.47-0.94, P = 0.02, P for trend <0.05). There was an interaction between sleep patterns and OBS (P for interaction = 0.03). Participants with unhealthy (intermediate and poor) sleep patterns and pro-oxidant OBS (Q1 and Q2) were significantly associated with increased risk of total CVD (OR = 2.31; 95% CI = 1.42-3.74, P < 0.05), as well as angina and congestive heart failure, but not coronary heart disease (CHD). Stratified analysis showed that among individuals without hyperlipidaemia, participants with both unhealthy sleep patterns and pro-oxidant OBS exhibited a higher risk of CHD compared to those with healthy sleep patterns and antioxidative OBS.
CONCLUSIONS
Unhealthy sleep patterns and reduced oxidative balance are positively associated with an increased risk of overall and specific CVD. Interventions that target healthy sleep habits and antioxidant-rich diets and lifestyles may be important for reducing the risk of CVD.
Topics: Adult; Humans; Nutrition Surveys; Cardiovascular Diseases; Antioxidants; Reactive Oxygen Species; Risk Factors; Sleepiness; Oxidative Stress; Sleep
PubMed: 38085249
DOI: 10.7189/jogh.14.04170 -
The Cochrane Database of Systematic... Jun 2022Many people with cancer experience moderate to severe pain that requires treatment with strong opioids, such as oxycodone and morphine. Strong opioids are, however, not... (Review)
Review
BACKGROUND
Many people with cancer experience moderate to severe pain that requires treatment with strong opioids, such as oxycodone and morphine. Strong opioids are, however, not effective for pain in all people, neither are they well tolerated by all people. The aim of this review was to assess whether oxycodone is associated with better pain relief and tolerability than other analgesic options for adults with cancer pain. This is an updated Cochrane review previously published in 2017.
OBJECTIVES
To assess the effectiveness and tolerability of oxycodone by any route of administration for pain in adults with cancer.
SEARCH METHODS
For this update, we searched the Cochrane Central Register of Controlled Trials (CENTRAL) in the Cochrane Library, MEDLINE and MEDLINE In-Process (Ovid), Embase (Ovid), Science Citation Index, Conference Proceedings Citation Index - Science (ISI Web of Science), BIOSIS (ISI), and PsycINFO (Ovid) to November 2021. We also searched four trial registries, checked the bibliographic references of relevant studies, and contacted the authors of the included studies. We applied no language, date, or publication status restrictions.
SELECTION CRITERIA
We included randomised controlled trials (parallel-group or cross-over) comparing oxycodone (any formulation or route of administration) with placebo or an active drug (including oxycodone) for cancer background pain in adults by examining pain intensity/relief, adverse events, quality of life, and participant preference.
DATA COLLECTION AND ANALYSIS
Two review authors independently sifted the search, extracted data and assessed the included studies using standard Cochrane methodology. We meta-analysed pain intensity data using the generic inverse variance method, and pain relief and adverse events using the Mantel-Haenszel method, or summarised these data narratively along with the quality of life and participant preference data. We assessed the overall certainty of the evidence using GRADE.
MAIN RESULTS
For this update, we identified 19 new studies (1836 participants) for inclusion. In total, we included 42 studies which enrolled/randomised 4485 participants, with 3945 of these analysed for efficacy and 4176 for safety. The studies examined a number of different drug comparisons. Controlled-release (CR; typically taken every 12 hours) oxycodone versus immediate-release (IR; taken every 4-6 hours) oxycodone Pooled analysis of three of the four studies comparing CR oxycodone to IR oxycodone suggest that there is little to no difference between CR and IR oxycodone in pain intensity (standardised mean difference (SMD) 0.12, 95% confidence interval (CI) -0.1 to 0.34; n = 319; very low-certainty evidence). The evidence is very uncertain about the effect on adverse events, including constipation (RR 0.71, 95% CI 0.45 to 1.13), drowsiness/somnolence (RR 1.03, 95% CI 0.69 to 1.54), nausea (RR 0.85, 95% CI 0.56 to 1.28), and vomiting (RR 0.66, 95% CI 0.38 to 1.15) (very low-certainty evidence). There were no data available for quality of life or participant preference, however, three studies suggested that treatment acceptability may be similar between groups (low-certainty evidence). CR oxycodone versus CR morphine The majority of the 24 studies comparing CR oxycodone to CR morphine reported either pain intensity (continuous variable), pain relief (dichotomous variable), or both. Pooled analysis indicated that pain intensity may be lower (better) after treatment with CR morphine than CR oxycodone (SMD 0.14, 95% CI 0.01 to 0.27; n = 882 in 7 studies; low-certainty evidence). This SMD is equivalent to a difference of 0.27 points on the Brief Pain Inventory scale (0-10 numerical rating scale), which is not clinically significant. Pooled analyses also suggested that there may be little to no difference in the proportion of participants achieving complete or significant pain relief (RR 1.02, 95% CI 0.95 to 1.10; n = 1249 in 13 studies; low-certainty evidence). The RR for constipation (RR 0.75, 95% CI 0.66 to 0.86) may be lower after treatment with CR oxycodone than after CR morphine. Pooled analyses showed that, for most of the adverse events, the CIs were wide, including no effect as well as potential benefit and harm: drowsiness/somnolence (RR 0.88, 95% CI 0.74 to 1.05), nausea (RR 0.93, 95% CI 0.77 to 1.12), and vomiting (RR 0.81, 95% CI 0.63 to 1.04) (low or very low-certainty evidence). No data were available for quality of life. The evidence is very uncertain about the treatment effects on treatment acceptability and participant preference. Other comparisons The remaining studies either compared oxycodone in various formulations or compared oxycodone to different alternative opioids. None found any clear superiority or inferiority of oxycodone for cancer pain, neither as an analgesic agent nor in terms of adverse event rates and treatment acceptability. The certainty of this evidence base was limited by the high or unclear risk of bias of the studies and by imprecision due to low or very low event rates or participant numbers for many outcomes.
AUTHORS' CONCLUSIONS
The conclusions have not changed since the previous version of this review (in 2017). We found low-certainty evidence that there may be little to no difference in pain intensity, pain relief and adverse events between oxycodone and other strong opioids including morphine, commonly considered the gold standard strong opioid. Although we identified a benefit for pain relief in favour of CR morphine over CR oxycodone, this was not clinically significant and did not persist following sensitivity analysis and so we do not consider this important. However, we found that constipation and hallucinations occurred less often with CR oxycodone than with CR morphine; but the certainty of this evidence was either very low or the finding did not persist following sensitivity analysis, so these findings should be treated with utmost caution. Our conclusions are consistent with other reviews and suggest that, while the reliability of the evidence base is low, given the absence of important differences within this analysis, it seems unlikely that larger head-to-head studies of oxycodone versus morphine are justified, although well-designed trials comparing oxycodone to other strong analgesics may well be useful. For clinical purposes, oxycodone or morphine can be used as first-line oral opioids for relief of cancer pain in adults.
Topics: Adult; Analgesics, Opioid; Cancer Pain; Constipation; Humans; Morphine; Nausea; Neoplasms; Oxycodone; Pain; Quality of Life; Reproducibility of Results; Sleepiness; Vomiting
PubMed: 35679121
DOI: 10.1002/14651858.CD003870.pub7 -
Sensors (Basel, Switzerland) Jul 2021Drowsiness when in command of a vehicle leads to a decline in cognitive performance that affects driver behavior, potentially causing accidents. Drowsiness-related road...
Drowsiness when in command of a vehicle leads to a decline in cognitive performance that affects driver behavior, potentially causing accidents. Drowsiness-related road accidents lead to severe trauma, economic consequences, impact on others, physical injury and/or even death. Real-time and accurate driver drowsiness detection and warnings systems are necessary schemes to reduce tiredness-related driving accident rates. The research presented here aims at the classification of drowsy and non-drowsy driver states based on respiration rate detection by non-invasive, non-touch, impulsive radio ultra-wideband (IR-UWB) radar. Chest movements of 40 subjects were acquired for 5 m using a lab-placed IR-UWB radar system, and respiration per minute was extracted from the resulting signals. A structured dataset was obtained comprising respiration per minute, age and label (drowsy/non-drowsy). Different machine learning models, namely, Support Vector Machine, Decision Tree, Logistic regression, Gradient Boosting Machine, Extra Tree Classifier and Multilayer Perceptron were trained on the dataset, amongst which the Support Vector Machine shows the best accuracy of 87%. This research provides a ground truth for verification and assessment of UWB to be used effectively for driver drowsiness detection based on respiration.
Topics: Automobile Driving; Humans; Neural Networks, Computer; Respiratory Rate; Support Vector Machine; Wakefulness
PubMed: 34300572
DOI: 10.3390/s21144833 -
Revista de Neurologia Jul 2023Narcolepsy type 1 is a focal degenerative disease of the hypothalamus that selectively affects orexin (hypocretin)-producing neurons. It presents multiple clinical...
INTRODUCTION
Narcolepsy type 1 is a focal degenerative disease of the hypothalamus that selectively affects orexin (hypocretin)-producing neurons. It presents multiple clinical manifestations, both in wakefulness and in sleep. The symptoms are often so disruptive that they cause enormous suffering and impair patients' quality of life. Although a non-pharmacological approach is sometimes sufficient, the vast majority of patients need medication for adequate clinical management.
CASE REPORT
A male who, at 43 years of age, began to present acutely with excessive daytime sleepiness and episodes of cataplexy. After a thorough examination, he was diagnosed with narcolepsy type 1. Throughout the course of the disease, he was prescribed antidepressants, neurostimulants and sodium oxybate, in monotherapy or in combination. The response to pharmacological treatment was insufficient and accompanied by numerous side effects. Following the introduction of pitolisant, there was a marked improvement in his symptoms and a reduction in the dose of the other drugs and their adverse effects was achieved.
CONCLUSION
A number of measures are now available to address the cardinal symptoms of the disease, although there are still cases that are resistant to anti-narcoleptic treatment. Drugs with mechanisms of action that act upon receptors in the histaminergic system can be very useful in these cases.
Topics: Humans; Male; Antidepressive Agents; Cataplexy; Central Nervous System Stimulants; Narcolepsy; Quality of Life; Sodium Oxybate; Adult; Drug Resistance, Multiple; Sleepiness
PubMed: 37477029
DOI: 10.33588/rn.77s01.2023198 -
Child Development Mar 2022Reciprocal relations between sleep and adjustment were investigated. Participants included 246 adolescents (M = 15.80 years; 67.5% White, 32.5% Black/African...
Reciprocal relations between sleep and adjustment were investigated. Participants included 246 adolescents (M = 15.80 years; 67.5% White, 32.5% Black/African American; 53% female, 47% male) at Time 1 (data collected 2012-2013), 227 at Time 2 (M = 16.78 years) and 215 at Time 3 (M = 17.70 years). Sleep-wake variables were measured with self-reports (sleepiness) and actigraphy (average sleep minutes and efficiency, variability in sleep minutes and efficiency). Adolescents reported on depression and anxiety symptoms, and parents reported on externalizing problems. Greater variability in sleep duration and efficiency as well as sleepiness predicted adjustment problems (range of R : 36%-60%). Reciprocal relations were supported mostly for sleepiness (range of R : 16%-32%). Results help understand bidirectional relations between sleep and adjustment.
Topics: Actigraphy; Adolescent; Anxiety; Female; Humans; Male; Self Report; Sleep; Sleep Wake Disorders; Sleepiness
PubMed: 34757645
DOI: 10.1111/cdev.13703 -
European Respiratory Review : An... Jun 2022Excessive daytime sleepiness (EDS) is a major symptom of obstructive sleep apnoea (OSA), defined as the inability to stay awake during the day. Its clinical descriptors... (Review)
Review
Excessive daytime sleepiness (EDS) is a major symptom of obstructive sleep apnoea (OSA), defined as the inability to stay awake during the day. Its clinical descriptors remain elusive, and the pathogenesis is complex, with disorders such as insufficient sleep and depression commonly associated. Subjective EDS can be evaluated using the Epworth Sleepiness Scale, in which the patient reports the probability of dozing in certain situations; however, its reliability has been challenged. Objective tests such as the multiple sleep latency test or the maintenance of wakefulness test are not commonly used in patients with OSA, since they require nocturnal polysomnography, daytime testing and are expensive. Drugs for EDS are available in the United States but were discontinued in Europe some time ago. For European respiratory physicians, treatment of EDS with medication is new and they may lack experience in pharmacological treatment of EDS, while novel wake-promoting drugs have been recently developed and approved for clinical use in OSA patients in the USA and Europe. This review will discuss 1) the potential prognostic significance of EDS in OSA patients at diagnosis, 2) the prevalence and predictors of residual EDS in treated OSA patients, and 3) the evolution of therapy for EDS specifically for Europe.
Topics: Disorders of Excessive Somnolence; Humans; Reproducibility of Results; Sleep Apnea, Obstructive; Sleepiness; Wakefulness
PubMed: 35613742
DOI: 10.1183/16000617.0230-2021 -
Accident; Analysis and Prevention May 2019Not just detecting but also predicting impairment of a car driver's operational state is a challenge. This study aims to determine whether the standard sources of...
Not just detecting but also predicting impairment of a car driver's operational state is a challenge. This study aims to determine whether the standard sources of information used to detect drowsiness can also be used to predict when a given drowsiness level will be reached. Moreover, we explore whether adding data such as driving time and participant information improves the accuracy of detection and prediction of drowsiness. Twenty-one participants drove a car simulator for 110min under conditions optimized to induce drowsiness. We measured physiological and behavioral indicators such as heart rate and variability, respiration rate, head and eyelid movements (blink duration, frequency and PERCLOS) and recorded driving behavior such as time-to-lane-crossing, speed, steering wheel angle, position on the lane. Different combinations of this information were tested against the real state of the driver, namely the ground truth, as defined from video recordings via the Trained Observer Rating. Two models using artificial neural networks were developed, one to detect the degree of drowsiness every minute, and the other to predict every minute the time required to reach a particular drowsiness level (moderately drowsy). The best performance in both detection and prediction is obtained with behavioral indicators and additional information. The model can detect the drowsiness level with a mean square error of 0.22 and can predict when a given drowsiness level will be reached with a mean square error of 4.18min. This study shows that, on a controlled and very monotonous environment conducive to drowsiness in a driving simulator, the dynamics of driver impairment can be predicted.
Topics: Adult; Distracted Driving; Eye Movements; Female; Humans; Male; Neural Networks, Computer; Sleepiness; Time Factors; Video Recording; Wakefulness; Young Adult
PubMed: 29203032
DOI: 10.1016/j.aap.2017.11.038 -
Journal of Medical Signals and Sensors 2022Drowsy driving is one of the leading causes of severe accidents worldwide. In this study, an analyzing method based on drowsiness level proposed to detect drowsiness...
BACKGROUND
Drowsy driving is one of the leading causes of severe accidents worldwide. In this study, an analyzing method based on drowsiness level proposed to detect drowsiness through electroencephalography (EEG) measurements and vehicle dynamics data.
METHODS
A driving simulator was used to collect brain data in the alert and drowsy states. The tests were conducted on 19 healthy men. Brain signals from the parietal, occipital, and central parts were recorded. Observer Ratings of Drowsiness (ORD) were used for the drowsiness stages assessment. This study used an innovative method, analyzing drowsiness EEG data were in respect to ORD instead of time. Thirteen features of EEG signal were extracted, then through Neighborhood Component Analysis, a feature selection method, 5 features including mean, standard deviation, kurtosis, energy, and entropy are selected. Six classification methods including K-nearest neighbors (KNN), Regression Tree, Classification Tree, Naive Bayes, Support vector machines Regression, and Ensemble Regression are employed. Besides, the lateral position and steering angle as a vehicle dynamic data were used to detect drowsiness, and the results were compared with classification result based on EEG data.
RESULTS
According to the results of classifying EEG data, classification tree and ensemble regression classifiers detected over 87.55% and 87.48% of drowsiness at the moderate level, respectively. Furthermore, the classification results demonstrate that if only the single-channel P4 is used, higher performance can achieve than using data of all the channels (C3, C4, P3, P4, O1, O2). Classification tree classifier and regression classifiers showed 91.31% and 91.12% performance with data from single-channel P4. The best classification results based on vehicle dynamic data were 75.11 through KNN classifier.
CONCLUSION
According to this study, driver drowsiness could be detected at the moderate drowsiness level based on features extracted from a single-channel P4 data.
PubMed: 36726417
DOI: 10.4103/jmss.jmss_124_21 -
Current Opinion in Pulmonary Medicine Nov 2022The purpose of this review is to describe the nonclassical symptoms and manifestations occurring in patients with obstructive sleep apnea (OSA), both from a standpoint... (Review)
Review
PURPOSE OF REVIEW
The purpose of this review is to describe the nonclassical symptoms and manifestations occurring in patients with obstructive sleep apnea (OSA), both from a standpoint of prevalence and in terms of clinical relevance. Particular emphasis will be given to nightmares, comorbid insomnia, restless legs syndrome and periodic limb movement disorder, bruxism, morning headache, nocturia, acid reflux, chronic cough and dysphagia.
RECENT FINDINGS
A review of the recent literature suggests that nonclassical symptoms have a high prevalence, are underestimated, and can interact with quality of life. Although these disturbances may occur together by mere coincidence, they may interact reciprocally. However, the degree of symptoms is not always correlated with OSA severity.
SUMMARY
OSA is a heterogeneous disease with variable clinical manifestations. This review highlights the need for detailed evaluation of patients with OSA to diagnose other important sleep disorders and clinical manifestations, given their frequent association.
Topics: Humans; Polysomnography; Prevalence; Quality of Life; Sleep Apnea, Obstructive; Sleep Initiation and Maintenance Disorders; Sleepiness
PubMed: 36101923
DOI: 10.1097/MCP.0000000000000915 -
Inflammopharmacology Apr 2023COVID-19 is often associated with long-lasting pulmonary symptoms. Data are scarce about interstitial lung disease (ILD) in patients following COVID-19 hospitalization... (Review)
Review
COVID-19 is often associated with long-lasting pulmonary symptoms. Data are scarce about interstitial lung disease (ILD) in patients following COVID-19 hospitalization with persistent symptoms. We retrospectively reviewed all cases sent to pulmonary post-COVID evaluation due to persistent symptoms between February 2021 and February 2022 (N = 318). All patients with suspected ILD (N = 44) were reviewed at the multidisciplinary discussion. Patient characteristics, symptoms, time since hospitalization, detailed lung function measurements and 6-min walk test (6MWT) were evaluated. The post-COVID ILD suspected group included more men (68.2 vs. 31.8%) with significantly older age compared to the control group (64.0 ± 12.3 vs. 51.3 ± 14.9 years). Most patient needed hospital care for COVID-19 pneumonia (68.6% of all patients and 84.1% of ILD suspected group) and average time since hospitalization was 2.4 ± 2.3 months. Persisting symptoms included fatigue (34%), dyspnoea (25.2%), cough (22.6%), and sleep disorders (insomnia 13.2%; sleepiness 8.2%). Post-COVID ILD presented more often with new symptoms of cough and sleepiness. Functional impairment, especially decreased walking distance and desaturation during 6-min walk test (6MWT) were detected in the ILD-suspected group. Respiratory function test in the post-COVID ILD group showed slight restrictive ventilatory pattern (FVC: 76.7 ± 18.1%, FEV1: 83.5 ± 19.1%, TLC: 85.6 ± 28.1%) and desaturation during 6MWT were detected in 41% of patients. LDCT changes were mainly ground glass opacities (GGO) and/or reticular abnormalities in most cases affecting < 10% of the lungs. Our data indicate that suspected post-COVID ILD is affecting 13.8% of symptomatic patients. High resolution chest CT changes were mainly low extent GGO/reticulation, while long-term lung structural changes need further evaluation.
Topics: Male; Humans; Cough; Retrospective Studies; Sleepiness; COVID-19; Lung Diseases, Interstitial; Lung
PubMed: 36961666
DOI: 10.1007/s10787-023-01191-3