What is the best measure of daytime sleepiness in adults with heart failure?

Daily rhythms, light exposure and social jetlag correlate with demographic characteristics and health in a nationally representative survey

The timing of daily activity in humans have been associated with various demographic and health-related factors, but the possibly complex patterns of confounding and interaction between these has not been systematically explored. We use data from Hungarostudy 2021, a nationally representative survey of 7000 Hungarian adults to assess the relationship between self-reported chronotype, social jetlag (using the Munich Chronotype Questionnaire), demographic variables and self-reported health and demographic variables, including ethnic minority membership. Supporting the validity of self-reports, participants with later chronotypes reported the lowest daytime sleepiness at a later clock time. We found that older age, female sex, a more eastward and southward geographical position, residence in a smaller settlement, less education and income, religiousness and cohabiting with small children were associated with an earlier chronotype. Younger age, higher education and income, and cohabiting with small children were associated with increased social jetlag. Of the 48 health-related variables surveyed, the relationship with both chronotype and social jetlag were mostly accounted for by age, sex, and socioeconomic effects, but we identified alcohol consumption, smoking, and physical activity as predictors of both social jetlag and chronotype, while a number of disorders were either positively or negatively associated with chronotype and social jetlag. Our findings from a large, nationally representative sample indicate that both biological and social factors influence chronotype and identified both demographic and health-related variables as risk factors for social jetlag. Our results, however, do not support a causal relationship between light exposure and mental health.

The People's Trial: supporting the public's understanding of randomised trials

Background

Randomised trials are considered the gold standard in providing robust evidence on the effectiveness of interventions. However, there are relatively few initiatives to help increase public understanding of what randomised trials are and why they are important. This limits the overall acceptance of and public participation in clinical trials. The People’s Trial aims to help the public learn about randomised trials, to understand why they matter, and to be better equipped to think critically about health claims by actively involving them in all aspects of trial design. This was done by involving the public in the design, conduct, and dissemination of a randomised trial.

Methods

Using a reflexive approach, we describe the processes of development, conduct, and dissemination of The People’s Trial.

Results

Over 3000 members of the public, from 72 countries, participated in The People’s Trial. Through a series of online surveys, the public designed a trial called The Reading Trial. They chose the question the trial would try to answer and decided the components of the trial question. In December 2019, 991 participants were recruited to a trial to answer the question identified and prioritised by the public, i.e. ‘Does reading a book in bed make a difference to sleep in comparison with not reading a book in bed?’ We report the processes of The People’s Trial in seven phases, paralleling the steps of a randomised trial, i.e. question identification and prioritisation, recruitment, randomisation, trial conduct, data analysis, and sharing of findings. We describe the decisions we made, the processes we used, the challenges we encountered, and the lessons we learned.

Conclusion

The People’s Trial involved the public successfully in the design, conduct, and dissemination of a randomised trial demonstrating the potential for such initiatives to help the public learn about randomised trials, to understand why they matter, and to be better equipped to think critically about health claims.

Trial registration

ClinicalTrials.govNCT04185818. Registered on 4 December 2019

Supplementary Information

The online version contains supplementary material available at 10.1186/s13063-021-05984-1.

Does reading a book in bed make a difference to sleep in comparison to not reading a book in bed? The People's Trial-an online, pragmatic, randomised trial

BACKGROUND

The best way of comparing healthcare treatments is through a randomised trial. In a randomised trial, we compare something (a treatment or intervention) to something else, often another treatment. Who gets what is decided at random, meaning everyone has an equal chance of getting any of the treatments. This means any differences found can be put down to the treatment received rather than other things, such as where people live, or health conditions they might have. The People's Trial aimed to help the public better understand randomised trials by inviting them to design and carry out a trial. The question chosen by the public for The People's Trial was: 'Does reading a book in bed make a difference to sleep, in comparison to not reading a book in bed?' This paper describes that trial, called 'The Reading Trial'.

METHODS

The Reading Trial was an online, randomised trial. Members of the public were invited to take part through social media campaigns. People were asked to either read a book in bed before going to sleep (intervention group) or not read a book in bed before going to sleep (control group). We asked everyone to do this for 7 days, after which they measured their sleep quality.

RESULTS

During December 2019, a total of 991 people took part in The Reading Trial, half (496 (50%)) in the intervention group and half (495 (50%)) in the control group. Not everyone finished the trial: 127 (25.6%) people in the intervention group and 90 (18.18%) people in the control group. Of those providing data, 156/369 (42%) people in the intervention group felt their sleep improved, compared to 112/405 (28%) of those in the control group, a difference of 14%. When we consider how certain we are of this finding, we estimate that, in The Reading Trial, sleep improved for between 8 and 22% more people in the intervention group compared to the control group.

CONCLUSIONS

Reading a book in bed before going to sleep improved sleep quality, compared to not reading a book in bed.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04185818. Registered on 4 December 2019.

Diagnostic accuracy and suitability of instruments that screen for obstructive sleep apnoea, insomnia and sleep quality in cardiac patients: a meta-analysis

BACKGROUND

A number of clinical guidelines recommend that all cardiac rehabilitation patients should be screened for potential sleep disorders with a validated screening instrument. There is currently no consensus on what specific tools should be used.

OBJECTIVE

To identify tools that are practical to use in the clinical environment and have high diagnostic accuracy.

METHODS

We systematically searched online databases to identify patient reported outcome instruments that have been used in published research studies to assess the likelihood of obstructive sleep apnoea (OSA) in cardiac patients. In studies that provided diagnostic data, these data were extracted and verified via an evidence-based diagnostic calculator. Where sufficient numbers of studies were available, a meta-analysis was conducted to determine pooled estimates of specificity, sensitivity and diagnostic odds ratios. Selected papers were qualitatively assessed using the Standards for Reporting Diagnostic accuracy studies (STARD).

RESULTS

Of the 21 instruments identified, six detected likelihood of OSA, two assessed daytime sleepiness, five assessed insomnia and eight examined sleep quality. A meta-analysis of 14 studies that assessed diagnostic accuracy of moderate OSA, revealed moderate sensitivity for the Berlin Questionnaire, Sens = 0.49 (95% CI 0.45-0.52) and good sensitivity for the Stop-BANG, Sens = 0.93 (95% CI 0.87-0.96) but poor specificity at standard cut-off criteria.

CONCLUSION

There are promising practical tools available to screen patients with OSA and other sleep disorders in cardiac rehabilitation settings, but specificity could be improved. Additional assessment of sleep quality may enhance prognostic ability with both OSA and insomnia screening.

Effect of Sudarshan Kriya Yoga (SKY) on daytime and situational sleep propensity in novice practitioners: a prospective cohort study

OBJECTIVES

Hectic, late-night lifestyle has reduced 90 min sleep in 20% adults resulting in insomnia and excessive daytime sleepiness (EDS). We assess the scope of Sudarshan Kriya Yoga (SKY), a 4-component, breathing process in reducing EDS, generally and situationally.

METHODS

This is a prospective, controlled study involving randomized subjects without any sleep-wake cycle anomalies and prior experience in SKY. Subjects (n=52) performed 30 min of SKY for 6 days/week for 8 weeks, while controls (n=53) performed sitting activity and Suryanamaskar for 4-weeks each. Epworth Sleepiness Scale (ESS) was used to measure EDS at 0, 4, and 8 weeks.

RESULTS

SKY group showed significant ESS score improvements between 0-4 weeks and 4-8 weeks of 1.22 (p=0.0001) and 1.66 (p=0.001) respectively. Controls however failed to improve with score differences of 0.02 (p=0.892) and 0.02 (p=0.8212) respectively. SKY group showed significant ESS score improvement over controls at 4-weeks (difference=1.74; p=0.013) and 8-weeks (difference eight; p=0.0001). Improvement was most for obese people and those sitting in a halted car.

CONCLUSIONS

Improvement in subjects' nighttime sleep and daytime wakefulness in SKY practitioners can be attributed to polyvagal theory. Increased heart rate variability (HRV) alterations and sympathetic hyperarousal in chronic insomnia; and cholinergic and GABAergic dysregulation in anxiety disorders are countered by regulated vagal nerve stimulation post SKY. Our study establishes effectivity of SKY in reducing EDS (total and situational), provides a clinical correlation for prior polysomnographic evidence and paves way for larger trials directed towards SKY prescriptions for insomnia.

Mechanisms of reduced sleepiness symptoms in heart failure and obstructive sleep apnea

Patients with both heart failure and obstructive sleep apnea often have poor, repeatedly disrupted sleep, and yet they frequently do not complain of excessive daytime sleepiness. Understanding this lack of perceived sleepiness is crucial for the case identification and treatment of obstructive sleep apnea in the heart failure population at high risk of this disease, especially given the association between untreated obstructive sleep apnea and mortality among patients with heart failure. In this review, we present epidemiologic evidence concerning the lack of sleepiness symptoms in heart failure and obstructive sleep apnea, explore possible mechanistic explanations for this relationship, assess the benefits of treatment in this population, discuss implications for clinical practice and explore directions for future research.

Daytime sleepiness and risk of coronary heart disease and stroke: results from the Nurses' Health Study II

OBJECTIVE

The objective of this study was to determine whether daytime sleepiness is independently associated with coronary heart disease (CHD) and stroke or whether the positive association is explained by short sleep duration, disturbed sleep, and circadian disruption, conditions that are associated with cardiometabolic risk factors for vascular events.

METHODS

Longitudinal analyses of data from the Nurses' Health Study II comprising 84,003 female registered nurses aged 37-54 at baseline were conducted in 2001 with follow-up until 2009. Multivariate Cox regression was used to explore the relationship between reported daytime sleepiness and the incidence of either CHD or stroke (n=500 cases).

RESULTS

Women who reported daytime sleepiness almost every day, compared with rarely/never, had an elevated adjusted risk of cardiovascular disease (CVD) (hazard ratio (HR)=1.58, 95% confidence interval (CI) 1.15-2.17). Controlling for sleep variables (sleep duration, snoring, shift work, and sleep adequacy) or potential metabolic biological mediators of disrupted sleep (diabetes, hypercholesterolemia, and hypertension) appreciably attenuated the relationship (HR=1.17, 95% CI 0.84-1.65; and HR=1.34, 95% CI 0.97-1.85, respectively). Controlling for both sleep variables and metabolic risk factors eliminated an independent association (HR=1.09, 95% CI 0.77-1.53). A similar pattern was observed for CHD and stroke individually.

CONCLUSIONS

Daytime sleepiness was not an independent risk factor for CVD in this cohort of women, but rather, was associated with sleep characteristics and metabolic abnormalities that are risk factors for CVD.

What puts heart failure patients at risk for poor medication adherence?

BACKGROUND

Medication nonadherence is a major cause of hospitalization in patients with heart failure (HF), which contributes enormously to health care costs. We previously found, using the World Health Organization adherence dimensions, that condition and patient level factors predicted nonadherence in HF. In this study, we assessed a wider variety of condition and patient factors and interactions to improve our ability to identify those at risk for hospitalization.

MATERIALS AND METHODS

Medication adherence was measured electronically over the course of 6 months, using the Medication Event Monitoring System (MEMS). A total of 242 HF patients completed the study, and usable MEMS data were available for 218 (90.1%). Participants were primarily white (68.3%), male (64.2%), and retired (44.5%). Education ranged from 8-29 years (mean, 14.0 years; standard deviation, 2.9 years). Ages ranged from 30-89 years (mean, 62.8 years; standard deviation, 11.6 years). Analyses used adaptive methods based on heuristic searches controlled by cross-validation scores. First, individual patient adherence patterns over time were used to categorize patients in poor versus better adherence types. Then, risk factors for poor adherence were identified. Finally, an effective model for predicting poor adherence was identified based on identified risk factors and possible pairwise interactions between them.

RESULTS

A total of 63 (28.9%) patients had poor adherence. Three interaction risk factors for poor adherence were identified: a higher number of comorbid conditions with a higher total number of daily medicines, older age with poorer global sleep quality, and fewer months since diagnosis of HF with poorer global sleep quality. Patients had between zero and three risk factors. The odds for poor adherence increased by 2.6 times with a unit increase in the number of risk factors (odds ratio, 2.62; 95% confidence interval, 1.78-3.86; P<0.001).

CONCLUSION

Newly diagnosed, older HF patients with comorbid conditions, polypharmacy, and poor sleep are at risk for poor medication adherence. Interventions addressing these specific barriers are needed.

Double jeopardy: the influence of excessive daytime sleepiness and impaired cognition on health-related quality of life in adults with heart failure

AIMS

To determine how excessive daytime sleepiness (EDS) and impaired cognition contribute to health-related quality of life (HRQL) in heart failure (HF).

METHODS AND RESULTS

Adults with chronic HF were enrolled into a prospective cohort study. Data were obtained from 280 subjects enrolled from three sites in the northeastern USA; 242 completed the 6-month study. At baseline, cohorts with and without EDS were identified using the Epworth Sleepiness Scale. Each EDS group was further subdivided into those with and without impaired cognition using a battery of five neuropsychological tests. Two disease-specific measures, the Kansas City Cardiomyopathy Questionnaire (KCCQ) and the Functional Outcomes of Sleep Questionnaire (FOSQ), were used to measure HRQL. General linear modelling of square-transformed variables was used to test the hypothesis that cohort membership was a significant predictor of HRQL. At 6 months the remaining sample was 62.5 [standard deviation (SD) 12] years old, mostly male (63%), white (65%), and functionally compromised [72% New York Heart Association (NYHA) class III/IV]. The cohort with both EDS and impaired cognition had the lowest KCCQ overall summary score (60.5 ± 22.5) compared with the cohort without EDS or impaired cognition (74.6 ± 17.4, P ≤ 0.001). A similar effect was seen on the FOSQ (16.0 ± 2.8 vs. 18.5 ± 2.2, P < 0.001).

CONCLUSION

Impaired cognition alone did not explain poor HRQL, but the addition of EDS poses a significant risk for poor HRQL. Interventions designed to influence EDS may improve HRQL in this population.