Recommended timing of medications that impact sleep and wakefulness: A review of the American Prescribers' Digital Reference.

An appreciable number of medicines have a recommended unique single time-of-day or asymmetrical or unequal-interval multiple-daily administration schedule. Many prescription and over-the-counter (OTC) products, according to administration time, can exert positive or negative impact on nighttime sleep and daytime wakefulness. Intuitively, medicines used to manage nighttime sleep and daytime wake disorders should be taken, respectively, at night before bedtime and morning after arising. However, some utilized for other medical conditions, if improperly timed, may compromise nocturnal sleep and diurnal attentiveness. We conducted a comprehensive review of the American Prescribers' Digital Reference, internet version of the Physician's Desk Reference, for the recommended scheduling of medications and OTC remedies that can impact sleep and wakefulness. The search revealed several hundred therapies of various classes -- α2-receptor agonists, antidepressants, barbiturates, central nervous system stimulants, benzodiazepines, dopamine agonists, dopamine norepinephrine reuptake inhibitors, selective norepinephrine reuptake inhibitors, eugeroics, γ-aminobutyric acid modulators, H1 and H3-receptor antagonists, melatonin analogues, OTC melatonin-containing products, non-benzodiazepine benzodiazepine-receptor agonists, dual orexin-receptor antagonists, and serotonin modulators -- that have a recommended unique dosing schedule. The tables and text of this article are intended to guide the proper scheduling of these medicines to optimize desired and/or minimize undesired effects.

Circadian rhythms of risk factors and management in atherosclerotic and hypertensive vascular disease: Modern chronobiological perspectives of an ancient disease.

Atherosclerosis, a chronic inflammatory disease of the arteries that appears to have been as prevalent in ancient as in modern civilizations, is predisposing to life-threatening and life-ending cardiac and vascular complications, such as myocardial and cerebral infarctions. The pathogenesis of atherosclerosis involves intima plaque buildup caused by vascular endothelial dysfunction, cholesterol deposition, smooth muscle proliferation, inflammatory cell infiltration and connective tissue accumulation. Hypertension is an independent and controllable risk factor for atherosclerotic cardiovascular disease (CVD). Conversely, atherosclerosis hardens the arterial wall and raises arterial blood pressure. Many CVD patients experience both atherosclerosis and hypertension and are prescribed medications to concurrently mitigate the two disease conditions. A substantial number of publications document that many pathophysiological changes caused by atherosclerosis and hypertension occur in a manner dependent upon circadian clocks or clock gene products. This article reviews progress in the research of circadian regulation of vascular cell function, inflammation, hemostasis and atherothrombosis. In particular, it delineates the relationship of circadian organization with signal transduction and activation of the renin-angiotensin-aldosterone system as well as disturbance of the sleep/wake circadian rhythm, as exemplified by shift work, metabolic syndromes and obstructive sleep apnea (OSA), as promoters and mechanisms of atherogenesis and risk for non-fatal and fatal CVD outcomes. This article additionally updates advances in the clinical management of key biological processes of atherosclerosis to optimally achieve suppression of atherogenesis through chronotherapeutic control of atherogenic/hypertensive pathological sequelae.

Novel temperature-controlled sleep system to improve sleep: a proof-of-concept study.

The sleep-wake cycle is regulated by circadian Process C and homeostatic Process S. Selective thermal stimulation (STS) of the cervical spine region enhances glabrous skin blood flow (GSBF) and augments body heat dissipation to increase distal-to-proximal skin gradient (DPG) causing decrease of core body temperature (CBT), which can shorten sleep onset latency (SOL) and improve sleep quality. A total of 11 young healthy/normal sleeper males challenged to go to bed (lights-off) 2 h earlier than usual were subjected in a randomised order to non-consecutive treatment and control night-time sleep sessions. The treatment night entailed activation of a dual-temperature zone mattress with a cooler centre and warmer periphery plus STS pillow that applied mild heating to the cervical spinal skin for 30 min after lights-off for sleep. During the first 30 min after lights-off, GSBF (mean [standard error (SE)] Δ = 49.77 [19.13] perfusion units, p = 0.013) and DPG (mean [SE] Δ = 2.05 [0.62] °C, p = 0.005) were significantly higher and CBT (mean [SE] Δ = -0.15 [0.07] °C, p = 0.029) was significantly lower in the treatment than control night, while there was no significant difference in these variables during the 45 min prior to lights-off (baseline). Moreover, SOL was significantly reduced (mean [SE] Δ = -48.6 [23.4] min, p = 0.032) and subjective sleep quality significantly better (p < 0.001) in the treatment than control night. In conclusion, the novel sleep facilitating system comprised of the STS pillow plus dual-temperature zone mattress induced earlier increase in GSBF and DPG and earlier decline in CBT. This resulted in statistically significant shortened SOL and improved overall sleep quality, thereby reducing sleep pressure of Process S, even under the challenging investigative protocol requiring participants to go to sleep 2 h earlier than customary.

The Circadian Rhythm of Thermoregulation Modulates both the Sleep/Wake Cycle and 24 h Pattern of Arterial Blood Pressure.

Borbély proposed an interacting two-component model of sleep regulation comprising a homeostatic Process S and a circadian Process C. The model has provided understanding of the association between core body temperature (CBT) as a key element of Process C that is deterministic of sleep onset and offset. However, it additionally provides a new perspective of the importance of the thermoregulatory mechanisms of Process C in modulating the circadian rhythm of arterial blood pressure (ABP). Herein, we examine the circadian physiology of thermoregulation, including at the end of the activity span the profound redistribution of cardiac output from the systemic circulation to the arteriovenous anastomoses of the glabrous skin that markedly enhances convective transfer of heat from the body to the environment to cause (i) decrease of the CBT as a pathway to sleep onset and (ii) attenuation of the asleep ABP mean and augmentation of the ABP decline (dipping) from the wake-time mean, in combination the strongest predictors of the risk for blood vessel and organ pathology and morbid and mortal cardiovascular disease events. We additionally review the means by which blood perfusion to the glabrous skin can be manipulated on demand by selective thermal stimulation, that is, mild warming, on the skin of the cervical spinal cord to intensify Process C as a way to facilitate sleep induction and promote healthy asleep ABP. © 2021 American Physiological Society. Compr Physiol 11:1-14, 2021.

Guidelines for the design and conduct of human clinical trials on ingestion-time differences - chronopharmacology and chronotherapy - of hypertension medications.

Current hypertension guidelines fail to provide a recommendation on when-to-treat, thus disregarding relevant circadian rhythms that regulate blood pressure (BP) level and 24 h patterning and medication pharmacokinetics and pharmacodynamics. The ideal purpose of ingestion-time (chronopharmacology, i.e. biological rhythm-dependent effects on the kinetics and dynamics of medications, and chronotherapy, i.e. the timing of pharmaceutical and other treatments to optimize efficacy and safety) trials should be to explore the potential impact of endogenous circadian rhythms on the effects of medications. Such investigations and outcome trials mandate adherence to the basic standards of human chronobiology research. In-depth review of the more than 150 human hypertension pharmacology and therapeutic trials published since 1974 that address the differential impact of upon-waking/morning versus at-bedtime/evening schedule of treatment reveals diverse protocols of sometimes suboptimal or defective design and conduct. Many have been "time-of-day," i.e. morning versus evening, rather than circadian-time-based, and some relied on wake-time office BP rather than around-the-clock ambulatory BP measurements (ABPM). Additionally, most past studies have been of too small sample size and thus statistically underpowered. As of yet, there has been no consensual agreement on the proper design, methods and conduct of such trials. This Position Statement recommends ingestion-time hypertension trials to follow minimum guidelines: (i) Recruitment of participants should be restricted to hypertensive individuals diagnosed according to ABPM diagnostic thresholds and of a comparable activity/sleep routine. (ii) Tested treatment-times should be selected according to internal biological time, expressed by the awakening and bed times of the sleep/wake cycle. (iii) ABPM should be the primary or sole method of BP assessment. (iv) The minimum-required features for analysis of the ABPM-determined 24 h BP pattern ought to be the asleep (not "nighttime") BP mean and sleep-time relative BP decline, calculated in reference to the activity/rest cycle per individual. (v) ABPM-obtained BP means should be derived by the so-called adjusted calculation procedure, not by inaccurate arithmetic averages. (vi) ABPM should be performed with validated and calibrated devices at least hourly throughout two or more consecutive 24 h periods (48 h in total) to achieve the highest reproducibility of mean wake-time, sleep-time and 48 h BP values plus the reliable classification of dipping status. (vii) Calculation of minimum required sample size in adherence with proper statistical methods must be provided. (viii) Hypertension chronopharmacology and chronotherapy trials should preferably be randomized double-blind, randomized open-label with blinded-endpoint, or crossover in design, the latter with sufficient washout period between tested treatment-time regimens.

Deep Neural Network Sleep Scoring Using Combined Motion and Heart Rate Variability Data.

Background: Performance of wrist actigraphy in assessing sleep not only depends on the sensor technology of the actigraph hardware but also on the attributes of the interpretative algorithm (IA). The objective of our research was to improve assessment of sleep quality, relative to existing IAs, through development of a novel IA using deep learning methods, utilizing as input activity count and heart rate variability (HRV) metrics of different window length (number of epochs of data). Methods: Simultaneously recorded polysomnography (PSG) and wrist actigraphy data of 222 participants were utilized. Classic deep learning models were applied to: (a) activity count alone (without HRV), (b) activity count + HRV (30-s window), (c) activity count + HRV (3-min window), and (d) activity count + HRV (5-min window) to ascertain the best set of inputs. A novel deep learning model (Haghayegh Algorithm, HA), founded on best set of inputs, was developed, and its sleep scoring performance was then compared with the most popular University of California San Diego (UCSD) and Actiwatch proprietary IAs. Results: Activity count combined with HRV metrics calculated per 5-min window produced highest agreement with PSG. HA showed 84.5% accuracy (5.3-6.2% higher than comparator IAs), 89.5% sensitivity (6.2% higher than UCSD IA and 6% lower than Actiwatch proprietary IA), 70.0% specificity (8.2-34.3% higher than comparator IAs), and 58.7% Kappa agreement (16-23% higher than comparator IAs) in detecting sleep epochs. HA did not differ significantly from PSG in deriving sleep parameters-sleep efficiency, total sleep time, sleep onset latency, and wake after sleep onset; moreover, bias and mean absolute error of the HA model in estimating them was less than the comparator IAs. HA showed, respectively, 40.9% and 54.0% Kappa agreement with PSG in detecting rapid and non-rapid eye movement (REM and NREM) epochs. Conclusions: The HA model simultaneously incorporating activity count and HRV metrics calculated per 5-min window demonstrates significantly better sleep scoring performance than existing popular IAs.

A Study of the Relationship Between Uric Acid and Substantia Nigra Brain Connectivity in Patients With REM Sleep Behavior Disorder and Parkinson's Disease.

Low levels of the natural antioxidant uric acid (UA) and the presence of REM sleep behavior disorder (RBD) are both associated with an increased likelihood of developing Parkinson's disease (PD). RBD and PD are also accompanied by basal ganglia dysfunction including decreased nigrostriatal and nigrocortical resting state functional connectivity. Despite these independent findings, the relationship between UA and substantia nigra (SN) functional connectivity remains unknown. In the present study, voxelwise analysis of covariance was used in a cross-sectional design to explore the relationship between UA and whole-brain SN functional connectivity using the eyes-open resting state fMRI method in controls without RBD, patients with idiopathic RBD, and PD patients with and without RBD. The results showed that controls exhibited a positive relationship between UA and SN functional connectivity with left lingual gyrus. The positive relationship was reduced in patients with RBD and PD with RBD, and the relationship was found to be negative in PD patients. These results are the first to show differential relationships between UA and SN functional connectivity among controls, prodromal, and diagnosed PD patients in a ventral occipital region previously documented to be metabolically and structurally altered in RBD and PD. More investigation, including replication in longitudinal designs with larger samples, is needed to understand the pathophysiological significance of these changes.

Resolution of sexsomnia with paroxetine.

None: Sexsomnia is a parasomnia consisting of sexual behavior during non-rapid eye movement sleep. To date, there have been 116 clinical cases of sexsomnia reported and most were treated with clonazepam. We present a case of an adult male with sexsomnia that started during his college days. He presented to us because of problems in his current marriage arising from sexual behavior during sleep. Polysomnography revealed no significant sleep-disordered breathing, electroencephalography abnormality, or abnormal movement during non-rapid eye movement and rapid eye movement (REM) sleep. Alcohol consumption was reported to worsen his sexsomnia. To avoid the neuro-depressant effects of benzodiazepines, paroxetine was administered and resulted in complete resolution of sexsomnia.

Pathophysiological characteristics and therapeutic approaches for pulmonary injury and cardiovascular complications of coronavirus disease 2019.

The pandemic of coronavirus disease 2019 (COVID-19) has emerged as a major health crisis, with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) having infected over a million people around the world within a few months of its identification as a human pathogen. Initially, SARS-CoV-2 infects cells in the respiratory system and causes inflammation and cell death. Subsequently, the virus spreads out and damages other vital organs and tissues, triggering a complicated spectrum of pathophysiological changes and symptoms, including cardiovascular complications. Acting as the receptor for SARS-CoV entering mammalian cells, angiotensin converting enzyme-2 (ACE2) plays a pivotal role in the regulation of cardiovascular cell function. Diverse clinical manifestations and laboratory abnormalities occur in patients with cardiovascular injury in COVID-19, characterizing the development of this complication, as well as providing clues to diagnosis and treatment. This review provides a summary of the rapidly appearing laboratory and clinical evidence for the pathophysiology and therapeutic approaches to COVID-19 pulmonary and cardiovascular complications.

Performance assessment of new-generation Fitbit technology in deriving sleep parameters and stages.

We compared performance in deriving sleep variables by both Fitbit Charge 2™, which couples body movement (accelerometry) and heart rate variability (HRV) in combination with its proprietary interpretative algorithm (IA), and standard actigraphy (Motionlogger® Micro Watch Actigraph: MMWA), which relies solely on accelerometry in combination with its best performing 'Sadeh' IA, to electroencephalography (EEG: Zmachine® Insight+ and its proprietary IA) used as reference. We conducted home sleep studies on 35 healthy adults, 33 of whom provided complete datasets of the three simultaneously assessed technologies. Relative to the Zmachine EEG method, Fitbit showed an overall Kappa agreement of 54% in distinguishing wake/sleep epochs and sensitivity of 95% and specificity of 57% in detecting sleep epochs. Fitbit, relative to EEG, underestimated sleep onset latency (SOL) by ~11 min and overestimated sleep efficiency (SE) by ~4%. There was no statistically significant difference between Fitbit and EEG methods in measuring wake after sleep onset (WASO) and total sleep time (TST). Fitbit showed substantial agreement with EEG in detecting rapid eye movement and deep sleep, but only moderate agreement in detecting light sleep. The MMWA method showed 51% overall Kappa agreement with the EEG one in detecting wake/sleep epochs, with sensitivity of 94% and specificity of 53% in detecting sleep epochs. MMWA, relative to EEG, underestimated SOL by ~10 min. There was no significant difference between Fitbit and MMWA methods in amount of bias in estimating SOL, WASO, TST, and SE; however, the minimum detectable change (MDC) per sleep variable with Fitbit was better (smaller) than with MMWA, respectively, by ~10 min, ~16 min, ~22 min, and ~8%. Overall, performance of Fitbit accelerometry and HRV technology in conjunction with its proprietary IA to detect sleep vs. wake episodes is slightly better than wrist actigraphy that relies solely on accelerometry and best performing Sadeh IA. Moreover, the smaller MDC of Fitbit technology in deriving sleep parameters in comparison to wrist actigraphy makes it a suitable option for assessing changes in sleep quality over time, longitudinally, and/or in response to interventions.

Accuracy of Wristband Fitbit Models in Assessing Sleep: Systematic Review and Meta-Analysis.

BACKGROUND: Wearable sleep monitors are of high interest to consumers and researchers because of their ability to provide estimation of sleep patterns in free-living conditions in a cost-efficient way. OBJECTIVE: We conducted a systematic review of publications reporting on the performance of wristband Fitbit models in assessing sleep parameters and stages. METHODS: In adherence with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement, we comprehensively searched the Cumulative Index to Nursing and Allied Health Literature (CINAHL), Cochrane, Embase, MEDLINE, PubMed, PsycINFO, and Web of Science databases using the keyword Fitbit to identify relevant publications meeting predefined inclusion and exclusion criteria. RESULTS: The search yielded 3085 candidate articles. After eliminating duplicates and in compliance with inclusion and exclusion criteria, 22 articles qualified for systematic review, with 8 providing quantitative data for meta-analysis. In reference to polysomnography (PSG), nonsleep-staging Fitbit models tended to overestimate total sleep time (TST; range from approximately 7 to 67 mins; effect size=-0.51, P<.001; heterogenicity: I2=8.8%, P=.36) and sleep efficiency (SE; range from approximately 2% to 15%; effect size=-0.74, P<.001; heterogenicity: I2=24.0%, P=.25), and underestimate wake after sleep onset (WASO; range from approximately 6 to 44 mins; effect size=0.60, P<.001; heterogenicity: I2=0%, P=.92) and there was no significant difference in sleep onset latency (SOL; P=.37; heterogenicity: I2=0%, P=.92). In reference to PSG, nonsleep-staging Fitbit models correctly identified sleep epochs with accuracy values between 0.81 and 0.91, sensitivity values between 0.87 and 0.99, and specificity values between 0.10 and 0.52. Recent-generation Fitbit models that collectively utilize heart rate variability and body movement to assess sleep stages performed better than early-generation nonsleep-staging ones that utilize only body movement. Sleep-staging Fitbit models, in comparison to PSG, showed no significant difference in measured values of WASO (P=.25; heterogenicity: I2=0%, P=.92), TST (P=.29; heterogenicity: I2=0%, P=.98), and SE (P=.19) but they underestimated SOL (P=.03; heterogenicity: I2=0%, P=.66). Sleep-staging Fitbit models showed higher sensitivity (0.95-0.96) and specificity (0.58-0.69) values in detecting sleep epochs than nonsleep-staging models and those reported in the literature for regular wrist actigraphy. CONCLUSIONS: Sleep-staging Fitbit models showed promising performance, especially in differentiating wake from sleep. However, although these models are a convenient and economical means for consumers to obtain gross estimates of sleep parameters and time spent in sleep stages, they are of limited specificity and are not a substitute for PSG.

Performance comparison of different interpretative algorithms utilized to derive sleep parameters from wrist actigraphy data.

We compared performance of four popular interpretative algorithms (IAs), i.e., Cole-Kripke, Rescored Cole-Kripke, Sadeh, and UCSD, utilized to derive sleep parameters from wrist actigraphy data. We conducted in-home sleep study of 40 healthy adults (17 female/23 male; age 26.7 ± 12.1 years), assessing sleep variables both by Motionlogger® Micro Watch Actigraphy (MMWA) and Zmachine® Insight+ electroencephalography (EEG). Data of MMWA were separately scored per 30 sec epochs by each of the four popular IAs, and data of the Zmachine were also scored per 30 sec epochs by its proprietary IA. In reference to the EEG Zmachine method, all four of the MMWA algorithms showed high (~94 to 98%) sensitivity and moderate (~42 to 54%) specificity in detecting Sleep epochs. All of them significantly underestimated Sleep Onset Latency (SOL: ~9 to 20 min), and all of them, except the Sadeh IA, significantly underestimated Wake After Sleep Onset (WASO: ~22 to 25 min) and overestimated Total Sleep Time (TST: ~32 to 45 min) and Sleep Efficiency (SE: ~7 to 9%). The Sadeh IA showed significantly smaller bias than the other three IAs in deriving WASO, TST, and SE. Overall, application of 'Rescoring Rules' improved performance of the Cole-Kripke IA. The Sadeh and Rescored Cole-Kripke IAs exhibited highest agreement with the EEG Zmachine method (Cohen's Kappa: ~51%), while the UCSD IA exhibited lowest agreement (Cohen's kappa: ~47%). However, minimum detectable change across all sleep parameters was smallest with use of the UCSD IA and, except for SOL, largest with use of the Sadeh algorithm. Findings of this study indicate the Sadeh IA is most appropriate for deriving sleep parameters of healthy adults, while the UCSD IA is most appropriate for evaluating change in sleep parameters over time or in response to medical intervention.

Before-bedtime passive body heating by warm shower or bath to improve sleep: A systematic review and meta-analysis.

Water-based passive body heating (PBHWB) as a warm shower or bath before bedtime is often recommended as a simple means of improving sleep. We searched PubMed, CINAHL, Cochran, Medline, PsycInfo, and Web of Science databases and extracted pertinent information from publications meeting predefined inclusion and exclusion criteria to explore the effects of PBHWB on sleep onset latency (SOL), wake after sleep onset, total sleep time, sleep efficiency (SE), slow wave sleep, and subjective sleep quality. The search yielded 5322 candidate articles of which 17 satisfied inclusion criteria after removing duplicates, with 13 providing comparable quantitative data for meta-analyses. PBHWB of 40-42.5 °C was associated with both improved self-rated sleep quality and SE, and when scheduled 1-2 h before bedtime for little as 10 min significant shortening of SOL. These findings are consistent with the mechanism of PBHWB effects being the extent of core body temperature decline achieved by increased blood perfusion to the palms and soles that augments the distal-to-proximal skin temperature gradient to enhance body heat dissipation. Nonetheless, additional investigation is required because the findings regarding PBHWB are limited by the relative scarcity of reported research, especially its optimal timing and duration plus exact mechanisms of effects.

Sleep-disordered breathing in heart failure patients after ventricular assist device implantation and heart transplantation.

Chronic heart failure (CHF) represents a major health and economic burden and is associated with high rates of hospital admission, morbidity, mortality and decreased quality-adjusted life years. New advances in the treatment of CHF such as ventricular assist devices (VADs) and heart transplantation have helped improve outcomes. Sleep-disordered breathing (SDB) is highly prevalent in CHF patients and the associated morbidity makes it essential for physicians to be more cognizant about its existence, interaction and need for treatment. This is a review of what is known to date about SDB in CHF patients who have undergone advanced treatments with VADs and/or heart transplantation.

Ventricular assist devices and sleep-disordered breathing.

Congestive heart failure is one of the leading causes of morbidity and mortality in the United States, and left ventricular assist devices have revolutionized treatment of end-stage heart failure. Given that sleep apnea results in significant morbidity in these patients with advanced heart failure, practicing sleep physicians need to have an understanding of left ventricular assist devices. In this review, we summarize what is known about ventricular assist devices as they relate to sleep medicine.