Relação entre apoio social e sono de pessoas idosas cuidadoras em vulnerabilidade social / Relationship between social support and sleep of elderly caregivers in social vulnerability / Relación entre apoyo social y sueño de adultos mayores cuidadores con vulnerabilidad social

Objetivo: analisar a relação entre apoio social e qualidade do sono de pessoas idosas que cuidam de outros idosos em ambiente de vulnerabilidade social. Método: estudo transversal realizado com 65 cuidadores entrevistados por meio de instrumento de caracterização, Índice de Katz, Escala de Lawton e Brody, Índice de Qualidade do Sono de Pittsburgh e Escala de Apoio Social do Medical Outcomes Study, com dados analisados com testes de comparação e de correlação. Resultados: a maioria eram mulheres, cônjuges do idoso cuidado e possuíam sono de má qualidade. Observou-se correlação fraca e inversa entre má qualidade do sono e a dimensão interação social positiva (Rho=-0,27; p=0,028). Identificou-se relação significativa entre: apoio material e disfunção diurna (p=0,034); apoio afetivo e eficiência do sono (p=0,026); interação social positiva e qualidade subjetiva do sono (p=0,001) e disfunção diurna (p=0,008). Conclusão: Quanto maior a interação social positiva, melhor é a qualidade do sono.

Objective: to analyze the relationship between social support and sleep quality of elderly individuals who care for other elderly individuals in a socially vulnerable environment. Method: a cross-sectional study conducted with 65 caregivers interviewed using a characterization instrument, Katz Index, Lawton and Brody Scale, Pittsburgh Sleep Quality Index, and Medical Outcomes Study Social Support Scale, with data analyzed using comparison and correlation tests. Results: the majority were women, spouses of the elderly being cared for, and had poor sleep quality. A weak and inverse correlation was observed between poor sleep quality and the positive social interaction dimension (Rho=-0.27; p=0.028). Significant relationships were identified between: material support and daytime dysfunction (p=0.034); emotional support and sleep efficiency (p=0.026); positive social interaction and subjective sleep quality (p=0.001), as well as daytime dysfunction (p=0.008). Conclusion: The higher the positive social interaction, the better the sleep quality.

Objetivo: analizar la relación entre el apoyo social y la calidad del sueño de personas mayores que cuidan de otras personas mayores en entornos socialmente vulnerables. Método: estudio transversal realizado con 65 cuidadores entrevistados mediante un instrumento de caracterización, Índice de Katz, Escala de Lawton y Brody, Índice de Calidad del Sueño de Pittsburgh y Escala de Apoyo Social del Medical Outcomes Study, los datos fueron analizados mediante pruebas de comparación y correlación. Resultados: la mayoría eran mujeres, cónyuges del adulto mayor que recibe el cuidado y tenían mala calidad del sueño. Se observó una correlación débil e inversa entre la mala calidad del sueño y la dimensión de interacción social positiva (Rho=-0,27; p=0,028). Se identificó que había relación significativa entre: apoyo material y disfunción diurna (p=0,034); apoyo afectivo y eficiencia del sueño (p=0,026); interacción social positiva y calidad subjetiva del sueño (p=0,001) y disfunción diurna (p=0,008). Conclusión: Cuanto mayor sea la interacción social positiva, mejor será la calidad del sueño.

NREM sleep brain networks modulate cognitive recovery from sleep deprivation.

Decrease in cognitive performance after sleep deprivation followed by recovery after sleep suggests its key role, and especially non-rapid eye movement (NREM) sleep, in the maintenance of cognition. It remains unknown whether brain network reorganization in NREM sleep stages N2 and N3 can uniquely be mapped onto individual differences in cognitive performance after a recovery nap following sleep deprivation. Using resting state functional magnetic resonance imaging (fMRI), we quantified the integration and segregation of brain networks during NREM sleep stages N2 and N3 while participants took a 1-hour nap following 24-hour sleep deprivation, compared to well-rested wakefulness. Here, we advance a new analytic framework called the hierarchical segregation index (HSI) to quantify network segregation across spatial scales, from whole-brain to the voxel level, by identifying spatio-temporally overlapping large-scale networks and the corresponding voxel-to-region hierarchy. Our results show that network segregation increased in the default mode, dorsal attention and somatomotor networks during NREM sleep compared to wakefulness. Segregation within the visual, limbic, and executive control networks exhibited N2 versus N3 sleep-specific voxel-level patterns. More segregation during N3 was associated with worse recovery of working memory, executive attention, and psychomotor vigilance after the nap. The level of spatial resolution of network segregation varied among brain regions and was associated with the recovery of performance in distinct cognitive tasks. We demonstrated the sensitivity and reliability of voxel-level HSI to provide key insights into within-region variation, suggesting a mechanistic understanding of how NREM sleep replenishes cognition after sleep deprivation.

Polysomnography parameters in a large cohort of people with multiple sclerosis.

BACKGROUND: Disordered and disturbed sleep is quite common among people with multiple sclerosis (PwMS). It is associated with fatigue one of most disabling symptoms in MS. This study aims at comparing polysomnographic (PSG) sleep parameters in a large single cohort of PwMS from a single center to that of the published norms. Hence establishing PSG parameters in PwMS. METHODS: This is a retrospective review of 299 consecutive adult PwMS who were seen and evaluated with an overnight PSG at a Comprehensive MS Care Center between 11/19/2001 to 9/17/2014. Data extracted from the PSG included Total Sleep Time (TST), sleep efficiency (SE), sleep onset latency (SOL), Relative REM latency, total apnea-hypopnea indices (AHI), spontaneous arousal indices (AI), total periodic leg movements indices (PLMI) and, sleep architecture metrics including percentage spent in stages N1/N2, N3, and REM. RESULTS: PwMS, compared to normative data, had, on average, 85.9 min shorter TST (p < 0.001), 27.3 min longer SOL (p < 0.0001), 62.1 min longer REM latency (p < 0.0001), 10.7 % lower SE (p < 0.0001), 16.4 % more N1/N2 (p < 0.0001) and 11.4 % less N3 (p < 0.0001). REM latency The prevalence of Obstructive Sleep Apnea (OSA) was high at 60.7 % and the mean AHI was higher by 11.1 events per hour (p < 0.0001). CONCLUSIONS: This study establishes PSG parameters in the largest PwMS cohort reported to date. It is important to be vigilant of sleep complaints in PwMS. Future prospective large single cohort studies with standardized methods are needed to further understand sleep disturbances in PwMS as well as their causes and implications.

Long-term exposure to ozone and sleep disorders in children: A multicity study in China.

Evidence regarding the link between long-term ambient ozone (O3) exposure and childhood sleep disorders is little. This study aims to examine the associations between long-term exposure to O3 and sleep disorders in children. We conducted a population-based cross-sectional survey, including 185,428 children aged 6-18 years in 173 schools across 14 Chinese cities during 2012 and 2018. Parents or guardians completed a checklist using Sleep Disturbance Scale for Children, and O3 exposure at residential and school addresses was estimated using a satellite-based spatiotemporal model. We used generalized linear mixed models to test the associations with adjustment for factors including socio-demographic variables, lifestyle, meteorology and multiple pollutants. Mean concentrations of O3, particulate matter with diameters ≤2.5 mm (PM2.5) and nitrogen dioxide (NO2) were 89.0 µg/m3, 42.5 µg/m3 and 34.4 µg/m3, respectively. O3 and NO2 concentrations were similar among provinces, while PM2.5 concentration varied significantly among provinces. Overall, 19.4% of children had at least one sleep disorder. Long-term exposure to O3 was positively associated with odds of sleep disorders for all subtypes. For example, each interquartile increment in home-school O3 concentrations was associated with a higher odds ratio for global sleep disorder, at 1.22 (95% confidence interval: 1.18, 1.26). Similar associations were observed for sleep disorder subtypes. The associations remained similar after adjustment for PM2.5 and NO2. Moreover, these associations were heterogeneous regionally, with more prominent associations among children residing in southeast region than in northeast and northwest regions in China. We concluded that long-term exposure to O3 is positively associated with risks of childhood sleep disorders. These associations varied by geographical region of China.

Capturing patient-reported sleep disturbance in atopic dermatitis clinical trials.

BACKGROUND: Patient-focused approaches to capturing day-to-day variability in sleep disturbance are needed to properly evaluate the sleep benefits of new treatments. Such approaches rely on patient-reported outcome (PRO) measures validated in the target patient population. METHODS: Using atopic dermatitis (AD) as an example of a disease in which sleep is commonly disturbed, we developed a strategy for measuring sleep disturbance in AD trials. In developing this strategy, we conducted a targeted literature review and held concept elicitation interviews with adolescents and adults with AD. We subsequently identified potentially suitable PRO measures and cognitively debriefed them. Finally, we evaluated their psychometric properties using data from phase 2b (NCT03100344) and phase 3 (NCT03985943 and NCT03989349) clinical trials. RESULTS: The literature review confirmed that sleep disturbance is a key impact of AD but failed to identify validated PRO measures for assessing fluctuations in sleep disturbance. Subsequent concept elicitation interviews confirmed the multidimensional nature of sleep disturbance in AD and supported use of a single-item measure to assess overall sleep disturbance severity, complemented by a diary to capture individual components of sleep disturbance. The single-item sleep disturbance numerical rating scale (SD NRS) and multi-item Subject Sleep Diary (SSD)-an AD-adapted version of the Consensus Sleep Diary-were identified as potentially suitable PRO measures. Cognitive debriefing of the SD NRS and SSD demonstrated their content validity and their understandability to patients. Psychometric analyses based on AD trial data showed that the SD NRS is a well-defined, reliable, and fit-for-purpose measure of sleep disturbance in adults with AD. Furthermore, the SD NRS correlated with many SSD sleep parameters, suggesting that most concepts from the SSD can be covered using the SD NRS. CONCLUSIONS: Using these findings, we developed an approach for measuring sleep disturbance in AD trials. Subject to further research, the same approach could also be applied to future trials of other skin diseases where itch causes sleep disturbance.

Detection and severity assessment of obstructive sleep apnea according to deep learning of single-lead electrocardiogram signals.

Developing a convenient detection method is important for diagnosing and treating obstructive sleep apnea. Considering availability and medical reliability, we established a deep-learning model that uses single-lead electrocardiogram signals for obstructive sleep apnea detection and severity assessment. The detection model consisted of signal preprocessing, feature extraction, time-frequency domain information fusion, and classification segments. A total of 375 patients who underwent polysomnography were included. The single-lead electrocardiogram signals obtained by polysomnography were used to train, validate and test the model. Moreover, the proposed model performance on a public dataset was compared with the findings of previous studies. In the test set, the accuracy of per-segment and per-recording detection were 82.55% and 85.33%, respectively. The accuracy values for mild, moderate and severe obstructive sleep apnea were 69.33%, 74.67% and 85.33%, respectively. In the public dataset, the accuracy of per-segment detection was 91.66%. A Bland-Altman plot revealed the consistency of true apnea-hypopnea index and predicted apnea-hypopnea index. We confirmed the feasibility of single-lead electrocardiogram signals and deep-learning model for obstructive sleep apnea detection and severity evaluation in both hospital and public datasets. The detection performance is high for patients with obstructive sleep apnea, especially those with severe obstructive sleep apnea.

Novel Sleep Phenotypic Profiles Associated With Incident Atrial Fibrillation in a Large Clinical Cohort.

BACKGROUND: While sleep disorders are implicated in atrial fibrillation (AF), the interplay of physiologic alterations and symptoms remains unclear. Sleep-based phenotypes can account for this complexity and translate to actionable approaches to identify at-risk patients and therapeutic interventions. OBJECTIVES: This study hypothesized discrete phenotypes of symptoms and polysomnography (PSG)-based data differ in relation to incident AF. METHODS: Data from the STARLIT (sleep Signals, Testing, And Reports LInked to patient Traits) registry on Cleveland Clinic patients (≥18 years of age) who underwent PSG from November 27, 2004, to December 30,2015, were retrospectively examined. Phenotypes were identified using latent class analysis of symptoms and PSG-based measures of sleep-disordered breathing and sleep architecture. Phenotypes were included as the primary predictor in a multivariable-adjusted Cox proportional hazard models for incident AF. RESULTS: In our cohort (N = 43,433, age 51.8 ± 14.5 years, 51.9% male, 74.9% White), 7.3% (n = 3,166) had baseline AF. Over a 7.6- ± 3.4-year follow-up period, 8.9% (n = 3,595) developed incident AF. Five phenotypes were identified. The hypoxia subtype (n = 3,245) had 48% increased incident AF (HR: 1.48; 95% CI: 1.34-1.64), the apneas + arousals subtype (n = 4,592) had 22% increased incident AF (HR: 1.22; 95% CI: 1.10-1.35), and the short sleep + nonrapid eye movement subtype (n = 6,126) had 11% increased incident AF (HR: 1.11; 95% CI: 1.01-1.22) compared with long sleep + rapid eye movement (n = 26,809), the reference group. The hypopneas subtype (n = 2,661) did not differ from reference (HR: 0.89; 95% CI: 0.77-1.03). CONCLUSIONS: Consistent with prior evidence supporting hypoxia as an AF driver and cardiac risk of the sleepy phenotype, this constellation of symptoms and physiologic alterations illustrates vulnerability for AF development, providing potential value in enhancing our understanding of integrated sleep-specific symptoms and physiologic risk of atrial arrhythmogenesis.

Study on the preventive effect of dexmedetomidine on anesthetic associated sleep disturbance in young to middle-aged female patients undergoing hysteroscopy: a study protocol for a crossover randomized controlled trial.

BACKGROUND: Postoperative sleep disturbance has a potentially detrimental effect on postoperative recovery. Perioperative patients are affected by several factors. General anesthesia induces a non-physiological state that does not resemble natural sleep. Exposure to propofol/sevoflurane can lead to desynchronization of the circadian rhythm, which may result in postoperative sleep disturbance characterized by mid-cycle advancement of sleep and daytime sleepiness. Dexmedetomidine is a highly selective α2-adrenoceptor agonist with a unique sedative effect that facilitates the transition from sleep to wakefulness. Basic research has shown that dexmedetomidine induces deep sedation, similar to physical sleep, and helps maintain forebrain connectivity, which is likely to reduce delirium after surgery. The aim of this study is to evaluate the influence of exposure to the mono-anesthetic propofol on the development of postoperative sleep disturbance in young and middle-aged female patients undergoing hysteroscopy and whether prophylactic administration of dexmedetomidine influences reducing postoperative sleep disturbance. METHODS: This prospective randomized controlled trial (RCT) will include 150 patients undergoing hysteroscopy at the First Affiliated Hospital of Xiamen University. Participants will be randomly assigned to three groups in a 1:1:1 ratio. The dexmedetomidine group will have two subgroups and will receive a nasal spray of 0.2 µg/kg or 0.5 µg/kg 25 min before surgery, while the control group will receive a saline nasal spray. Three groups will undergo hysteroscopy with propofol-based TIVA according to the same scheme. Sleep quality will be measured using a wearable device and double-blind sleep assessments will be performed before surgery and 1, 3, and 7 days after surgery. SPSS 2.0 is used for statistical analysis. A χ2 test is used to compare groups, and t-test is used to determine statistical the significance of continuous variables. DISCUSSION: The purpose of this study is to investigate the incidence of propofol-associated sleep disorders and to test a combination of dexmedetomidine anesthesia regimen for the prevention of postoperative sleep disorders. This study will help to improve patients' postoperative satisfaction and provide a new strategy for comfortable perioperative medical treatment. TRIAL REGISTRATION: ClinicalTrials.gov NCT06281561. Registered on February 24, 2024.

Digital Measures Development: Lessons Learned from an Expert Workshop Addressing Cross-Therapeutic Area Measures of Sleep.

Introduction: The Digital Measures Development: Core Measures of Sleep project, led by the Digital Medicine Society (DiMe), emphasizes the importance of sleep as a cornerstone of health and the need for standardized measurements of sleep and its disturbances outside the laboratory. This initiative recognizes the complex relationship between sleep and overall health, addressing it as both a symptom of underlying conditions and a consequence of therapeutic interventions. It aims to fill a crucial gap in healthcare by promoting the development of accessible, nonintrusive, and cost-effective digital tools for sleep assessment, focusing on factors important to patients, caregivers, and clinicians. Methods: A central feature of this project was an expert workshop conducted on April 19th, 2023. The workshop convened stakeholders from diverse backgrounds, including regulatory, payer, industry, academic, and patient groups, to deliberate on the project's direction. This gathering focused on discussing the challenges and necessities of measuring sleep across various therapeutic areas, aiming to identify broad areas for initial focus while considering the feasibility of generalizing these measures where applicable. The methodological emphasis was on leveraging expert consensus to guide the project's approach to digital sleep measurement. Results: The workshop resulted in the identification of seven key themes that will direct the DiMe Core Digital Measures of Sleep project and the broader field of sleep research moving forward. These themes underscore the project's innovative approach to sleep health, highlighting the complexity of omni-therapeutic sleep measurement and identifying potential areas for targeted research and development. The discussions and outcomes of the workshop serve as a roadmap for enhancing digital sleep measurement tools, ensuring they are relevant, accurate, and capable of addressing the nuanced needs of diverse patient populations. Conclusion: The Digital Medicine Society's Core Measures of Sleep project represents a pivotal effort to advance sleep health through digital innovation. By focusing on the development of standardized, patient-centric, and clinically relevant digital sleep assessment tools, the project addresses a significant need in healthcare. The expert workshop's outcomes underscore the importance of collaborative, multi-stakeholder engagement in identifying and overcoming the challenges of sleep measurement. This initiative sets a new precedent for the integration of digital tools into sleep health research and practice, promising to improve outcomes for patients worldwide by enhancing our understanding and measurement of sleep.

The Two Fundamental Shapes of Sleep Heart Rate Dynamics and Their Connection to Mental Health in College Students.

Introduction: Wearable devices are rapidly improving our ability to observe health-related processes for extended durations in an unintrusive manner. In this study, we use wearable devices to understand how the shape of the heart rate curve during sleep relates to mental health. Methods: As part of the Lived Experiences Measured Using Rings Study (LEMURS), we collected heart rate measurements using the Oura ring (Gen3) for over 25,000 sleep periods and self-reported mental health indicators from roughly 600 first-year university students in the USA during the fall semester of 2022. Using clustering techniques, we find that the sleeping heart rate curves can be broadly separated into two categories that are mainly differentiated by how far along the sleep period the lowest heart rate is reached. Results: Sleep periods characterized by reaching the lowest heart rate later during sleep are also associated with shorter deep and REM sleep and longer light sleep, but not a difference in total sleep duration. Aggregating sleep periods at the individual level, we find that consistently reaching the lowest heart rate later during sleep is a significant predictor of (1) self-reported impairment due to anxiety or depression, (2) a prior mental health diagnosis, and (3) firsthand experience in traumatic events. This association is more pronounced among females. Conclusion: Our results show that the shape of the sleeping heart rate curve, which is only weakly correlated with descriptive statistics such as the average or the minimum heart rate, is a viable but mostly overlooked metric that can help quantify the relationship between sleep and mental health.

Application of dezocine patient-controlled epidural analgesia in postoperative analgesia in patients with total myomectomy.

BACKGROUND: Uterine fibroids are common benign gynecological conditions. Patients who experience excessive menstruation, anemia, and pressure symptoms should be administered medication, and severe cases require a total hysterectomy. This procedure is invasive and causes severe postoperative pain, which can affect the patient's postoperative sleep quality and, thus, the recovery process. AIM: To evaluate use of dezocine in patient-controlled epidural analgesia (PCEA) for postoperative pain management in patients undergoing total myomectomy. METHODS: We selected 100 patients undergoing total abdominal hysterectomy for uterine fibroids and randomized them into two groups: A control group receiving 0.2% ropivacaine plus 0.06 mg/mL of morphine and an observation group receiving 0.2% ropivacaine plus 0.3 mg/mL of diazoxide in their PCEA. Outcomes assessed included pain levels, sedation, recovery indices, PCEA usage, stress factors, and sleep quality. RESULTS: The observation group showed lower visual analog scale scores, shorter postoperative recovery indices, fewer mean PCEA compressions, lower cortisol and blood glucose levels, and better polysomnographic parameters compared to the control group (P < 0.05). The cumulative incidence of adverse reactions was lower in the observation group than in the control group (P < 0.05). CONCLUSION: Dezocine PCEA can effectively control the pain associated with total myomectomy, reduce the negative impact of stress factors, and have less impact on patients' sleep, consequently resulting in fewer adverse effects.

Analysis of sleep quality, disease uncertainty, and psychological tolerance in patients undergoing chemotherapy for digestive tract malignancies.

BACKGROUND: Colorectal cancer is the second leading cause of cancer-related deaths among digestive tract malignancies, following gastric cancer. Sleep is of great significance for maintaining human health. The incidence of sleep disorders in patients with cancer is approximately twice that observed in the general population. Lack of sleep can prolong hospital stays, increase the likelihood of infection, and increase mortality rates. Therefore, studying the factors related to sleep quality is significant for improving the quality of life of patients with malignant tumors of the digestive tract. AIM: To investigate the relationships among sleep quality, disease uncertainty, and psychological resilience in patients undergoing chemotherapy for digestive tract malignancies. METHODS: A total of 131 patients with malignant digestive tract tumors who were treated at Hefei BOE Hospital between April 2021 and September 2022 were selected as research participants. Based on their Pittsburgh Sleep Quality Index (PSQI) scores, participants were divided into either the sleep disorder group (PSQI score > 7) or the normal sleep group (PSQI score ≤ 7). The clinical data-together with the Mishel Uncertainty in Illness Scale for Adults (MUIS-A) and Connor-Davidson Resilience Scale (CD-RISC) scores-were compared. RESULTS: In this study, 78 (59.54%) patients with digestive tract malignancies developed sleep disorders after chemotherapy. Sleep disorder incidence was higher in patients with colorectal cancer than in those with gastric and esophageal cancers (P < 0.05). The total MUIS-A score and those for each item in the sleep disorder group were higher than those in the normal sleep group. The total CD-RISC score and those for each item in the sleep disorder group were lower than those in the normal sleep group (P < 0.05). The PSQI scores of patients with malignant digestive tract tumors were positively correlated with the scores for lack of disease information, disease uncertainty, and unpredictability in the MUIS-A and negatively correlated with the scores for tenacity, self-improvement, and optimism in the CD-RISC (P < 0.05). CONCLUSION: Patients undergoing chemotherapy for digestive tract malignancies are prone to sleep problems related to disease uncertainty and psychological resilience. Therefore, interventions can be implemented to improve their sleep quality.

Risk factors and management countermeasures for obstructive sleep apnea hypoventilation syndrome in children.

BACKGROUND: Obstructive sleep apnea hypoventilation syndrome (OSAHS) in children is a sleep respiratory disorder characterized by a series of pathophysiologic changes. Statistics in recent years have demonstrated an increasing yearly incidence. AIM: To investigate the risk factors for OSAHS in children and propose appropriate management measures. METHODS: This study had a case-control study design. Altogether, 85 children with OSAHS comprised the case group, and healthy children of the same age and sex were matched at 1:1 as the control group. Basic information, including age, sex, height, weight and family history, and medical history data of all study participants were collected. Polysomnography was used to detect at least 8 h of nocturnal sleep. All participants were clinically examined for the presence of adenoids, enlarged tonsils, sinusitis, and rhinitis. RESULTS: The analysis of variance revealed that the case group had a higher proportion of factors such as adenoid grading, tonsil indexing, sinusitis, and rhinitis than the control group. CONCLUSION: A regression model was established, and glandular pattern grading, tonsil indexing, sinusitis, and pharyngitis were identified as independent risk factors affecting OSAHS development.

Perceptions of Emerging Adults With Type 1 Diabetes Mellitus on How the Condition Influences Sleep Quality: A Qualitative Study.

Background: Emerging adulthood is a phase characterized by exploration which potentially affecting sleep quality. While many emerging adults are healthy, the effects of chronic diseases such as Type 1 Diabetes Mellitus (T1DM) on sleep may be underestimated. Considering the frequency of nocturnal glycemic alterations that cause awakenings, this study explored the perceptions of emerging adults in Andalusia on the influence of T1DM on their sleep quality. Methods: A qualitative approach was used for this study. Purposive sampling through diabetes associations was initially utilized, supplemented by snowball sampling, in order to conduct semistructured interviews with 73 emerging adults (aged 18-29) diagnosed with T1DM, to explore their perceptions of the influence of T1DM on sleep quality. Interpretative Phenomenological Analysis was used for data analysis. Results: Sleep disruptions caused by overnight hyperglycemia and hypoglycemia were identified as significant factors. However, 62% of participants did not perceive the influence of diabetes on their sleep quality, despite experiencing frequent overnight glycemic alterations (reported by 40.9%). Conclusions: Perception of the impact of T1DM on sleep quality does not always align with the frequency of disruptions. Nonetheless, promoting healthy sleep and systematically assessing sleep quality can benefit both sleep and glycemic outcomes, regardless of individual perceptions.

Prediction of Mild Cognitive Impairment Status: Pilot Study of Machine Learning Models Based on Longitudinal Data From Fitness Trackers.

BACKGROUND: Early signs of Alzheimer disease (AD) are difficult to detect, causing diagnoses to be significantly delayed to time points when brain damage has already occurred and current experimental treatments have little effect on slowing disease progression. Tracking cognitive decline at early stages is critical for patients to make lifestyle changes and consider new and experimental therapies. Frequently studied biomarkers are invasive and costly and are limited for predicting conversion from normal to mild cognitive impairment (MCI). OBJECTIVE: This study aimed to use data collected from fitness trackers to predict MCI status. METHODS: In this pilot study, fitness trackers were worn by 20 participants: 12 patients with MCI and 8 age-matched controls. We collected physical activity, heart rate, and sleep data from each participant for up to 1 month and further developed a machine learning model to predict MCI status. RESULTS: Our machine learning model was able to perfectly separate between MCI and controls (area under the curve=1.0). The top predictive features from the model included peak, cardio, and fat burn heart rate zones; resting heart rate; average deep sleep time; and total light activity time. CONCLUSIONS: Our results suggest that a longitudinal digital biomarker differentiates between controls and patients with MCI in a very cost-effective and noninvasive way and hence may be very useful for identifying patients with very early AD who can benefit from clinical trials and new, disease-modifying therapies.

A Preliminary Analysis of Stress Burden and Cognitive Function and Clinically-Adjudicated Cognitive Outcomes in Black American Adults.

BACKGROUND: The combination of exposure to multiple stressors and psychological distress may contribute to the disproportionate burden of dementia risk among Black Americans. This study estimates the effect of an index of stress and psychological distress (i.e., "stress burden") on cognitive function and clinically-adjudicated cognitive outcomes among older Black American adults, and examines sleep as a mediator. METHODS: The sample included 204 Black adults (79% female; mean age=64 years) from Pittsburgh, PA. Stress burden comprised three self-reported stress and distress measures assessed in 2016: discrimination, psychological distress, and post-traumatic stress. Potential mediators included actigraphy-assessed sleep duration and efficiency from 2018. Cognitive battery and clinical adjudication in 2019 assessed cognitive function and clinically-adjudicated outcomes. Causal mediation analysis estimated the direct effect between stress burden and cognitive outcomes, and indirect effects through sleep, after adjusting for socio-demographics and hypertension. RESULTS: Higher stress burden had a significant direct effect on lower executive functioning and visuospatial performance. However, there were no significant indirect effects (i.e., mediation) by sleep disturbances on any domain of cognitive function assessed. Also, there were no significant direct or indirect effects on clinically-adjudicated outcomes. CONCLUSIONS: Multiple stressors often co-occur and may contribute to racial disparities in cognitive health. Findings suggest that higher stress burden had negative effects on functioning in executive and visuospatial domains in this community-based sample of older Black American adults. However, there was no evidence of mediation by sleep. Findings highlight the importance of continued work to identify modifiable pathways between stress burden and cognitive health disparities.

Sleep-specific repetitive negative thinking processes and prenatal insomnia symptoms: A naturalistic follow-up study from mid- to late-pregnancy.

Insomnia symptoms are highly prevalent during pregnancy; therefore, identifying modifiable risk markers is important for risk prediction and early intervention. This study aimed to examine the role of sleep-specific rumination and sleep-specific worry in prenatal insomnia symptoms. A total of 859 married pregnant women without history of psychiatric illnesses (mean [standard deviation] age, 30.15 [3.86] years; 593 [69.0%] with a bachelor's degree or above) were enrolled from the obstetrical outpatient departments of two tertiary comprehensive hospitals in Shandong, China, who completed assessments of sleep-specific rumination, sleep-specific worry, and insomnia symptoms at baseline (mid-pregnancy) and follow-up (late-pregnancy). Measures included Daytime Insomnia Symptom Response Scale, Anxiety and Preoccupation about Sleep Questionnaire, and Insomnia Severity Index. Our results showed that after controlling for covariates, both sleep-specific rumination and sleep-specific worry showed significant concurrent and prospective associations with insomnia symptoms, and the increases in scores of sleep-specific rumination and sleep-specific worry over time were significantly associated with the increased likelihood of insomnia symptoms at follow-up. Moreover, the increases in sleep-specific rumination and sleep-specific worry over time were significantly associated with the increased likelihood of reporting newly developed insomnia symptoms rather than persistent normal sleep. However, the changes in sleep-specific rumination and sleep-specific worry were not significantly associated with the likelihood of reporting persistent or remitted insomnia symptoms rather than persistent normal sleep. In conclusion, sleep-specific rumination and sleep-specific worry were significantly associated with concurrent or subsequent insomnia symptoms; thus, they may be promising cognitive risk markers and intervention targets.

Rationale, Design, and Baseline Characteristics of Participants in the Health@NUS mHealth Augmented Cohort Study Examining Student-to-Work Life Transition: Protocol for a Prospective Cohort Study.

BACKGROUND: Integration of mobile health data collection methods into cohort studies enables the collection of intensive longitudinal information, which gives deeper insights into individuals' health and lifestyle behavioral patterns over time, as compared to traditional cohort methods with less frequent data collection. These findings can then fill the gaps that remain in understanding how various lifestyle behaviors interact as students graduate from university and seek employment (student-to-work life transition), where the inability to adapt quickly to a changing environment greatly affects the mental well-being of young adults. OBJECTIVE: This paper aims to provide an overview of the study methodology and baseline characteristics of participants in Health@NUS, a longitudinal study leveraging mobile health to examine the trajectories of health behaviors, physical health, and well-being, and their diverse determinants, for young adults during the student-to-work life transition. METHODS: University students were recruited between August 2020 and June 2022 in Singapore. Participants would complete biometric assessments and questionnaires at 3 time points (baseline, 12-, and 24-month follow-up visits) and use a Fitbit smartwatch and smartphone app to continuously collect physical activity, sedentary behavior, sleep, and dietary data over the 2 years. Additionally, up to 12 two-week-long bursts of app-based ecological momentary surveys capturing lifestyle behaviors and well-being would be sent out among the 3 time points. RESULTS: Interested participants (n=1556) were screened for eligibility, and 776 participants were enrolled in the study between August 2020 and June 2022. Participants were mostly female (441/776, 56.8%), of Chinese ethnicity (741/776, 92%), undergraduate students (759/776, 97.8%), and had a mean BMI of 21.9 (SD 3.3) kg/m2, and a mean age of 22.7 (SD 1.7) years. A substantial proportion were overweight (202/776, 26.1%) or obese (42/776, 5.4%), had indicated poor mental well-being (World Health Organization-5 Well-Being Index ≤50; 291/776, 37.7%), or were at higher risk for psychological distress (Kessler Psychological Distress Scale ≥13; 109/776, 14.1%). CONCLUSIONS: The findings from this study will provide detailed insights into the determinants and trajectories of health behaviors, health, and well-being during the student-to-work life transition experienced by young adults. TRIAL REGISTRATION: ClinicalTrials.gov NCT05154227; https://clinicaltrials.gov/study/NCT05154227. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/56749.

Circuit dynamics of superficial and deep CA1 pyramidal cells and inhibitory cells in freely moving macaques.

Diverse neuron classes in hippocampal CA1 have been identified through the heterogeneity of their cellular/molecular composition. How these classes relate to hippocampal function and the network dynamics that support cognition in primates remains unclear. Here, we report inhibitory functional cell groups in CA1 of freely moving macaques whose diverse response profiles to network states and each other suggest distinct and specific roles in the functional microcircuit of CA1. In addition, pyramidal cells that were grouped by their superficial or deep layer position differed in firing rate, burstiness, and sharp-wave ripple-associated firing. They also showed strata-specific spike-timing interactions with inhibitory cell groups, suggestive of segregated neural populations. Furthermore, ensemble recordings revealed that cell assemblies were preferentially organized according to these strata. These results suggest that hippocampal CA1 in freely moving macaques bears a sublayer-specific circuit organization that may shape its role in cognition.

Mapping of the network connection between sleep quality symptoms, depression, generalized anxiety, and burnout in the general population of Peru and El Salvador.

BACKGROUND: A meta-analysis of randomized controlled trials has suggested a bidirectional relationship between sleep problems and mental health issues. Despite these findings, there is limited conclusive evidence on the relationship between sleep quality, depression, anxiety, and burnout. OBJECTIVE: The current study aimed to evaluate the relationships between sleep quality symptoms, anxiety, depression, and burnout in samples of adult individuals from two Latin American countries, Peru and El Salvador, through network analysis and to identify key symptoms that reinforce the correlation and intensify the syndromes. METHODS: A total of 1012 individuals from El Salvador and Peru participated, with an average age of 26.5 years (SD = 9.1). Symptom networks were constructed for both countries based on data from the Jenkins Sleep Scale, Patient Health Questionnaire-2, General Anxiety Disorder-2, and a single burnout item. RESULTS: The results indicated that Depressed Mood, Difficulty Falling Asleep, and Nervousness were the most central symptoms in a network in the participating countries. The strongest conditional associations were found between symptoms belonging to the same construct, which were similar in both countries. Thus, there is a relationship between Nervousness and Uncontrollable Worry, Anhedonia and Depressed Mood, and Nighttime Awakenings and Difficulty in Staying Asleep. It was observed that burnout is a bridge symptom between both countries and presents stronger conditional associations with Tiredness on Awakening, Depressed Mood, and Uncontrollable Worry. Other bridge symptoms include a Depressed Mood and Nervousness. The network structure did not differ between the participants from Peru and El Salvador. CONCLUSION: The networks formed by sleep quality, anxiety, depression, and burnout symptoms play a prominent role in the comorbidity of mental health problems among the general populations of Peru and El Salvador. The symptom-based analytical approach highlights the different diagnostic weights of these symptoms. Treatments or interventions should focus on identifying central and bridge symptoms.