Objective Sleep Measures in Inpatients With Subacute Stroke Associated With Levels and Improvements in Activities of Daily Living

Sleep Following a Stroke: Multimodal Evaluation of Sleep Health and Disruptions and Impact on Recovery During Acute Inpatient Rehabilitation

BackgroundOur understanding of sleep during early stroke care and its impact on rehabilitation outcomes remains limited. The objectives of this work were to (1) evaluate multidimensional sleep health and disruptions during acute inpatient rehabilitation for individuals with stroke, and (2) explore the relationship between sleep health/disruptions and functional recovery.MethodsData from 103 individuals with stroke were analyzed during acute inpatient rehabilitation. Sleep health/disruptions were assessed via patient reports, actigraphy, and biometric sensors. Functional outcomes were measured at admission and discharge. Generalized Linear Models (GLMs) were used to describe changes in sleep health over time, and multivariate regressions analyzed sleep disruptions and sleep-related predictors of functional recovery.ResultsOver inpatient stays, sleep improved with a 23% reduction in wake after sleep onset and 15% fewer multiple overnight disruptions. GLMs revealed that improved sleep quality was associated with reduced overnight activity and increased heart rate over time. Poor initial sleep quality and cognitive status were associated with more overnight disruptions. Lastly, minimal associations were found between sleep health and functional recovery.ConclusionsSleep health during inpatient stroke rehabilitation is generally poor, though improves over time. Sleep is affected by neurological recovery and hospital environment. Overnight activity and autonomic biomarkers were associated with perceived sleep health, and both physiological and environmental factors triggered disruptions. The association between functional recovery and indirect indicators of sleep health requires further investigation. These findings reveal new insights about inpatient sleep which can inform early, targeted sleep interventions to optimize post-stroke outcomes.SIESTA, ClinicalTrials.gov (NCT04254484).

Poor sleep quality and its determinants among stroke survivors in Northwest Ethiopia

Sleep disorders are highly prevalent and linked bidirectionally to stroke as risk factors for stroke to worsen the outcomes. To date, most of the studies on post-stroke sleep were conducted in Western countries. Quality of sleep among stroke patients is masked by other physical and medical complications and limited attention is given in Ethiopia. To address this gap the current study aims to estimate the incidence of poor sleep quality and its determinants among stroke survivors in Northwest Ethiopia. A prospective cohort study was conducted in three public referral hospitals from June 2022 to December 2022. The study included 403 stroke survivors at the three-month follow-up. We conducted analyses of bivariable and multivariable logistic regression to look into the relationship between the outcome and the explanatory variables. Statistics were given as odds ratios and 95% confidence intervals, with a significance level of p < 0.05. The overall incidence of poor sleep quality was 50.1%, with a mean Global Sleep Quality (GSQ score) of 5.15 (SD ± 0.16). According to Pittsburgh Sleep Quality Index (PSQI) data, the mean sleep hour was 6.15. History of alcohol consumption, complications during admission, and time between the onset of symptoms and hospital arrival were predictors of sleep quality. Sleep quality was observed in half of stroke survivors. The study's findings point to the significance of screening for sleep quality following a stroke and further research is needed including admitted and non-admitted stroke patients.

A parallel-group randomized controlled trial of blue light versus red light for improving sleep, fatigue, and cognition following stroke: Pilot results and recommendations for further study

BACKGROUND

Disordered sleep and fatigue are common in the acute phase of stroke and can impede recovery.

OBJECTIVE

A randomized parallel group placebo-controlled pilot study compared daily morning exposure to blue light or red light (placebo) for improving daytime sleepiness, fatigue, nocturnal sleep, and cognition in patients receiving inpatient rehabilitation for acute stroke.

METHODS

43 patients with disordered sleep secondary to first episode stroke (n = 34 ischemic, n = 9 hemorrhagic; aged 66.2 ± 14.1 years) were randomized to receive 25 min of blue or red light for 5 or more days depending on inpatient rehabilitation length of stay (blue-light n = 21, red-light n = 22). At baseline and study discharge, daytime sleepiness was measured with the Karolinska Sleepiness Scale and Wits Pictorial Sleepiness Scale, fatigue with a visual analogue scale, and cognitive function with the Rey Auditory Verbal Learning Test and Trail Making Test (TMT). Wrist actigraphs measured nocturnal sleep parameters. Effect sizes were used to estimate sample sizes for larger studies.

RESULTS

Blue light exposure led to significant improvements in daytime sleepiness, fatigue, auditory verbal learning, and time to sleep onset (all p < .05) relative to red light exposure (effect size range 0.75 to 1.83). Change in TMT, minutes of nocturnal sleep, and number of awakenings after sleep onset were not statistically significant (effect sizes range 0.38 to 0.57).

CONCLUSION

Morning blue light exposure for 5 or more days after acute stroke led to greater improvements than red light exposure. Effect sizes suggest a larger study is warranted to confirm generalizability of pilot findings.

TRIAL REGISTRATION

ClinicalTrials.govNCT03125967 (Registered 01/01/2017).

Impact of Sleep Disorders and Disturbed Sleep on Brain Health: A Scientific Statement From the American Heart Association

Accumulating evidence supports a link between sleep disorders, disturbed sleep, and adverse brain health, ranging from stroke to subclinical cerebrovascular disease to cognitive outcomes, including the development of Alzheimer disease and Alzheimer disease-related dementias. Sleep disorders such as sleep-disordered breathing (eg, obstructive sleep apnea), and other sleep disturbances, as well, some of which are also considered sleep disorders (eg, insomnia, sleep fragmentation, circadian rhythm disorders, and extreme sleep duration), have been associated with adverse brain health. Understanding the causal role of sleep disorders and disturbances in the development of adverse brain health is complicated by the common development of sleep disorders among individuals with neurodegenerative disease. In addition to the role of sleep disorders in stroke and cerebrovascular injury, mechanistic hypotheses linking sleep with brain health and biomarker data (blood-based, cerebrospinal fluid-based, and imaging) suggest direct links to Alzheimer disease-specific pathology. These potential mechanisms and the increasing understanding of the "glymphatic system," and the recognition of the importance of sleep in poststroke recovery, as well, support a biological basis for the indirect (through the worsening of vascular disease) and direct (through specific effects on neuropathology) connections between sleep disorders and brain health. Given promising evidence for the benefits of treatment and prevention, sleep disorders and disturbances represent potential targets for early treatment that may improve brain health more broadly. In this scientific statement, we discuss the evidence supporting an association between sleep disorders and disturbances and poor brain health ranging from stroke to dementia and opportunities for prevention and early treatment.

Identification of sleep quality clusters among stroke patients: A multi-center Latent Profile Analysis study

BACKGROUND

Quality sleep plays a crucial role in maintaining good health. Nevertheless, sleep disruption is a common and complex issue after a stroke. It can increase the likelihood of stroke recurrence by influencing modifiable risk factors. However, there is currently a lack of research on the latent classes or clusters of sleep quality and its predictive factors among stroke patients.

OBJECTIVES

This study aims to identify latent classes of sleep quality and explore the predictive factors associated with different sleep quality clusters among stroke patients.

METHODS

A total of 500 participants were recruited through cluster random sampling from January 2023 to May 2023. Latent profile analysis was conducted to identify latent classes of sleep quality within the sample of stroke patients. Additionally, multinomial regression analyses were employed to investigate the predictors associated with the different latent classes identified in the analysis.

RESULTS

Out of the 500 participants, 458 (91.6 %) completed the survey, and 71 % of them reported experiencing sleep problems. The analysis revealed three latent profile classes: the "good sleep quality-deficient duration" group (65.4 %), the "moderate sleep quality-more disturbances" group (14.1 %), and the "poor sleep quality-low efficiency" group (20.5 %). Factors associated with sleep quality were identified. Protective factors for sleep quality included being male, having the TOAST type of large-artery atherosclerosis, having a good education, high household income, no family history of stroke, residing in rural areas, and having better environmental and social support (all p < 0.05). Risk factors for sleep quality included smoking, high perceived stress, and a greater number of comorbidities (all p < 0.05).

CONCLUSIONS

This study has successfully identified three distinct latent profile classes of sleep quality and their associated predictors among stroke patients in China. The findings offer both theoretical guidance and practical insights for the development of targeted intervention programs aimed at enhancing the sleep quality of stroke patients.

Comparison of three measures for insomnia in ischemic stroke patients: Pittsburgh sleep quality index, insomnia severity index, and Athens insomnia scale

Objective

This study investigated the consistency and determined the optimal threshold values of three scales in the diagnosis of insomnia of ischemic stroke (IS) patients.

Methods

Participants in this study consisted of 569 acute IS patients. All 569 patients completed the assessment of the three insomnia scales. Insomnia of IS patients were assessed by Pittsburgh sleep quality index (PSQI), Insomnia Severity Index (ISI), and Athens insomnia scale (AIS). Also, basic patient information, neurological function, and activities of daily living were assessed. General information was compared between the insomnia group and the no-insomnia group. Cronbach's α coefficients, Cohen's Kappa consistency, Receiver operating characteristic (ROC) curve and DeLong's test analysis were used to analyze the reliability and diagnostic validity of PSQI, ISI, and AIS.

Results

The PSQI and ISI showed high reliability with Cronbach's α of 0.875 and 0.858, respectively, while the AIS had an α coefficient of 0.734, demonstrating acceptable reliability. The PSQI, ISI, and AIS showed outstanding diagnostic ability with an AUC of 0.960 (95% CI: 0.946, 0.974), 0.911 (95% CI: 0.882, 0.941), and 0.876 (95% CI:0.837, 0.916). The best diagnostic cutoffs for PSQI, ISI, and AIS are ≥9, ≥15, and ≥8.

Conclusion

Each of the three questionnaires has advantages and disadvantages when assessing insomnia. In the evaluation of insomnia in IS patients, the best questionnaire selection should be made according to the purpose of clinical evaluation and considering the sensitivity and specificity.

Relationship between sleep disorders and the prognosis of neurological function after stroke

OBJECTIVE

This study aims to investigate the effects of sleep disorders on the prognosis of neurological function after stroke and other factors affecting the prognosis after stroke.

METHOD

We designed a cohort study. A total of 1,542 patients with their first stroke were hospitalized in the department of neurology of Tianjin Huanhu Hospital from 2015.6.1 to 2016.12.31. We recorded the personal histories of patients. The MMSE (mini-mental state examination), MoCA (Montreal Cognitive Assessment), HAMD (Hamilton Depression Scale), National Institutes of Health Stroke Scale (NIHSS) score, mRS (Modified Rankin Scale), BI (Barthel Index), PSQI (Pittsburgh Sleep Quality Index), ESS (Epworth Sleepiness Scale), Berlin questionnaire, and nocturnal TST (Total sleep time) were assessed before discharge, 3 months, 6 months, and 4 years (2019-2020) after stroke.

RESULT

Low sleep quality (OR 2.019, 95%CI 1.199-3.398, p = 0.008), nocturnal TST (<7 h) (OR 4.060, 95%CI 1.494-11.034, p = 0.006), nocturnal TST (>8 h) (OR 5.928, 95% CI 2.134-16.464, p = 0.001) were risk factors for poor neurological function recovery at 3 months after stroke. Nocturnal TST (<7 h) (OR 13.042, 95%-CI 2.576-66.027, p = 0.002) and nocturnal TST (>8 h) (OR 11.559, 95%-CI 2.108-63.390, p = 0.005) were risk factors for poor neurological function at 6 months after stroke. Nocturnal TST (<7 h) (OR 2.668, 95% CI 1.250-5.698, p = 0.011) and nocturnal TST (>8 h) (OR 2.516, 95% CI 1.080-5.861, p = 0.033) were risk factors for poor neurological function at 4 years after stroke. High risk of OSA (HR 1.582, 95%CI 1.244-2.012, p < 0.001) was a risk factor for all-cause death in patients followed up for 4 years after stroke.

CONCLUSION

Low sleep quality is associated with short-term poor neurological function after stroke. Unusual nocturnal TST (long or short) is associated with short-term or long-term poor neurological function after stroke. A high risk of OSA is associated with a higher risk of all-cause death after stroke.

Sleep Monitoring during Acute Stroke Rehabilitation: Toward Automated Measurement Using Multimodal Wireless Sensors

Sleep plays a critical role in stroke recovery. However, there are limited practices to measure sleep for individuals with stroke, thus inhibiting our ability to identify and treat poor sleep quality. Wireless, body-worn sensors offer a solution for continuous sleep monitoring. In this study, we explored the feasibility of (1) collecting overnight biophysical data from patients with subacute stroke using a simple sensor system and (2) constructing machine-learned algorithms to detect sleep stages. Ten individuals with stroke in an inpatient rehabilitation hospital wore two wireless sensors during a single night of sleep. Polysomnography served as ground truth to classify different sleep stages. A population model, trained on data from multiple patients and tested on data from a separate patient, performed poorly for this limited sample. Personal models trained on data from one patient and tested on separate data from the same patient demonstrated markedly improved performance over population models and research-grade wearable devices to detect sleep/wake. Ultimately, the heterogeneity of biophysical signals after stroke may present a challenge in building generalizable population models. Personal models offer a provisional method to capture high-resolution sleep metrics from simple wearable sensors by leveraging a single night of polysomnography data.

Association Between Sleep Duration and Functional Disability in Inpatient Stroke Rehabilitation: A Pilot Observational Study

Objective

To describe the change in sleep duration during inpatient rehabilitation and to determine if sleep quality and sleep duration is associated with functional disability for individuals after stroke. It was hypothesized that participants who experienced optimal sleep during inpatient rehabilitation would have greater functional ability at discharge.

Design

Longitudinal observation study.

Setting

Inpatient rehabilitation unit at a large, urban hospital.

Participants

Thirty-seven individuals with acute stroke (N=37; mean age, 62.5±11.8y, male=20, female=17) were recruited from September 2018 to September 2019. Participants were invited to participate in the study by clinical personnel associated with their usual care as they were admitted to inpatient rehabilitation.

Interventions

Not applicable.

Main Outcome Measures

Participants were asked to wear an actigraph for the duration of their rehabilitation program to assess sleep. The first 3 nights of actigraphy data were averaged to obtain total sleep time (TST) and sleep efficiency (SE) at admission, and the last 3 nights were averaged for TST and SE at discharge. Functional disability (primary outcome was FIM) at admission and discharge was gathered from the participants’ medical records. One-way analysis of variance and chi-square analyses assessed for group differences, and regression modeling was used to determine if sleep was associated with functional ability at discharge.

Results

Sixteen participants (43%) were categorized as “good sleepers” and 21 (57%) were “poor sleepers” based on their TST at admission. Of the poor sleepers, 14 participants (66%) remained short duration sleepers (<7h at admission and discharge). Sleep outcomes did not significantly predict FIM score at discharge.

Conclusions

Most participants had less than optimal sleep duration during inpatient rehabilitation. Efforts may be warranted to optimize sleep during inpatient rehabilitation.

Acupuncture Reduced the Risk for Insomnia in Stroke Patients: A Propensity-Score Matched Cohort Study

Background: Post-stroke insomnia (PSI) affects the quality of life for stroke patients, reduces the likelihood of successful rehabilitation, and produces additional complications following stroke. Previous reports have provided some information regarding PSI risk factors, but little is known concerning protective factors for PSI. This study analyzed the relationship between acupuncture and insomnia in stroke patients and explored the use of acupuncture as a preventive treatment.

Methods: Patients diagnosed with stroke from 2010 to 2019 were identified in the case database of the First Affiliated Hospital of Guangzhou University of Chinese These patients followed until 2020, and numerous factors were examined, including gender, age, stroke type, stroke location, and baseline comorbidities. A 1:1 propensity score was used to match an equal number of patients receiving acupuncture with stroke patients who did not receive acupuncture (N = 1,680 for each group). The purpose of the study was to compare the incidence of insomnia in these two stroke cohorts. We used the Cox regression model and Kaplan-Meier method to estimate the risk of insomnia as the outcome event.

Results: Compared with the non-acupuncture cohort in general, stroke patients who received acupuncture treatment exhibited a lower risk of insomnia after adjusting for age, gender, stroke type, stroke location, and comorbidities (adjusted hazard ratio HR = 0.27, 95% confidential interval = 0.23 to 0.32). Acupuncture also reduced the risk of PSI for both genders. The respective risks were HR = 0.28 (adjusted) for males and HR = 0.26 (adjusted) for females. Acupuncture also lowered the risk for PSI for different age groups. The risks were HR = 0.22 (adjusted) for individuals 18 to 39 years of age, HR = 0.31 (adjusted) for individuals 40 to 59 years of age, HR = 0.28 (adjusted) for those 60 to 79 years of age, and HR = 0.18 (adjusted) for individuals 80 years of age and older. Concerning the stroke type, regardless of whether the stroke was ischemic, hemorrhagic, or a combination of the two stroke types, patients who received acupuncture exhibited lower risk (adjusted HR = 0.28, 0.17, and 0.49, respectively). Concerning stroke location, except for the cerebral hemispheres (adjusted HR = 1.10, 95% confidential interval = 0.12 to 1.01), the risk of PSI after receiving acupuncture was lower for the frontal lobe (adjusted HR = 0.42), the basal ganglia (adjusted HR = 0.22), the radiation crown (adjusted HR = 0.42), the diencephalon (adjusted HR = 0.20), or multiple partial strokes (adjusted HR = 0.26), the risk of PSI after receiving acupuncture was lower. For all baseline complications, acupuncture reduced the risk of insomnia. The cumulative incidence of insomnia in the acupuncture cohort was significantly lower than the non-acupuncture cohort (log-rank test, P = 0.000).

Limitations: First, our research only included patients from a single center. Second, we did not classify the post-stroke insomnia severity. Second, the information was extracted manually. Overall, the sample size was small, and we needed to increase the sample size to strengthen the conclusions.

Conclusion: Acupuncture treatment reduced the risk of insomnia in stroke patients. Future research be conducted with increased sample sizes and further elaboration on the specific acupuncture protocols that were used.

Acupuncture combined with moxibustion for insomnia after stroke: A protocol for systematic review and meta analysis

BACKGROUND

Stroke is the main cause of death and disability in the world and insomnia is a common complication of stroke patients. Insomnia will not only seriously affect the prognosis and quality of life of patients with stroke, but even cause the recurrence of stroke. Many studies have proved that acupuncture and moxibustion can effectively improve insomnia symptoms. This study will systematically evaluate the effectiveness and safety of acupuncture combined with moxibustion in treating insomnia after stroke.

METHODS

The following 8 databases will be searched from the inception to October 31, 2020, including China National Knowledge Infrastructure Database (CNKI), Chinese Scientific Journal Database (VIP database), China Biomedical Literature Database (CBM), Wanfang Data Chinese Database, PubMed, the Cochrane Central Register of Controlled Trials (CENTRAL), Allied and Alternative Medicine Database (AMED), Excerpt Medica Database (Embase). We will also search for ongoing trials from the World Health Organization International Clinical Trial Registration Platform search portal, Chinese Clinical Trial Register, Clinical trials.gov. In addition, the reference lists of studies meeting the inclusion criteria will also be searched for achieving the comprehensive retrieval to the maximum. All randomized controlled trials of acupuncture and moxibustion in treating insomnia after stroke will be included. Two reviewers will conduct literature screening, data extraction, and quality evaluation respectively. The main outcome is the Pittsburgh sleep quality index (PSQI), and the secondary outcomes include clinical efficacy, quality of life, and safety. RevMan V.5.4.1 will be used for meta-analysis. We will express the results as risk ratio (RR) with 95% confidence intervals (CIs) for dichotomous data and mean difference (MD) or standard mean difference (SMD) 95% CIs for continuous data.

RESULTS

This study will provide a comprehensive review of the available evidence of acupuncture combined with moxibustion in treating insomnia after stroke.

CONCLUSION

The conclusion of our study will provide the updated evidence to judge the effectiveness and safety of acupuncture combined with moxibustion for the treatment of insomnia after stroke.

TRIAL REGISTRATION NUMBER

PROSPERO CRD42020216720.

Sleep Disturbance and Disorders within Adult Inpatient Rehabilitation Settings: A Systematic Review to Identify Both the Prevalence of Disorders and the Efficacy of Existing Interventions

OBJECTIVES

Older people who are admitted to inpatient rehabilitation settings often experience sleep disturbance or disorders. Both intrinsic and environmental factors may contribute to reduced sleep quality. Poor sleep quality has been reported to be associated with poorer rehabilitation outcomes. The aim of this review was (1) to describe the prevalence of sleep disturbance or disorder among older people participating in inpatient rehabilitation, and (2) to describe interventions that have been trialed to increase sleep quality and/or quantity in older people in rehabilitation settings and report on their efficacy.

DESIGN

Systematic review involving search of 3 electronic databases and gray literature. Two authors independently reviewed citations and reviewed full text and agreed on included studies. Data were extracted and synthesized and risk of bias was assessed.

SETTING AND PARTICIPANTS

Studies were included if they provided quantitative data about the prevalence of sleep disturbance or disorder in older people in a rehabilitation setting or if they reported the results of a randomized trial evaluating an intervention to improve sleep quality in older people in a rehabilitation setting.

MEASURES

Studies were included if they reported data from monitoring (such as polysomnography or actigraphy), clinical assessments, or questionnaires.

RESULTS

16 studies reporting prevalence data and 3 studies reporting evaluations of interventions were included in this review. Studies reported data from stroke and mixed population rehabilitation settings. The prevalence of obstructive sleep apnea was high and ranged from 12% to 92% in stroke rehabilitation settings. Other types of sleep disturbance, such as difficulty initiating sleep, were also common.

CONCLUSIONS AND IMPLICATIONS

Many older people participating in inpatient rehabilitation have sleep disturbance or sleep disorders. Poor sleep quality is associated with poorer health status and recovery; therefore, it is important that rehabilitation settings take steps to enhance sleep quality for inpatients drawing on the principles of good sleep hygiene.

Sleep Disruption After Brain Injury Is Associated With Worse Motor Outcomes and Slower Functional Recovery

Background. Sleep is important for consolidation of motor learning, but brain injury may affect sleep continuity and therefore rehabilitation outcomes. Objective. This study aims to assess the relationship between sleep quality and motor recovery in brain injury patients receiving inpatient rehabilitation. Methods. Fifty-nine patients with brain injury were recruited from 2 specialist inpatient rehabilitation units. Sleep quality was assessed (up to 3 times) objectively using actigraphy (7 nights) and subjectively using the Sleep Condition Indicator. Motor outcome assessments included Action Research Arm test (upper limb function), Fugl-Meyer Assessment (motor impairment), and the Rivermead Mobility Index. The Functional Independence Measure (FIM) was assessed at admission and discharge by the clinical team. Fifty-five age- and gender-matched healthy controls completed one assessment. Results. Inpatients demonstrated lower self-reported sleep quality (P < .001) and more fragmented sleep (P < .001) than controls. For inpatients, sleep fragmentation explained significant additional variance in motor outcomes, over and above that explained by admission FIM score (P < .017), such that more disrupted sleep was associated with poorer motor outcomes. Using stepwise linear regression, sleep fragmentation was the only variable found to explain variance in rate of change in FIM (R²_adj = 0.12, P = .027), whereby more disrupted sleep was associated with slower recovery. Conclusions. Inpatients with brain injury demonstrate impaired sleep quality, and this is associated with poorer motor outcomes and slower functional recovery. Further investigation is needed to determine how sleep quality can be improved and whether this affects outcome.