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Schruers KB, Weightman M, Guttesen AÁV, Robinson B, Johansen-Berg H, Fleming MK. Sleep regularity index as a novel indicator of sleep disturbance in stroke survivors: a secondary data analysis. Sci Rep 2025; 15:17510. [PMID: 40394026 DOI: 10.1038/s41598-025-01332-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2025] [Accepted: 05/05/2025] [Indexed: 05/22/2025] Open
Abstract
Sleep disturbance is common but often overlooked after stroke. Regular sleep is increasingly recognised as important for overall health, yet little is known about how sleep regularity changes after stroke. This study examined differences in the Sleep Regularity Index (SRI) between stroke survivors and healthy controls using actigraphy data from an existing dataset (~ 1 week per participant). Data were analysed for 162 stroke survivors (mean age 61 ± 14 years, 5 ± 5 years post-stroke, 89 males) and 60 controls (mean age 57 ± 17 years, 32 males). Stroke survivors had significantly lower SRI scores than controls (p = 0.001), indicating less regular sleep. In the stroke group, higher SRI correlated with longer total sleep time (p = 0.003) and better self-reported sleep quality (p = 0.001) but not with other sleep metrics. Lower SRI was associated with worse depressive symptoms (p = 0.006) and lower quality of life (p = 0.001) but not with disability (p = 0.886) or time since stroke (p = 0.646). These findings suggest that sleep regularity is disrupted post-stroke and may influence well-being. Future research should explore interventions to improve sleep regularity and related health outcomes in stroke survivors.
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Affiliation(s)
- Katrijn B Schruers
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging (WIN), FMRIB, John Radcliffe Hospital, University of Oxford, Oxford, OX3 9DU, UK
- Faculty of Psychology and Neurosciences, Maastricht University, Maastricht, The Netherlands
| | - Matthew Weightman
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging (WIN), FMRIB, John Radcliffe Hospital, University of Oxford, Oxford, OX3 9DU, UK
| | - Anna Á V Guttesen
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging (WIN), FMRIB, John Radcliffe Hospital, University of Oxford, Oxford, OX3 9DU, UK
| | - Barbara Robinson
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging (WIN), FMRIB, John Radcliffe Hospital, University of Oxford, Oxford, OX3 9DU, UK
| | - Heidi Johansen-Berg
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging (WIN), FMRIB, John Radcliffe Hospital, University of Oxford, Oxford, OX3 9DU, UK
| | - Melanie K Fleming
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging (WIN), FMRIB, John Radcliffe Hospital, University of Oxford, Oxford, OX3 9DU, UK.
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Lo TLT, Leung ICH, Leung LLW, Chan PPY, Ho RTH. Assessing sleep metrics in stroke survivors: a comparison between objective and subjective measures. Sleep Breath 2024; 29:45. [PMID: 39630297 PMCID: PMC11618179 DOI: 10.1007/s11325-024-03212-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2024] [Revised: 10/30/2024] [Accepted: 11/18/2024] [Indexed: 12/08/2024]
Abstract
INTRODUCTION Stroke survivors are at risk of sleep disturbance, which can be reflected in discrepancies between objective and subjective sleep measures. Given there are limited studies on this phenomenon and using portable monitoring devices is more convenient for stroke survivors to monitor their sleep, this study aimed to compare objectively measured (Belun Ring) and subjectively reported (sleep diary) sleep metrics (total sleep time (TST) and wakefulness after sleep onset (WASO)) in stroke survivors. METHODS In this cross-sectional study, thirty-five participants wore a ring-shaped pulse oximeter (Belun Ring) and kept a sleep diary for three consecutive nights in one week. The effects of various factors on TST and WASO were analyzed by linear mixed models. Systematic bias between two measures was examined by the Bland-Altman analysis. RESULTS TST and WASO were significantly affected by measures (p <.001), but not night. TST was significantly lower and WASO was significantly higher in the Belun Ring than in the sleep diary (p <.05). Age was the only covariate that had a significant effect on WASO (p <.05). The Bland-Altman analysis demonstrated positive bias in TST (29.55%; 95% CI [16.57%, 42.53%]) and negative bias in WASO (-117.35%; 95% CI [-137.65%, -97.06%]). Proportional bias was exhibited in WASO only (r =.31, p <.05). CONCLUSION The findings revealed discrepancies between objective and subjective sleep measures in stroke survivors. It is recommended that objective measures be included when assessing and monitoring their sleep conditions.
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Affiliation(s)
- Temmy L T Lo
- Centre on Behavioral Health, The University of Hong Kong, Pok Fu Lam, Hong Kong
| | - Ian C H Leung
- Centre on Behavioral Health, The University of Hong Kong, Pok Fu Lam, Hong Kong
| | | | - Paul P Y Chan
- Belun Technology Company Limited, Sha Tin, Hong Kong
| | - Rainbow T H Ho
- Centre on Behavioral Health, The University of Hong Kong, Pok Fu Lam, Hong Kong.
- Department of Social Work and Social Administration, The University of Hong Kong, Pok Fu Lam, Hong Kong.
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Allgood JE, Roe A, Sparks BB, Castillo M, Cruz A, Brooks AE, Brooks BD. The Correlation of Sleep Disturbance and Location of Glioma Tumors: A Narrative Review. J Clin Med 2023; 12:4058. [PMID: 37373751 DOI: 10.3390/jcm12124058] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Revised: 06/08/2023] [Accepted: 06/14/2023] [Indexed: 06/29/2023] Open
Abstract
Sleep disturbance can occur when sleep centers of the brain, regions that are responsible for coordinating and generating healthy amounts of sleep, are disrupted by glioma growth or surgical resection. Several disorders cause disruptions to the average duration, quality, or patterns of sleep, resulting in sleep disturbance. It is unknown whether specific sleep disorders can be reliably correlated with glioma growth, but there are sufficient numbers of case reports to suggest that a connection is possible. In this manuscript, these case reports and retrospective chart reviews are considered in the context of the current primary literature on sleep disturbance and glioma diagnosis to identify a new and useful connection which warrants further systematic and scientific examination in preclinical animal models. Confirmation of the relationship between disruption of the sleep centers in the brain and glioma location could have significant implications for diagnostics, treatment, monitoring of metastasis/recurrence, and end-of-life considerations.
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Affiliation(s)
- JuliAnne E Allgood
- Department of Neuroscience, University of Wyoming, Laramie, WY 82071, USA
| | - Avery Roe
- College of Osteopathic Medicine, Rocky Vista University, Greenwood Village, CO 80112, USA
| | - Bridger B Sparks
- Department of Neuroscience, University of Wyoming, Laramie, WY 82071, USA
| | - Mercedes Castillo
- College of Osteopathic Medicine, Rocky Vista University, Greenwood Village, CO 80112, USA
| | - Angel Cruz
- College of Osteopathic Medicine, Rocky Vista University, Greenwood Village, CO 80112, USA
| | - Amanda E Brooks
- College of Osteopathic Medicine, Rocky Vista University, Greenwood Village, CO 80112, USA
| | - Benjamin D Brooks
- College of Osteopathic Medicine, Rocky Vista University, Greenwood Village, CO 80112, USA
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Clemente A, Attyé A, Renard F, Calamante F, Burmester A, Imms P, Deutscher E, Akhlaghi H, Beech P, Wilson PH, Poudel G, Domínguez D JF, Caeyenberghs K. Individualised profiling of white matter organisation in moderate-to-severe traumatic brain injury patients. Brain Res 2023; 1806:148289. [PMID: 36813064 DOI: 10.1016/j.brainres.2023.148289] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 12/22/2022] [Accepted: 02/15/2023] [Indexed: 02/22/2023]
Abstract
BACKGROUND AND PURPOSE Approximately 65% of moderate-to-severe traumatic brain injury (m-sTBI) patients present with poor long-term behavioural outcomes, which can significantly impair activities of daily living. Numerous diffusion-weighted MRI studies have linked these poor outcomes to decreased white matter integrity of several commissural tracts, association fibres and projection fibres in the brain. However, most studies have focused on group-based analyses, which are unable to deal with the substantial between-patient heterogeneity in m-sTBI. As a result, there is increasing interest and need in conducting individualised neuroimaging analyses. MATERIALS AND METHODS Here, we generated a detailed subject-specific characterisation of microstructural organisation of white matter tracts in 5 chronic patients with m-sTBI (29 - 49y, 2 females), presented as a proof-of-concept. We developed an imaging analysis framework using fixel-based analysis and TractLearn to determine whether the values of fibre density of white matter tracts at the individual patient level deviate from the healthy control group (n = 12, 8F, Mage = 35.7y, age range 25 - 64y). RESULTS Our individualised analysis revealed unique white matter profiles, confirming the heterogenous nature of m-sTBI and the need of individualised profiles to properly characterise the extent of injury. Future studies incorporating clinical data, as well as utilising larger reference samples and examining the test-retest reliability of the fixel-wise metrics are warranted. CONCLUSIONS Individualised profiles may assist clinicians in tracking recovery and planning personalised training programs for chronic m-sTBI patients, which is necessary to achieve optimal behavioural outcomes and improved quality of life.
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Affiliation(s)
- Adam Clemente
- Neuroscience of Addiction and Mental Health Program, Healthy Brain and Mind Research Centre, School of Behavioural, Health and Human Sciences, Faculty of Health Sciences, Australian Catholic University, Melbourne, Victoria, Australia.
| | - Arnaud Attyé
- CNRS LPNC UMR 5105, University of Grenoble Alpes, Grenoble, France; School of Biomedical Engineering, The University of Sydney, Sydney, New South Wales 2006, Australia
| | - Félix Renard
- CNRS LPNC UMR 5105, University of Grenoble Alpes, Grenoble, France
| | - Fernando Calamante
- School of Biomedical Engineering, The University of Sydney, Sydney, New South Wales 2006, Australia; Sydney Imaging - The University of Sydney, Sydney, Australia
| | - Alex Burmester
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Victoria, Australia
| | - Phoebe Imms
- Leonard Davis School of Gerontology, University of Southern California, Australia
| | - Evelyn Deutscher
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Victoria, Australia
| | - Hamed Akhlaghi
- Emergency Department, St. Vincent's Hospital, University of Melbourne, Melbourne, Victoria, Australia; Department of Psychology, Faculty of Health, Deakin University, Australia
| | - Paul Beech
- Department of Radiology and Nuclear Medicine, The Alfred Hospital, Melbourne, Victoria, Australia
| | - Peter H Wilson
- Development and Disability over the Lifespan Program, Healthy Brain and Mind Research Centre, School of Behavioural, Health and Human Sciences, Faculty of Health Sciences, Australian Catholic University, Melbourne, Victoria, Australia
| | - Govinda Poudel
- Mary MacKillop Institute for Health Research, Faculty of Health Sciences, Australian Catholic University, Melbourne, Victoria, Australia
| | - Juan F Domínguez D
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Victoria, Australia
| | - Karen Caeyenberghs
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Victoria, Australia
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Hale E, Gottlieb E, Usseglio J, Shechter A. Post-stroke sleep disturbance and recurrent cardiovascular and cerebrovascular events: A systematic review and meta-analysis. Sleep Med 2023; 104:29-41. [PMID: 36889030 PMCID: PMC10098455 DOI: 10.1016/j.sleep.2023.02.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Revised: 02/10/2023] [Accepted: 02/18/2023] [Indexed: 02/22/2023]
Abstract
Despite improvements in survival rates, risk of recurrent events following stroke remains high. Identifying intervention targets to reduce secondary cardiovascular risk in stroke survivors is a priority. The relationship between sleep and stroke is complex: sleep disturbances are likely both a contributor to, and consequence of, stroke. The current aim was to examine the association between sleep disturbance and recurrent major acute coronary events or all-cause mortality in the post-stroke population. Thirty-two studies were identified, including 22 observational studies and 10 randomized clinical trials (RCTs). Identified studies included the following as predictors of post-stroke recurrent events: obstructive sleep apnea (OSA, n = 15 studies), treatment of OSA with positive airway pressure (PAP, n = 13 studies), sleep quality and/or insomnia (n = 3 studies), sleep duration (n = 1 study), polysomnographic sleep/sleep architecture metrics (n = 1 study), and restless legs syndrome (n = 1 study). A positive relationship of OSA and/or OSA severity with recurrent events/mortality was seen. Findings on PAP treatment for OSA were mixed. Positive findings indicating a benefit of PAP for post-stroke risk came largely from observational studies (pooled RR [95% CI] for association between PAP and recurrent cardiovascular event: 0.37 [0.17-0.79], I2 = 0%). Negative findings came largely from RCTs (RR [95% CI] for association between PAP and recurrent cardiovascular event + death: 0.70 [0.43-1.13], I2 = 30%). From the limited number of studies conducted to date, insomnia symptoms/poor sleep quality and long sleep duration were associated with increased risk. Sleep, a modifiable behavior, may be a secondary prevention target to reduce the risk of recurrent event and death following stroke. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42021266558.
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Affiliation(s)
- Evan Hale
- Columbia University Vagelos College of Physicians and Surgeons, New York, NY, USA
| | - Elie Gottlieb
- The Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia; SleepScore Labs, Carslbad, CA, USA
| | - John Usseglio
- Center for Behavioral Cardiovascular Health, Columbia University Irving Medical Center, New York, NY, USA; Augustus C. Long Health Sciences Library, Columbia University Irving Medical Center, New York, NY, USA
| | - Ari Shechter
- Center for Behavioral Cardiovascular Health, Columbia University Irving Medical Center, New York, NY, USA; Center of Excellence for Sleep & Circadian Research, Columbia University Irving Medical Center, New York, NY, USA.
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6
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Cable J, Schernhammer E, Hanlon EC, Vetter C, Cedernaes J, Makarem N, Dashti HS, Shechter A, Depner C, Ingiosi A, Blume C, Tan X, Gottlieb E, Benedict C, Van Cauter E, St-Onge MP. Sleep and circadian rhythms: pillars of health-a Keystone Symposia report. Ann N Y Acad Sci 2021; 1506:18-34. [PMID: 34341993 PMCID: PMC8688158 DOI: 10.1111/nyas.14661] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Accepted: 06/21/2021] [Indexed: 12/24/2022]
Abstract
The human circadian system consists of the master clock in the suprachiasmatic nuclei of the hypothalamus as well as in peripheral molecular clocks located in organs throughout the body. This system plays a major role in the temporal organization of biological and physiological processes, such as body temperature, blood pressure, hormone secretion, gene expression, and immune functions, which all manifest consistent diurnal patterns. Many facets of modern life, such as work schedules, travel, and social activities, can lead to sleep/wake and eating schedules that are misaligned relative to the biological clock. This misalignment can disrupt and impair physiological and psychological parameters that may ultimately put people at higher risk for chronic diseases like cancer, cardiovascular disease, and other metabolic disorders. Understanding the mechanisms that regulate sleep circadian rhythms may ultimately lead to insights on behavioral interventions that can lower the risk of these diseases. On February 25, 2021, experts in sleep, circadian rhythms, and chronobiology met virtually for the Keystone eSymposium "Sleep & Circadian Rhythms: Pillars of Health" to discuss the latest research for understanding the bidirectional relationships between sleep, circadian rhythms, and health and disease.
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Affiliation(s)
| | - Eva Schernhammer
- Department of Epidemiology, Center for Public Health, Medical University of Vienna, Vienna, Austria
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, and Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Erin C Hanlon
- Department of Medicine, Section of Endocrinology, Diabetes and Metabolism, University of Chicago, Chicago, Illinois
| | - Céline Vetter
- Department of Integrative Physiology, University of Colorado at Boulder, Boulder, Colorado
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts
| | - Jonathan Cedernaes
- Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
| | - Nour Makarem
- Department of Epidemiology, Mailman School of Public Health, Columbia University Irving Medical Center, New York, New York
| | - Hassan S Dashti
- Department of Integrative Physiology, University of Colorado at Boulder, Boulder, Colorado
- Center for Genomic Medicine, Massachusetts General Hospital, and Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Ari Shechter
- Department of Medicine and Sleep Center of Excellence, Columbia University Irving Medical Center, New York, New York
| | - Christopher Depner
- Department of Health and Kinesiology, University of Utah, Salt Lake City, Utah
| | - Ashley Ingiosi
- Department of Biomedical Sciences, Elson S. Floyd College of Medicine, Washington State University, Spokane, Washington
| | - Christine Blume
- Centre for Chronobiology, Psychiatric Hospital of the University of Basel, and Transfaculty Research Platform Molecular and Cognitive Neurosciences, University of Basel, Basel, Switzerland
| | - Xiao Tan
- Department of Neuroscience (Sleep Science, BMC), Uppsala University, Uppsala, Sweden
- Department of Clinical Neuroscience, Karolinska Institutet, Solna, Sweden
| | - Elie Gottlieb
- The Florey Institute of Neuroscience and Mental Health, and University of Melbourne, Melbourne, Victoria, Australia
| | - Christian Benedict
- Department of Neuroscience (Sleep Science, BMC), Uppsala University, Uppsala, Sweden
| | - Eve Van Cauter
- Department of Medicine, Section of Endocrinology, Diabetes and Metabolism, University of Chicago, Chicago, Illinois
| | - Marie-Pierre St-Onge
- Sleep Center of Excellence, Columbia University Irving Medical Center, New York, New York
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Fixel-based Analysis of Diffusion MRI: Methods, Applications, Challenges and Opportunities. Neuroimage 2021; 241:118417. [PMID: 34298083 DOI: 10.1016/j.neuroimage.2021.118417] [Citation(s) in RCA: 148] [Impact Index Per Article: 37.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2020] [Revised: 07/11/2021] [Accepted: 07/20/2021] [Indexed: 12/13/2022] Open
Abstract
Diffusion MRI has provided the neuroimaging community with a powerful tool to acquire in-vivo data sensitive to microstructural features of white matter, up to 3 orders of magnitude smaller than typical voxel sizes. The key to extracting such valuable information lies in complex modelling techniques, which form the link between the rich diffusion MRI data and various metrics related to the microstructural organization. Over time, increasingly advanced techniques have been developed, up to the point where some diffusion MRI models can now provide access to properties specific to individual fibre populations in each voxel in the presence of multiple "crossing" fibre pathways. While highly valuable, such fibre-specific information poses unique challenges for typical image processing pipelines and statistical analysis. In this work, we review the "Fixel-Based Analysis" (FBA) framework, which implements bespoke solutions to this end. It has recently seen a stark increase in adoption for studies of both typical (healthy) populations as well as a wide range of clinical populations. We describe the main concepts related to Fixel-Based Analyses, as well as the methods and specific steps involved in a state-of-the-art FBA pipeline, with a focus on providing researchers with practical advice on how to interpret results. We also include an overview of the scope of all current FBA studies, categorized across a broad range of neuro-scientific domains, listing key design choices and summarizing their main results and conclusions. Finally, we critically discuss several aspects and challenges involved with the FBA framework, and outline some directions and future opportunities.
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Fleming MK, Smejka T, Henderson Slater D, Chiu EG, Demeyere N, Johansen-Berg H. Self-Reported and Objective Sleep Measures in Stroke Survivors With Incomplete Motor Recovery at the Chronic Stage. Neurorehabil Neural Repair 2021; 35:851-860. [PMID: 34196598 PMCID: PMC8442123 DOI: 10.1177/15459683211029889] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
Background. Stroke survivors commonly complain of difficulty sleeping. Poor sleep is associated with reduced quality of life and more understanding of long-term consequences of stroke on sleep is needed. Objective. The primary aims were to (1) compare sleep measures between chronic stroke survivors and healthy controls and (2) test for a relationship between motor impairment, time since stroke and sleep. Secondary aims were to explore mood and inactivity as potential correlates of sleep and test the correlation between self-reported and objective sleep measures. Methods. Cross-sectional sleep measures were obtained for 69 chronic stroke survivors (mean 65 months post-stroke, 63 years old, 24 female) and 63 healthy controls (mean 61 years old, 27 female). Self-reported sleep was assessed with the sleep condition indicator (SCI) and sleep diary ratings, objective sleep with 7-nights actigraphy and mood with the Hospital Anxiety and Depression Scale. Upper extremity motor impairment was assessed with the Fugl-Meyer assessment. Results. Stroke survivors had significantly poorer SCI score (P < .001) and higher wake after sleep onset (P = .005) than controls. Neither motor impairment, nor time since stroke, explained significant variance in sleep measures for the stroke group. For all participants together, greater depression was associated with poorer SCI score (R2adj = .197, P < .001) and higher age with more fragmented sleep (R2adj = .108, P < .001). There were weak correlations between nightly sleep ratings and actigraphy sleep measures (rs = .15-.24). Conclusions. Sleep disturbance is present long-term after stroke. Depressive symptoms may present a modifiable factor which should be investigated alongside techniques to improve sleep in this population.
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Affiliation(s)
- Melanie K Fleming
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, 6396University of Oxford, Oxford, UK.,552380NIHR Oxford Biomedical Research Centre, UK.,212787Oxford Centre for Enablement, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Tom Smejka
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, 6396University of Oxford, Oxford, UK.,552380NIHR Oxford Biomedical Research Centre, UK.,212787Oxford Centre for Enablement, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - David Henderson Slater
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, 6396University of Oxford, Oxford, UK.,212787Oxford Centre for Enablement, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | | | - Nele Demeyere
- Department of Experimental Psychology, 6396University of Oxford, Oxford, UK
| | - Heidi Johansen-Berg
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, 6396University of Oxford, Oxford, UK.,552380NIHR Oxford Biomedical Research Centre, UK
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9
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Zhao Y, Hu B, Liu Q, Wang Y, Zhao Y, Zhu X. Social support and sleep quality in patients with stroke: The mediating roles of depression and anxiety symptoms. Int J Nurs Pract 2021; 28:e12939. [PMID: 33870617 DOI: 10.1111/ijn.12939] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 02/09/2021] [Accepted: 03/17/2021] [Indexed: 12/15/2022]
Abstract
BACKGROUND Research has demonstrated that higher social support is associated with better psychological health, quality of life, cognition, activities of daily living and social participation, but the relationship between social support and sleep quality remains unknown. AIMS This study aimed to assess the incidence of poor sleep quality, clarify the relationship between social support and sleep quality amongst stroke patients and determine whether anxiety and depression symptoms mediate this relationship. METHODS We conducted a quantitative, cross-sectional study involving 238 patients with stroke (median age of 61 [range 29-87] years, 68.1% male) recruited from a comprehensive tertiary care hospital between September 2019 and January 2020. A self-administered, structured questionnaire was used for the survey. The mediating effect of anxiety and depression symptoms was assessed using the bootstrap method via Model 4 (parallel mediation) of the SPSS PROCESS macro. RESULTS Results showed that the incidence of poor sleep quality amongst stroke patients was 65%. Mediation analysis showed that social support exerted significant direct effects on sleep quality, and anxiety and depression symptoms mediated the relationship between social support and sleep quality. CONCLUSION Measures should be taken to enhance social support to improve the sleep quality of stroke patients. SUMMARY STATEMENT What is already known about this topic? Patients with stroke have a high rate of sleep disorders, anxiety and depression symptoms. Anxiety and depression symptoms have a negative effect on sleep quality. Social support may be an effective intervention to reduce anxiety and depression symptoms and improve sleep quality amongst stroke patients. What this paper adds? The incidence of poor sleep was high amongst stroke patients. Social support had a direct positive effect on sleep quality. Anxiety and depression symptoms played multiple mediating roles in the relationship between social support and sleep quality. The implications of this paper: Our study adds to the existing literature by clarifying how social support impacts the sleep quality of stroke patients. We suggested improving the sleep quality of stroke patients through enhancing social support and reducing anxiety and depression symptoms, especially in patients with low levels of social support.
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Affiliation(s)
- Yaling Zhao
- School of Nursing, Department of Medicine, Qingdao University, Qingdao, China
| | - Bo Hu
- Department of Thoracic Surgery, Municipal Hospital, Qingdao, China
| | - Qingwei Liu
- School of Nursing, Department of Medicine, Qingdao University, Qingdao, China
| | - Ying Wang
- School of Nursing, Department of Medicine, Qingdao University, Qingdao, China
| | - Yuxue Zhao
- School of Nursing, Department of Medicine, Qingdao University, Qingdao, China
| | - Xiuli Zhu
- School of Nursing, Department of Medicine, Qingdao University, Qingdao, China
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10
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Gottlieb E, Khlif MS, Bird L, Werden E, Churchward T, Pase MP, Egorova N, Howard ME, Brodtmann A. Sleep architectural dysfunction and undiagnosed obstructive sleep apnea after chronic ischemic stroke. Sleep Med 2021; 83:45-53. [PMID: 33991892 DOI: 10.1016/j.sleep.2021.04.011] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Revised: 03/22/2021] [Accepted: 04/08/2021] [Indexed: 11/27/2022]
Abstract
OBJECTIVE/BACKGROUND Sleep-wake dysfunction is bidirectionally associated with the incidence and evolution of acute stroke. It remains unclear whether sleep disturbances are transient post-stroke or are potentially enduring sequelae in chronic stroke. Here, we characterize sleep architectural dysfunction, sleep-respiratory parameters, and hemispheric sleep in ischemic stroke patients in the chronic recovery phase compared to healthy controls. PATIENTS/METHODS Radiologically confirmed ischemic stroke patients (n = 28) and matched control participants (n = 16) were tested with ambulatory polysomnography, bi-hemispheric sleep EEG, and demographic, stroke-severity, mood, and sleep-circadian questionnaires. RESULTS Twenty-eight stroke patients (22 men; mean age = 69.61 ± 7.4 years) were cross-sectionally evaluated 4.1 ± 0.9 years after mild-moderate ischemic stroke (baseline NIHSS: 3.0 ± 2.0). Fifty-seven percent of stroke patients (n = 16) exhibited undiagnosed moderate-to-severe obstructive sleep apnea (apnea-hypopnea index >15). Despite no difference in total sleep or wake after sleep onset, stroke patients had reduced slow-wave sleep time (66.25 min vs 99.26 min, p = 0.02), increased time in non-rapid-eye-movement (NREM) stages 1-2 (NREM-1: 48.43 vs 28.95, p = 0.03; NREM-2: 142.61 vs 115.87, p = 0.02), and a higher arousal index (21.46 vs 14.43, p = 0.03) when compared to controls. Controlling for sleep apnea severity did not attenuate the magnitude of sleep architectural differences between groups (NREM 1-3=ηp2 >0.07). We observed no differences in ipsilesionally versus contralesionally scored sleep architecture. CONCLUSIONS Fifty-seven percent of chronic stroke patients had undiagnosed moderate-severe obstructive sleep apnea and reduced slow-wave sleep with potentially compensatory increases in NREM 1-2 sleep relative to controls. Formal sleep studies are warranted after stroke, even in the absence of self-reported history of sleep-wake pathology.
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Affiliation(s)
- Elie Gottlieb
- The Florey Institute of Neuroscience and Mental Health, Melbourne, VIC, Australia; University of Melbourne, Melbourne, VIC, Australia.
| | - Mohamed S Khlif
- The Florey Institute of Neuroscience and Mental Health, Melbourne, VIC, Australia; University of Melbourne, Melbourne, VIC, Australia
| | - Laura Bird
- The Florey Institute of Neuroscience and Mental Health, Melbourne, VIC, Australia; University of Melbourne, Melbourne, VIC, Australia
| | - Emilio Werden
- The Florey Institute of Neuroscience and Mental Health, Melbourne, VIC, Australia; University of Melbourne, Melbourne, VIC, Australia
| | - Thomas Churchward
- Institute for Breathing and Sleep, Melbourne, VIC, Australia; Austin Health, Heidelberg, VIC, Australia
| | - Matthew P Pase
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, VIC, Australia; Harvard T.H. Chan School of Public Health, Harvard University, MA, USA
| | - Natalia Egorova
- The Florey Institute of Neuroscience and Mental Health, Melbourne, VIC, Australia; University of Melbourne, Melbourne, VIC, Australia; Melbourne School of Psychological Sciences, University of Melbourne, Melbourne, VIC, Australia
| | - Mark E Howard
- University of Melbourne, Melbourne, VIC, Australia; Institute for Breathing and Sleep, Melbourne, VIC, Australia; Austin Health, Heidelberg, VIC, Australia
| | - Amy Brodtmann
- The Florey Institute of Neuroscience and Mental Health, Melbourne, VIC, Australia; University of Melbourne, Melbourne, VIC, Australia
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Gottlieb E, Churilov L, Werden E, Churchward T, Pase MP, Egorova N, Howard ME, Brodtmann A. Sleep-wake parameters can be detected in patients with chronic stroke using a multisensor accelerometer: a validation study. J Clin Sleep Med 2021; 17:167-175. [PMID: 32975195 DOI: 10.5664/jcsm.8812] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
STUDY OBJECTIVES Sleep-wake dysfunction is bidirectionally associated with the pathogenesis and evolution of stroke. Longitudinal and prospective measurement of sleep after chronic stroke remains poorly characterized because of a lack of validated objective and ambulatory sleep measurement tools in neurological populations. This study aimed to validate a multisensor sleep monitor, the SenseWear Armband (SWA), in patients with ischemic stroke and control patients using at-home polysomnography. METHODS Twenty-eight radiologically confirmed patients with ischemic stroke (aged 69.61 ± 7.35 years; mean = 4.1 years poststroke) and 16 control patients (aged 73.75 ± 7.10 years) underwent overnight at-home polysomnography in tandem with the SWA. Lin's concordance correlation coefficient and reduced major axis regressions were employed to assess concordance of SWA vs polysomnography-measured total sleep time, sleep efficiency, sleep onset latency, and wake after sleep onset. Subsequently, data were converted to 30-second epochs to match at-home polysomnography. Epoch-by-epoch agreement between SWA and at-home polysomnography was estimated using crude agreement, Cohen's kappa, sensitivity, and specificity. RESULTS Total sleep time was the most robustly quantified sleep-wake variable (concordance correlation coefficient = 0.49). The SWA performed poorest for sleep measures requiring discrimination of wakefulness (sleep onset latency; concordance correlation coefficient = 0.16). The sensitivity of the SWA was high (95.90%) for patients with stroke and for control patients (95.70%). The specificity of the SWA was fair-moderate for patients with stroke (40.45%) and moderate for control patients (45.60%). Epoch-by-epoch agreement rate was fair (78%) in patients with stroke and fair (74%) in controls. CONCLUSIONS The SWA shows promise as an ambulatory tool to estimate macro parameters of sleep-wake; however, agreement at an epoch level is only moderate-fair. Use of the SWA warrants caution when it is used as a diagnostic tool or in populations with significant sleep-wake fragmentation.
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Affiliation(s)
- Elie Gottlieb
- The Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia.,University of Melbourne, Melbourne, Victoria, Australia
| | | | - Emilio Werden
- The Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia.,University of Melbourne, Melbourne, Victoria, Australia
| | - Thomas Churchward
- Institute for Breathing and Sleep, Melbourne, Victoria, Australia.,Austin Health, Heidelberg, Victoria, Australia
| | - Matthew P Pase
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Victoria, Australia.,Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts
| | - Natalia Egorova
- The Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia.,Melbourne School of Psychological Sciences, University of Melbourne, Melbourne, Victoria, Australia
| | - Mark E Howard
- University of Melbourne, Melbourne, Victoria, Australia.,Institute for Breathing and Sleep, Melbourne, Victoria, Australia.,Austin Health, Heidelberg, Victoria, Australia.,Co-senior authors
| | - Amy Brodtmann
- The Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia.,University of Melbourne, Melbourne, Victoria, Australia.,Co-senior authors
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