FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2006996829> ?p ?o ?g. }

• W2006996829 endingPage "543" @default.
• W2006996829 startingPage "535" @default.
• W2006996829 abstract "Free AccessSleep QualityThe Effects of Sleep Dysfunction on Cognition, Affect, and Quality of Life in Individuals with Cerebellar Ataxia Akshata Sonni, B.S., Lauri B.F. Kurdziel, M.S., Bengi Baran, M.S., Rebecca M.C. Spencer, Ph.D. Akshata Sonni, B.S. Neuroscience and Behavior, University of Massachusetts, Amherst MA Search for more papers by this author , Lauri B.F. Kurdziel, M.S. Neuroscience and Behavior, University of Massachusetts, Amherst MA Search for more papers by this author , Bengi Baran, M.S. Department of Psychology, University of Massachusetts, Amherst MA Search for more papers by this author , Rebecca M.C. Spencer, Ph.D. Address correspondence to: Rebecca M.C. Spencer, Ph.D., 135 Hicks Way, Tobin Hall Room 419, University of Massachusetts, Amherst, MA 01003(863) 235-0031 E-mail Address: [email protected] Neuroscience and Behavior, University of Massachusetts, Amherst MA Department of Psychology, University of Massachusetts, Amherst MA Search for more papers by this author Published Online:May 15, 2014https://doi.org/10.5664/jcsm.3706Cited by:5SectionsAbstractPDF ShareShare onFacebookTwitterLinkedInRedditEmail ToolsAdd to favoritesDownload CitationsTrack Citations AboutABSTRACTStudy Objective:Cerebellar ataxia comprises a group of debilitating diseases that are the result of progressive cerebellar degeneration. Recent studies suggest that, like other neurodegenerative diseases, sleep impairments are common in cerebellar ataxia. In light of the role of sleep in mood regulation and cognition, we sought to assess interactions between sleep, cognition, and affect in individuals with cerebellar ataxia.Methods:A survey of 176 individuals with cerebellar ataxia was conducted. The battery of instruments included a modified International Cooperative Ataxia Rating Scale, Pittsburgh Sleep Quality Index, Restless Leg Syndrome Questionnaire, REM Behavior Disorder Questionnaire, Beck Depression Inventory, Epworth Sleepiness Scale, and a Composite Cognitive Questionnaire.Results:Fifty-one percent of individuals indicated significant sleep disturbances on the Pittsburgh Sleep Quality Index, 73% of participants had two or more symptoms of restless leg syndrome, and 88% had two or more symptoms of REM behavior disorder. Ataxia severity, based on the modified International Cooperative Ataxia Rating Scale, predicted scores on the Pittsburgh Sleep Quality Index, the Epworth Sleepiness Scale and REM Behavior Disorder Questionnaire. Median split analyses revealed that cognitive function appeared to be reduced and depressive symptoms were greater for those individuals with poor subjective sleep quality and severe RLS. Importantly, sleep appears to play a mediatory role between disease severity and depressive symptoms.Conclusions:These results suggest that disturbed sleep may have detrimental effects on cognition and affect in individuals with cerebellar ataxia. While objective measures are needed, such results suggest that treating sleep deficits in these individuals may improve cognitive and mental health as well as overall quality of life.Citation:Sonni A, Kurdziel LB, Baran B, Spencer RM. The effects of sleep dysfunction on cognition, affect, and quality of life in individuals with cerebellar ataxia. J Clin Sleep Med 2014;10(5):535-543.INTRODUCTIONSleep disturbances are common among individuals with neurodegenerative disorders, and symptoms of disturbed sleep often precede the onset of the symptoms associated with neurodegeneration by ten or more years.1 This has great implications for furthering the understanding of disease mechanisms and for making earlier diagnoses. Cerebellar ataxia comprises a large group of neurodegenerative disorders that are progressive, debilitating, and irreversible.2 Although cerebellar ataxia is a relatively rare disease, it results in significant disability and diminished quality of life for those affected. Sleep disturbances commonly occur in cerebellar ataxia, with higher frequencies reported in the autosomal dominant spinocerebellar ataxias (SCA)—specifically SCA1, SCA2, SCA3 (Machado-Joseph disease), and SCA6—than in the other subtypes.3 The most prevalent among these sleep disturbances are RBD, RLS, periodic leg movement disorder, excessive daytime sleepiness (EDS), insomnia, and obstructive sleep apnea.2–5BRIEF SUMMARYCurrent Knowledge/Study Rationale: As in the case for numerous neurodegenerative disorders, individuals with cerebellar ataxia often complain of poor sleep. Concurrently, Cerebellar Cognitive Affective Syndrome describes a spectrum of disorders including, cognitive disabilities and emotional dysfunction, that are common in conjunction with cerebellar lesions. In an effort to understand the mechanisms underlying these symptoms, the current study aimed at looking at how poor sleep quality and the presence of sleep disorders may contribute to diminished cognitive abilities and negative affect in individuals with cerebellar ataxia.Study Impact: This study provides insight into the role of poor sleep in mediating cognitive and affective deficits that markedly reduce quality of life. Results suggest that improving the quality of sleep could result in improved daytime functioning and mood in this population, thus providing novel therapeutic targets for the management of cerebellar ataxia.Disordered sleep in cerebellar ataxias may come about through several pathways. Firstly, abnormal motor activity during sleep in individuals with cerebellar ataxia is most likely a result of damage to the well-defined cerebellar motor circuitry.6 Likewise, the cyclic motor activities associated with breathing require sound cerebellar function.7,8 There is also evidence pointing toward a direct involvement of the cerebellum in sleep-wake behavior which may be disturbed as a result of the cerebellar degeneration associated with cerebellar ataxias.9 Additionally, many forms of ataxia have substantial extracerebellar pathology, particularly in the brainstem,7,8 and therefore, in addition to pathways involving cerebellar involvement, brainstem degeneration may also lead to negative outcomes on sleep quality. Degeneration of pontomedullary pathways required for maintenance of REM atonia can cause disorders that are associated with abnormal motor movements during sleep.7,8,10,11 Furthermore, degeneration of respiratory centers in the brainstem could adversely affect control of the anatomical structures involved in breathing and ventilation. Therefore, the cerebellum and brainstem structures, together with their projections to the thalamus and cerebral cortex, are involved in regulating various aspects of sleep behavior; damage to any of these structures may result in significant sleep disturbances.Individuals with cerebellar ataxia are reported to have cognitive deficits such as impairments in learning, language processing, and visuospatial processing, among others.12–15 Here, we consider whether sleep may underlie such deficits. Recently, we and others have shown that, during sleep, new memories are transformed into more stable representations and integrated into preexisting memory networks.16 These sleep-dependent processes are not only important for memory consolidation, but also for providing insight into hidden rules,17,18 and for decision making.19 EDS may also account for impaired cognitive performance in cerebellar ataxia as it has been shown to negatively impact cognitive domains such as attention, memory, motivation and alertness, thus affecting mood, productivity, and quality of life.20–24We have also demonstrated that emotional reactivity is maintained by sleep.25 This role of sleep in emotional processing may contribute to mood regulation. Mosko and colleagues26 reported that a large percentage of individuals with sleep disorders presenting at a sleep clinic also showed depressive symptoms, and in many cases, a major affective disorder. When these individuals were administered the appropriate treatment for their sleep disorder, they subsequently showed improvement in their affect, supporting a link between healthy sleep and regulation of emotion and mood. This is of particular consequence in light of the comorbid sleep disturbances observed in individuals with cerebellar ataxia. Specifically, the cerebellar cognitive affective syndrome describes a spectrum of deficits, including cognitive impairments and impairments in affective processing, ranging from emotional blunting to depression.12,13 Although the association between sleep and depression has been observed and reported in various populations,27–29 it has yet to be explored in the cerebellar ataxia population. The present study is an effort to bridge this gap in the literature.To probe the relationship between impaired sleep and cognitive and affective functions in ataxia, we administered a battery of instruments designed to assess sleep, cognition, affect and quality of life, to a large sample of individuals across various subtypes of cerebellar ataxia. We hypothesized that (1) ataxia severity would be related to severity of sleep disturbances, depressive symptomatology, reduced cognitive function and overall reduced quality of life; (2) severity of sleep disturbances would correlate with depressive symptomatology, reduced cognitive function and reduced quality of life; (3) poor sleep quality would mediate the relationship between ataxia severity and reduced cognitive function and depressive symptomatology; and (4) EDS would mediate the relationship between severity of sleep disorders and reduced quality of life.METHODSParticipantsParticipants were recruited from across the United States via advertisements sent to support groups and appearing in the National Ataxia Foundation website and newsletter. Recruitment took place from June 2011 until February 2013. Individuals over 18 years with a diagnosis of cerebellar ataxia, regardless of subtype, were invited to participate. Exclusion criteria included presence of another neurological disorder and/ or history of head trauma.Two hundred fourteen individuals with cerebellar ataxia responded to the survey. Given the limited distribution of the survey (directly targeted to individuals with ataxia), it is assumed that self-reported diagnoses of ataxia and subtype are accurate. There was no compensation for participation, which we assume further reduced dishonest responding.ProceduresProcedures were approved by the Institutional Review Board of the University of Massachusetts, Amherst. The advertisement contained a URL for the web-based survey. This survey began with a consent form explaining the nature of the research and the enrollment criteria. The survey could be completed by the individuals with ataxia themselves or dictated to a companion or caregiver (given that keyboard responses may be prohibitive to some individuals). Participants were instructed that it would take approximately 60 min to complete all questions and that they could complete this in multiple sessions if they so choose. Participants could skip questions at any time.MeasuresModified International Cooperative Ataxia Rating ScaleDisease severity was measured by means of a modified International Cooperative Ataxia Rating Scale (ICARS).30 The ICARS is a well-established clinical rating scale used to assess cerebellar symptoms and to determine the extent of impairment. The test-retest reliability of the original ICARS shows a high rate of internal consistency (Cronbach α = 0.97).31 We modified the ICARS for online administration and for collecting subjective instead of the clinician-reported responses (available upon request). We included 3 questions related to posture and gait functions, 2 questions related to kinetic function, 2 questions related to speech, and 1 question related to occulomotor function.The Pittsburgh Sleep Quality IndexThe Pittsburgh Sleep Quality Index (PSQI) is a questionnaire used to determine an individual's sleep quality over the previous 30 days,32 and has been shown to be a reliable (Cronbach α = 0.87) and valid instrument for the measurement of sleep disturbances, such as primary insomnia, with a high correlation with sleep log data.33Epworth Sleepiness ScaleThe Epworth Sleepiness Scale (ESS) is a short questionnaire used to measure daytime sleepiness.34 The ESS is a reliable instrument (Cronbach α = 0.88)35 and has high sensitivity (93.5%) and specificity (100%). ESS scores ≥ 10 are indicative of abnormal somnolence relative to the average person.Restless Leg Syndrome QuestionnaireThe Restless Leg Syndrome Questionnaire (RLSQ), designed to determine whether the participant has symptoms of RLS, was developed by sleep clinicians at the Athens Center for Sleep Disorders and is used routinely in their screening procedures.36 Participants are asked whether they experience symptoms such as “creeping, crawling, tingling” feelings in the legs at night that are partially relieved by movement, fidgeting and wiggling of feet and toes. For each question, greater scores indicated increasing severity of the symptom. A caveat of this measure is that reliability and validity measures are not yet available.REM Behavior Disorder ScreeningThe REM Sleep Behavior Disorder Screening Questionnaire (RBDSQ) contains a set of questions that are related to symptoms of RBD. Again, responses were coded such that greater severity was reflected by higher scores. This screening questionnaire has been found to have high sensitivity (96%) and specificity (92%).37Composite Cognitive QuestionnaireIn order to gather information about the individual's everyday cognitive abilities, we included a Composite Cognitive Questionnaire (CCQ). This survey was a 27-question composite of the Cognitive Failure Questionnaire (CFQ),38 which has been determined to have adequate internal consistency and validity,39 and 5 additional questions from the Information Questionnaire on Cognitive Decline in the Elderly (IQCODE),40 used to screen dementia. Careful selection of questions from the 2 questionnaires was conducted in order to minimize time and maximize the breadth. Specifically, one question from the CFQ was removed for potential confound with motor deficits (“Do you drop things”), 2 questions were removed in order to save time (“Do you leave important letters unanswered for days” and “Do you fail to see what you want in a supermarket [although it's there]”), and questions from the IQCODE were added that were related to the ability to remember phone numbers and dates, to carry out simple math problems, follow stories on the television, and to learn to use new gadgets. Responses for both the CFQ and IQCODE have 5 levels of responses on a Likert scale based on severity of the symptom, such that each question has a possible score ranging from 0 to 4; we added an additional option of “not applicable” that was not scored on the Likert scale, for those participants that did not feel like the question was relevant, resulting in a range of scores from 0 to 108.Beck Depression InventoryTo assess the prevalence and severity of depressive symptoms in our sample, we included the Beck Depression Inventory (BDI-II).41 The internal consistency of the BDI-II was found to be acceptable when calculated in a German sample (Cronbach α = 0.84).42Abbreviated Activities of Daily Living QuestionnaireWe included a modified, shortened version of the Activities of Daily Living Questionnaire (ADLQ) to assess an individual's capacity to carry out self-care activities.43 The original ADLQ has high reproducibility (Lin concordance coefficient = 0.86) and a strong positive correlation with other measures of ability to live independently.45 We included 8 of the original 28 questions in the ADLQ, one each regarding ability to use a telephone, shopping, food preparation, housekeeping, laundry, using transport, taking medications, and ability to handle finances.Demographic InformationDemographic information included date of birth, handedness, level of education, race, ethnicity and whether English was their first language. We also collected information regarding their medical history, namely, if and when they were diagnosed with ataxia and if they were genetically tested for ataxia subtype.Data AnalysisBDI scores were divided into 3 categories as described by Robinson and Kelley41: scores of 1-16 characterized the “low depression” group, 17-30 the “moderate depression” group, and > 30 the “significant depression” group. ADLQ was scored according to Johnson and colleagues.44 Since we used fewer questions than the original ADLQ, we calculated total percent impairment rather than separate subscales.Individual component scores of the PSQI were calculated as per Buysse and colleagues,32 and these components were summed to provide a global PSQI score; global PSQI scores ≥ 5 are indicative of significant sleep disturbances. Therefore, global PSQI scores ≥ 5 were considered “poor sleepers” while those < 5 were considered “good sleepers.” Similarly, RBDSQ scores ≥ 6 were characterized as “severe RBD” and scores < 6 were characterized as “mild-to-no RBD.” RLSQ scores < 5 were characterized as “low-to-no RLS” and scores ≥ 5 were “high RLS.” To test the interactions with other measures, the median split scores were subjected to independent samples t-tests.Partial correlational analyses between scores on the modified ICARS and each measure were conducted controlling for age, number of years since disease onset and disease subtype. We report Pearson correlation coefficient, r, for each of these analyses.For all of the above analyses, to correct for multiple comparisons, we used α = 0.01 to detect significance. For data that was not normally distributed, we conducted the nonparametric Spearman rank correlations in addition to the Pearson correlation.We used the Baron and Kenny45 method to test whether the interactions between our measures could be explained by the presence of mediators. To this end, we tested the following hypotheses: (1) whether poor subjective sleep quality mediates the relationship between disease severity and depressive symptoms, (2) whether severity of sleep disorders mediates the relationship between disease severity and reduced cognitive functioning, and (3) whether excessive daytime sleepiness mediates the relationship between severity of sleep disorders and reduced quality of life. Significance levels for mediation analyses were set at α = 0.01 in order to correct for multiple comparisons as mentioned previously. The Baron and Kenny45 approach to mediation analyses describes a mediator as a variable that is not only independently associated with both the predictor and the outcome variables, but also accounts for the majority of the variance in the relationship between the two. Therefore, for a variable to be considered as a mediator, the relationship between the predictor and outcome variables as reflected by the regression coefficient must reduce when controlling for the mediator. Additionally, in order to control for age-related changes in sleep and mood, we added age as an independent variable in each step of the model.Much of the literature related to changes in sleep, cognition and affect in individuals with cerebellar ataxia either focuses on single subtypes, or alternatively, on those subtypes that are characterized by cerebellar pathology either with or without the absence of brainstem involvement.2,5,6,10 Thus, to investigate the role of cerebellar subtype, in a final analysis we divided our cohort into two groups based on pathology as per descriptions provided by Schöls and colleagues.46 The Cerebellar Pathology group (n = 36) consisted of individuals with diagnosis of SCA 5, 6, 8, 10 or 14 which constitute those subtypes that have pure cerebellar pathology without cerebral atrophy. The olivopontocerebellar atrophy group (OPCA; n = 54) consisted of individuals with diagnosis of SCA 1, 2, 3 or 7. Individuals with Friedreich ataxia, episodic ataxia, and unknown (including idiopathic ataxias) were excluded from this analysis. Using independent samples t-tests, we compared the 2 groups with relation to scores on all measures. We used an alpha of 0.01 to correct for multiple comparisons.RESULTSSample CharacteristicsOf the 214 respondents to our survey, we included 176 individuals in our final analyses. Individuals were excluded for the following reasons: ataxia reportedly as a result of toluene exposure (n = 1), history of brain tumor (n = 8), history of epilepsy (n = 4), history of stroke (n = 9), history of head trauma (n = 14), and diagnosis of multiple systems atrophy (n = 2; excluded due to widely distributed pathology). Of those included in the analyses, 5 individuals dictated their responses to their companion or caregiver. One hundred forty-three participants had a genetic test confirming their diagnosis. The age-range of respondents was 19-78 years (M = 53.14, SD 12.44). One hundred sixty-five individuals were native English speakers, 8 were non-native English speakers.Additional sample characteristics and demographics are summarized in Table 1. Given that participants were told they could skip questions, sample size varied across items (Table 2).Table 1 Sample characteristics and demographics (n = 176).Table 1 Sample characteristics and demographics (n = 176).Table 2 Summary of neuropsychiatric instruments used and response rateTable 2 Summary of neuropsychiatric instruments used and response rateOne hundred thirty-six individuals completed the ICARS. The range of possible scores on the modified version of the ICARS was 0-17. The average score in our sample was 8.4 ± 3.5. Average scores are broken down by subscale in Table 3.Table 3 Average ICARS scores by subscaleTable 3 Average ICARS scores by subscaleAll questionnaire data was found to be parametric, with the exception of the ADLQ. In order to ensure robust statistical results, we conducted nonparametric analyses, namely Spearman rank correlations, for comparisons involving this measure.SleepFifty-one percent of individuals who completed the PSQI (n = 91) had scores that indicated significant sleep disturbances during the past month. Disease severity, measured through the modified ICARS, significantly predicted PSQI scores (n = 73; r = 0.344, p = 0.004; Figure 1). The mean score on the ESS was 8.44 ± 5.06. Thirty-three percent of individuals that responded to this questionnaire (n = 109) had scores that indicated that they tended to be more somnolent during the day than the average person. Disease severity significantly predicted sleepiness scores on the ESS (n = 82; r = 0.302, p = 0.007; Figure 1).Figure 1: Relationship between disease severity and scores on the Epworth Sleepiness Scale (ESS; n = 82), Pittsburgh Sleep Quality Index (PSQI; n = 73), Activities of Daily Living Questionnaire (ADLQ; n = 82) and REM Sleep Behavior Disorder Screening Questionnaire (RBDSQ; n = 45).Download FigurePrevalence of sleep disorders was high in this cohort; 73% of participants had ≥ 2 symptoms of RLS, and a majority of participants (88%) reported having ≥ 2 symptoms of RBD. Disease severity predicted severity of RBD at near-significance level (n = 45; r = 0.363, p = 0.018; Figure 1). No significant correlation was found between disease severity and RLSQ scores (n = 83; r = 0.164; p = 0.146).Cognitive MeasuresOne hundred forty-eight participants completed the CCQ. No significant correlation was found between disease severity and cognitive impairment (n = 106; r = −0.006; p = 0.955).Mood MeasuresOf those who completed the BDI (n = 147), 65% were characterized in the “low depression” group, 30% in the “moderate depression” group, and 5% in the “significant depression” group. Disease severity was correlated with severity of depressive symptoms at trend-level (n = 107; r = 0.179; p = 0.069).Quality of Life MeasuresAverage percent impairment for those that completed the ADLQ (n = 142) was 16.8% (SD 18.35). Disease severity significantly predicted the impairment in carrying out daily activities (n = 120; Spearman ρ = 0.589, p < 0.001; Figure 1).Interactions between Sleep, Cognitive, and Mood MeasuresDepression scores on the BDI were not significantly different for the severe RBD group (n = 29) and the mild-to-no RBD group (n = 31; t58 = −1.713, p = 0.095). However, the low-tono RLS group (n = 43) had significantly lower scores than the high RLS (n = 52) group on the BDI (t93 = −2.648, p = 0.008; Figure 2A) and the CCQ (t92 = −3.900, p < 0.001). Using the overall PSQI score, “poor sleepers” (n = 50) had significantly higher scores than the “good sleepers” on the BDI (n = 49; t82 = −4.379, p < 0.001; Figure 2B) and CCQ (trend level; t52 = −2.415, p = 0.018; Figure 2B).Figure 2: Severity of cognitive deficits as measured by the Composite Cognitive Questionnaire (CCQ; range 0-108) and depressive symptoms as measured by the Beck Depression Index (BDI; range 0-84) with relation to (A) restless leg syndrome (RLS) severity: “low-to-no RLS” and “high RLS” groups based on a median split, and (B) Pittsburgh Sleep Quality Index (PSQI) defined “good sleepers” (PSQI < 5) and “poor sleepers” (PSQI ≥ 5).* p < 0.01, # trend-level p-value. Error bars represent standard deviation.Download FigureESS scores were significantly correlated with cognitive impairment measured by the CCQ (α = 0.01, n = 83; r = 0.385, p < 0.001; Figure 3) and RBD severity (α = 0.01, n = 90; Pearson r = 0.426, p < 0.001; Figure 3). ESS scores were correlated with scores on the BDI at trend level (α = 0.01, n = 90; r = 0.231, p = 0.032).Figure 3: The relationship between scores on the Epworth Sleepiness Scale (ESS) and those on the REM Sleep Behavior Disorder Screening Questionnaire (RBDSQ; n = 57), as well as on the Composite Cognitive Questionnaire (CCQ; n = 93).Download FigureWe also found that the when controlling for changes in sleep and mood with age, our data supported the model that poor sleep quality plays a mediatory role in the relationship between disease severity and severity of depression, at a clear trend-level. As Figure 4 illustrates, the standardized regression coefficient for the association between the ICARS and BDI scores decreased from b = 0.188 to b = 0.113 when controlling for scores on the PSQI, and the association changed to a nonsignificant one (p = 0.232). The other conditions of mediation were also met: disease severity was an independent predictor of depression severity at trend level (b = 0.188, t114 = 2.177, p = 0.032) and of subjective sleep quality (b = 0.348, t69 = 3.286, p = 0.002). Additionally, subjective sleep quality was a significant predictor of depression severity while controlling for disease severity (b = 0.506, t69 = 5.518, p < 0.001).Figure 4: Theoretical model of mediation of the effect of sleep disturbances on depressive symptomatology in cerebellar ataxias.Age was included as an independent variable in all regression models. * p < 0.01, # trend-level p-value. Numbers represent regression coefficient, β as per conditions of a mediation model, β becomes non-significant when accounting for the mediator (in parentheses).Download FigureOur data were not consistent with the mediation model suggesting that the relationship between ataxia severity and cognitive deficits was mediated by poor sleep. Likewise, our data did not support the hypothesis that the relationship between the severity of sleep disturbances and reduced quality of life was mediated by excessive daytime sleepiness.Cerebellar Pathology vs. Olivopontocerebellar AtrophyAs Figure 5 illustrates, using an α of 0.01, independent samples t-tests revealed no significant differences between the Cerebellar Pathology and OPCA groups with relation to scores on the PSQI (Cerebellar n = 15, OPCA n = 35, t48 = 0.808, p = 0.423), ESS (Cerebellar n = 23, OPCA n = 38, t59 = −0.867, p = 0.390), BDI (Cerebellar n = 29, OPCA n = 45, t72 = 0.764, p = 0.447), ICARS (Cerebellar n = 30, OPCA n = 40, t68 = −0.340, p = 0.735), and ADLQ (Cerebellar n = 27, OPCA n = 46, t71 = −1.494, p = 0.140). However, the two groups significantly differed on scores on the RLSQ (Cerebellar n = 24, OPCA n = 36, t58 = −2.815, p = 0.007), where the higher scores were observed in the OPCA group than the Cerebellar Pathology group. Similarly, a trend toward statistical significance was observed for the RBDSQ (Cerebellar n = 12, OPCA n = 21, t31 = −2.054, p = 0.048) and CCQ (Cerebellar n = 29, OPCA n = 43, t70 = −2.029, p = 0.046), and in both cases, the OPCA group had higher scores than the Cerebellar Pathology group.Figure 5: Comparison of scores on the Pittsburgh Sleep Quality Index (PSQI), the Restless Leg Syndrome Questionnaire (RLSQ), the REM Sleep Behavior Disorder Screening Questionnaire (RBDSQ), the Epworth Sleepiness Scale (ESS), the Composite Cognitive Questionnaire (CCQ), the Beck Depression Inventory (BDI), the modifies International Cooperative Ataxia Rating Scale (ICARS), the Activities of Daily Living Questionnaire (ADLQ) between the “cerebellar pathology” group and the “olivopontocerebellar atrophy (OPCA)” group.* p < 0.01, # trend-level p-value. Error bars represent standard deviation.Download FigureDISCUSSIONWe designed an extensive web-based survey to assess sleep, cognition, and mood in a sample of individuals with cerebellar ataxia. Our results revealed that (1) sleep disturbances are prevalent in our cohort of individuals with cerebellar ataxia and the severity of the sleep disturbances is correlated with disease severity; (2) depressive symptoms are also prevalent, and the severity is correlated with disease severity; and (3) the relationship between disease severity and negative affect may be mediated by poor sleep quality.Fifty-one percent of individuals with cerebellar ataxia reported having disturbed sleep as per the PSQI criteria.32 This suggests a much higher prevalence of disturbed sleep in individuals with cerebellar ataxia compared to the genera" @default.
• W2006996829 created "2016-06-24" @default.
• W2006996829 creator A5037894159 @default.
• W2006996829 creator A5043664827 @default.
• W2006996829 creator A5063678131 @default.
• W2006996829 creator A5090781065 @default.
• W2006996829 date "2014-05-15" @default.
• W2006996829 modified "2023-09-27" @default.
• W2006996829 title "The Effects of Sleep Dysfunction on Cognition, Affect, and Quality of Life in Individuals with Cerebellar Ataxia" @default.
• W2006996829 cites W157463286 @default.
• W2006996829 cites W1606961096 @default.
• W2006996829 cites W1689342635 @default.
• W2006996829 cites W1956529915 @default.
• W2006996829 cites W1969143553 @default.
• W2006996829 cites W197066864 @default.
• W2006996829 cites W1971354242 @default.
• W2006996829 cites W1971440513 @default.
• W2006996829 cites W1977975426 @default.
• W2006996829 cites W2001605283 @default.
• W2006996829 cites W2006318999 @default.
• W2006996829 cites W2007380326 @default.
• W2006996829 cites W2007880428 @default.
• W2006996829 cites W2010970884 @default.
• W2006996829 cites W2012065969 @default.
• W2006996829 cites W2015057891 @default.
• W2006996829 cites W2016883776 @default.
• W2006996829 cites W2024614399 @default.
• W2006996829 cites W2029703642 @default.
• W2006996829 cites W2034379782 @default.
• W2006996829 cites W2043288745 @default.
• W2006996829 cites W2051178577 @default.
• W2006996829 cites W205609681 @default.
• W2006996829 cites W2061699541 @default.
• W2006996829 cites W2072667894 @default.
• W2006996829 cites W2072743331 @default.
• W2006996829 cites W2074999466 @default.
• W2006996829 cites W2076331605 @default.
• W2006996829 cites W2077437003 @default.
• W2006996829 cites W2082802757 @default.
• W2006996829 cites W2083568873 @default.
• W2006996829 cites W2089011621 @default.
• W2006996829 cites W2090009642 @default.
• W2006996829 cites W2094616210 @default.
• W2006996829 cites W2096529213 @default.
• W2006996829 cites W2104284834 @default.
• W2006996829 cites W2105954114 @default.
• W2006996829 cites W2120564644 @default.
• W2006996829 cites W2121782025 @default.
• W2006996829 cites W2125359851 @default.
• W2006996829 cites W2134977136 @default.
• W2006996829 cites W2145850223 @default.
• W2006996829 cites W2147722776 @default.
• W2006996829 cites W2148311331 @default.
• W2006996829 cites W2151487996 @default.
• W2006996829 cites W2155477373 @default.
• W2006996829 cites W2157355794 @default.
• W2006996829 cites W2159385597 @default.
• W2006996829 cites W2164305812 @default.
• W2006996829 cites W2170172094 @default.
• W2006996829 cites W2171876105 @default.
• W2006996829 cites W2303635956 @default.
• W2006996829 cites W2315896787 @default.
• W2006996829 doi "https://doi.org/10.5664/jcsm.3706" @default.
• W2006996829 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/4013382" @default.
• W2006996829 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/24812539" @default.
• W2006996829 hasPublicationYear "2014" @default.
• W2006996829 type Work @default.
• W2006996829 sameAs 2006996829 @default.
• W2006996829 citedByCount "7" @default.
• W2006996829 countsByYear W20069968292016 @default.
• W2006996829 countsByYear W20069968292017 @default.
• W2006996829 countsByYear W20069968292021 @default.
• W2006996829 countsByYear W20069968292022 @default.
• W2006996829 countsByYear W20069968292023 @default.
• W2006996829 crossrefType "journal-article" @default.
• W2006996829 hasAuthorship W2006996829A5037894159 @default.
• W2006996829 hasAuthorship W2006996829A5043664827 @default.
• W2006996829 hasAuthorship W2006996829A5063678131 @default.
• W2006996829 hasAuthorship W2006996829A5090781065 @default.
• W2006996829 hasBestOaLocation W20069968291 @default.
• W2006996829 hasConcept C111919701 @default.
• W2006996829 hasConcept C118552586 @default.
• W2006996829 hasConcept C15744967 @default.
• W2006996829 hasConcept C159110408 @default.
• W2006996829 hasConcept C169760540 @default.
• W2006996829 hasConcept C169900460 @default.
• W2006996829 hasConcept C2775841894 @default.
• W2006996829 hasConcept C2776035688 @default.
• W2006996829 hasConcept C2779951463 @default.
• W2006996829 hasConcept C2780148635 @default.
• W2006996829 hasConcept C2780906641 @default.
• W2006996829 hasConcept C41008148 @default.
• W2006996829 hasConcept C46312422 @default.
• W2006996829 hasConcept C70410870 @default.
• W2006996829 hasConcept C71924100 @default.
• W2006996829 hasConcept C99508421 @default.
• W2006996829 hasConceptScore W2006996829C111919701 @default.
• W2006996829 hasConceptScore W2006996829C118552586 @default.

• next