Sleep disturbances are more common in Parkinson’s disease (PD) than in the general population and up to 90% of persons with PD have sleep problems. The main types of sleep disturbances in PD are insomnia, rapid-eye-movement (REM) sleep behavior disorder, and excessive daytime sleepiness (EDS) (1). The general hypothesis of sleep disturbances in PD is that the disease itself affects brain areas involved in the control of sleep and wakefulness (e.g., the hypothalamic suprachiasmatic nuclei and mesocorticolimbic circuits including the ventral tegmental area, nucleus coeruleus, and the hypothalamus), but that the pharmacological treatment also can play a role together with secondary effects due to PD symptoms (1). Daytime sleepiness has been defined as the inability to stay awake and alert during the day,
A. Ho€glund1,2, J.-E. Broman3, S. P alhagen1,2, S. Fredrikson1,2, P. Hagell4 1 Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden; 2Department of Neurology, Karolinska University Hospital Huddinge, Stockholm, Sweden; 3Department of Neuroscience, Psychiatry, Uppsala University, Uppsala, Sweden; 4The PRO-CARE Group, School of Health and Society, Kristianstad University, Kristianstad, Sweden
Key words: disorders of excessive somnolence; factor analysis; Parkinson’s disease; symptom assessment; regression analysis A. H€oglund, Department of Neurology, Karolinska University Hospital Huddinge, R52, SE-141 86 Stockholm, Sweden Tel.: +46 8 585 819 08 Fax: +46 8 585 827 17 e-mail: [email protected] Accepted for publication December 19, 2014
resulting in unintended episodes of drowsiness or sleep; it may vary in severity and is more likely to occur in monotonous, passive situations (2). EDS is commonly identified and quantified by rating scales such as the Epworth Sleepiness Scale (ESS) (1, 3). The ESS assesses situational sleep propensity, that is, the habitual tendency to doze or stay awake in certain situations as part of daily life (4). With these considerations in mind and for the purposes of the current study, EDS is defined as a subjective experience of daytime sleepiness, tendency to fall asleep, or nod off during daytime without prior planning to go to sleep. EDS is more common in PD than in the general population as well as in other neurological diseases and has been estimated to occur in up to 74% of persons with PD (3, 5). Despite its prevalence, the exact role of EDS and its relationships with other PD features remain uncertain. 97
H€ oglund et al. However, factors such as dopaminergic medication, disease severity, age-related changes, other coexisting sleep disorders, cognitive impairment, psychiatric complications, dysautonomia, anxiety, and depression have been postulated as potential risk factors (1, 5–11). However, few studies (7, 9, 12) have considered the profile of motor symptoms and its potential differential associations with EDS, and even less is known regarding how EDS appears to interrelate with other motor and non-motor features (13). There is thus a need to improve our understanding of the role of EDS in PD and its relation to other PD features as this may provide clues as to whether EDS is directly related to other symptoms or a separate disease manifestation. This study aimed at exploring the role of EDS in PD relative to other motor and non-motor symptoms. Specifically, we investigated potential predictors of EDS in PD and explored how EDS appear to relate to other motor and non-motor features of PD. Materials and methods Sample
Data were taken from a consecutively recruited cross-sectional multicenter sample of 118 persons with PD from four Swedish university hospital movement disorder clinics. Exclusion criteria were participation in other ongoing studies, ongoing infections, and clinically significant psychiatric adverse drug reactions and comorbidities (including dementia and ongoing clinical depression), as determined by the attending clinicians (14). Successful ongoing antidepressant therapy with no clinical depression was not regarded a reason for exclusion. All participants signed informed consent. The study was approved by the local research ethics committees.
Instruments – EDS was assessed using the ESS, an 8-item rating scale that inquires about the propensity of dozing off or falling asleep during various day-to-day activities (17, 18). Scores range between 0 and 24 (24 = more daytime sleepiness) and scores >10 suggest abnormal levels of daytime sleepiness (4). Participants also completed the following selfreport rating scales: the Functional Assessment of Chronic Illness Therapy—Fatigue scale (FACITF), the Pittsburgh Sleep Quality Index (PSQI; (19)), the Hospital Anxiety and Depression Scale (HADS; (20)), and the Nottingham Health Profile (21), from which the pain section (NHP-Pain) was used here. All patient-reported scales were completed during the ‘on’ phase, and their reliabilities (coefficient alpha) were ≥0.70. Antiparkinsonian medications were recorded from medical records and verified by participants. Clinical assessments were conducted using the UPDRS, HY, and the Mini-Mental State Exam during the ‘on’ phase. HY stages were also estimated for the ‘off’ phase from patient reported history and medical records. UPDRS part III (motor score) was used as an overall measure of the severity of parkinsonian motor symptoms. In addition, the following motor symptom profile scores were calculated (22): axial/postural/gait impairments (items 18, 19, 27–31), rest tremor (item 20), postural tremor (item 21), rigidity (item 22), and limb bradykinesia (items 23–26). UPDRS part IV (complications of therapy) was used to derive scores of dyskinesias (items 32–35) and motor fluctuations (items 36–39). Items 2 (thought disorder), 4 (motivation), and 42 (symptomatic orthostatism) of the UPDRS parts I (items 2 and 4) and IV (item 42) were used as coarse indicators of psychiatric dopaminergic side effects (primarily hallucinations), apathy, and dysautonomy, respectively. Analyses
Procedures and data collection
Clinical assessments were performed by one experienced assessor (a specialized PD nurse) at each center. Before initiating data collection, all raters underwent standardized video-based training (15, 16) regarding clinical assessments according to the Unified Parkinson0 s Disease Rating Scale (UPDRS) and the Hoehn & Yahr (HY) staging of PD. This was followed by independent ratings of patient video sequences where all assessors rated the same sequences. Inter-rater concordance was ≥0.85 (Kendall’s coefficient of concordance) for all scores. 98
Data were checked regarding underlying assumptions and described and analyzed accordingly using IBM SPSS 20 (IBM Corp., Armonk, NY, USA) and LISREL 8.8 (Scientific Software International, Inc., Skokie, IL, USA). The alpha level of significance was set at 0.05 (2-tailed). Antiparkinsonian medications were expressed as daily levodopa equivalent (LDE) doses (23) for the total medication as well as for levodopa and dopamine agonists separately. First, bivariate analyses (Spearman correlations, Mann–Whitney and Kruskal–Wallis tests) were conducted. Clinical PD features significantly
EDS in PD associated with ESS scores were entered into a multiple linear regression model (enter method with manual backward deletion) with EDS (ESS) as the dependent variable, and controlling for age and gender. To ease interpretation, all scores were adjusted to be in the same direction (higher scores = more problems). We then conducted a principal component analysis (PCA) with varimax rotation to explore the interrelationships between EDS and other motor and non-motor aspects of PD. In PCA, variables that cluster together (‘load’) strongly on the same component have more in common than those that do not. Therefore, this technique was used to explore relationships among variables. Two PCAs were conducted: one using the total UPDRS III (motor score) as an indicator of parkinsonism, and one using the five UPDRS III derived motor symptom profile scores instead. Other variables entered into the PCAs were EDS (ESS), fatigue (FACIT-F), depressive symptomatology (HADS), anxiety symptoms (HADS), sleep quality (PSQI), pain (NHP-Pain), cognition (MMSE), symptomatic orthostatism (UPDRS IV), motivation (UPDRS I), thought disorder (UPDRS I), dyskinesias (UPDRS IV), and motor fluctuations (UPDRS IV). PCA is typically based on Pearson correlations, which assumes interval or ratio level measurement. Because most variables were no more than ordinal, the PCAs were based on matrices of Pearson, polychoric, and polyserial correlations, as appropriate (24). Results
Sample characteristics are reported in Table 1. Antiparkinsonian treatment consisted of oral levodopa (n = 114), oral dopamine agonists (n = 77), COMT inhibitors (n = 56), selegiline (n = 16), amantadine (n = 11), anticholinergics (n = 1), intraduodenal levodopa infusion (n = 1), and subcutaneous apomorphine infusion (n = 3). Eight participants had undergone neurosurgical interventions for their PD. Three participants not receiving levodopa therapy were treated with subcutaneous apomorphine infusion monotherapy, subthalamic nucleus deep-brain stimulation, and pramipexole, respectively; one was not yet on any medical antiparkinsonian therapy. Thirty-four participants were on antidepressant medication. Four persons did not respond to all ESS items (1–4 missing item responses) and were therefore excluded from the analyses, as total ESS scores could not be computed. Among the remaining 114 persons, ESS scores ranged between 0 (n = 2)
and 21 (n = 1), with a median (q1–q3) of 10 (6– 13), and a mean (SD) of 9.6 (5.0); 53 persons (46.5%) scored above 10. ESS scores did not differ across HY stages, neither in the ‘on’ (P = 0.703; Kruskal–Wallis’ test) nor the ‘off’ phase (Fig. 1). Nor were there any differences in ESS scores between genders (median (q1–q3) female/male scores, 9 (6–13)/10 (6–13); P = 0.989; Mann–Whitney test) or between those with/without symptomatic orthostatism (median (q1–q3) scores, 10 (4–13)/10 (6–14); P = 0.367; Mann– Whitney test). Results from bivariate tests of associations between ESS scores and other variables are shown in Table 1. Significant bivariate associations were found between ESS scores and fatigue (FACIT-F), depressive symptomatology (HADS), anxiety symptoms (HADS), pain (NHP-Pain), and the axial/postural/gait impairment score of the UPDRS III. In addition, there was a significant bivariate association between ESS scores and total daily LDE dose. Regression analysis with ESS scores as the dependent variable (controlling for age and gender) showed significant independent associations with axial/postural/gait impairment, depressive symptomatology, and pain (Table 2). This model was able to account for about 20% of the variation in ESS scores. Because of the bivariate association between ESS scores and total daily LDE dose, the analysis was repeated including total daily LDE dose as an additional independent variable. This did not alter the results. EDS did not load significantly together with any other of the PD features entered into the PCA (Table 3). This finding was consistent regardless of whether the total UPDRS III motor score was included in the analysis as an indicator of parkinsonism (Table 3) or if the five UPDRS III derived motor symptom profile scores were used instead (details available on request). Discussion
This study explored EDS in relation to a broader range of motor and non-motor PD features. Although depressive symptomatology, pain, and axial/postural/gait impairment were found to be independently associated with EDS, these associations were generally weak and EDS did not load with other motor or non-motor aspects of PD in exploratory PCA. These observations suggest that EDS is a separate disease manifestation differing from, for example, poor sleep quality and fatigue. This interpretation is also supported by the lack of associations between EDS and, for example, PD duration and HY stages. 99
H€ oglund et al. Table 1 Participant characteristics and bivariate associations between EDS (ESS scores) and other variables (n = 118)a Spearman correlations
Male gender, n (%) Age (years), mean (SD) Time since PD diagnosis (years), mean (SD) Daily levodopa equivalent dose (total)b Daily levodopa equivalent dose (levodopa)c Daily levodopa equivalent dose (dopamine agonists)d Hoehn & Yahr stage of PD during ‘on’ (I-V)e Hoehn & Yahr stage of PD during ‘off’ (I-V)e UPDRS III, total motor score during ‘on’ (0–108)f UPDRS III, axial/postural/gait score during ‘on’ (0–28)f UPDRS III, resting tremor score during ‘on’ (0–20)f UPDRS III, action tremor score during ‘on’ (0–8)f UPDRS III, limb bradykinesia score during ‘on’ (0–32)f UPDRS III, rigidity score during ‘on’ (0–20)f UPDRS IV, dyskinesia score (0–13)f UPDRS IV, fluctuation score (0–7)f MMSE score (0–30)g Thought disorder (item 2, UPDRS I) (0–4)f Motivation (item 4, UPDRS I) (0–4)f Fatigue (FACIT-F) score (0–52), mean (SD)g HADS depressive symptomatology (0–21)f HADS anxiety symptoms (0–21)f PSQI (0–21)f NHP Pain (0–100)f Symptomatic orthostatism (item 42, UPDRS IV), n (%)
EDS, excessive daytime sleepiness; ESS, Epworth Sleepiness Scale; rs, Spearman correlation coefficient; N.A., not applicable; PD, Parkinson’s disease; UPDRS, Unified Parkinson’s Disease Rating Scale; MMSE, Mini-Mental State Exam; FACIT-F, Functional Assessment of Chronic Illness Therapy—Fatigue scale; SD: standard deviation; HADS, Hospital Anxiety and Depression Scale; PSQI, Pittsburgh Sleep Quality Index; NHP, Nottingham Health Profile. a Data are median (q1–q3) unless otherwise noted. b Including all antiparkinsonian medications; derived according to Tomlinson et al. (23). c Including only levodopa (and associated enzyme inhibitors); derived according to Tomlinson et al. (23). d Including only dopamine agonists; derived according to Tomlinson et al. (23). e Range, I-V (I = mild unilateral disease; II = bilateral disease without postural impairment; III = bilateral disease with postural impairment, moderate disability; IV = severe disability, still able to walk and stand unassisted; V = confined to bed or wheelchair unless aided). f High scores = more problems. g High scores = less problems.
We found an independent association between EDS and pain. This is in contrast to findings by Kurtis et al. (10) who failed to observe an association when regressing pain (and other nonmotor symptoms) on daytime sleepiness scores of the SCales for Outcomes in PArkinson’s disease (SCOPA)-Sleep scale. However, in addition to the use of a different EDS rating scale as the dependent variable, it is unclear what pain scores represent as pain was assessed using visual analog scales of both pain intensity and frequency (10). The pain rating scale used here had acceptable measurement properties in our sample (e.g., coefficient alpha, 0.84; corrected item-total correlations, ≥0.4), and mainly addresses general pain perception and pain in relation to various activities (e.g., walking, climbing stairs, and changing position). As such, it primarily appears to represent musculoskeletal (nociceptive) pain, which is the most common type in PD and often is associ100
ated with akinetic/rigid and postural symptomatology (25). Although the association between pain and EDS needs to be further investigated to be better understood, they could both represent markers of a more severe type of PD. These interpretations are supported also when considering the overall results of the regression analysis. The model (i.e., depressive symptomatology, pain, and axial/postural/gait impairment, together with age and gender) could account for only a fifth of the variance in EDS. This is in accordance with previous observations (R2 range, 0.09–0.24 (5, 7, 10, 11, 26)) and suggests that those independent variables represent associated phenomena rather than direct explanatory variables. However, it is interesting to note that these three EDS associated features also represent markers of a generally more rapid, disabling, and severe disease trajectory manifested through axial/postural/gait impairments, which closely
EDS in PD 24
20 16 12 8 4 0 HY I
Hoehn & Yahr stage of PD ( off )
Figure 1. Daytime sleepiness (ESS scores) across ‘off’ phase HY stages (higher scores = more sleepiness). Kruskal–Wallis’ test did not show any differences across HY stages (P = 0.90). Solid horizontal lines are median values, boxes are inter-quartile ranges (25th to 75th percentiles), error bars are ranges.
mimics the postural instability-gait difficulty (PIGD) type of PD (27). For example, depression has been found less likely to occur in tremor dominant than in the PIGD subtype of PD (28), and pain is typically related to rigidity, akinesia, and postural abnormalities (25). However, the generally weak associations in combination with lack of associations with markers of nigrostriatal dopamine depletion (e.g., bradykinesia scores (29)) and absence of loadings with other PD features in the PCAs suggest that EDS is not directly related to other PD features or to the primary nigrostriatal dopaminergic degeneration. Instead, EDS might be an expression of more widespread pathology (including non-dopaminergic involvement), which has been associated with, for example, axial/PIGD-type PD and the development of dementia (12, 30, 31). Kato et al. (32)
recently studied regional brain atrophy among non-demented and non-hallucinating people with PD with and without EDS (on similar levodopa and dopamine agonist dosages) and healthy ageand sex-matched controls using voxel-based morphometry (32) They found marked gray matter atrophy in the frontal, temporal, occipital, and limbic lobes (including the nucleus basalis of Meynert) in PD with EDS compared to both controls and PD without EDS (32) These observations accord with clinical data reported here and elsewhere (7–9, 12, 30, 31), and support the notion that EDS is more related to neuropathological than to pharmacological factors. For example, the occurrence of EDS has been found associated with cognitive decline both in PD and in general elderly populations (9, 10, 31, 33). This suggests that EDS could be an early marker of more widespread pathology and a more aggressive disease trajectory, particularly as our sample (similarly to that of Kato et al. (32)) excluded people with clinically significant psychiatric adverse drug reactions and comorbidities such as dementia and depression. While additional studies are needed for firmer conclusions, an important clinical implication of this line of reasoning would be that EDS should be screened for already early in the disease process. The role of dopaminergic treatment in the development of EDS in PD has been debated. Whereas some studies (1, 5, 7, 8, 10, 11, 34) suggest that dopaminergic therapy may be a risk factor for EDS, there are also those speaking against this (1, 5, 6, 34, 35). Our study appears to be in line with previous results as we found a weak but significant bivariate association between EDS and total daily LDE dosages (but not with levodopa or dopamine agonist derived LDE dosages), and this association did not remain significant in the multiple regression model. These
Table 2 Multiple linear regression model (controlled for age and gender) with EDS (ESS scores) as dependent variablea Significant independent variablesb Age Genderc Axial/postural/gait impairment (UPDRS III) Pain (NHP Pain) Depressive symptomatology (HADS)
EDS, excessive daytime sleepiness; ESS, Epworth Sleepiness Scale; B, regression coefficient; CI, confidence interval; b, standardized regression coefficient; FACIT-F, Functional Assessment of Chronic Illness Therapy—Fatigue scale; NHP, Nottingham Health Profile; UPDRS, Unified Parkinson’s Disease Rating Scale; HADS, Hospital Anxiety and Depression Scale. a Backward manual deletion. b Independent variables included in the analysis: fatigue (FACIT-F), depressive symtomatology (HADS), anxiety symptoms (HADS), pain (NHP-Pain), and the axial/postural/gait impairment score of the UPDRS III motor score. Control variables are italics. c Female = 0; male = 1.
H€ oglund et al. Table 3 Principal component analysis (varimax rotation) using the total UPDRS III motor scorea Componentb 1 Fluctuations (UPDRS IV) Dyskinesias (UPDRS IV) Parkinsonism (UPDRS III) Cognition (MMSE) Motivation (UPDRS I) Depressive symptomatology (HADS) Fatigue (FACIT-F) Sleep quality (PSQI) Symptomatic orthostatism (UPDRS IV) Thought disorder (UPDRS I) Pain (NHP-Pain) Anxiety symptoms (HADS) Excessive daytime sleepiness (ESS) Eigenvaluec Variance explained (%)c Total variance explained (%)
UPDRS, Unified Parkinson’s Disease Rating Scale; HADS, Hospital Anxiety and Depression Scale; FACIT-F, Functional Assessment of Chronic Illness Therapy—Fatigue scale; PSQI, Pittsburgh Sleep Quality Index; MMSE, Mini-Mental State Exam; NHP, Nottingham Health Profile; ESS, Epworth Sleepiness Scale. a Kaiser–Meyer–Olkin measure of sampling adequacy, 0.583; Bartlet’s test, P < 0.001. b Bold loadings indicate the strongest loading for each variable; significant loadings (>0.481; Norman & Streiner) (36) are indicated with*. c Initial/rotated solution.
findings may be due to the relatively mild levels of PD and moderate doses of dopaminergic medication in our sample. EDS did not load with any other of the PD features entered into the PCAs. This suggests that EDS appears to be a separate manifestation from other PD features (e.g., sleep quality and fatigue), but could be seen as counterintuitive given its associations with axial/postural/gait impairment, depressive symptomatology, and pain. However, it should be borne in mind that those associations were weak and that the sample represented relatively mild PD without clinically significant depressive or cognitive features. Furthermore, PCA is a distribution-dependent procedure and if a more advanced sample with concomitant neuropsychiatric features had been studied, the results may have been different. Sampling considerations may, in part, also contribute to the discrepancy between our results and those from van Rooden et al. (13), who found daytime sleepiness to load with psychotic symptoms, dysautonomia, cognitive impairments, and axial symptoms in an exploratory factor analysis. Other explanations for this discrepancy may be the somewhat limited sample size in this study and that our PCAs were based on matrices of Pearson, polychoric, and polyserial correlations, as appropriate given the measurement levels of the respective variables. Finally, von Rooden et al. (13) used an oblique rotation, whereas we applied an orthogonal rota102
tion. However, re-running our PCAs using oblique rotation did not alter our resulting patterns (data not shown). Our study had limitations. The sample was recruited from specialized movement disorder clinics and although the sample represented all five HY stages of PD, overall severity was skewed toward less severe stages and excluded persons with clinically significant comorbidities such as depression and dementia. However, the prevalence and magnitude of EDS was similar to that reported elsewhere (7, 34). Although this type of target population is common, its characteristics must be borne in mind when interpreting the results or the generalizability will be challenged. The sample size was at the lower end, particularly from the perspective of the PCAs. However, as stated a priori, these analyses were primarily conducted for exploratory purposes and should thus be interpreted as such. Furthermore, we did not have a control group. However, as the study objectives regard associations between EDS and other PD features, we do not consider this to be of major concern. Finally, non-motor scales were not disease-specific because of their unavailability in Swedish at the time of data collection. However, the generic scales used here have all been validated with good results in PD. Although it should be acknowledged that several variables (e.g., dysautonomia and cognition) were assessed by relatively coarse methods, a major strength of
EDS in PD this study is its relative comprehensiveness in terms of the range of disease related factors studied. As such, it illustrates the importance of considering broad ranges of symptoms, including non-motor symptoms and profiles of motor symptoms to advance understanding of this complex disorder. Taken together, we found EDS to be associated with axial/postural/gait impairment, depressive symptomatology, and pain, suggesting that EDS may be an additional early feature of the PIGD phenotype of PD. As such, EDS may manifest an early marker for a more rapid and severe disease trajectory. However, only a small proportion of the variation in EDS could be accounted for by these and other studied PD features, and PCA identified EDS as an independent component from other motor and non-motor symptoms. This suggests that EDS is a separate disease manifestation, although more studies are needed to clarify its role in PD. Acknowledgements The authors want to thank the study participants for their cooperation; B. Eriksson, I. Ruuth Knutsson, and J. Reimer for assistance with data collection; and Drs. J. Ahlberg, N. Dizdar, H. Edwall, B. Johnels, J. L€ okk, H. Widner, and T. Willows for patient recruitment. The study was supported by the Swedish Research Council, the Swedish Parkinson Foundation, the Swedish Parkinson Academy, the Basal Ganglia Disorders Linnaeus Consortium (BAGADILICO) at Lund University, and the Department of Neurology, Karolinska University Hospital Huddinge, Stockholm, Sweden.
Conﬂict of interest The authors declare that there is no conflict of interests regarding the publication of this article.
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