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Effect of motor, non-motor clinical features including sleep quality, and prescription pattern on adherence to antiparkinsonian medications in Parkinson’s disease
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Received: ,
Accepted: ,
How to cite this article: Samanta S, Kumar N, Kanimozhi M, Bisht M, Gupta R. Effect of motor, non-motor clinical features including sleep quality, and prescription pattern on adherence to antiparkinsonian medications in Parkinson’s disease. J Neurosci Rural Pract. doi: 10.25259/JNRP_585_2023
Abstract
Objectives:
Adherence to antiparkinsonian medications (APMs) may significantly influence Parkinson’s disease (PD) outcome. The present study assesses the role of motor and non-motor features, and prescription patterns on adherence.
Materials and Methods:
This observational and cross-sectional study included 50 PD patients taking APMs for ≥24 months. Demographic data, PD characteristics, treatment, and follow-up history were collected. Patients following up at least once in six months were considered as regular, else were labeled irregular. Montreal cognitive assessment, patient health questionnaire-4, Pittsburgh sleep quality (SQ) index, Epworth sleepiness scale, global quality of life (GQOL) scale, and Morisky Green Levine medication adherence scale (MGL-MAS) were used to evaluate cognition, depressive and anxiety features, SQ, excessive daytime sleepiness (EDS), quality of life (QOL), and APMs adherence, respectively.
Results:
Nearly half (46%) of the PD patients reported high adherence (MGL-MAS = 0). Most of the clinical characteristics were comparable between those with medium/low and high adherence, except for a larger proportion of patients in the medium/low adherence group belonging to Hoehn–Yahr stage >2 (P = 0.02). A comparable proportion of patients in both groups reported poor SQ (P = 0.52) and EDS (P = 0.32). In comparison to the high adherence group, a significantly lower median GQOL score was observed in the medium/low adherence group (median [interquartile range] = 65 [50–70] vs. 80 [70–85]; P < 0.001). The APMs prescription and follow-up patterns were comparable between both groups.
Conclusion:
More than half the PD patients reported medium-to-low adherence. While motor severity and depressive symptoms were associated with medium-to-low adherence, poor SQ was comparable in both groups. Those with medium-to-low adherence reported poor QOL.
Keywords
Parkinson’s disease
Antiparkinsonian medications
Prescription pattern
Sleep quality
Depression
INTRODUCTION
Parkinson’s disease (PD) is the second most prevalent neurodegenerative disorder affecting approximately 1% of individuals above the age of 60 years and 3–4% above 80 years.[1] The current treatment options in PD patients focus on either improving the dopaminergic deficit or reducing the cholinergic overactivity.[1] In addition to the dopaminergic agents including levodopa–carbidopa and dopamine agonists, catecholamine-o-methyl-transferase inhibitors and monoamine oxidase-B inhibitors may be used. Anticholinergics including trihexyphenidyl are used, especially for alleviating tremor.[1] To manage levodopa-induced dyskinesias, amantadine is used because of multiple modes of action.[1]
In addition to disease behavior and efficacy of antiparkinsonian medications (APMs), adherence to APMs also affects the success of pharmacotherapy in PD. Some studies have assessed the prevalence and factors affecting adherence to APMs in PD,[2-11] with only a single study from India.[8] PD duration, cognitive status, mood disorders including depression, poor follow-up compliance, and APMs-related adverse events have been reported to influence adherence to APMs.[2,4,5,8] However, in one of these studies, a diagnosis of depression and cognition was not made using standardized methods.[4] Even in two of these studies,[6,7] cognition was assessed using a mini-mental status examination, which has lesser sensitivity than Montreal Cognitive Assessment (MoCA) in diagnosing impaired cognition, due to two issues – ceiling effect and lack of identification of heterogeneity in cognitive functions.[12] We could find only a single study, which provided reliable evidence regarding the effect of cognition (using MoCA) on treatment adherence among PD patients.[13]
Nearly 98% of patients with PD report some form of sleep dysfunction, making it one of the most common non-motor features of the disease.[14] Sleep quality (SQ) affects cognition, mood, energy, and initiative which are important for adherence to APMs. While poor SQ has been observed to affect medication adherence in patients with chronic neurological disorders including epilepsy,[15,16] similar assessment in patients with PD is lacking.[2,4,5,10,13] We hypothesized that poor SQ would reduce the APM’s adherence in PD patients. Simultaneously, we also studied the role of non-motor and motor features of PD (depression, anxiety, daytime sleepiness, and quality of life), pill burden of APMs, and regularity of follow-up on medication adherence among PD patients.
MATERIALS AND METHODS
Consecutive patients visiting the movement disorders clinic and diagnosed with PD were included in this single-center, observational, and cross-sectional study that spanned from October 2020 to April 2022, following Institute Ethical Committee approval.
Inclusion and exclusion criteria
Patients aged ≥18 years on APMs for at least the past 24 months were included after taking written informed consent. The diagnosis of PD was made by a neurologist with a specialization in movement disorder (NK) using the United Kingdom PD Society brain bank criteria.[17] Exclusion criteria included pregnancy, Parkinson-plus syndromes (including multiple system atrophy, progressive supranuclear palsy, and cortico-basal degeneration), dementia with Lewy body disease, and secondary parkinsonism (e.g., drug/toxin-induced and vascular).
Assessment of PD and treatment variables
Collected data comprised PD onset age, presentation age, and disease phenotype (tremor dominant, postural instability/gait difficulty, or indeterminate type).[18] The severity of motor and non-motor symptoms (NMSs) was assessed using the movement disorders society-unified PD rating scale (MDS-UPDRS)-III (motor) score in “off ” state,[19] and MDS-NMS rating scale, respectively.[20] The severity of PD was assessed using the Hoehn–Yahr stage.[21] Details of therapy, namely, name and dose of APMs were noted from the prescription, and levodopa equivalent daily dose (LEDD) was calculated.[22]
Assessment of cognitive status
Cognition status was assessed using the MoCA score.[23] The cutoff score of 24 was used in this study, as at this score, MoCA has shown approximately 81% sensitivity as well as specificity to detect mild cognitive impairment with area under the curve at 0.84.[24]
Pill burden
Since levodopa–carbidopa plasma concentration exceeds the “on” threshold for nearly 3 h,[25] the optimal prescription pattern for levodopa-carbidopa combination pill is 3–4 times per day. Pill burden was divided into two groups: One with ≤4 pills per day and the second with >4 pills per day.
Morisky green levine medication adherence scale (MGL-MAS)
Adherence to APMs was measured using MGL-MAS. This scale has four self-reported items where items are scored as no (=0) or yes (=1), making the range of total score between 0 and 4. While a total score of 0 suggests high adherence, a score of 1–2 and 3–4 suggests medium and low adherence to treatment, respectively.[26]
Evaluation of depressive and anxiety symptoms
Patient Health Questionnaire-4 evaluates participants on four items, the first two for anxiety and the remaining two for depressive symptoms. Each item is scored on a four-point Likert scale, varying from 0 (no such symptom) to 3 (symptom present almost every day).[27] A total score of ≥3 for the first two items suggests anxiety and the same score for the remaining two items indicates depression.
Assessment of excessive daytime sleepiness (EDS)
The propensity to fall asleep during daytime can be measured by an Epworth Sleepiness Scale (ESS) that assesses chances to fall asleep (EDS) when involved in eight separate acts. These items are rated from 0 to 3, with 0 meaning no dozing and 3 indicating a high chance of sleepiness. The total score ranges from 0 to 24.[28] A cutoff score of more than 10 indicates EDS. We used a validated Hindi version of this scale.[29]
Assessment of SQ
Self-reported, 19-item questionnaire-Pittsburgh SQ Index (PSQI) was used for assessing the quality of sleep of participants. It shows the quality of sleep over the past 1 month.[30] Besides the global score, PSQI provides scores on seven sub-scales: (1) duration of sleep, (2) disturbance during sleep, (3) sleep latency, (4) disturbance in daytime functioning, (5) sleep efficiency, (6) overall SQ, and (7) use of medications to induce or maintain sleep. The score of each component varies from 0 to 3, with 3 indicating the highest disturbance. Global score is calculated by adding scores of seven subscales (score range 0–21). A cutoff of 5 of the global PSQI score has been found to differentiate between good sleepers from poor sleepers (>5 indicating poor SQ).[30]
Global quality of life (GQOL) scale
The GQOL scale is a self-rated scale. It has a single item, which can be scored on a scale of 0–100 (0 = no quality of life to 100 = perfect quality of life). Thus, better quality of life is indicated by higher scores. Participants were requested to indicate any number between 0 and 100 that best represents their quality of life.[31]
Regularity of follow-up
From the treatment chart, follow-up patterns for the past one year were assessed. Patients who visited the movement disorder clinic as per the follow-up schedule of our center (at least once in six months) were considered “regular” in follow-up, else were labeled “irregular.”
Comorbid disorders
Associated comorbidities including hypertension and/or diabetes mellitus were also diagnosed based on medical records and/or clinical examination.
Statistical analysis
The Statistical Package for Social Sciences v 28.0 was used to analyze the data. The normal distribution of quantitative/continuous variables was assessed using the Shapiro–Wilk test. While normally distributed quantitative variables were depicted as mean with standard deviation (SD), non-parametric quantitative variables were presented as median with interquartile range (IQR). A between-groups comparison of normally distributed quantitative variable was done using an independent sample t-test, and the Mann–Whitney U-test was employed for non-parametrically distributed variables. Qualitative/categorical variables were presented as percentages and proportions. Qualitative variables were compared using Chi-square and Fisher’s Exact tests, as applicable. P < 0•05 (two-tailed) was considered statistically significant.
RESULTS
Demographic, clinical characteristics, and prescription pattern of APMs in PD patients
Fifty of the 112 screened PD patients fulfilled the inclusion and exclusion criteria [Supplementary Figure 1]. Of the 50 PD patients, 31 (62%) were male. The average onset age of PD was 53 ± 9.92 years, and the mean age at assessment was 59.18 ± 9.94 years. One-third of patients belonged to the young onset PD group. Two-thirds of patients had tremor-onset PD. While nearly half the patients (46%) were prescribed only levodopa–carbidopa monotherapy, 28% of patients were on >2 APMs. The median GQOL scale score was 70 for the entire cohort of patients. The remaining demographic and clinical characteristics of the participants are depicted in Table 1.
| Variables | PD patients (n=50) |
|---|---|
| Age at onset of PD (in years):*Mea n(±SD) | 53±9.92 |
| Age at assessment (in years):*Mea n(±SD) | 59.18±9.94 |
| Male gender: n(%) | 31 (62) |
| Comorbidities – HT and/or DM: n(%) | 19 (38) |
| PD characteristics | |
| Disease duratio n(in months):# Media n(IQR) | 57.5 (36–99) |
| YOPD: n(%) | 17 (34) |
| PD subtypes:$ | |
| Tremor-dominant PD: n(%) | 33 (66) |
| Postural instability and gait disorder: n(%) | 16 (32) |
| MDS-UPDRS-III score:# Media n(IQR) | 38.5 (27–44) |
| MDS-NMS score:# Media n(IQR) | 59.5 (31–90) |
| Hoehn–Yahr stage >2: n(%) | 12 (24) |
| Anxiety: n(%) | 15 (30) |
| Depression: n(%) | 16 (32) |
| EDS (ESS>10): n(%) | 4 (8) |
| Poor sleep quality (PSQI >5): n(%) | 28 (56) |
| Cognitive impairment (MoCA <26):@ n(%) | 10/44 (22.7) |
| Type of APMs prescribed: | |
| Levodopa–carbidopa: n(%) | 50 (100) |
| Pramipexole: n(%) | 14 (28) |
| Ropinirole: n(%) | 4 (8) |
| Anticholinergic: n(%) | 10 (20) |
| Rasagiline: n(%) | 8 (16) |
| Amantadine: n(%) | 5 (10) |
| Entacapone: n(%) | 4 (8) |
| Combination of APMs prescribed | |
| Levodopa–carbidopa only: n(%) | 23 (46) |
| 2 APMs: n(%) | 13 (26) |
| >2 APMs: n(%) | 14 (28) |
| LEDD (mg):# Media n(IQR) | 525 (400–862.5) |
| High pill burden: n(%) | 31 (62) |
| Regular follow-up: n(%) | 44 (88) |
| Global Quality of Life Scale score: # Media n(IQR) |
70 (63.75–80) |
Comparison of demographic and clinical characteristics of patients with high adherence versus those with medium/low adherence to APMs
Among the 50 recruited PD patients, nearly half (46%) patients reported high adherence (MGL-MAS = 0) to APMs. The majority of demographic and clinical features in the two groups were comparable [Table 2]. Medium/low adherence was associated with greater severity of PD (Hoehn–Yahr stage >2; medium/low adherence vs. high adherence = 37% vs. 8.7%; P = 0.02). Although, depressive symptoms were noted in a much higher proportion of patients in the medium/low adherence as compared to the group having high adherence, but did not reach statistical significance (44.4% vs. 17.4%; P = 0.06). Patients in the medium/low adherence group had poorer life quality than those in the high adherence group (median [IQR] = 65 [50–70] vs. 80 [70–85]; P < 0.001). However, poor SQ (P = 0.52) and EDS (P = 0.22) did not affect adherence to medication.
| Variables | High adherence (n=23) |
Medium/low adherence (n=27) |
P-value | df | Test value |
|---|---|---|---|---|---|
| Age at onset of PD (in years):* Mea n (SD) | 55.09 (10.04) | 51.22 (9.65) | 0.17 | 48 | C.I=−9.47–1.74 |
| Age at assessment (in years):* Mea n (SD) | 60.30 (9.45) | 58.22 (10.43) | 0.46 | 48 | C.I=−7.78–3.62 |
| Male gender: n (%) | 14 (60.9) | 17 (63) | 0.88 | 1 | χ2=0.02 |
| Comorbidities – HT and/or DM: n (%) | 9 (39.1) | 10 (37) | 0.88 | 1 | χ2=0.02 |
| PD characteristics | |||||
| Disease duratio n (in months):# Media n (IQR) | 46 (36–84) | 60 (36–120) | 0.27 | - | U=254 |
| YOPD: n (%) | 8 (34.8) | 9 (33.3) | 0.91 | 1 | χ2=0.01 |
| PD subtypes$ | |||||
| Tremor-dominant PD: n (%) | 16 (69.6) | 17 (63) | 0.31 | 2 | χ2=2.36 |
| Postural instability and gait disorder: n (%) | 6 (26.1) | 10 (37) | |||
| MDS-UPDRS-III score#: Media n (IQR) | 38 (25–44) | 40 (27–47) | 0.94 | - | U=314.5 |
| MDS-NMS score#: Media n (IQR) | 52 (29–85) | 79 (32–125) | 0.16 | - | U=239 |
| Hoehn–Yahr stage >2: n (%)** | 2 (8.7) | 10 (37) | 0.02 | - | - |
| Anxiety: n (%) | 8 (34.8) | 7 (25.9) | 0.49 | 1 | χ2=0.46 |
| Depression: n (%)** | 4 (17.4) | 12 (44.4) | 0.06 | - | - |
| EDS (ESS>10): n (%)** | 3 (13) | 1 (3.7) | 0.32 | - | - |
| Poor sleep quality (PSQI >5): n (%) | 14 (60.9) | 14 (51.9) | 0.52 | 1 | χ2=0.41 |
| Cognitive impairment (MoCA <26):@ n (%) | 3/21 (14.3) | 7/23 (30.4) | 0.74 | 1 | χ2=0.11 |
| Global quality of life scale score:# Media n (IQR) | 80 (70-85) | 65 (50-70) | <0.001 | - | U=502.5 |
| APMs prescribed | |||||
| Levodopa–carbidopa: n (%) | 23 (100) | 27 (100) | - | - | - |
| Dopamine agonist: n (%) | 7 (30.4) | 11 (40.7) | 0.45 | 1 | χ2=0.57 |
| Anticholinergic: n (%)** | 4 (17.4) | 6 (22.2) | 0.74 | - | - |
| MAOBI: n (%)** | 3 (13) | 5 (18.5) | 0.71 | - | - |
| Amantadine: n (%)** | 1 (4.3) | 4 (14.8) | 0.36 | - | - |
| COMTI: n (%)** | 2 (8.7) | 2 (7.4) | 1.00 | - | - |
| Combination of APMs prescribed | |||||
| Levodopa–carbidopa+COMTI: n (%) | 12 (52.2) | 12 (44.4) | 0.59 | 1 | χ2=0.29 |
| LD-carbidopa+other APMs: n (%) | 11 (47.8) | 15 (55.6) | |||
| LEDD (mg)#: Media n (IQR) | 415 (400–725) | 600 (400–900) | 0.29 | - | U=257 |
| High pill burde n (>4 pills per day): n (%) | 12 (52.2) | 19 (70.4) | 0.18 | 1 | χ2=1.75 |
| Regular follow-up: n (%)** | 21 (91.3) | 23 (85.2) | 0.67 | - | - |
Comparison of treatment characteristics and follow-up pattern of patients with and without high adherence to APMs
A comparison of treatment characteristics including prescription pattern and follow-up pattern of patients in high versus medium/low adherence group is shown in Table 2. Levodopa–carbidopa combination (n = 50; 100%) was the most commonly prescribed drug. The prescription pattern of APMs, LEDD, pill burden, and follow-up pattern was comparable between both groups.
Comparison of clinical and treatment-related variables between patients with and without poor quality of sleep
Comparison of clinical and treatment-related variables of PD patients with and without poor SQ are depicted in Supplementary Table 1. While majority of the characteristics were comparable in those with and without poor quality of sleep, except that a significantly higher proportion of patients with poor quality of sleep reported depressive symptoms (P = 0.02).
DISCUSSION
More than half the PD patients (54%) in this study reported medium/low adherence to APMs. While the majority of other characteristics including demographic, disease-related, and APMs prescription patterns were comparable in both groups, a significantly higher proportion of patients in the medium/low adherence group belonged to Hoehn–Yahr stage >2. A much higher proportion of PD patients in the medium/low adherence group reported depressive symptoms, although not significant. The SQ and EDS were not associated with adherence to APMs. The median GQOL score in patients with medium/low adherence was significantly lower than those in the high adherence group. Levodopa–carbidopa monotherapy was most commonly prescribed (46%).
Lack of adherence to APMs is a significant problem in PD[32,33] as it influences the therapeutic response,[4,9] thereby affecting the life quality of patients and care providers. It also affects the decision-making regarding modifications in APMs dosage and frequency. In our study, 54% of PD patients reported medium/low adherence to APMs, similar to that reported in prior studies, which observed medium/low adherence in 56.8–61% of PD patients.[8,9,11] While one of these studies used an 8-item Morisky MAS, a self-reported assessment scale,[8] the second assessed medication possession ratio,[9] and the third study utilized an electronic microprocessor-monitoring to detect the opening of the pill container.[11] In a review comprising nine studies, the non-adherence rate varied between 10% and 67%.[33] The wide variability of the non-adherence rate was related to differences in the assessment methods such as the use of a visual analog scale, self-reporting by patients, counting the pills while refilling in the pharmacy, and electronically monitoring of opening the pill container.[33]
We observed poor quality of sleep and EDS in a comparable proportion of patients in both medium/low and high adherence groups. A previous study reported no significant difference in ESS score in PD patients (n = 54) with/without adequate medication adherence.[4] It may be difficult to interpret their result as they compared the mean (SD) of ESS score rather than the proportion of PD patients with EDS (ESS >10). While we hypothesized poor SQ to affect the APMs adherence, it was not observed in our cohort and this may be related to the low sample size. However, a significantly higher percentage of PD patients with poor quality of sleep reported depressive features (P = 0.02), and this may have influenced the APMs adherence as discussed in the subsequent paragraph. Poor SQ may affect cognition and emotional reactivity and induce physiological changes including reduced ACTH response, thereby precipitating depressive features.[34]
Previous studies have reported a significant association between depression and poor APMs adherence.[2,4,8] In the present study, a much higher proportion of patients in the medium/low adherence group reported depressive symptoms as compared to the high adherence group, although not statistically significant (P = 0.06), which may be due to the low sample size. Depression is commonly reported by PD patients, with one in every three PD patients having clinically bothersome depression.[35] Dopaminergic, noradrenergic, and serotonergic dysfunction in brainstem, limbic, and cortical areas have been implicated in causing depression symptoms in PD.[35] Patients suffering from depression may underappreciate the benefits of APMs, which may affect their adherence. Moreover, the lack of adherence may precipitate dopaminergic dysfunction, thereby, precipitating depression along with other Parkinsonian motor and NMSs.[32,33] Thus, maintaining adequate adherence may overcome this vicious cycle. While a single study has reported an association of other NMSs including constipation, anxiety, and falls with suboptimal adherence to APMs,[13] the proportion of patients with anxiety was comparable in both medium/low and high adherence groups in the present study. Moreover, the MDS-NMS scores were comparable in the two groups among our PD patients. Cognitive impairment and behavioral issues such as alcohol abuse have been reported to be associated with poor APMs adherence.[32,33] While the present study did not assess the behavioral issues, impaired cognition was seen in a comparable proportion of patients in both groups.
The worsening of parkinsonian symptoms due to poor adherence may result in a higher motor score. A multicentric European study involving 112 PD patients reported a significantly higher motor severity in the suboptimal adherence group (median unified PD rating scale motor score [IQR] in the satisfactory adherence vs. suboptimal adherence groups = 19 [13–26] vs. 29 [20–41]; P = 0.005), although median Hoehn–Yahr stage was comparable in both groups.[5] While the MDS-UPDRS motor score was comparable in both groups, a significantly higher percentage of our patients in the medium/low adherence group belonged to the Hoehn–Yahr stage >2. It is likely that PD patients with higher motor severity have more motor fluctuations and dyskinesias and may develop a perception of reduced efficacy of APMs, thereby resulting in suboptimal adherence. By exacerbating Parkinsonian symptoms, poor adherence is likely to affect the quality of life in PD patients. The median GQOL score in our patients with medium/low adherence was significantly reduced than that in the high adherence group, similar to previous reports.[4,5]
Polypharmacy and use of multiple APMs may result in poor medication adherence in PD patients.[32,33] The treatment characteristics including prescription pattern of APMs, pill burden, LEDD, and follow-up pattern were comparable in both adherence groups in the present study. Levodopa–carbidopa monotherapy was the most commonly prescribed (46%) APM in our patients, with the remainder (54%) receiving two or more APMs. While previous studies reported poor adherence in those taking more APMs,[4,5] we did not find any association between high pill burden and medium/low adherence. Less number of patients in the present cohort (n = 50) as compared to the previous studies (54 and 112)[4,5] may be one of the reasons for the same. Moreover, higher age at assessment in the previous two studies (61.9 years and 65 years)[4,5] as compared to the present study (59.1 years) may be another contributory factor as older age (≥65) has been reported to be associated with suboptimal adherence to APMs.[33]
This study has some limitations. First, it is a single-center and cross-sectional study with a low sample size, thereby limiting the generalizability of our results. However, we included only those patients who were on APMs for at least for past 24 months. Second, we did not take into consideration the adverse effects of APMs while assessing adherence. Since adverse events likely result in poor medication adherence early after initiating APMs, it is unlikely to have affected this study as all included patients were on APMs for the past 24 months. Third, the adherence in this study was assessed using a self-rated scale which is likely to result in underestimation. Fourth, we did not assess social and financial insecurity and educational status. While these factors have been linked to poor APMs adherence in developed countries,[32,33] the single Indian study to date failed to find such an association.[8] Fifth, we used a GQOL scale rather than PD specific QOL scale. However, this is the first study assessing the relation of adherence to APMs with a detailed non-motor evaluation using the MDS-NMS scale along with SQ and EDS assessment.
CONCLUSION
More than half the PD patients reported medium/low adherence to APMs. While the proportion of patients with poor SQ and EDS was comparable in both groups, higher motor severity of PD was more common in those with medium/low adherence. Although lacking statistical significance, a much higher percentage of PD patients in the medium/low adherence group reported depressive symptoms. PD patients with medium/low adherence reported poor quality of life.
Ethical approval
The research/study was approved by the Institutional Review Board at All India Institute of Medical Sciences, Rishikesh, number AIIMS/IEC/19/1277, dated November 29, 2019.
Declaration of patient consent
The authors certify that they have obtained all appropriate patient consent.
Conflicts of interest
There are no conflicts of interest.
Use of artificial intelligence (AI)-assisted technology for manuscript preparation
The authors confirm that there was no use of artificial intelligence (AI)-assisted technology for assisting in the writing or editing of the manuscript and no images were manipulated using AI.
Supplementary material available on:
https://doi.org/10.25259/JNRP_585_2023
Financial support and sponsorship
Nil.
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