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Abstract

Background:

Parkinson’s disease with mild cognitive impairment (PD-MCI) or dementia (PDD) has been shown to be correlated with poor quality of life (QoL). The association between specific cognitive domains and QoL is less clear.

Objective:

To determine how the cognitive domains affect QoL in different cognitive states in PD.

Methods:

We recruited 600 PD patients, including 185 PD patients with normal cognition (PD-NC), 336 PD-MCI patients, and 79 PDD patients. All patients underwent a scale-based assessment (PDQ-39) for QoL, as well as clinical evaluations and neuropsychological tests.

Results:

Compared to PD-NC group, QoL became more impaired in the PD-MCI and PDD groups. Generalized linear model revealed that no neuropsychological test was significantly associated with QoL in PD-NC group; neuropsychological tests in attention and language domains were significantly associated with QoL in PD-MCI patients; neuropsychological tests in memory and language domains were significantly associated with QoL in PDD patients.

Conclusions:

Cognitive domains contribute differently to QoL in PD. These findings may prompt clinicians to target specific cognitive domains for improving QoL in the PD patients.

Keywords

Parkinson’s disease mild cognitive impairment dementia quality of life

INTRODUCTION

Cognitive decline is a prevalent comorbidity in Parkinson’s disease (PD), and up to 80% of patients ultimately suffer from dementia (PDD) [1]. Mild cognitive impairment in PD (PD-MCI) represents a less severe cognitive deficit in the patients and is defined as a transition from unnoticeable changes in cognition to dementia [2].

It is vital to assess the quality of life (QoL) in PD patients, and QoL is considered to be a crucial outcome indicator in PD. Accruing studies have reported that non-motor symptoms make significant contributions to QoL in PD patients [3, 4]. As one of the most common nonmotor symptoms in PD, cognitive impairment also contributes to QoL. It has been shown that PDD causes distress and is markedly correlated with QoL [5, 6], while PD-MCI also significantly contributes to poor QoL [6 –9].

Deficit in attention, memory or executive function has been reported to be directly correlated with poor QoL in PD [6, 8]. However, the impact of specific cognitive domains on QoL in the different cognitive states in PD has yet to be evaluated. Identification of the effects of cognitive performance on QoL may help clinicians determine which pharmacological and non pharmacological interventions are particularly effective. Here, we analyzed how the cognitive domains are associated with QoL in PD patients with normal cognition (PD-NC), MCI and dementia.

METHODS

Subjects

A total of 600 PD patients aged from 50 to 80 were consecutively enrolled from March, 2011 to February, 2019 in the department of neurology, Huashan Hospital affiliated with Fudan University. PD was diagnosed by at least two specialists on movement disorders based on the United Kingdom PD Society Brain Bank [10], and confirmed by at least 2-year follow-up. Clinical signs satisfying the criteria of possible atypical Parkinsonism were excluded. Cases with any history of stroke, epilepsy, encephalitis, traumatic brain injury, malignancies, cardiac events, or severe psychiatric illness (schizophrenia and bipolar disorder) were excluded. The study obtained an approval from the Human Studies Institutional Review Board of Huashan Hospital, and the Declaration of Helsinki based informed written consent was provided by all enrolled patients.

Clinical and neuropsychological assessments

Clinical and neuropsychological assessments were performed at Huashan Hospital. Before clinical assessment, the patients were off anti-Parkinsonian medications for at least 12 h. The modified Hoehn and Yahr scale and the Unified Parkinson’s Disease Rating Scale motor (UPDRS-III) sub score were used to determine the stage and severity of parkinsonism for each patient. The dosage of anti-parkinsonian drugs was converted into a total daily levodopa equivalent dose (LED) for data standardization of medications [11].

After motor assessment, patients who were taking the regular medications (Med-On) took the cognitive assessment. The Mini-Mental State Examination (MMSE) was used to evaluate global cognitive function [12], and the Geriatric Depression Rating Scale (GDS) was performed to evaluate depression. A full set of neuropsychological tests for five specific cognitive domains were carried out as follows [13]: 1) Symbol Digit Modality Test (SDMT) [14] and Trail Making Test A (TMT-A) [15] for attention and working memory; 2) Trail Making Test B (TMT-B) [15] and Stroop Color-Word Test (CWT) [16] for executive function; 3) Animal Fluency Test (AFT) and Boston Naming Test (BNT) [17] for language; 4) Auditory Verbal Learning Test (AVLT) [18] and Rey-Osterrieth Complex Figure Test (CFT-delay) [19] for memory; and 5) Rey-Osterrieth Complex Figure Test (CFT-copy) [19] and Clock Drawing Test (CDT) [20] for visuospatial function (Supplementary Table 1).

PDD was diagnosed according to the Movement Disorder Society (MDS) criteria [21]. The MDS Task Force Level 2 was applied for PD-MCI diagnosis [22]. A score of 1.5 SDs below the norm for a given cognitive test was defined as abnormal. PD-MCI was diagnosed based on detection of impairment on two or more neuropsychological tests, characterized by either one impaired test involving two independent cognitive domains or two impaired tests involving the same domain. The patients who were excluded from PD-MCI and PDD were defined as PD-NC.

The routinely used Parkinson’s Disease Questionnaire (PDQ-39) was conducted for determining QoL [23]. Higher scores indicate worse QoL. PDQ-39 was fulfilled by the patient alone.

Statistics

SAS 9.4 (SAS Institute Inc., NC, USA) was applied for performing statistical analysis. The normal distribution of data was checked by visual histograms and Kolmogorov-Smirnov test. For the comparison of means among groups on the continuous and normal distributed data, the one-way analysis of variance (ANOVA) was used. Kruskal-Wallis test was performed for the data with a non-normal distribution. Bonferroni’s correction was performed for the multiple comparisons. To analyze the correlation between two variables, Spearman’s rank correlation was applied. After adjusting for age, gender, education years, UPDRS-III score, disease duration, LED, and GDS score, the association between neuropsychological tests and PDQ-39 was analyzed based on generalized linear model. The significance level was set at 0.05.

RESULTS

Clinical characteristics and QoL in all PD patients

The demographic profiles and clinical characteristics for all the PD patients were summarized in Table 1.

Table 1

Clinical characteristics and neuropsychological evaluations of the participants

	Total	PD-NC	PD-MCI	PDD	p ^a	p	p	p
	(N = 600)	(N = 185)	(N = 336)	(N = 79)	PD-NC vs PD-MCI	PD-NC vs PDD	PD-MCI vs PDD

Gender (M/F)	338/262	107/78	181/155	50/29	0.2788 ^b	1.0000	1.0000	0.3879
Age (y)	61.93±6.71	61.33±6.68	62.06±6.66	62.8±6.93	0.2963	0.5118	0.2936	0.7328
Age (y), min, max	50, 79	50, 77	50, 79	50, 77
Education (y)	10.67±4.01	12.74±2.9	9.58±4.21	10.32±3.6	<0.0001	<0.0001	<0.0001	0.5276
UPDRS-III score	34.93±15.79	28.39±14.12	37.55±15.26	41.6±16.99	<0.0001	<0.0001	<0.0001	0.2466
Disease duration (y)	4.42 (1.67, 9.67)	3.08 (1.50, 7.17)	4.96 (2.00, 10.71)	5.17 (1.67, 10.42)	0.0054	0.0043	0.1331	0.9512
Disease duration (y), min, max	0.42, 23.08	0.42, 22.00	0.42, 23.08	1.42, 18.50
Levodopa equivalent dose (mg/day)	525.20	450.00	537.50	600.00	0.1308	0.2188	0.1987	0.7170
	(500.00, 825.60)	(300.00, 750.40)	(300.00, 825.60)	(331.55, 1000.50)
GDS score	12.02±7.41	10.26±7.46	12.35±7.15	14.84±7.38	<0.0001	0.0018	<0.0001	0.0254
Existence of a caregiver (Yes/No)	556/44	176/9	311/25	74/5	0.5200	0.3400	0.8520	0.9190
PDQ-39	39.78±28.16	30.86±24.47	41.49±27.27	53.35±33.07	<0.0001	<0.0001	<0.0001	0.0125
Cognitive characteristics
MMSE	26.44±3.32	28.21±1.58	26.79±2.28	20.76±3.98	<0.0001	<0.0001	<0.0001	<0.0001
Attention and working memory
SDMT	28.42±15.34	41.1±9.73	24.1±13.39	17.11±14.89	<0.0001	<0.0001	<0.0001	0.0004
TMT-A (s)	84.24±50.93	56.17±14.15	92.79±47.31	121.15±84.33	<0.0001	<0.0001	<0.0001	0.0636
Executive function
CWT-C time (s)	93.13±44.06	76±16.38	95.82±36.98	126.31±84	<0.0001	<0.0001	<0.0001	0.0004
CWT-C right	44.28±5.93	46.65±3.14	43.57±6.54	41.17±6.57	<0.0001	<0.0001	<0.0001	0.0021
TMT-B (s)	189.04±86.77	141.21±39.94	206.03±82.81	251.22±131.85	<0.0001	<0.0001	<0.0001	0.0066
Language
AFT	14.51±4.81	17.25±4.46	13.8±4.34	11.13±4.3	<0.0001 ^c	<0.0001	<0.0001	<0.0001
BNT	21.58±4.68	24.58±3.1	20.39±4.65	19.61±4.62	<0.0001	<0.0001	<0.0001	0.3850
Memory
AVLT-delay recall	3.62±2.53	5.3±2.04	3.15±2.3	1.68±2.25	<0.0001	<0.0001	<0.0001	<0.0001
AVLT-T	20.96±9.35	27.23±7.92	19.03±8.13	14.49±9.35	<0.0001	<0.0001	<0.0001	<0.0001
CFT-delay recall	11.71±7.45	17.24±6.14	9.58±6.32	7.19±7.19	<0.0001	<0.0001	<0.0001	0.0010
Visuospatial function
CFT	28.18±9.35	33.79±1.86	26.24±9.82	22.83±11.55	<0.0001	<0.0001	<0.0001	0.1068
CDT	18.58±7.50	22.48±5.24	17.18±7.59	13.67±7.62	<0.0001	<0.0001	<0.0001	0.0058

PD-NC, Parkinson’s disease with no cognitive impairment; PD-MCI, Parkinson’s disease with mild cognitive impairment; PDD, Parkinson’s disease with dementia; UPDRS, Unified Parkinson’s Disease Rating Scale; GDS, Geriatric Depression Rating Scale; PDQ, Parkinson’s Disease Questionnaire; MMSE, Mini-Mental State Examination; SDMT, Symbol Digit Modality Test; TMT, Trail Making Test; CWT, Stroop Color-Word Test; BNT, Boston Naming Test; AFT, Animal Fluency Test; AVLT, Auditory Verbal Learning Test; CFT, the Rey-Osterrieth Complex Figure Test; CDT, Clock Drawing Test. The data of disease duration and levodopa equivalent dose are presented as median (25%, 75%), and the else data are presented as mean±SD. Note: ^a Comparison among the three groups with PD-NC, PD-MCI, and PDD. ^b The categorical variables were compared among the three groups by Chi-squared test. ^c The continuous variable of AFT was compared among the three groups by one-way ANOVA test. The other continuous variables were compared among the three groups by Kruskal-Wallis test.

The correlation between clinical characteristics and PDQ-39 in all patients was investigated. The analysis revealed that higher GDS and UPDRS-III scores, longer disease duration, higher LED and fewer years of education were related to poorer QoL in the patients (Table 2).

Table 2

Correlation between clinical characteristics and PDQ-39 in all PD patients

	PDQ-39
	r	p
GDS score	0.6597	<0.0001
UPDRS-III score	0.6138	<0.0001
Disease duration	0.4929	<0.0001
Levodopa equivalent dose	0.4371	<0.0001
Education	– 0.1621	<0.0001
Age	0.0184	0.6526

PDQ, Parkinson’s Disease Questionnaire; GDS, Geriatric Depression Rating Scale; UPDRS, Unified Parkinson’s Disease Rating Scale. Note: r-Spearman correlation coefficient. Spearman’s rank correlation coefficient was used to test their correlation.

Cognitive function and QoL in all PD patients

All participants were classified into the three groups as follows: PD-NC (n = 185), PD-MCI (n = 336), and PDD (n = 79). As indicated in Table 1, we found that the education years, UPDRS-III score, disease duration, and GDS score were significantly different among the three groups. All neuropsychological scores in both PD-MCI and PDD groups were poorer than those in PD-NC group. PDD group displayed lower scores in all the tests except TMT-A, BNT, and CFT compared with PD-MCI group.

We performed a QoL assessment on all the patients based on the PDQ-39, and QoL was more impaired across the three groups (PD-NC < PD-MCI < PDD). Correlation analysis between neuropsychological tests and PDQ-39 was performed in all patients (Table 3). TMT-A, TMT-B, and CWT-C time were positively but weak associated with PDQ-39. And MMSE, SDMT, CWT-C right, AFT, BNT, AVLT-delay recall, AVLT-T, CFT-delay recall, CDT, and CFT were negatively but weak associated with PDQ-39. It indicated that without controlling for confounding factors, poor scores in all these neuropsychological tests were related to poor QoL.

Table 3

Correlation between cognitive function and PDQ-39 in all PD patients

	PDQ-39
	r	p
MMSE	– 0.1963	<0.0001
SDMT	– 0.3508	<0.0001
TMT-A	0.2942	<0.0001
CWT-C time	0.2108	<0.0001
CWT-C right	– 0.1521	0.0003
TMT-B	0.2148	<0.0001
AFT	– 0.2482	<0.0001
BNT	– 0.1695	0.0001
AVLT-delay recall	– 0.2205	<0.0001
AVLT-T	– 0.2500	<0.0001
CFT-delay recall	– 0.2816	<0.0001
CFT	– 0.2805	<0.0001
CDT	– 0.1672	0.0002

PDQ, Parkinson’s Disease Questionnaire; MMSE, Mini Mental State examination; SDMT, Symbol Digit Modality Test; TMT, Trail Making Test; CWT, Stroop Color-Word Test; AFT, Animal Fluency Test; BNT, Boston Naming Test; AVLT, Auditory Verbal Learning Test; CFT, the Rey-Osterrieth Complex Figure Test; CDT, Clock Drawing Test. Note: r-Spearman correlation coefficient. Spearman’s rank correlation coefficient was used to test their correlation.

To explore the effects of cognitive domains on QoL in all the patients, a generalized linear model was performed, controlling for age, gender, education years, UPDRS-III score, disease duration, LED, and GDS score. The results showed that the SDMT (β= – 0.2476, p = 0.0011), TMT-A (β= 0.0501, p = 0.0092), and CWT-C time (β= 0.0468, p = 0.0367) were associated with PDQ-39 for all patients (Table 4).

Table 4

Generalized linear analysis of cognitive domains and PDQ-39

		All			PD-NC			PD-MCI			PDD
Variables	β	95% CI	p	β	95% CI	p	β	95% CI	p	β	95% CI	p
SDMT	– 0.25	(– 0.40, – 0.10)	0.0011	– 0.07	(– 0.41, 0.27)	0.6863	– 0.22	(– 0.44, – 0.00)	0.0459	– 0.45	(– 0.96, 0.07)	0.0904
TMT-A	0.05	(0.01, 0.09)	0.0092	– 0.01	(– 0.24, 0.21)	0.9230	0.03	(– 0.03, 0.08)	0.3722	0.05	(– 0.03, 0.13)	0.2443
CWT-C time	0.05	(0.00, 0.09)	0.0367	– 0.01	(– 0.19, 0.17)	0.9270	0.02	(– 0.07, 0.11)	0.6721	0.04	(– 0.02, 0.10)	0.2259
CWT-C right	– 0.13	(– 0.44, 0.18)	0.4133	0.26	(– 0.56, 1.09)	0.5340	– 0.08	(– 0.49, 0.32)	0.6853	– 0.02	(– 0.86, 0.82)	0.9581
TMT-B	0.02	(0.00, 0.04)	0.1043	0.01	(– 0.07, 0.08)	0.8984	– 0.00	(– 0.04, 0.03)	0.7503	0.04	(– 0.00, 0.09)	0.0589
AFT	– 0.44	(– 0.88, 0.00)	0.0524	0.24	(– 0.41, 0.90)	0.4717	– 0.80	(– 1.49, – 0.11)	0.0236	0.16	(– 1.30, 1.62)	0.8328
BNT	– 0.17	(– 0.62, 0.29)	0.4718	0.39	(– 0.54, 1.32)	0.4086	0.12	(– 0.50, 0.75)	0.6985	– 1.66	(– 3.00, – 0.32)	0.0151
AVLT-delay recall	– 0.77	(– 1.55, 0.02)	0.0556	– 1.22	(– 2.58, 0.13)	0.0775	0.20	(– 1.00, 1.41)	0.7418	– 4.08	(– 7.54, – 0.62)	0.0209
AVLT-T	– 0.16	(– 0.38, 0.06)	0.1525	– 0.19	(– 0.54, 0.16)	0.2907	0.09	(– 0.26, 0.43)	0.6166	– 0.68	(– 1.54, 0.18)	0.1197
CFT-delay recall	– 0.16	(– 0.45, 0.13)	0.2772	0.10	(– 0.36, 0.56)	0.6708	– 0.13	(– 0.61, 0.34)	0.5751	0.24	(– 0.65, 1.14)	0.5950
CFT	– 0.13	(– 0.35, 0.09)	0.2441	0.49	(– 1.00, 1.98)	0.5224	– 0.11	(– 0.40, 0.17)	0.4347	0.16	(– 0.40, 0.71)	0.5791
CDT	– 0.16	(– 0.42, 0.11)	0.2414	0.51	(– 0.05, 1.07)	0.0743	– 0.10	(– 0.47, 0.27)	0.6127	– 0.32	(– 1.09, 0.44)	0.4064

β, beta coefficient; CI, confidence interval; PDQ, Parkinson’s Disease Questionnaire; PD-NC, Parkinson’s disease with no cognitive impairment; PD-MCI, Parkinson’s disease with mild cognitive impairment; PDD, Parkinson’s disease with dementia; SDMT, Symbol Digit Modality Test; TMT, Trail Making Test; CWT, Stroop Color-Word Test; BNT, Boston Naming Test; AFT, Animal Fluency Test; AVLT, Auditory Verbal Learning Test; CFT, the Rey-Osterrieth Complex Figure Test; CDT, Clock Drawing Test. Note: Generalized linear model adjusted for age, sex, education, UPDRS-III score, disease duration, levodopa equivalent dose, and GDS score.

Cognitive domains and QoL in PD-NC, PD-MCI, and PDD patients

After adjusting for age, gender, education years, UPDRS-III score, disease duration, LED, and GDS score in the generalized linear model, no neuropsychological test was related to PDQ-39 for PD-NC patients; the AFT (β= – 0.8011, p = 0.0236) and SDMT (β= – 0.2235, p = 0.0459) were related to PDQ-39 for PD-MCI patients; the BNT (β= – 1.6582, p = 0.0151) and AVLT-delay recall (β= – 4.0782, p = 0.0209) were related to PDQ-39 for PDD patients (Table 4).

DISCUSSION

To our knowledge, it is the first study to explore specific cognitive domains regarding QoL among PD-NC, PD-MCI, and PDD patients. We demonstrated that impaired cognition was associated with poor QoL in PD, and cognitive domains contribute differently to QoL across the varied cognitive states in PD

In accordance with the previous report [6], we showed that QoL became more impaired in the PD-MCI and PDD groups. However, another study demonstrated that although PDD was correlated with reduced QoL, PD-MCI group had similar QoL with PD-NC group [5]. The above discrepancy could be attributed to the fact that the Level I criteria was used for defining the “possible” PD-MCI in this study [22]. Here, PD-MCI was diagnosed based on MDS level II category guidelines, which are considered more stringent criteria. As such, patients with more impaired cognitive function were included in PD-MCI group. Lawson et al. demonstrated that the severity of PD-MCI was related to QoL [7].

The contribution of cognitive domains on QoL for all the PD patients was investigated. The results showed that SDMT, TMT-A, and CWT-time were significantly associated with QoL. Given that the SDMT and TMT-A are routinely used for evaluating attention and working memory, and CWT-time provides a measure of executive function, this finding suggests that attention and executive function deficits in PD are significantly associated with poor QoL. It is known that the most common impaired domains in PD involve attention and executive function [24, 25]. Attention deficit led to an impairment in instrumental and functional activities, such as dressing, washing, eating, interacting socially, and managing medications, which are important for a good QoL [26]. Lawson et al. demonstrated that attention can act as the most powerful indicator for QoL both in the baseline and in the longitudinal analysis [6]. In addition to attention, executive function, including planning, organization and regulation of goal-directed behavior, was also associated with QoL. Klepac et al. showed that executive function was independently and positively associated with health related QoL [22].

Interestingly, our sample showed that in PD-MCI patients, tests of attention (SDMT) and language (AFT) were significantly associated with QoL, whereas in PDD patients, tests of memory (AVLT) and language (BNT) were significantly correlated with QoL. These results may be partially explained by the different pattern of cognitive impairment in the varied cognitive states in PD [27]. The patients at the initial stage of PD can present subtle alterations in cognition known as PD-MCI, which are driven mainly by dopaminergic dysmodulation [27, 28]. The initial neuropsychological profile is mainly of a non-amnesic type, characterized by executive dysfunction, attention deficits, operative memory deficits and faulty retrieval of information [29]. However, PD patients could develop dementia related to non-dopaminergic, cholinergic cortical dysfunction. During the progression from PD-MCI to PDD, executive dysfunction and attention deficit persist, while more profound memory and visuo-spatial impairments were detected [29 –31]. According to the results, we suppose that memory might impose a greater impact on QoL than other cognitive domains including attention when dementia occurs in PD.

Language was found to be associated with QoL both in PD-MCI and PDD patients. Usually, language is not considered as a main impaired cognitive domain. However, numerous studies have found that PD patients had a substantial decline in language function, such as verbal fluency, naming, and sentence comprehension [32]. A progressive deterioration in language and speech throughout the disease course impairs the patient’s ability to communicate with family, friends, and other members in the communities. It is well recognized that language deficits have substantial psychosocial effects on the individuals, their independence, and family dynamics [33], thus contributing to QoL. Interestingly, our results showed that different language tests were associated with QoL in PD-MCI and PDD groups (the AFT in PD-MCI group and the BNT in PDD group). Language is a quite complex behavior involving the contribution of some cognitive processes, and different language tasks provide rich information on the different cognitive processes [32]. AFT requires two cognitive processes known as ‘clustering’ and ‘switching’ [34]. AFT is largely dependent on executive function as well as semantic network [35]. However, impairment in BNT can be attributed to several abnormalities, such as language and semantic dysfunction, visuospatial deficits (especially perceptual deficits), and reduced phonological/motor output [36]. Although AFT and BNT are slightly different neural processes, our results may indicate that extra attention on the language therapy was recommended in both PD-MCI and PDD patients.

Strengths of the study include a relatively large number of enrolled PD patients and a full set of neuropsychological tests, with no less than two tests for every single cognitive domain. There are several limitations in our study. For one, this study is a cross-sectional design, which could not investigate the role of declined cognition in QoL. Thus, further studies are required to analyze longitudinal impacts of cognitive alteration on QoL. Also, potential confounders were minimized by adjusting for age, gender, education years, UPDRS-III score, disease duration, LED, and GDS score in this study. Nonetheless, we cannot fully exclude the possibility of some remaining confounders, such as anxiety, sleep disturbance, apathy, impulse control disorders and time to Med-on, were relevant to QoL. Future studies with information on these potentially important confounders will need to minimize potential biases.

Conclusion

In conclusion, the present study demonstrated that QoL is more impaired in PD-MCI and PDD patients compared to PD-NC patients. Attention and language impairment are associated with poor QoL in PD-MCI patients, and memory and language deficits are associated with poor QoL in PDD patients. When initiating pharmacological or non pharmacological interventions, such as cognitive rehabilitation, clinicians might need to focus on specific cognitive impairment domains based on the cognitive states in PD.

CONFLICT OF INTEREST

The authors have no conflict of interest to report.

Footnotes

ACKNOWLEDGMENTS

This work was supported by the Grants (grant numbers: 81801260, 81771372, 81571232, 91949118) from the National Natural Science Foundation of China, the Project (grant number: 2016YFC1306504) from Ministry of Science and technology of China, and Shanghai Municipal Science and Technology Major Project (grant number: 2018SHZDZX01) and ZJLab.

The supplementary material is available in the electronic version of this article: .

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Cognitive Function and Quality of Life in Parkinson’s Disease: A Cross-Sectional Study

Abstract

Background:

Objective:

Methods:

Results:

Conclusions:

Keywords

INTRODUCTION

METHODS

Subjects

Clinical and neuropsychological assessments

Statistics

RESULTS

Clinical characteristics and QoL in all PD patients

Cognitive function and QoL in all PD patients

Cognitive domains and QoL in PD-NC, PD-MCI, and PDD patients

DISCUSSION

Conclusion

CONFLICT OF INTEREST

Footnotes

ACKNOWLEDGMENTS

References