Clinical Markers May Identify Patients at Risk for Early Parkinson’s Disease Dementia: A Prospective Study

Abstract

Background:

The study aims at identifying features predictive of early onset of dementia in Parkinson’s disease (PD).

Methods:

103 non-demented PD patients were evaluated on various scales at baseline and 89 patients at 3-year follow-up.

Results:

By the end of the study 43.8% of patients developed dementia. The development of dementia was linked to the baseline Mini Mental State Examination score (Pearson coefficient r = .404, p = 0.013), the presence of autonomic dysfunctions (r = −.621, p < 0.001) and insomnia (r = −.526, p = 0.001). A binary logistic regression analysis showed that the development of dementia was correlated strongly with the presence of autonomic dysfunctions (95% CI 2.60 to 52.83, p < 0.001), and insomnia (95% CI 0.60 to 0.95, p = 0.017).

Conclusion:

Patients with signs of autonomic dysfunction and insomnia are at higher risk for developing dementia and deserve closer monitoring of cognitive symptoms.

Keywords

Parkinson disease dementia autonomic dysfunction sleep disturbances

Significance Statement

Insomnia and particularly the presence of autonomic dysfunctions early after onset may indicate a higher risk for dementia in Parkinson disease patients

Higher doses of levodopa were also linked with a more rapid onset of dementia in PD patients.

Background

Neuropsychiatric disturbances accompany Parkinson disease (PD) leading to a decline in the quality of life. PD patients frequently exhibit cognitive deficits as well, often evolving into dementia, causing increased caregiver burden, increased mortality, and often institutionalization. The prevalence of dementia in PD ranges between 24% and 50%, and accounts for about 3% to 4% of all cases of dementia in the general population.¹ An incidence rate of approximately 100 per 1,000 patient-years has been estimated, which is more than 5 times that of age-matched controls.² Searching for the factors predictive of PD dementia is not only important in identifying high-risk patients for appropriate counseling and planning future care, but also in recognizing early signs of cognitive impairment for initiating therapeutic interventions. Advanced age is the most commonly established risk factor for dementia. Non-motor features such as REM sleep behavior disorder (RBD), baseline cognitive impairment, olfactory disturbances, and autonomic dysfunction have been identified as possible dementia predictors.^3

-6 However, in many studies the tests were designed for clinical trial conditions, tests which are more difficult to apply as screening methods in real-life conditions and add to the costs of health care.

In our study, we assessed clinically, under conditions applicable in an outpatient care setting, a number of potential clinical risk factors for dementia in a 3-year prospective cohort study.

Methods

The present prospective study was conducted in accordance with the Declaration of Helsinki (1964) after approval of the Ethical Committee of the hospital.

Patient Selection

Patients were recruited from the Neurology ward and outpatient clinic of our hospital. The period of enrollment extended from November 2012 to June 2014. A total of 130 patients were asked to undergo the neurological and psychological evaluation described below after signing a written informed consent which allowed them to withdraw at any time.

Exclusion criteria were:

– Secondary parkinsonisms or Parkinson-plus syndromes

– Dementia diagnosed at screening

– Significant comorbidities (e.g., cancer, stroke with motor impairment or aphasia) which could impede the patient to complete the follow-up period or to complete the required tests

Parkinson disease was diagnosed in accordance with the UK Brain Bank criteria.⁷ Dementia was diagnosed by a certified psychiatrist according to the DSM-IV criteria taking into account also the particularities of Parkinson disease dementia (impairment of at least 2 of the following domains: attention, executive function, visuo-constructive ability, memory).⁸

On the basis of the presence of dementia at enrollment 18 patients were excluded, and 9 denied enrollment for various reasons. A number of 14 patients were lost to follow-up. Therefore we analyzed the data from 89 patients who completed the 3-year study period.

Patient Evaluation

Patients underwent a complete neurological evaluation performed by a certified neurologist and a psychological evaluation at enrollment and after 3 years (36 ± 3 months) performed by a psychologist certified in clinical psychology. Meanwhile they had regular follow-up visits, scheduled every 6 ± 2 months and as needed by the patient, dose adjustments of antiparkinsonian medication, and psychological and/or psychiatric evaluation as needed. Patients diagnosed at any point during the study with dementia (according to the DSM-IV criteria) were considered to have converted to dementia. At the end of the study, patients with MMSE below 20 were included into the group who converted to dementia, while those with impairments in attention, executive functions, visuo-constructive abilities, or memory were referred to a psychiatrist for evaluation of a possible dementia based on the DSM IV criteria. Figure 1. describes the patient selection and evaluation.

Figure 1.

Flowchart describing the patient selection and evaluation.

Information on demographics, disease duration, and antiparkinsonian medication were recorded. PD evaluation included:

Motor variables:

1.1 Unified Parkinson’s Disease Rating Scale (UPDRS)—total and subscales I-IV.⁹ This scale was developed to assess severity and progression of Parkinson disease. The first 4 segments are made up of 42 items, looking at:

(I) mentation, behavior and mood,

(II) activities of daily living,

(III) motor function, and

(IV) complications of therapy in the prior week

Parts I-III are scored on a 0-4 rating scale, while part IV is scored with yes and no ratings. The total scores were used for analysis. No further scales for assessing functional decline in activities of daily living were used during the study

1.2 Hoehn and Yahr staging.¹⁰

1.3 Records of falls and freezing in the history.

2. Autonomic variables—assessed through symptoms and signs of autonomic dysfunction (part III of the Unified Multiple System Atrophy Rating Scale)—at baseline.¹¹

The scale assesses variations of systolic (1) and diastolic (2) blood pressure and heart rate (3) between supine and standing position after 2 minutes, and records orthostatic symptoms (4), such as lightheadedness, dizziness, blurred vision, nausea, palpitations, tremulousness, or headache occurring after 2 minutes in the supine position. Drops of ≥ 20 mm Hg in systolic blood pressure, ≥ 10 mm Hg in diastolic blood pressure, or increases of ≥ 30 beats/minute in heart rate were considered to indicate autonomic dysfunction¹² As such, patients were scored between 0 and 4.

3. Sleep disorders were assessed by determining the Insomnia Severity Index (ISI).¹³ The ISI has 7 questions assessing the difficulties in falling, staying asleep, or problems regarding early wakefulness, the overall satisfaction of the patient with his current sleep pattern and its interference with his quality of life as well as the distress of the patient with regard to his sleep pattern. The patient is asked to rate these questions in terms of intensity from absent (0) to very severe (4). Total score categories were considered as follows:

0-7 = No clinically significant insomnia

8-14 = Subthreshold insomnia

15-21 = Clinical insomnia (moderate severity)

22-28 = Clinical insomnia (severe)

4. Cognition:

The Mini Mental State Examination (MMSE) score was determined, using a cut point of 20 to differentiate between normal cognition or mild cognitive impairment vs. moderate/severe cognitive impairment.¹⁴ Further, patients were asked to complete the clock drawing test. Patients with a MMSE score ≤ 20, with executive dysfunctions outlined by the clock-drawing test, with visuo-constructive disabilities at the pentagon copying item of the MMSE, or patients with other symptoms suggestive of dementia were referred for psychiatric evaluation, which used the DSM-IV criteria for diagnosing dementia.

5. Neuropsychiatric evaluation

The 10-item version of the Neuropsychiatric Inventory (NPI) was used to evaluate neuropsychiatric symptoms.¹⁵ Screening questions for each of the 10 neuropsychiatric symptoms were posed first, and if a positive response was obtained, the symptom was further explored. Ratings from 1 through 4 were obtained for frequency and from 1 through 3 for severity of each symptom. A composite score for each symptom was calculated as the product of the frequency and severity. The total sum was used for analysis.

6. Mood.

The Hamilton Rating Scale for Depression (HAM-D17), a 17 item questionnaire measuring psychological and physiological symptoms of depression¹⁶ was administered to each patient at baseline, at 3-year follow-up visit, and between these 2 visits as needed. Severity ranges were considered as follows¹⁷: no depression (0-7); mild depression (8-16); moderate depression (17-23); and severe depression (≥24).

Statistical Analysis

Statistical analysis was performed using IBM-SPSS version 19.0, trademark of International Business Machines Corp, registered in many jurisdictions worldwide. Analyses consisted of description of the various scores, and calculation of means and proportions. Differences between groups were tested for statistical significance with the Independent samples T-test. Factors significantly associated with dementia were identified with a partial correlation analysis controlling for age and disease duration, after which they were included into a binary logistic regression analysis. 95% confidence intervals and odds-ratios were determined. Statistical significance was set at p < 0.05.

Results

The gender distribution was 59.6% male and 40.4% female patients.

A number of 39 patients (43.8%) were diagnosed with dementia according to the DSM IV criteria up to the 3-year follow-up.

The age of the patients lost to follow-up ranged from 59 through 77 years, with a mean age of 69 years (± 5.85). A number of 4 patients developed strokes with either aphasia or motor impairment, making it difficult for them to complete the follow-up visits and evaluations, 4 patients moved to other cities, one had a cranio-cerebral traumatism and was left impaired, choosing to remain under the care of the general physician, and 5 patients died during the study due to various comorbidities. Patients who developed dementia by the end of the study were aged between 57 and 81 years, with a mean age of 69.56 years (± 5.65), significantly higher than the age of the patients in the non-converter group (aged between 56 and 74 years, mean age 63.46 ± 4.83).

The number of neurological visits throughout the study ranged from 6 through 12 in both the converter and non-converter group, with a mean of 8.21 visits (± 1.45) in the group who developed dementia and 8.34 visits (± 1.8) in the group with preserved cognitive function at the end of the study.

More than half of the patients (53.9%) had complaints regarding their sleep pattern, while significant depressive clinical traits affected only 36% of patients at baseline. 26 patients (28%) reported falls and freezing in their history.

After 3 years 57 patients (65%) had clinically significant insomnia, while moderate-to-severe depression affected 47 patients (51,6%).

Comparatively, the prescribed dose of Levodopa and various scores of patients who did develop dementia at 3-year follow-up versus patients with preserved cognitive functions is provided in Table 1 both at baseline and at follow-up. All the analyzed parameters were significantly different between the 2 subgroups of patients, with p < 0.001 according to the Independent Samples t-test as well as to the non-parametric Kruskal-Wallis test.

Table 1.

Comparative Description at Baseline and Follow-Up of Patients With PD Who Did Develop Dementia Versus Those Who Had Preserved Cognitive Function at the End of the Study.^a

Parameter		Group 1	Group 2
Dose of Levodopa in mg (mean ± SD)	at baseline	871.79 ± 189.10	573.00 ± 129.83
Dose of Levodopa in mg (mean ± SD)	at follow-up	1241 ± 209.6	685.5 ± 173.8
UPDRS score (mean ± SD)	at baseline	75.77 ± 10.33	48.18 ± 12.97
UPDRS score (mean ± SD)	at follow-up	124 ± 15.69	62.80 ± 17.74
UMSAR score (mean ± SD)	at baseline	3.41 ± 0.78	1.62 ± 0.75
ISI score (mean ± SD)	at baseline	17.67 ± 3.59	11.24 ± 399
	at follow-up	20.56 ± 3.74	12.90 ± 4.73
NPI score (mean ± SD)	at baseline	39.13 ± 9.27	15.38 ± 7.65
NPI score (mean ± SD)	at follow-up	63.45 ± 8.36	21.22 ± 9.43
HAMD score (mean ± SD)	at baseline	13.10 ± 3.12	8.46 ± 4.05
HAMD score (mean ± SD)	at follow-up	16.38 ± 3.73	9.92 ± 4.54
MMSE score (mean ± SD)	at baseline	21.51 ± 1.18	26.39 ± 2.24
MMSE score (mean ± SD)	at follow-up	15.67 ± 1.67	24.98 ± 2.56

^a Group 1 = patients who were diagnosed with dementia after 3 years of follow-up. Group 2 = PD patients with preserved cognitive function after 3 years.

As expected, PD patients who developed dementia after 3 years of follow-up were older, with more severe Parkinson disease (as assessed by the UPDRS score), had a longer duration of the disease, although the diagnosis does not coincide with the disease onset, and had more severe neuropsychiatric disturbances, depressive traits, and lower MMSE scores at baseline. However, age and duration of disease cannot be controlled and are not amenable to modification by treatment. As such, it would be useful to know if any particular symptoms or signs were linked to a more rapid onset of dementia in an attempt to preserve for as long as possible the cognitive functions in these patients.

In order to see which clinical characteristics are correlated with a more rapid evolution toward cognitive decline, we ran a partial correlation analysis setting as dependent variable the MMSE score at the end of the study, and the baseline MMSE, the dose of Levodopa at baseline, the baseline UPDRS score, the presence of autonomic dysfunctions at baseline (as indicated by 1 or more symptoms of autonomic dysfunction scored on the UMSAR scale), the Insomnia Severity Index (ISI) at baseline, the Hamilton Depression Rating Scale (HAM-D17) score at baseline, and the Neuropsychiatric Inventory (NPI) score at baseline as independent variables. Since with age and duration of disease, the likelihood of developing dementia increases, we controlled for these 2 factors. The results are shown in Table 2 for patients who developed dementia, and in Table 3 for patients who had preserved cognitive functions at the end of the study.

Table 2.

Correlation Analysis of the MMSE at Follow-Up and the Baseline MMSE and Various Scores of the Patients at Baseline for the Group of Patients Who Developed Dementia by the End of the Study.^a

Control variables			MM SE-1	Dose	UP DRS	UM SAR	ISI	NPI	HAM-D17	Duration	Age
-none	MMSE-2	Correlation	.471	-.398	-.304	-.673	-.622	-.267	-.057	-.343	-.594
		Sig (2-tailed)	.002	.012	.060	.000	.000	.101	.731	.033	.000
		df	37	37	37	37	37	37	37	37	37
	Dura-tion	Correlation	-.204	.658	.522	.326	.290	.431	.280	1.000	.734
		Sig (2-tailed)	.212	.000	.001	.043	.073	.006	.084	.	.000
		df	37	37	37	37	37	37	37	0	37
	Age	Correlation	-.275	.679	.465	.385	.403	.507	.317	.734	1.000
		Sig (2-tailed)	.090	.000	.003	.015	.011	.001	.049	.000	.
		df	37	37	37	37	37	37	37	37	0
Dura-tion & Age	At MMSE-2	Correlation	.404	-.049	-.097	-.621	-.526	.034	.163
		Sig (2-tailed)	.013	.773	.570	.000	.001	.843	.336
		df	35	35	35	35	35	35	35

^a MMSE-1 = baseline MMSE; MMSE-2 = MMSE at the end of the study. Dose = dose of levodopa at baseline; Duration = duration of the disease at baseline.

Table 3.

Correlation Analysis of the MMSE at Follow-Up and the Baseline MMSE and Various Scores of the Patients at Baseline for the Group of Patients Who Did Not Develop Dementia by the End of the Study.^a

Control variables			MM SE-1	Dose	UP DRS	UM SAR	ISI	NPI	HAM-D17	Duration	Age
-none-^a	MMSE-2	Correlation	.924	-.542	-.440	-.574	-.408	-.299	-.287	-.437	-.579
		Sig (2-tailed)	.000	.000	.001	.000	.003	.035	.043	.002	.000
		df	48	48	48	48	48	48	48	48	48
	Dura-tion	Correlation	-.507	.600	.590	.477	.120	.365	-.120	1.000	.648
		Sig (2-tailed)	.000	.000	.000	.000	.408	.009	.406	.	.000
		df	48	48	48	48	48	48	48	0	48
	Age	Correlation	-.551	.495	.395	.464	.134	.421	.064	.648	1.000
		Sig (2-tailed)	.000	.000	.005	.001	.355	.002	.659	.000	.
		df	48	48	48	48	48	48	48	48	0
Dura-tion & Age	MMSE Follow-up	Correlation	-.353	-.353	-.268	-.413	-.407	-.062	-.338
		Sig (2-tailed)	.014	.014	.066	.004	.004	.678	.019
		df	46	46	46	46	46	46	46

^a MMSE-1 = baseline MMSE; MMSE-2 = MMSE at the end of the study. Dose = dose of levodopa at baseline; Duration = duration of the disease at baseline.

In patients who went on to developing dementia, the MMSE score at 3-year follow-up was significantly correlated with the basline MMSE (r = 0.404, p = 0.013), the Insomnia Severity index (Pearson coefficient—0.526, p = 0.001) and the presence of autonomic symptoms and signs (Pearson coefficient: −0.621, p < 0.001). Neither dose of Levodopa, UPDRS score at baseline, nor Hamilton Depression Rating Scale score were significantly related to the development of dementia in our patients.

In patients who did not develop dementia the MMSE score at 3-year follow-up was influenced most significantly by the UMSAR score (r = −0.413, p = 0.004) and the ISI at baseline (r = −0.407, p = 0.004), as well as by the baseline MMSE, and the dose of Levodopa (Pearson coefficient −0.353, p = 0.014). In this group of patients, depressive symptoms, as revealed by the HAM-D17 score, appeared to be also correlated with lower MMSE scores at follow-up (r = −0.338, p = 0.019).

Further, after assessing for multicollinearity, which didn’t appear to be a major issue (VIF’s < 4), we ran a binary logistic regression analysis setting the conversion to dementia (whether demented or not at the end of the study) as dependent variable, and age, duration of disease and Insomnia Severity Index score at baseline as covariates together with the presence of autonomic dysfunction divided into 2 categories: ≤ 2 and > 3 in the UMSAR score. The model explained 61% of the variance in conversion to Parkinson disease dementia (Nagelkerke R²) (Table 4) and correctly classified 86.5% of the cases (Table 5).

Table 4.

Age, Duration of Disease, ISI and UMSAR Scores Explain 61% of the Variance in Conversion to PD Dementia.

Model summary
Step	-2 Log likelihood	Cox & Snell R Square	Nagelkerke R Square
1	68.407^a	.461	.614

^a Estimation terminated at iteration number 5 because parameter estimates changed by less than .001.

Table 5.

Our Model Classifies Correctly Over 86% of the Cases Into Demented and Non-Demented PD Patients After the Follow-Up Period.

Classification table^a
Observed			Predicted
			PD-dementia		Percentage correct
			PD dementia present	Non-demented PD	Percentage correct
Step 1	PD-dementia	PD dementia present	32	7	82.1
	PD-dementia	non-demented PD	5	45	90.0
	Overall Percentage				86.5

^a The cut value is .500.

Patients with at least 3 points on the UMSAR scale (looking at systolic, diastolic blood pressure and heart rate variability in the standing position and recording autonomic symptoms after 2 minutes of standing) were 11 times more likely to develop dementia after a 3-year follow-up, 95% CI 2.6-52.8 (Table 6). Sleep disturbances, reflected in the Insomnia Severity Index at baseline, also increased the likelihood of developing dementia in a short period of time.

Table 6.

Influence of the Various Factors Analyzed on Conversion to Dementia in PD Patients.

Variables in the equation
		B	S.E.	Wald	df	Sig.	Exp(B)	95% C.I.for EXP(B)
		B	S.E.	Wald	df	Sig.	Exp(B)	Lower	Upper
Step 1^a	Duration of disease	-.052	.230	.051	1	.821	.949	.604	1.490
	Insomnia Severity Index at baseline	-.275	.115	5.700	1	.017	.760	.607	.952
	Autonomic dysfunction(1)	2.463	.768	10.294	1	.001	11.737	2.607	52.835
	Age	-.088	.106	.693	1	.405	.916	.744	1.127
	Constant	8.936	6.709	1.774	1	.183	7600.769

^a Variable(s) entered on step 1: duration of disease, insomnia severity index at baseline, autonomic dysfunction, age.

Discussion

Of our 89 patients included in the study, 39 developed dementia in the 3 year follow-up period, at higher risk being those patients who presented signs of autonomic dysfunction and insomnia.

At the moment of inclusion in the study almost half of the patients complained about their sleep patterns, while depression affected 37% of patients at inclusion in the study. After 3 years, sleep was disturbed in more than two third of patients, and depression rates exceeded 50%. The data provided for the depression rates by other studies resemble our findings.^18,19

Focusing on the development of dementia, our study shows that a 3-year follow up was sufficient to show a significant decline in cognitive functions. It is true that the baseline MMSE was significantly lower in patients who were diagnosed with dementia after 3 years as compared with patients who were not demented after 36 months (21.39 vs. 26.38; p < 0.001). A simple MMSE test may have lacked specificity for evaluating cognition in Parkinson disease, since it focuses mainly on cortical functions, while Parkinson disease dementia is a subcortical type of dementia. It may well be that a part of these patients might have been diagnosed with dementia upon a more detailed testing. Moreover, patients who converted to dementia at follow-up were older and had a longer duration of the disease at baseline. However, even after controlling for these variables, the partial correlation analysis shows that the cognitive functions of patients diagnosed with dementia at follow-up were influenced by the UMSAR score and the Insomnia Severity Index at baseline.

Tools for a more detailed testing have been developed and are available, but in everyday practice these are time-consuming and more difficult to apply. Our study focused more on screening tools, trying to identify predictors of dementia in order to select those patients who should be evaluated in more detail and seen more often as opposed to patients who can be confidently discharged to their family practitioner and reevaluated at longer periods of time.

The UMSAR score reflects signs of autonomic dysfunction. Previous cross-sectional studies have found strong correlations between low cognitive status and orthostatic hypotension.²⁰ The cause for this strong relationship is unclear. It is possible that autonomic dysfunction is a marker of a more “diffuse” disease subtype, in which autonomic areas and cortical regions involved in dementia degenerate as well.²¹ For example, the strong association between constipation and PD, constipation being considered by some researchers even a symptom preceding PD motor dysfunction by 10-20 years, as well as the demonstration of abnormal α-synuclein deposition in the enteric nervous system, demonstrates the strong link between gut dysfunction, mediated by autonomic nervous fibers, and PD.²² However, an alternative mechanism may also be discussed. In the general population low diastolic blood pressure has been linked to brain atrophy, particularly when associated with reduced cerebral blood flow.²³ Although cerebrovascular autoregulation mechanisms prevent orthostatic changes from reducing cerebral blood flow, moderate changes in PD, which may associate multisystem and cardiovascular dysautonomia, might cause significant cerebral hypoperfusion. Hypoxia and hypotension have been shown in animal models and human studies to cause neuronal damage and increases in accumulation of beta-amyloid and other pathologic proteins.^24,25 Therefore, one may reasonably hypothesize that repeated episodes of hypotension in PD over the years can augment damage to cortical neurons already made vulnerable by the synucleopathy. A prospective observational study, showing that treatment of orthostatic hypotension improved cognition in dementia, supports this view.²⁶

Another factor associated with dementia was the presence of insomnia. The sleep rhythm is driven by a central circadian pacemaker located in the suprachiasmatic nucleus of the anterior hypothalamus.²⁷ Studies of sleep deprivation and sleep restriction in healthy subjects revealed the importance of sleep in memory function and mental health.²⁸ Experimentally induced sleep loss in healthy subjects is associated with impairments in a broad range of cognitive functions, and cognitive impairments have been identified in people with sleep disorders such as insomnia and sleep apnea. In fact, a meta-analysis showed that insomnia is associated with incident Alzheimer’s disease (AD), while sleep disordered breathing is linked to a higher incidence of AD, vascular and all-cause dementia.²⁹ Sleep appears to be necessary for both memory encoding and consolidation. Sleep deprivation also affects emotional memory, with preservation of mainly negative compared to positive and neutral memories.²⁷

Disruptions in the sleep–wake cycle and sleep complaints are commonly found in community-based studies of older people. Over 50% of adults aged over 65 have at least 1 chronic sleep-related problem.³⁰ Advancing age with the associated decline in the melatonin and cortisol rhythms which entrain day-night activity patterns contribute to the changes in circadian rhythms which have been demonstrated in elderly persons.³¹ However, the link between sleep disturbances and Parkinson disease is stronger. It has been estimated that a patient presenting typical Rapid Eye Movement sleep behavior disorder (REMBD) will have a 50% chance of developing a parkinsonian syndrome within 5 years.³²

We did not find a significant correlation between the Hamilton Depression Rating Scale score and MMSE score, neither in patients converted to dementia nor in patients who did not develop dementia, although in the latter group of patients the link was stronger. Depression did not correlate with cognitive variables although it was more often present and more severe in PD patients with cognitive impairment. It has been suggested that patients with no depression and no dementia have a normally functioning dopaminergic mesocortico-limbic system, while the opposite were true for PD patients with depression and/or cognitive impairment.²⁵ Supporting this hypothesis is the finding of a lower metabolic activity in the head of the caudate nucleus and in the inferior frontal cortex in the depressed PD patients as well as that of a significant inverse correlation between glucose metabolism in the inferior frontal cortex and depression scores.³³

An interesting finding is the link between dose of Levodopa and decline of the MMSE at 3 year follow up. The relationship between Levodopa treatment and cognitive functions is complex and subject to debate. While some researchers reported no compromise of cognitive performances in PD patients treated with Levodopa over 3 months, although verbal attention and memory did show some degree of deterioration³⁴ other authors pointed out that dopamine and dopaminergic medication may either improve or impair cognitive performance depending on the nature of the tasks and the basal level of dopamine in the cortico-striatal circuits.³⁵ Hence, the effect of Levodopa over cognition appears to be domain-specific. The MMSE test (used by us to assess cognition), however, measures only global cognition, while in PD cognitive decline is heterogeneous.

Levodopa, after crossing the blood-brain barrier, is decarboxylated to dopamine by aromatic amino acid decarboxylase, found in neurons and glia, and binds to the dopaminergic receptors. Un-sequestered dopamine is enzymatically degraded by monoamine oxidase B, a reaction during which hydrogen peroxide, a powerful oxidant, results as a by-product. In addition, dopamine can undergo auto-oxidation, resulting in highly reactive quinones, which bind to proteins and interfere with the normal function of the latter. Increased oxidative stress also causes mitochondrial dysfunction and DNA damage, adding to the levodopa-induced neurotoxicity.³⁶

The results presented provide further reasons for investigating adjunctive therapies to L-dopa for PD, such as antioxidants, as well as to delay treatment with Levodopa for as long as possible, although only mildly impaired PD patients may obtain symptom relief with anticholinergics or dopamine agonists.¹⁸ The cognitive outcome of patients treated with controlled release L-DOPA formulations, with device-assisted continuous intestinal L-DOPA infusion, or with deep brain stimulation deserves further investigation.

We are aware of the limitations of our study, namely:

– We did not record family history of psychiatric disturbances, or of personal history of head trauma due to lacking documentation regarding the exact diagnosis or trauma severity, respectively

– We did not record the use of non-parkinsonian medication, but this might have been changed frequently during the study

– We did not perform a detailed cognitive testing, neither at baseline nor at follow up, and relied only on the MMSE, clock drawing test, and psychiatric evaluation

– We assessed the presence of sleep disturbances only through the ISI, without further looking at the sleep architecture

– We observed a relatively small number of patients for a rather short period of time (36 months), which may explain the wide confidence intervals in the statistical analysis.

– We did not take into consideration the possible impairment of the visuospatial performance, assessed by the pentagon-copying item of the MMSE, by the motor dysfunction of Parkinson disease itself

– 14 patients, representing 13.6% of the initial group, were lost to follow-up, which may undermine the validity of our findings. Nonetheless, the baseline characteristics of these patients did not differing significantly from those of patients who completed the study and they were less than 20% of the whole group, which is why we still consider our results to be reliable.³⁷

In addition, given the small sample size and the high conversion rate to dementia, type I errors cannot be excluded. Being a preliminary study, we did not calculate the necessary sample size for a prespecified statistical power. However, we wished to remain in the frame of an evaluation applicable as part of a ususal outpatient visit.

Conclusions

In our opinion, our findings show that:

– Cognitive evaluation in initial and follow up assessment of Parkinson disease patients may select those at risk for developing dementia raising the possibility of targeting future neuroprotective agents at patients with this condition.

– Identifying and analyzing non-motor symptoms, especially symptoms of autonomic dysfunction and sleep disturbances, may identify patients at risk for PDD and enable correction of these factors as well as more frequent assessments to diagnose dementia at early stages. Whether addressing autonomic dysfunction early may delay the cognitive impairment is yet unsettled.

– Symptoms of autonomic dysfunction, such as variations in systolic or diastolic blood pressure, heart rate, or orthostatic symptoms, and sleep architecture could be included in a predictive score for PD dementia, as has been done with motor symptoms and energy expenditure in the development of a probability score for prodromal PD.³⁸

– The cognitive functions of patients treated with device-assisted treatment or beep brain stimulation deserves further investigation.

Footnotes

Abbreviations

Authors’ Note

The datasets used during the current study are available from the corresponding author on reasonable request. All patients gave written informed consent, and the ethical committee of the hospital approved the study. Since patients with dementia at screening were not included in the study we did not ask for a family member or legal guardian’s consent. Partial results after a preliminary analysis were presented at the European Academy of Neurology Congress held in 2016 in Copenhagen (p 22093, Eur J Neurol 2016, 23: 529).

Acknowledgments

The authors wish to thank the patients and their families for participating in this study.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Anamaria Jurcau

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