Influence of cognitive dysfunction on spatiotemporal gait parameters in patients with diabetic polyneuropathy

Mohamed S El-Tamawy; Moshera H Darwish; Shereen S Mohamed; Montaser Hegazy; Mye A Basheer

doi:10.4103/1110-1083.202387

ORIGINAL ARTICLE

Year : 2016 | Volume : 53 | Issue : 4 | Page : 253-257

Influence of cognitive dysfunction on spatiotemporal gait parameters in patients with diabetic polyneuropathy

Mohamed S El-Tamawy MD ¹, Moshera H Darwish², Shereen S Mohamed², Montaser Hegazy¹, Mye A Basheer³
¹ Department of Neurology, Faculty of Medicine, Cairo University, Cairo, Egypt
² Department of Neuromuscular Disorder, Faculty for Physical Therapy, Cairo University, Cairo, Egypt
³ Department of Clinical Neurophysiology Unit, Faculty of Medicine, Cairo University, Cairo, Egypt

Date of Submission	15-Mar-2016
Date of Acceptance	01-May-2016
Date of Web Publication	17-Mar-2017

Correspondence Address:
Mohamed S El-Tamawy
Department of Neurology, Faculty of Medicine, Cairo University, 11562
Egypt

Source of Support: None, Conflict of Interest: None

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DOI: 10.4103/1110-1083.202387

Abstract

Background
An accurate rehabilitation program of diabetic polyneuropathy (DPN) depends on a precise assessment of cognition and determination of its relation to gait using different objective and valid methods.
Objective
Our aim was to assess cognitive function and analyze the influence of cognitive dysfunction on the spatiotemporal gait parameters under three different gait conditions (walking without a cognitive task, walking with verbal fluency, and walking with an arithmetic task) in DPN patients.
Patients and methods
Twenty patients with type II diabetes mellitus with moderate polyneuropathy (PN) (group 1) and 20 matched patients with type II diabetes mellitus without PN (group 2) represented the sample of this study. Different cognitive domains of cognition were assessed using a computer-based RehaCom procedure. Spatiotemporal gait parameters were assessed using a 2D video-based motion analysis under the three different gait conditions.
Results
The results showed a significant decrease in all cognitive domains in the DPN patients (group 1) (P<0.05). All spatiotemporal gait parameters were significantly affected in the DPN (group 1), especially during dual-task performance (P<0.05).
Conclusion
There is an association between cognitive dysfunction and PN complications in diabetic patients. Spatiotemporal gait parameters are affected more in DPN patients, especially under dual-task conditions, than in diabetic patients without PN.

Keywords: cognition, diabetic polyneuropathy, dual-task performance, reaction behavior, spatiotemporal gait parameters

How to cite this article:
El-Tamawy MS, Darwish MH, Mohamed SS, Hegazy M, Basheer MA. Influence of cognitive dysfunction on spatiotemporal gait parameters in patients with diabetic polyneuropathy. Egypt J Neurol Psychiatry Neurosurg 2016;53:253-7

How to cite this URL:
El-Tamawy MS, Darwish MH, Mohamed SS, Hegazy M, Basheer MA. Influence of cognitive dysfunction on spatiotemporal gait parameters in patients with diabetic polyneuropathy. Egypt J Neurol Psychiatry Neurosurg [serial online] 2016 [cited 2023 Jun 6];53:253-7. Available from: http://www.ejnpn.eg.net/text.asp?2016/53/4/253/202387

Introduction

Diabetes mellitus (DM) is a systemic disease that can damage any organ in the body. It occurs because of the decreased production of insulin (type I DM) or decreased sensitivity of body tissues to insulin (type II DM) [1],[2]. It is an important cause of peripheral neuropathy, accounting for almost half of all cases [3]. Diabetic polyneuropathy (DPN) is the presence of symptoms and/or signs of peripheral nerve dysfunction in diabetic patients. It is progressive and irreversible. It begins as a generalized and asymptomatic symmetrical dysfunction of peripheral nerves. Nerve damage starts by sensory loss in a stocking and glove distribution. It is followed by loss of motor function. It has a distal to proximal pattern involvement [4]. The prevalence of DPN is directly related to diabetes duration, the patient’s age, and metabolic control. Approximately 20% of diabetic patients develop clinically significant neuropathy within 5 years of diabetes onset. This proportion can increase to 50% after 10 or 15 years [5].

Cognitive decline is a common complication in DM. It is called the fourth diabetic microvascular disease [6]. Microvascular changes that arise outside the brain in DM are correlated with microvascular changes in the brain. Diabetic patients perform significantly worse on reaction times, attention, memory, and psychomotor abilities [7]. Alzheimer’s disease is called ‘type III diabetes’ because of the presence of microvascular infarcts in the brain [8]. These infarcts occur because of the toxic effect of hyperglycemia/hyperinsulinemia. It is responsible for brain atrophy and cognitive dysfunction [9]. The brain of dementia patients with diabetes had more microvascular infarcts compared with the brain of dementia patients without diabetes [10].

Diabetic peripheral neuropathy-related foot-sole somatosensory impairment leads to diminished walking speed, increased movement variability, and spending more time in double support. It is a disease of both peripheral and central nervous systems. Less regional gray matter (GM) volume that occurs in diabetes is associated with slower walking speed and walking disturbances [11].

Aim of this work

The aim of the present study was to assess the effect of cognitive dysfunction on the spatiotemporal gait parameters under the three different gait conditions in DPN patients and to provide declaration about the presence of cognitive dysfunction in patients with DPN.

Patients and methods

Forty diabetic patients were divided into two groups: 20 type II diabetic patients with moderate polyneuropathy (PN) (study group, group 1) [11 (55% men) and nine (45%) women] and 20 matched patients in (age, sex, and education) with type II DM without PN (control group, group 2) [13 (65%) men and seven (35%) women]. The patients were recruited from the diabetic clinics and Neurology Department in Kasr El-Aini Hospital, Cairo University, and from the Internal Medicine Hospital.

We included patients ranging in age from 40 to 60 years, BMI ranging from 20 to 30 kg/m², postprandial blood sugar less than 200 mg/dl, and duration of diabetic illness of 5 years for patients with PN and less than or equal to 2 years for patients without PN. All the patients in the DPN group had moderate severity (grade 2) according to Toxicity Grading Scales [12] and the Dyck classification scale [13]. The muscle power of the lower limbs was more than grade 2 and less than grade 4 in group 1 according to the neuropathy impairment score [14]. All the patients were able to walk independently with or without walking aids. Patients with severe visual, verbal, or acoustic impairments, under insulin medication, musculoskeletal disorders or ulcers, and amputation in the lower extremity were excluded.

The patients signed an informed consent form, and approval of the study protocol from the medical ethical committee of the Faculty of Physical Therapy, Cairo University, was obtained.

All patients were subjected to a full clinical assessment including history, and a full general and neurological examination. A nerve conduction study was performed for each patient. Different cognitive domains (attention/concentration, figural memory, and reaction behavior) were assessed for each patient using the RehaCom procedure [15]. Spatiotemporal gait parameters (velocity, stride length, and stride duration) were assessed using 2D video-based motion analysis [16]. It was measured by recording a film while the patient was walking and the films were analyzed by Auto-Cad program. Each patient was asked to walk at a self-selected speed along a 10 m walkway. The patient was instructed to start walking 1 m before the walkway and 1 m after the walkway to avoid acceleration or deceleration. Gait assessment was performed for each patient under three different gait conditions: (a) walking without a cognitive task, (b) walking while performing a verbal fluency task, and (c) walking while performing an arithmetic task. Five-minute rest periods were provided between each walk stage.

Statistical analysis

The collected data were summarized using descriptive statistics: mean and SD for quantitative variables. An unpaired t-test was used to compare between two independent means. To compare between three or more independent means, one-way analysis of variance was used. The least significant differences test was used to analyze the specific sample pairs ‘in three or more groups’ to appear the significant results. A P-value was used to indicate the level of significance (P>0.05 was considered significant and P<0.01 was considered highly significant).

Results

The patients and controls were age and sex matched, with no significant demographic differences between them. There were no significant differences in BMI and postprandial blood sugar between the two groups.

There was a significant difference in all cognitive domains in group 1 compared with group 2. Analysis of attention/concentration domains in group 1 showed a significant delay in the median reaction time (P=0.0026). In figural memory domains analysis, a significant decrease was found in the acquisition and solution time in group 1 (P=0.0001). In reaction behavior test domains analysis, a significant decrease in the percentage of correct reactions and a delay in the median reaction time in group 1 (P=0.0001) were found ([Table 1]).

Table 1 Mean values of the different cognitive domains for groups 1 and 2 in RehaCom cognition testing

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Results showed a significant effect in all spatiotemporal gait parameters in group 1 compared with group 2 under the three different gait conditions (P=0.0001) ([Table 2]). There was a significant decrease in velocity and stride length and an increase in stride duration in group 1 while walking with a verbal fluency task and walking with an arithmetic task than walking without a cognitive task (P=0.0001). No significant difference was found between walking with a verbal fluency task and walking with an arithmetic task (P>0.05) ([Table 3]).

Table 2 Mean values of the different variables of gait analysis between groups 1 and 2

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Table 3 Mean values of the different variables of gait analysis under the three gait conditions in groups 1 and 2

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Discussion

This study highlighted the presence of cognitive dysfunction in DPN and it affects the spatiotemporal gait parameters while counting backward and while reciting names during gait.

The postprandial blood sugar value for all the patients was less than 200 mg/dl taking into consideration the stricter glycemic control. Hyperglycemia has a negative effect on cognition independent of the presence of cerebrovascular disease or neuropathy [10].

The results showed a significant difference in all cognitive domains of RehaCom tests in group 1. This may be attributed to the extended regional brain atrophy of the frontal, cingulate cortex, prefrontal lobe, hippocampus, and limbic cortices in DPN. These areas are functionally related to attention, decision making, and memory [17]. Hyperglycemia damages the endothelium of brain microvessels, resulting in disruption of the blood–brain barrier and infarction of brain areas [18]. Silent brain infarction is associated with the decline of cognitive function in the diabetic patients [19]. Reduction of cognitive function in group 1 can be explained from the physiological point of view according to Rönnemaa et al. [20], who concluded that cerebral biochemical changes that occur in DPN cause alterations in glucose metabolism and an increase in both glucose and glutamate levels in the brain. This leads to neuronal damage. Impaired attention control may also be because of disruption within networks responsible for voluntary attention processes and the presence of leukoaraiosis with demyelination and increased water content or gliosis [21].

Insulin resistance is also linked to cognitive decline in DM because insulin is an important neurotrophic factor in the brain [22]. It leads to the formation of senile plaques and neurofibrillary tangles because of accumulation of amyloid-β-peptide and tau protein [10]. These two features are the pathological hallmarks of Alzheimer’s disease [19]. Lack of processing speed in DPN may because of a decrease in the level of neurotransmitters in the brain of diabetic patients including (acetylcholine production, serotonin turnover, and dopamine activity) [23]. Changes in brain metabolites in the diabetic brain such as myoinositol and N-acetylaspartate also lead to neuronal impairment and lack of cognitive function by higher osmotic pressure [24].

Our results are in contrast with those of Ba-Tin et al. [10], who reported that diabetes with microvascular complications such as DPN has the same effect on cognition as diabetes without PN. The discrepancy may be attributed to differences in the assessment scales, differences in the inclusion criteria in terms of the duration and severity of diabetes, severity scores of DPN, and the apparent age difference between the groups.

The results showed significant differences in all spatiotemporal gait parameters in group 1 under the different three gait conditions. This may be because DPN is a disease of both peripheral and central nervous systems. Central damage occurs because of microcirculation changes associated with poor glycemic control. A significant decrease in the GM volume of the cerebellum, dorsolateral prefrontal cortex, and basal ganglia was found in DPN. These structural changes are associated with slower walking speed and functional abnormalities [11],[25]. A 5.4% reduction was detected in the GM volume in patients with established DPN compared with healthy control participants [26].

In the present study, no statistical difference was observed between walking with a verbal fluency task and walking with an arithmetic task in group 1. However, walking with a verbal fluency task and walking with an arithmetic task affected the spatiotemporal gait parameters more than normal walking without a cognitive task in group 1. This may be because a verbal fluency task depends on semantic memory, which is stored in the medial temporal lobes and hippocampal areas, whereas both the arithmetic task and gait rely on working memory, which involves the prefrontal cortex. These areas show decreased volumes in DPN [11],[27]. In the current study, there is ample evidence that gait uses higher cognitive processing and that the attentional cognitive dual task can further affect gait in adults with DPN.

Our results are in contrast to those of Armand et al. [28], who did not find any differences in the gait parameters between diabetic patients with and without PN. The discrepancy may be attributed to the presence of uncorrected visual impairment and the use of different methods that limited the kinematic measurement as a tar surface where patients walked on it.

Conclusion

The results of the present study showed an association between cognitive dysfunction and PN complications in diabetic patients. Spatiotemporal gait parameters are more affected in DPN patients, especially during dual-task conditions, than in diabetic patients without PN. There was a significant negative influence of cognitive dysfunction on the different spatiotemporal gait parameters in DPN. Attention/concentration, figural memory, and reaction behavior are the main cognitive domains affected in DPN patients.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

References

1.	Vaz MM, Costa GC, Reisx JG, Junior WM, Albuquerque de Paula FJ, Abreu DC. Postural control and functional strength in patients with type 2 diabetes mellitus with and without peripheral neuropathy. Arch Phys Med Rehabil 2013; 94:2465–2470.
2.	Vijan S. Type 2 diabetes. Ann Intern Med 2010; 152:15–31.
3.	Davies M, Brophy S, Williams R, Taylor A. The prevalence, severity, and impact of painful diabetic peripheral neuropathy in type 2 diabetes. Diabetes Care 2006; 29:1518–1522.
4.	Dyck PJ, Albers JW, Andersen H, Arezzo JC, Biessels G, Bril V. Diabetic polyneuropathies: update on research definition, diagnostic criteria and estimation of severity. Diabetes Metab Res Rev 2011; 3:189–193.
5.	Rathur HM, Boulton AJM. Recent advances in the diagnosis and management of diabetic neuropathy. J Bone Joint Surg 2005; 87:1605–1610.
6.	Kawamura T, Umemura T. Is cognitive impairment the fourth diabetic microvascular complication? J Diabetes Investig 2011; 2:351–353.
7.	Ferguson SC, Blane A, Perros P. Cognitive ability and brain structure in type 1 diabetes: relation to microangiopathy and preceding severe hypoglycemia. Diabetes 2003; 52:149–156.
8.	Kawamura T, Umemura T, Hotta N. Cognitive impairment in diabetic patients: can diabetic control prevent cognitive decline? J Diabetes Investig 2012; 3:413–423.
9.	Kodl CT, Seaquist ER. Cognitive dysfunction and diabetes mellitus. Endocr Rev 2008; 29:494–511.
10.	Ba-Tin L, Strike P, Tabet N. Diabetic peripheral microvascular complications: relationship to cognitive function. Cardiovasc Psychiatry Neurol 2011; 2011:7.
11.	Manor B, Newton E, Abduljalil A, Novak V. The relationship between brain volume and walking outcomes in older adults with and without diabetic peripheral neuropathy. Diabetes Care 2012; 35:1907–1912.
12.	Almadrones L, McGuire DB, Walczak JR, Florio CM, Tian C. Psychometric evaluation of two scales assessing functional status and peripheral neuropathy associated with chemotherapy for ovarian cancer: A gynecologic oncology group study. Oncology Nursing Forum 2004; 31:615–623. doi:10.1188/04.ONF.615-623.
13.	Dyck PJ. Severity and staging of diabetic polyneuropathy. In: Gries FA, Cameron NE, Low PA, Ziegler D, editors. Textbook of diabetic neuropathy. Stuttgart, Germany: Thieme; 2003: 170–175.
14.	Singleton R, Bixby B, Russell JW, Feldman EL, Peltier A, Goldstein J et al. The Utah Early Neuropathy Scale: a sensitive clinical scale for early sensory predominant neuropathy. Diabetes Res Clin Pract 2008; 13:218–227.
15.	Mattioli F, Stampatori C, Zanotti D, Parinello G, Capra R. Efficacy and specificity of intensive cognitive rehabilitation of attention and executive functions in multiple sclerosis. J Neurol Sci 2010; 288:101–105.
16.	Sih BL, Hubbard M, Williams KR. Correcting out of plane errors in two dimensional imaging using non image-related information. J Biomech 2001; 34:257–260.
17.	Ryan JP, Fine DF, Rosano C. Type 2 diabetes and cognitive impairment contributions from neuroimaging. J Geriatr Psychiatry Neurol 2014; 27:47–55.
18.	Farrall AJ, Wardlaw JM. Blood-brain barrier: ageing and microvascular disease-systematic review and meta-analysis. Neurobiol Aging 2009; 30:337–352.
19.	Roriz-Filho JS, Sá-Roriz TM, Rosset I, Camozzato AL, Santos AC, Chaves MLF et al. (Pre)diabetes, brain aging, and cognition. Biochim Biophys Acta 2009; 1792:432–443.
20.	Rönnemaa E, Zethelius B, Sundelöf J, Sundström J, Degerman-Gunnarsson M, Lannfelt L et al. Glucose metabolism and the risk of Alzheimer’s disease and dementia: a population-based 12 year follow-up study in 71-year-old men. Diabetologia 2009; 52:1504–1510.
21.	Markus HS, Debette S. The clinical importance of white matter hyperintensities on brain magnetic resonance imaging: systematic review and meta-analysis. BMJ 2010; 341:3666.
22.	Lyoo IK, Yoon SJ, Musen G. Altered prefrontal glutamate-glutamine-γ-aminobutyric acid levels and relation to low cognitive performance and depressive symptoms in type 1 diabetes mellitus. Arch Gen Psychiatry 2009; 66:878–887.
23.	Beauquis J, Roig P, Homo-Delarche F, de Nicola A, Saravia F. Reduced hippocampal neurogenesis and number of hilar neurones in streptozotocin-induced diabetic mice: reversion by antidepressant treatment. N Engl J Med 2006; 23:1539–1546.
24.	Heikkilä O, Lundbom N, Timonen M, Groop PH, Heikkinen S, Mäkimattila S. Hyperglycaemia is associated with changes in the regional concentrations of glucose and myo-inositol within the brain. Diabetologia 2009; 52:534–540.
25.	Selvarajah D, Wilkinson ID, Maxwell M, Davies J, Sankar A, Boland E et al. Magnetic resonance neuroimaging study of brain structural differences in diabetic peripheral neuropathy. Diabetes Care 2014; 37:1681–1688.
26.	Musen G, Lyoo IK, Sparks CR, Weinger K, Hwang J, Ryan CM et al. Effects of type 1 diabetes on gray matter density as measured by voxel-based morphometry. Diabetes 2006; 55:326–333.
27.	Beauchet O, Dubost V, Aminian K, Gonthier R, Kressig RW. Dual-task-related gait changes in the elderly: does the type of cognitive task matter? J Mot Behav 2005; 37:259–264.
28.	Armand S, Allet L, de Bie RA, Monnin D, de Bruin ED. The gait and balance of patients with diabetes can be improved: a randomized controlled trial. Diabetologia 2010; 53:458–466.

Tables

[Table 1], [Table 2], [Table 3]

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