Diabetes mellitus refers to a group of common metabolic disorders that share the phenotype of hyperglycemia. Several distinct types of DM exist and are caused by a complex interaction of genetics and environmental factors. Factors contributing to hyperglycemia include reduced insulin secretion, decreased glucose utilization by the cells and increased glucose production. The metabolic dysregulation associated with DM causes secondary Patho physiological changes in multiple organ systems that impose tremendous burden on the health of the individual.1,2,3 Goals of treatment should aim to eliminate symptoms related to hyperglycemia, reduce or eliminate the long term microvascular and macrovascular complications and allow patient to achieve as normal a lifestyle as possible. The approach should be in terms of “Comprehensive Diabetic Care” to emphasize the fact that optimal diabetic therapy involves more than plasma glucose management.4.5 COGNITION It includes memory, language, orientation, judgment, conducting interpersonal relationships, performing actions (praxis) and problem solving. Cognitive disorders reflect disruption in one of the above domains and are frequently complicated by behavioral symptoms. It exemplifies the complex interface between neurology, medicine and psychiatry in the sense that neurological conditions often lead to cognitive disorders that in turn are associated with behavioral symptoms. Individuals with this condition may report problem remembering names, appointments or difficulty in solving complex problems. 5 Clinical evaluation: Modern cognitive tests originated through the work of Sir Francis Galton who coined the term "mental tests". One of the most widely used global cognitive assessment is Mini Mental State Evaluation (MMSE). It is a brief quantitative measure of cognitive status in adults that assesses all cognitive domains. It is quick and easy to administer. It is a 30 point questionnaire, a score below 25 suggests possible impairment and score below 20 indicates definite impairment. It can be used to screen cognitive impairment to follow the course of cognitive changes in an individual over time and to document an individual response to treatment.6 MMSE has a good specificity (94%) but poor sensitivity (64%).7 Evoked potentials: Evoked potential is an electrical response of the brain with specific characteristics to a given stimuli (sensory / motor) which occurs in a time locked fashion. It is beneficial in Psychological studies of memory, language and attention.8 Functional classification includes Brainstem Auditory Evoked Potential (BAEP), Mid Latency Auditory Evoked Potential (MLAEP), Long Latency Auditory Evoked Potential (LLAEP) and cognitive evoked potential. Cognitive evoked potential: Also known as P3, P300, Event Related Potential (ERP) or endogenous evoked potential appear at about 300 ms following task – related stimuli. P300 is considered to assess cognitive function because it is generated when subject attends and discriminates the stimuli that differ from one another in some dimension when presented unequally in a random fashion. It is a symmetrical wave maximum over midline, central and parietal regions. The latency varies between 250 and 600 ms depending on the parameters like stimulus and subject. Most commonly used stimulus is unexpected or infrequent stimuli randomly interspersed among frequent stimuli (oddball paradigm). Stimulus infrequency and attention to task relevance operate independently to produce different evoked potentials. The long latency components obtained include N1, P2, N2 and P3, out of which P3 is clinically more useful. 9 Review of other works Strachan MWJ and Deary IJ in their study proved that diabetic individuals performed poorly in at least one aspect of cognition. The psychometric tests which assessed attention, speed, lexical fluency, verbal memory showed that diabetics performed poorly as compared to controls. Psychomotor ability and frontal lobe functions were affected less consistently. The etiology of cognitive decrement in type 2 DM is likely to result from interaction between metabolic abnormalities, complications of diabetes.10 Ryan CM and Geckle MO in their study concluded that learning, memory and problem solving skills were unaffected by type 2 DM, similar to adults of same demographic background who did not have diabetes. Psychomotor slowing is associated with poor metabolic control. Mental slowing is related to chronic hyperglycemia and may be responsible for triggering cognitive impairment in diabetes.11 Mooradian AD, Perryman K, Fitten J, Kavonian GD and Morley JE in their study on cortical function in elderly Non Insulin Dependent Diabetes Mellitus (NIDDM) concluded that the P300 wave latencies were not elevated significantly. However, a trend towards longer latencies was evident at Fz and Cz recording sites. Acute hyperglycemia induced in healthy volunteers did not alter P300 component. Elderly type 2 DM patients have impairment in retrieving learned material with preservation of immediate recall and auditory attention.12 Pozzessere G, Valle E, Crignis SD, Cordischi VM, Fattapposta F, Rizzo PA et al., concluded that electrophysiological tests like P300 latency were significantly increased depicting that cognitive functions were affected in Insulin Dependent Diabetes Mellitus (IDDM). These tests highlight those changes that are not detectable by psychometric tests. Chronic hyperglycemia and frequent episodes of hypoglycemia might have deleterious effect on cognitive performance.13 Etgen T, Sander D, Bickel H, Sander K and Forstl H concluded that diabetes has a causal relationship in the development of mild cognitive impairment. There exists an age dependant relationship between blood pressure, elevated cholesterol levels and cognition. Hypercholesterolemia and hypertension in mid life serves as an independent risk factor for developing cognitive decline in future. Antidiabetic treatment benefits cognitive decline.14 Fontbonne A, Berr C, Ducimetiere P and Alperovitch A concluded that when compared to subjects with normal blood glucose, diabetic subjects had worsening of over 50% of the cognitive domains assessed using MMSE and other psychometric scales. Psychomotor speed, visual attention and memory were affected significantly. However, visual memory and facial recognition were stable over four years. The presence of small early cognitive defects may indicate higher probability of severe impairment in the future.15

The cognitive functions was evaluated using comprehensive psychometric and electrophysiological (P300 latencies) tests in diabetics and non diabetics in the age group of 40 - 59 years with same gender proportion. Selection of participants: The study comprised of 100 randomly selected subjects in the age group of 40 – 59 years. The case group comprised of 28 diabetic males and 22 diabetic females and control group included 30 non diabetic males and 20 non diabetics females in the same age group. The study protocol had the approval of scientific ethical committee of the Institute. Subjects received information about the study and subjects signed the informed written consent to participate in the study. Taking into consideration the predetermined inclusion and exclusion criteria, case and control groups were selected. On the day of cognitive assessment blood glucose levels were estimated to check their glycemic status. After selecting subjects, the following tests were done. 1. Electrophysiological test – Cognitive evoked potential 2. Psychometric tests- ● Mini Mental State Examination (MMSE) ● Clock Drawing Test (CDT) ● Four Word Short Term Memory Test (FWSTMT) Process of assessment ● Cognitive potential: P300 Electrophysiological test was recorded using RMS EMG EP MARK II supplied by recorders and Medicare system (P) limited, Chandigarh. The investigation of P300 was performed between 10.00 am and 12.00 pm, after breakfast in an acoustically shielded room using auditory stimulus. Subjects were instructed to sit comfortably on a wooden chair with back rest and eyes closed (to eliminate artifacts caused by ocular movements). ● Psychometric tests i. Clock Drawing Test ( CDT ) 16 The subjects were given a sheet of paper with a pre-drawn circle on it. They were then asked to draw numbers or marks in the circle to make circle look like the face of the clock, to read a particular time. This task indicates number of cognitive abilities such as memory, planning and understanding instructions. Higher scores reflect a greater number of errors and hence greater impairment. Score of 1 and 2 is normal. Score of ≥ 3 indicates cognitive impairment. ii. Mini Mental State Examination (MMSE): 17 Is a general cognitive function test with attention, orientation, memory, calculation and language components designed to screen cognitive impairment. The scale ranges from 0 to 30 with higher number indicating better performance. A score below 25 suggests possible impairment and score below 20 indicates definite impairment. iii. Four Word Short Term Memory Test (FWSTMT): 18 A task in which subjects heard four words read at a rate of 1 per second. They were then asked to recall the words after 1 minute and again after 5 minutes. Data analysis Data analysis was done using SPSS. ● Student unpaired T test to compare the mean of evoked potentials between the two groups. ● Chi Square test was used to analyze MMSE and CDT. ● Fischer exact test was used to analyze FWSTMT. ● Differences were considered significant at P<0.001.

In the present study, there were 28 male subjec ts and 22 female subjects in case group and control group included 30 male and 20 female subjects between 40 and 59 years of age. The mean age was 52.7+7.1 years for case group 50.06+6.3 years for control group (P value = 0.052). BMI was 25.3+3.5 kg/m2 for case group and 23.9 + 3.1 kg/m2 for the control group (P value = 0.03). Table 1. Cognitive evoked potential. Parameter Cases Controls P* Value N100 latency (ms) 76.0 + 20.9 77.4 + 19.5 0.73 P200 latency(ms) 167.3 + 26.3 165.4 + 29.3 0.73 N200 latency(ms) 185.0 + 31.2 179.7 + 29 0.30 P300 latency(ms) 334.8 + 20.8 285.7 + 14.9 <0.001* P300-N2(μV) 6.0 + 3.8 5.8 + 4.7 0.79 * Student's unpaired t test, P < 0.001 Graph 1: Amplitude of P300 – N2 among cases and controls. Graph 2: Latency of P300 among cases and controls. Mean P300 latency for case group was 334.8+20.8ms and that of controls was 285.7+14.9ms. The difference was highly significant with a P value of <0.001. There was no significant difference in amplitude of P300 – N2, latencies of N2 and P2 . Table 2. Comparison of MMSE results in study group and control group. Cases Controls MMSE Number of subjects Percentage Number of subjects Percentage Definite 10 20 6 12 Possible 14 28 16 32 Normal 26 52 28 56 Total 50 50 X2=1.2, P=0.54 Table 2 and Graph 3 show results of MMSE between cases and controls The number of subjects with definite cognitive involvement, possible involvement and normal cognitive function in case group was compared with that of control group. The P value was 0.54. Table 3. Comparison of CDT results in cases and controls. Cases Controls CDT Number of subjects % Number of subjects % Normal 26 52 33 66 Impaired 24 48 17 34 Total 50 50 X2=2.02,P=0.15 Graph 4. Comparison of CDT results in cases and controls Table 3 shows results of CDT suggestive of number of subjects with cognitive involvement and normal cognitive function. The P value was 0.15. Table 4. Comparison of FWSTMT results in cases and controls Cases Controls FWSTMT NO. % NO. % Able to recollect 44 88 49 98 Partial 3 6 0 0 Unable to recollect 3 6 1 2 Total 50 50 Fisher's exact test P= 0.11 Graph 5. FWSTMT results in cases and controls Table 4 and Graph 5 shows results of FWSTMT test suggestive of number of subjects with cognitive involvement and normal cognitive function. The P value was 0.11. Table 5: Comparison of MMSE and CDT among cases and control Cases Control P value MMSE 25.11 26.4 0.246 CDT 4.43 3.08 0.363 Unpaired Student T test, P <0.001 Table 5 shows, Comparison of mean values of MMSE among cases and controls. P value = 0.246, insignificant. Comparison of mean values of CDT among cases and controls. P value = 0.363, insignificant.

The diabetic patients complain of loss of memory and poor ability to concentrate. Self management of diabetes including avoidance of hypoglycemia is complex. The cerebral mechanism underlying the cognitive deficits and the responsible brain structures remains to be delineated. They are the topics of intense research, but brain atrophy and vascular changes have both been assumed.19 In our study absolute peak latencies of P300 component of endogenous cognitive evoked potentials was significantly prolonged among diabetics as compared to controls. The amplitude did not differ significantly in the two groups. Since the latencies of N100, N200 and P200 did not differ between cases and controls, prolongation of P300 latencies cannot be attributed to delay in perceptual encoding. It is thought to be produced by interaction between frontal lobe, hippocampus, temporal and parietal process. Hippocampus is involved in learning and memory. The delayed P3 in NIDDM therefore reflects inhibition or possible damage of this area.20 Diabetic milieu causes delay in cognitive processes by interacting with N200 and P3 generators in cerebral cortex21. The observed electrophysiological abnormality reflects impairment in attention, memory and speed of information processing which is indicative of early cognitive impairment in diabetes. Since the incidence of Alzheimer’s disease is increasing in diabetics, assessing cognitive function is very essential in preventing this co morbidity in the elderly diabetics.22 Older women with diabetes have poorer cognitive functioning and a more rapid cognitive decline than women with normal blood glucose level.23 Studies show that improving the metabolic control in IDDM patients with vigorous and continuous insulin, further deteriorates their cognition.24 In this study, we found that several patients in the diabetic group were of superior intelligence and good education that probably ranked above many in the control group. There appeared to be no marked increase in the errors which a diabetic makes in his work when compared to normal person. MMSE one of the most commonly used cognitive screening test has good specificity (96%) but poor sensitivity (64%) suggesting that cognitive changes remain undetected in number of individuals.25 The results of our study are in line with a study by Allen who also concluded that MMSE is less sensitive in detecting subtle cognitive changes than other psychometric tests.26 Validated measure of cognition that is easy to administer is CDT. CDT is brief face-to-face screening tool that can be used on an outpatient basis. Various studies have showed that CDT can be used for estimating moderate / severe cognitive impairment in an older community. But it is relatively poor at detecting milder cognitive impairment.27,28 FWSTMT is a simple test that assesses verbal memory and learning.18,29, However, literature shows negative results when memory and learning changes assessed using FWSTMT in middle aged diabetics.30 Adults over 65 years of age are at increased risk of developing memory and learning disabilities.11, 31 Psychometric tests conducted using MMSE, CDT and FWSTMT did not reveal significant difference among diabetics and non diabetic peers. The cognitive impairment was evident with electrophysiological tests and not with psychometric tests.

The aim of this study was to assess cognitive function in type 2 DM and to find out the usefulness of psychometric tests in detecting cognitive changes. In general we found that there was statistically significant difference in P300 latency between diabetics and non diabetics, with higher latency in diabetic group when compared to non diabetic group. The amplitude did not differ among the two groups. These results prove that diabetes affects cognition. Psychometric tests provided unconvincing support, with diabetic subjects performing almost equal to their non diabetic peers. But given the modest magnitude of cognitive deficits in this population, the psychometric tools were unable to detect subtle cognitive changes. Although psychometric tests are specific for detecting cognitive dysfunctions, the usefulness of these tool can be at its best only after clinical manifestation of the illness. The same diabetic population was assessed using both psychometric tests and electrophysiological tests. The cognitive impairment was evident with electrophysiological tests and not with psychometric tests. This highlights the fact that electrophysiological tests are more sensitive in detecting early cognitive impairment when compared to psychometric tests.

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