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| ORIGINAL ARTICLE |
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| Year : 2014 | Volume
: 6
| Issue : 1 | Page : 24-29 |
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Visual evoked potential in diabetes mellitus
Galal Mohamed Ismail
Department of Neuroscience, Faculty of Optometry and Visual Science, Al Neelain University, Khartoum, Sudan
| Date of Web Publication | 16-Aug-2014 |
Correspondence Address:
Galal Mohamed Ismail
Faculty of Optometry and Visual Science, Al Neelain University, Khartoum
Sudan
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/1858-540X.138847
Introduction: The visual evoked potential is suggested to be a sensitive indicator of functional changes in the visual processing pathway. Visually evoked potentials have previously been reported to be affected in diabetes. Materials and Methods: The equipment consisted of a Nicolet 1000 clinical averager, Nicolet HGA 200A amplifier and Nicolet N/C 1015 visual stimulator. The pattern check sizes used were 10 and 40 minute arc with contrast of 80 and 40% for each check size. The non-insulin dependent diabetes (NIDD) patients were recruited from the University of Bradford Diabetic Retinopathy Screening Programme. The non-diabetic control group was recruited from patients, partners and members of the University in departments other than Optometry. The age and duration of diabetes for all subject groups were normally distributed. Results: Correlation coefficients between the duration of diabetes and VEP latencies of the three diabetic groups individually and the diabetics as a group all failed to reach significance, reflecting the large variance within the data. Similarly, correlation coefficients between the duration of diabetes and VEP amplitudes of the three diabetic groups individually and the diabetics as a group all failed to reach significance, reflecting the large variance within the data. Conclusion: The visual evoked potential latency and amplitude seemed to be poor indicators of the duration and severity of diabetic retinopathy in diabetes. Keywords: Diabetes mellitus, diabetic retinopathy, visual evoked potential
How to cite this article:
Ismail GM. Visual evoked potential in diabetes mellitus. Sudanese J Ophthalmol 2014;6:24-9 |
| Introduction | |  |
The visual evoked potential is suggested to be a sensitive indicator of functional changes in the visual processing pathway. [1] The pattern visual evoked potential is employed in the present study to investigate any possible neural functional disorder at the level of the macular cortical pathway with and without retinopathy. Visually evoked potentials have previously been reported to be affected in diabetes. [2],[3],[4]
| Materials and Methods | | |
The equipment consisted of a Nicolet 1000 clinical averager, Nicolet HGA 200A amplifier and Nicolet N/C 1015 visual stimulator. The pattern check sizes used were 10 and 40 minute arc with contrast of 80 and 40% for each check size. Subjects were examined wearing their optimal refractive correction. Latencies and amplitudes were measured for all the subject groups.
The non-insulin dependent diabetes (NIDD) patients were recruited from the University of Bradford Diabetic Retinopathy Screening Programme. The patients were not in a tight diabetic control; therefore they can be accepted as reflecting a real image of the diabetic population. The non-diabetic control group was recruited from patients, partners and members of the University in departments other than Optometry. Diabetics and non-diabetics tested within the same period of the study.
Subjects were excluded from the study if they had any sign of cataract within the undilated pupillary area using direct ophthalmoscopy, if they reported any major systemic pathology other than diabetes.
The age and duration of diabetes for all subject groups were normally distributed. [Table 1] shows the values for the mean, standard deviation and ranges of age for the subject groups who participated in the study. [Table 2] shows the values for the mean, standard deviation and ranges of diabetic duration for the subject groups who participated in the study. None of the age means were significantly different from each other (F 3,100 = 2.406, P > 0.05). | Table 1: Means table of the age of the subject groups, showing the standard deviation, range and sex
distribution
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 | Table 2: Means table of the duration of diabetes for each diabetic subject group, showing the standard deviation and range
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Diabetic retinopathy grading systems
Quantitative systems of grading retinal changes are more acceptable compared to qualitative systems in which statistical analysis is difficult to apply. Davis's diabetic retinopathy grading was employed to the present study. The classification was containing stages 10-70 (i.e., seven fields) and only grade 10, 20 and 30 groups were used. [5],[6]
| Results | | |
Latency
[Table 3] shows the mean latency values, standard deviations and standard errors for all subject groups. Means are shown for the two check sizes (10 and 40 minutes of arc) and the two contrast levels (40 and 80%). | Table 3: Means table for visual evoked potential latencies for each check size, contrast and subject group
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[Figure 1] shows the VEP latencies for all sizes and contrasts plotted for each group. Standard error bars are shown. The data show little change in VEP latency as a function of diabetic category, but suggest that latency increases with a reduction in check size and contrast. This latter observation is a well-known phenomenon. [7],[8] | Figure 1: Plot of visual evoked potential latency against subject category for both each check size and contrast. Standard errors are shown
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A repeated measures Analysis of Variance with 2 within-subjects factors (check size, contrast) and 1 between-subjects factor (subject category) was carried out [Table 4]. This supported the lack of effect of subject category upon VEP latency (F 3,100 = 1.274, P > 0.1), and also the significant effects of size (F 1,100 = 96.1, P < 0.0001) and contrast (F 1,100 =99.7, P<0.0001). There was no significant interaction effect between size and contrast (F 1,100 = 0.015, P > 0.1), indicating that the effect of stimulus contrast was the same irrespective of check size. | Table 4: ANOVA table for the effect of subject category, check size and contrast upon VEP latency
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Correlation coefficients between the duration of diabetes and VEP latencies of the three diabetic groups individually and the diabetics as a group all failed to reach significance [Figure 2], reflecting the large variance within the data. The visual evoked potential latency seems to be a poor indicator of the duration of diabetes. | Figure 2: Relationship between VEP latency and duration of diabetes for each check size and contrast
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Amplitude
[Table 5] shows the mean amplitudes values, standard deviations and standard errors for all subject groups. Means are shown for the two check sizes (10 and 40 minutes of arc) and the two contrast levels (40 and 80%). | Table 5: Means table for visual evoked potential amplitudes for each check size, contrast and subject group
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[Figure 3] shows the amplitude for all sizes and contrasts plotted for each group. Standard error bars are shown. The data suggest that VEP amplitude is reduced in diabetes, and, that amplitude reduces with a reduction in check size, and at least for small check sizes, with a reduction in contrast.
A repeated measures Analysis of Variance with 2 within-subjects factors (check size, contrast) and 1 between-subjects factor (subject category) was carried out [Table 6]. This supported the significant effect of subject category upon VEP amplitude (F 3,100 = 4.816, P < 0.005), and also the significant effects of size (F 1,100 =87.94, P < 0.0001) and contrast (F 1,100 = 64.423, P < 0.0001). Interestingly, as can be predicted from [Figure 4], there is a significant interaction effect between size and contrast (F 1,100 = 49.521, P < 0.0001), supporting the observation that the effect of stimulus contrast depends upon check size. | Figure 3: Plot of visual evoked potential amplitude against subject category for both each check size and contrast. Standard errors are shown
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 | Table 6: ANOVA table for the effect of subject category, check size and contrast upon VEP amplitude
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A Scheffe's post hoc comparison test was used to reveal significance differences in VEP amplitude between subject groups. Nearly all amplitude comparisons failed to reach significance due to the variability within the data. However, the test did reveal a significant difference between normal subjects and diabetic group three (DRL20) (P < 0.05). Differences between normals and DRL10 and DRL30 just failed to reach significance at the P < 0.05 level.
Correlation coefficients between the duration of diabetes and VEP amplitudes of the three diabetic groups individually and the diabetics as a group all failed to reach significance [Figure 5], reflecting the large variance within the data. The visual evoked potential seems to be a poor indicator of the duration of diabetes. | Figure 5: Relationship between VEP amplitude and duration of diabetes for each check size and contrast
Click here to view |
| Discussion | | |
The visual evoked potential is defined as a gross electrical signal which is generated by the occipital region of the cortex in response to visual stimulus. It is one of the few methods to investigate neural changes objectively in the visual system of an alert and perceptually active human. [9] Clinically, the VEP has been used to study refractive errors, [10] visual acuity, (Bodis et al., 1977; Linkz, 1973; Marg et al., 1976; Sokol, 1976; Jenkins et al., 1985) [11],[12],[13],[14],[15] amblyopia (Odom et al., 1982), binocularity, [16],[17],[18],[19] (Apkarian et al., 1981; Sutija et al., 1990; Heravian et al., 1990), disease of the optic nerve [20],[21],[22],[23],[24] (Linkz, 1972; Halliday et al., 1972, 1973, 1976; Heinrichs and McLean, 1988) and field defects [25] (Eason et al., 1970). The VEP appears to be mainly a cone response and is suggested to be extremely sensitive to relatively subtle changes in visual function. [26],[27] (DeVoe et al., 1968; Ripps and Vaughan, 1969).
Puvanendran et al. (1983) studied the pattern reversal visual evoked responses in 16 diabetics with no retinopathy and approximately normal visual acuity. They found that the latency increased by more than 1 standard deviation in 81% of patients and by more than 3 standard deviations in 62.5% of the diabetics compared to the non-diabetic control group. They also noted that the latency increases were mostly associated with a marked reduction in amplitude. They related the latency delay and the reduction in amplitude to subclinical disturbance of optic nerve conduction in diabetics which occurs as a result of subclinical neuropathy. [3] Subclinical neuropathy has been reported to occur in about 40-73% of diabetic cases. [28]
Ponte et al. (1986) studied VEPs in an insulin dependent diabetes mellitus group with no diabetic retinopathy. They found latencies which were not significantly different to that of a normal control group. However, latencies were found to increase slightly with the duration of diabetes. They related the delay to the irreversible hypoxic lesions that occurred to the ganglion cells and optic nerve due to chronic, large fluctuations in glycaemia. [2]
Lovasik and Spafford (1988) studied VEPs as a part of their investigation in visual function in IDDM patients. They investigated 30 IDDM juvenile diabetics and an age- and sex-matched group of non diabetics. Their aim was to investigate if the VEP could reveal any functional neural disorders prior to observable structural changes in insulin dependent diabetes mellitus patients. They used four types of VEPs consisting of pattern steady-state and transient pattern reversing check patterns. They also investigated the effect of check size and contrast. They concluded that VEPs in the presence of relatively short term and well controlled diabetes did not reveal any serious functional neural deficits. They suggested that further electrophysiological investigations might be worthwhile taking into account variables such as the degree of diabetic retinopathy, age and sex, means of control and duration of diagnosis. [4]
Martinelli et al. (1991) studied visual evoked potentials with 7.5' checks at three contrast levels (10, 25, and 50%) and pattern electroretinograms at different spatial frequencies in insulin dependent diabetes mellitus with normal visual acuity. They found that the frequency of abnormal VEPs increased with increasing spatial frequency and with decreasing contrast levels. They also report that the mean PERG amplitude was significantly reduced in the diabetic group at all spatial frequencies and contrasts. They suggest that the mean VEP latency in eyes with reduced PERG amplitude is significantly increased compared to eyes with normal PERGs. Their conclusion was that PERG amplitude reduction seems to be the earliest detectable electrophysiological abnormality of the optic pathways in IDDM patients. [29]
Parisi et al. (1995) assessed visual evoked potentials under normal conditions and after photo stress in newly diagnosed diabetic patients free from any fluorescein angiographic sign of retinopathy. In normal conditions the latency was significantly increased in the diabetic group while the amplitude was similar to the control group. The opposite occurred following photo stress-amplitudes were significantly higher in diabetics while latency and recovery time were the same in both groups. They conclude that the impaired normal VEPs suggest an early defect of conduction in the optic nerve. In contrast, the preserved recovery time after photo stress indicates that diabetes of short duration does not induce physiopathological changes in macular function. [30]
Ziegler et al. (1994) examined VEPs in poorly controlled diabetics and then following tight short-term metabolic control. Their findings suggest that the abnormal VEP latencies in diabetics are partially reversible and include functional disturbances related to glucose metabolism. [31] An alternative view is given by Martinelli et al. (1992) who examined the effect of hyperglycemia on visual evoked potentials in type I diabetic patients. They recorded monocular pattern reversal VEPs (check size 15', contrast 50%) before and after a hyperglycaemic clamp (250 mg/dl for 180 min). No significant changes were found between both recording conditions and there was also no correlation with the duration of diabetes or the presence of retinopathy. They concluded that the neurophysiological abnormalities detected in type I diabetics are due to structural involvement of the central nervous pathways and not to functional damage induced by acute short-term hyperglycaemia. [32],[33],[34],[35]
The findings of the present study demonstrate no change in VEP latency as a function of diabetic category, in line with the findings of Ponte et al. (1986) and Lovasik and Spafford (1988) but contrary to the results of other authors (Puvanendran et al., 1983; Parisi et al., 1995). In line with early established data (Vaughan, 1969; Regan and Richard, 1973; Halliday et al., 1979; Lovasik and Spafford, 1988), latency increases with a reduction in check size and contrast [Figure 4]. The amplitudes of the VEPs in the present study were affected in the presence of diabetic retinopathy [Figure 4]. The reduction in amplitude for the diabetic group without retinopathy did not, however, reach significance, contrary to the findings of Puvanendran (1983), although this latter study investigated type 1 diabetics. Neither latencies nor amplitudes were correlated to diabetic duration.
The current findings therefore indicate that the visual evoked potential is not dramatically affected by diabetes or early diabetic retinopathy, apart from a small reduction in amplitude when retinopathy becomes manifest. Both this finding and the length of time necessary to perform the test argue against its role in diabetic retinopathy screening.
| Conclusions | | |
Visual Evoked Potential as an electrophysiological method was used to investigate the possible loss of integrity of visual function in type II diabetes mellitus. The results were interpreted in terms of the presence of functional changes relative to the severity of retinopathy and the length of time the patient had been diagnosed as a diabetic. They revealed significant amplitude of the visual evoked response. However, it identified the progression of retinopathy poorly, making it unsuitable in terms of a retinopathy monitoring test. The test failed to distinguish diabetics without retinopathy from those with early retinal changes. It also showed a negligible or, at best, weak relationship with the duration of diabetes.
| Acknowledgement | | |
The author would like to thank Professor David Whitaker for his help and support to study and the analysis. My sincere thanks go to the participants, secretarial and technical personnel who organised for this study at the optometry department, Bradford University, Bradford, UK.
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[Figure 2], [Figure 3], [Figure 4], [Figure 5]
[Table 1], [Table 2], [Table 3], [Table 4], [Figure 1], [Table 5], [Table 6]
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