Visual evoked potentials in infants of diabetic mothers: Relations to clinical and metabolic status during pregnancy and delivery

Clinical Neurophysiology 120 (2009) 563–568

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Visual evoked potentials in infants of diabetic mothers: Relations to clinical and metabolic status during pregnancy and delivery M. Brinciotti a,*, M. Matricardi a, A. Colatrella b, F. Torcia c, F. Fallucca b, A. Napoli b a

Department of Child Neuropsychiatry and Rehabilitation Sciences, Faculty of Medicine I, Sapienza Rome University, Via dei Sabelli, 108, 00185 Rome, Italy Department of Clinical Sciences, Diabetes Unit, Faculty of Medicine II, Sapienza University, Rome, Italy c Department of Gynaecology Perinatology and Child Health, Faculty of Medicine II, Sapienza University, Rome, Italy b

a r t i c l e

i n f o

Article history: Accepted 15 December 2008 Available online 31 January 2009 Keywords: Visual evoked potential Diabetes Pregnancy Infants Psychomotor development

a b s t r a c t Objective: To evaluate Visual Evoked Potentials (VEPs) and psychomotor development of infants of diabetic mothers (IDMs) in relation to clinical and metabolic data during pregnancy and delivery. Methods: VEPs and psychomotor development (Brunet–Lézine) were analysed in 40 two-month-old IDMs (21 males, 19 females), 24 from mothers with type-1 diabetes, 13 gestational diabetes, and 3 type-2 diabetes. Normative VEP data were obtained from 63 age matched controls. Results: VEP latencies were significantly longer in IDMs than in controls (O1 wave IV = 197.9 ± 35.5 vs 155.3 ± 30.3; P < 0.001; O2 wave IV = 200.2 ± 33.8 vs 155.6 ± 29.0; P < 0.001). The mean developmental quotient was normal. In IDMs with type-1 diabetes delayed VEPs were related to increased weight during pregnancy (r 0.516; P 0.009), 1st trimester fasting blood glucose (r 0.458; P 0.037), insulin requirement during the 2nd (r 0.441; P 0.035) and 3rd trimester (r 0.422; P 0.039); in IDMs with gestational diabetes, VEP latency showed negative relation to Apgar scores (r 0.748; P 0.008). Conclusions: IDMs have delayed VEPs, which may possibly be related to poor metabolic control in pregestational diabetes, and to delivery complications in gestational diabetes. Significance: IDMs show subtle neurophysiologic changes detectable by VEPs. Ó 2009 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

1. Introduction Experimental and clinical data show that in-utero exposure to diabetic environment may produce lasting changes on organ’s growth regulation of newborns (Jovanovic et al., 1998; Fallucca et al., 2000), but the effects of maternal diabetes on cognitive functions of the offspring are still not clear. Rizzo et al. (1991, 1994) found an overall healthy neuropsychological functioning in Infants of Diabetic Mothers (IDMs), although some indices of poor maternal metabolic regulation during pregnancy were significantly related to poor intellectual performance in children tested between 2 and 11 years of age. Silverman et al. (1998) reported that abnormal maternal metabolism was associated with poor intellectual performance in the offspring of diabetic mothers, even if the rates of major cerebral disorders (e.g. cerebral palsy, mental retardation) did not differ significantly from national estimates. Evoked potentials were used to study neurophysiologic changes related to maturational processes and clinical problems (Taylor and McCulloch, 1992) as well as to analyse drug effects (Drake et al., 1989; Brinciotti, 1994). Delayed maturation of Visual Evoked

* Corresponding author. Tel.: +39 06 44712260; fax: +39 06 4957857. E-mail address: [email protected] (M. Brinciotti).

Potentials (VEPs) has been noted during early infancy in children with prenatal substance exposure (Till et al., 2003). Delayed latencies of VEPs have been reported in diabetic patients (Ziegler et al., 1994; Uzun et al., 2006) and in adults with uncomplicated diabetes and normal brain CT scan (Das et al., 2001). We reported delayed latency of the major positive wave of VEP elicited by flash in IDMs despite their global psychomotor development was normal (Brinciotti et al., 2007). It is not known whether VEPs delayed latencies might be related to the type of maternal diabetes, to antepartum metabolic disregulation as well as to complications during pregnancy and delivery. Therefore the aim of this study was to determine the relationships among these factors. 2. Methods 2.1. Participants In a period of two years, we studied 62 consecutively born IDMs (34 females and 28 males), all living in a urban area, and examined within two months of life. All mothers had delivered at Obstetrical Clinic of Sapienza Rome University after being followed throughout pregnancy in our diabetologist and gynecologist conjunct out-patients’ service. Diabetic women were classified according to the

1388-2457/$36.00 Ó 2009 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.clinph.2008.12.028

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WHO criteria; Gestational Diabetes Mellitus (GDM) was diagnosed between the 24–28th week of gestation, on the basis of the 4th International Workshop-Conference on GDM (1998). 2.2. Diabetes management and clinical-metabolic data of mothers At the recruitment (15.5 ± 9.8 gestational weeks, C. I. 5–36 weeks), all women were treated with diet only or diet + insulin. Pregnancy dating, based on menstrual history and physical examination, was confirmed by an ultrasound scan before the 16th week of gestation. Women were examined every 1–2 weeks, recording home capillary blood glucose profiles 4–6 times a day, insulin requirement and adjustments, hypoglycaemic reactions, body weight, and conventionally measured Blood Pressure (BP). Blood glucose control was obtained with split-dosage regimen of regular insulin 3–6 times daily, using both short and intermediate-acting insulin along with dietary prescription. Mothers had treatment with diet or diet + insulin to achieve fasting blood glucose levels minor than 90 mg/dl (5 mol/dl) and 120 min postprandial values less than 120 mg/dl (6.6 mol/dl). Maternal glycohaemoglobin (HbA1c) was checked every 4–6 weeks. At each examination, number and degree of hypoglycaemias during the previous one or two weeks were recorded. Hypoglycaemic episodes was graded as Mild (symptoms spontaneously remitted or resolved by taking oral carbohydrate) or Severe (symptoms resolved by requiring admittance to hospital). Women checked ketonuria when they woke up and eventually before lunch, dinner and at bedtime. Pregnancies were defined as complicated in presence of polyamnios, oligoamnios, chronic or transient hypertension, Preclampsia (PH), or Hemolysis + Elevated Liver enzymes + Low Platelets (HELLP) syndrome. 2.3. Psychomotor development test Psychomotor development of IDMs was assessed by Brunet Lézine test (Brunet and Lézine, 1955). The scale is based on 4 sub-tests (Posture, Coordination, Language, and Socialization) with scores obtained by structured questions to parents and direct evaluation items. Weighted scores are used to estimate developmental age. Development Quotient (DQ) is derived by the ratio between developmental age and chronological age; DQ is then Adjusted for gestational age (ADQ). Abnormal values are considered for scores 680. The test was administered to all IDMs between 10.00 and 12.00 a.m. by the same trained examiner (M.M.). 2.4. VEPs VEP recordings were obtained in awake condition without sedation, checking infant alertness during the overall session. Responses were elicited by binocular flash stimulation (white light; intensity 0.3 Joule; frequency 1 Hz) presented about 25 cm in front of the infant’s eyes, and recorded by a four channel montage (O1Fz, Oz-Fz, O2-Fz, Fz-M1; M2 as ground) according to the American Electroencephalographic Society guidelines (AES, 1994). At least 100 responses were averaged for each trial within 512 ms after stimulus with a bandpass of 1–100 Hz; two or more trials were recorded to ensure reproducibility of the waveform (responses with excessive artefacts were automatically rejected). All reproducible waves were identified and labeled according to AES guidelines (1994); signals recorded from the 4th channel (Fz-M1) were used to ensure proper identification of the occipital components, but the mid-frontal responses were not considered for statistical analysis. Peak latencies and peak-to-peak amplitude of all occipital components were measured, but only the most stable waves III, IV, and V, corresponding with N2, P2, and N3 of International Society for Clinical Electrophysiology of Vision nomenclature (Odom et al., 2004) were used for statistical analysis. Signals from O1

and O2 were considered separately to evaluate inter-hemispheric differences. To avoid changes of infant behavioural status during the psychomotor assessment and the neurophysiologic recording, VEPs were obtained within 2 h since the development test administration, blindly as regards its result. Informed consent was obtained from both parents of each infant, after explaining nature and purpose of the procedures. VEPs were not obtained in 22 IDMs since their parents declined for practical reasons or denied consent. VEP data were available in 40 consecutive unselected IDMs (21 males, 19 females), and this sample was used for subsequent analysis. Infants were subdivided according to maternal diabetes type (24 type-1 diabetes; 3 type-2 diabetes, 13 GDM). Normative VEP data were obtained from 63 healthy infants (30 females and 33 males; mean age 47 ± 21 days); abnormal responses were considered for latencies longer than 3 SD from the mean. From this normative sample, a sub-group of 29 infants (13 females and 16 males) of non-diabetic mothers, matched for age at examination, maternal age at pregnancy, and gestational week of delivery was selected as a Control group for statistical comparisons (Table 1). VEPs and psychomotor developmental test were performed without knowledge of mothers’ antepartum metabolic status and perinatal history of infants. 2.5. Statistics Means and limits were calculated adopting tolerance limit of 99% with a confidence of 95%. To obtain normative VEP data, the distribution of observed values was previously examined by the Shapiro–Will’s goodness of fit for skeweness and/or kurtosis. v2, MANOVA, ANOVA and/or nonparametric tests were used for comparisons between and whithin groups, as appropriate. Linear and multiple regressions were used to analyse correlations among variables. Parameters considered for statistical analysis were: – Maternal variables: age at diabetes onset, duration of disease, gestational age at the first examination, increased weight during pregnancy, body mass index. – Pregnancy and parameters of metabolic control: Fasting Blood Glucose (FBG) during 1st, 2nd, and 3rd trimester, Post-Prandial Blood Glucose (PPBG) during 1st, 2nd, and 3rd trimester, HbA1c during 1st, 2nd, and 3rd trimester, number of hypoglycemias during 1st, 2nd, and 3rd trimester, insulin (IU/24 h) before pregnancy and during 1st, 2nd, and 3rd trimester, maternal hypertension, complicated pregnancy. – Delivery and neonatal variables: type of delivery (elective caesarian section, vaginal delivery, urgent caesarian section), sex, gestational age (<38 weeks and P38 weeks), weight at birth, Apgar scores at 10 and 50 , neonatal hypoxia, distressrespiratory syndrome, hypocalcaemia, and jaundice.

Table 1 Main characteristics of mothers and infants in studied sample (IDMs) and controls.

Maternal age at pregnancy (years) Age of infants at examination (days) Gestational age (weeks) Apgar-10 Apgar-50 Weight at birth (g)

IDMs (No. 40) X ± SD

Controls (No. 29) X ± SD

P

29.8 ± 5.6 44 ± 12 37.3 ± 2.2 7.2 ± 1.5 8.7 ± 0.9 3.264 ± 593

31.1 ± 5.1 48 ± 21 38.0 ± 1.3 8.5 ± 0.5 9.3 ± 0.6 2.959 ± 682

NS NS NS NS NS 0.011

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3.4. Development quotient, adjusted development quotient and VEP related to clinical and metabolic variables in IDMs

3. Results 3.1. Clinical and metabolic data related to diabetes type Clinical and metabolic data of IDMs are reported in Table 2. Significant differences among groups were noted for metabolic parameters during pregnancy, type of delivery, and newborn gender (no differences for gestational age, weight at birth, Apgar scores, neonatal hypoxia, distress-respiratory syndrome, hypocalcaemia, and jaundice). 3.2. Development quotient and adjusted development quotient in IDMs DQ, AQD, and related sub-test scores are shown in Table 3. No differences were found among diabetes types. Six patients (15%) had DQ scores <80 (4 in type-1 diabetes, and 2 in GDM), but only one of them (type-1 diabetes) had ADQ <80. 3.3. VEPs in IDMs and controls Reproducible VEPs were recorded in all studied infants (Fig. 1A). Mean latencies of wave III (only at O2), IV, and V were significantly longer in IDMs than in controls, while no differences were noted for amplitude (Table 4). The IV component was delayed also plotting data against adjusted ages (Fig. 1B). No VEP differences were found among diabetes types, and no relations were noted between developmental scores and VEPs. In 4 infants (10%) (2 GDM, 1 type1 and 1 type-2 diabetes, respectively) the latency was longer than 3 SD. Only one infant (type-1 diabetes) had both abnormal VEPs and ADQ.

Table 2 Main clinical and metabolic differences related to maternal diabetes type.

Clinical variables of mothers Age of diabetes onset (years) Duration of disease (years) Gestational age at the first examination (weeks) Increase weight (kg) Body mass index

Type-1 (No. 24) X ± SD

Type-2 (No. 3) X ± SD

GD (No. 13) X ± SD

P

10.8 ± 6.8 16.9 ± 6.5 10.4 ± 6.4

26.0 ± 12.8 6.7 ± 9.8 13.3 ± 6.8

0 0 26.2 ± 8.1

0.003 0.022 <0.001

13.4 ± 4.8 23.2 ± 2.8

10.0 ± 2.6 27.7 ± 3.2

8.4 ± 4.3 27.7 ± 4.6

0.012 0.002

132.7 ± 21.9 113.7 ± 25.6 123.9 ± 23.8 6.01 ± 0.96 5.69 ± 0.81 8.6 ± 7.3

99.7 ± 17.0 94.3 ± 21.4 101.3 ± 18.1 5.97 ± 1.0 4.80 ± 0.28 1 ± 1.7

91.4 ± 6.5 85.6 ± 9.2 98.8 ± 15.4 4.20 ± .84 4.81 ± .85 0

<0.001 0.002 0.046 0.002 0.015 0.001

8.8 ± 7.4

0

0

<0.001

4±5

1 ± 1.7

0.1 ± 0.3

Metabolic data during pregnancy FBG – 2nd trimester FBG – 3rd trimester PPBG – 2nd trimester HbA1c – 2nd trimester HbA1c – 3rd trimester N. of hypoglycemias – 1st trimester N. of hypoglycemias – 2nd trimester N. of hypoglycemias – 3rd trimester Insulin before pregnancy (IU/24 h) Insulin 1st trimester (IU/24 h) Insulin 2nd trimester (IU/24 h) Insulin 3rd trimester (IU/24 h)

44.3 ± 21.2

5.7 ± 9.8

0

<0.001

40.7 ± 8.7 57.9 ± 21.4 71.6 ± 27.9

10.7 ± 18.5 18.3 ± 31.7 42.3 ± 35.2

0 1.5 ± 4.8 12.1 ± 11.8

<0.001 <0.001 <0.001

Delivery and gender Elective caesarian section Vaginal delivery Urgent caesarian section Sex (males)

N (%) 23 (96) 0 (0) 1 (4) 9 (37.5)

N (%) 3 (100) 0 (0) 0 (0) 3 (100)

N (%) 5 (38.5) 5 (38.5) 3 (23.0) 9 (69)

FBG, fasting blood glucose; PPBG, post-prandial blood glucose.

0.035

0.001 0.001 0.001 0.042

DQ showed significant relation to the following variables: complicated pregnancy (present 85.3 ± 19.3 vs absent 101.7 ± 11.8; P 0.009), hypertension (present 84.5 ± 23.1 vs absent 98.8 ± 16.4; P 0.039), PPBG of the 3rd trimester (abnormal 85.2 ± 23.7 vs normal 100.0 ± 14.3; P 0.019), and neonatal hypoglycaemias (r 0.336; P 0.04). Negative predictive value was noted between DQ and hypoglycaemia during pregnancy, but non at significant level, while significant negative coefficients were found between language scores and number of hypoglycaemic episodes during 1st (r 0.3921; P 0.024) and 2nd trimester (r 0.385; P 0.027). ADQ scores were significantly related to the following variables: HbA1c of the 3rd trimester (r 0.379; P 0.029), insulin treatment during the 3rd trimester (yes 112.0 ± 28.2 vs no 195.2 ± 76.4; P 0.020), type of delivery (vaginal delivery 102.0 ± 12.3 vs elective caesarian 112.0 ± 29.1; P 0.007), gestational age (r 0.440; P 0.005), and weight at birth (r 0.385; P 0.014). Significant relations were found between VEPs and clinicalmetabolic variables: (i) wave III latency was delayed at channel O2 in the presence of maternal hypertension (present 146.3 ± 17 vs absent 126.2 ± 9; P 0.015); (ii) positive predictive value between wave III latency and 1st trimester FBG (O1 = r 0.528, P 0.008; O2 = r 0.49, P 0.015); (iii) positive predictive value between increased weight during pregnancy and latency of both components III and IV (O1: wave III = r 0.467; P 0.003; wave IV = r 0.405, P 0.011; O2: wave III = r 0.389, P 0.015; wave IV = r 0.387, P 0.016). 3.5. Development quotient, adjusted development quotient and VEP related to clinical and metabolic variables within groups Data are shown in Table 5. In type-1 diabetes, total ADQ was related to gestational age and weight at birth (sub-group <38 weeks), while VEP latencies were related to increased weight during pregnancy, FBG of the 1st trimester, insulin requirement during the 1st, 2nd and 3rd trimester, but no differences were noted for maternal treatment at pregnancy onset (diet only vs diet + insulin). In type-2 diabetes, significant relation was found between total ADQ and weight at birth (sub-group <38 weeks). In gestational diabetes, total ADQ was related to hypertension, 3rd trimester HbA1c, gestational age, and weight at birth (both sub-groups, > and <38 weeks), while a regression with negative predictive values was found among latencies of wave III and IV of VEPs and Apgar scores at 1 and 5 min.

4. Discussion Exposure to intrauterine diabetic environment may produce consequences on the offspring’ s physical development, but it is still not clear to what extent maternal diabetes affects brain functions. In the present study we sought to discern two main aspects: (i) whether the type of maternal diabetes (pre-gestational or gestational) and its complications may exert different effects on the early psychomotor development of the offspring; (ii) whether these effects may be reliably detected by VEPs. In our sample of IDMs we found a normal mean quotient of global psychomotor development, but 6 infants had abnormal DQ, and one of them showed ADQ <80. These data agree to previous reports on cognitive outcome of IDMs (Rizzo et al., 1994; Silverman et al., 1998). Recently, Kowalczyk et al. (2002) in IDMs tested by Brunet Lézine found abnormalities on speech, eye-movement coordination, and social aspects related to insufficiently controlled maternal diabetes with serious hypoglycaemias during pregnancy. In our sample, ADQ showed significant relation with some indexes of

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Table 3 DQ, ADQ, and related sub-test scores in IDMs. Scores

Overall IDMs

Type-1

Type-2

GD

DQ Mean ± SD

ADQ Mean ± SD

DQ Mean ± SD

ADQ Mean ± SD

DQ Mean ± SD

ADQ Mean ± SD

DQ Mean ± SD

ADQ Mean ± SD

Posture Coordination Language Socialization

96.1 ± 25 93.6 ± 26 92.4 ± 32 98.0 ± 24

123.0 ± 72 122.3 ± 76 115.6 ± 74 124.9 ± 67

97.1 ± 27 95.9 ± 29 88.6 ± 30 96.1 ± 24

118.2 ± 47 116.6 ± 49 106.6 ± 38 115.4 ± 33

106.3 ± 10 82.0 ± 17 113.0 ± 20 100.0 ± 14

106.3 ± 10 82.0 ± 17 113.0 ± 20 100.0 ± 14

91.8 ± 23 92.0 ± 22 94.7 ± 39 101.1 ± 28

135.8 ± 88 142.0 ± 89 135.8 ± 92 148.2 ± 94

Total

94.7 ± 19

121.2 ± 67

94.5 ± 18

114.0 ± 33

100.3 ± 10

100.3 ± 10

93.7 ± 24

139.3 ± 87

poor control of antepartum maternal metabolism, suggesting the occurrence of subtle negative effects on brain functions. As reported by Kowalczyk et al. (2002), we found lower sub-test scores on speech and coordination, with negative predictive values between speech items and number of hypoglycaemic episodes during 1st and 2nd trimester. In preterm infant, Duvanel et al. (1999) found that early episodes of hypoglycaemia were strongly correlated with persistent neurodevelopmental deficits until 5 years of age; our data support these findings, since DQ was negatively related to neonatal hypoglycaemias. The significant relation between maternal hypertension and lower DQ scores of the infants suggest the 24-h BP monitoring could be an useful tool to improve management and prognosis of diabetic pregnancy, as previously reported (Napoli et al., 2003). Anyway, even if the in-utero exposure to a diabetic environment may be detrimental in some infants, in many others its appear to be no clinically evident.

IDMs had mean latencies of the main VEP components significantly delayed compared to controls, while no differences were noted for the amplitudes. When infants were grouped according to maternal diabetes, the type-1 showed delayed latencies of all components (III, IV, and V), while other groups had significant delay of wave IV and V, but not III. Experimental and clinical data support the hypothesis of subcortical-cortical development of the visual system; during the first postnatal weeks, the visual system is under the prevailing control of subcortical centres (lateral geniculate body, superior colliculus) then, during the first two months of life, significant synaptogenesis and myelination occur to allow the primary geniculocalcarine cortical system to assume greater control over the visual system (Hickey, 1977). Visual processes continue to mature into childhood and these changes may be well documented by VEPs, as a decrease in latency, an increase in amplitude and the development of the waveform (Taylor and McCulloch, 1992; Brecelj, 2003; Lenassi et al., 2008). Although

Fig. 1. (A) Example of VEP recorded in IDM. In some infants, the phase-reversal signal recorded from the 4th channel (Fz-M1) was useful for a proper identification of the occipital components. (B) Relationship between adjusted age and wave IV latency of VEP (upper = O1; bottom = O2) in IDMs and controls (dotted line = regression in IDMs; continuous line = regression in Controls).

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M. Brinciotti et al. / Clinical Neurophysiology 120 (2009) 563–568 Table 4 VEP comparison between IDMs and controls. Overall IDMs X ± SD

Type-1 X ± SD

Type-2 X ± SD

GD X ± SD

Controls X ± SD

P*

Latency (ms) O1 III IV V

129.9 ± 27.4 197.9 ± 35.5à 290.5 ± 49.7à

134.5 ± 28.5  194.7 ± 35.74à 280.4 ± 45.2à

123.0 ± 6.6 228.7 ± 15.6à 348.3 ± 25.5à

123.0 ± 27.7 196.8 ± 36.9  295.7 ± 54.1 

106.7 ± 31.8 155.3 ± 30.3 222.7 ± 46.7

0.025 <0.001 <0.001

Oz III IV V

130.3 ± 24.9 199.1 ± 34.3à 290.6 ± 48.7à

135.1 ± 26.0  196.9 ± 34.0à 283.8 ± 45.8à

130.7 ± 13.5 223.2 ± 19.8à 327.3 ± 42.0à

121.6 ± 23.0 197.6 ± 36.4à 294.7 ± 52.5à

106.7 ± 31.8 155.3 ± 30.3 222.7 ± 46.7

0.030 <0.001 <0.001

O2 III IV V

132.9 ± 27.7  200.2 ± 33.8à 290.8 ± 48.3à

137.8 ± 27.9  199.0 ± 32.8à 287.2 ± 47.1à

136.0 ± 18.5 217.7 ± 25.4  306.3 ± 49.4 

122.9 ± 28.0 198.2 ± 37.3à 293.8 ± 53.1à

107.4 ± 31.3 155.6 ± 29.0 226.6 ± 43.5

0.009 <0.001 <0.001

Amplitude (lV) O1 III IV V

3.6 ± 2.3 6.2 ± 3.4 6.4 ± 4.4

2.9 ± 2.0 5.6 ± 3.2 5.8 ± 4.1

5.3 ± 2.2 8.6 ± 2.1 5.1 ± 1.0

4.6 ± 2.4 6.7 ± 3.8 7.7 ± 5.3

3.1 ± 2.5 5.9 ± 4.3 8.2 ± 5.2

NS NS NS

Oz III IV V

3.7 ± 2.2 7.1 ± 4.5 6.5 ± 4.3

3.2 ± 2.1 6.9 ± 4.9 6.8 ± 4.2

4.5 ± 1.9 9.7 ± 3.0 6.2 ± 3.7

4.4 ± 2.4 6.7 ± 3.5 6.6 ± 4.5

3.1 ± 2.5 5.9 ± 4.3 8.2 ± 5.2

NS NS NS

O2 III IV V

3.8 ± 2.2 8.0 ± 5.2 6.6 ± 4.1

3.6 ± 2.2 8.3 ± 6.1 7.1 ± 4.3

3.7 ± 1.6 10.9 ± 3.8 7.3 ± 5.5

4.2 ± 2.4 6.8 ± 3.4 5.5 ± 3.6

2.9 ± 2.0 5.7 ± 4.3 9.2 ± 6.1

NS NS NS

VEP

* à  

MANOVA; ANOVA (each group vs controls). P < 0.001. P < 0.01.

the generators of each VEP component are not yet clearly identified, the cortical origin of the wave IV is well documented by multichannel scalp recordings and clinical studies (Tsuneishi and Casaer, 2000; Di Russo et al., 2002; Tobimatsu and Celesia, 2006). According to these findings, our data show that some changes occur in the visual system of infants exposed to diabetic environment in-utero. Interferences on some process of brain development, such as dendrite arborization and synaptogenesis other than myelination, can explain the prolongation of VEP latencies. These effects

appear more diffuse, cortical and subcortical, in type-1 diabetes than in the others. VEPs seem to be more sensitive than psychometric test to detect brain dysfunctions, since abnormal responses were found in 4 infants, but only one of them had abnormal ADQ. Sub-clinical brain dysfunction may occur in diabetic patients and it can be reliably detected by evoked potentials (Das et al., 2001). Nelson et al. (2000) reported that event-related potential showed evidence consistent with memory deficits in 6-month-old IDMs compared with controls,

Table 5 Clinical and metabolic variables significantly related to DQ, ADG and VEPs according to maternal diabetes type. Variables

Type-1 (No. 24)

Increased weight

VEP latency IV – O1 VEP latency IV – O2

Hypertension Present Absent FBG 1st trimester HbA1c 3rd trimester Insulin 1st trimester Insulin 2nd trimester Insulin 3rd trimester Gestational age Weight at birth <38 weeks >38 weeks Apgar 10

Type-2 (No. 3)

GD (No. 13)

P

r .516 r .429

0.0900 0.0360 0.0021

DQ 62.0 ± 25.1 104.2 ± 11.7 VEP latency III – O1 VEP latency IV – O2

r .466 r .458

VEP latency III – O1 VEP latency IV – O1 VEP latency IV – O1 ADQ

r r r r

ADQ

ADQ

r .723

ADQ

r .760

0.0330 0.0370 0.0180 0.0470 0.0350 0.0390 <.0039 <.0040

ADQ ADQ VEP latency VEP latency VEP latency VEP latency VEP latency VEP latency VEP latency

r r r r r r r r r

<.0499 0.0390 0.0090 0.0220 0.0300 0.0270 0.0080 0.0370 0.0009

.480 .441 .422 .590

r .449

Apgar 50

Numbers are means ± SD, correlation coefficients (r) or significant P-level (P).

ADQ r .455

III – O1 III – O2 IV – O2 III – O1 IV – O1 III – O2 IV – O2

.423 .434 .739 .466 .458 .658 .748 .630 .849

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while the ‘‘looking time” and the Bayley Scale failed to distinguish between the groups. In the same way, we did not find significant relations between behavioural scores and VEPs; these findings may be due to the complexity of integrated processes underlining cognitive functions compared to the relatively simple parameter of conduction time within a sensory (visual) system measured by VEPs. However, in IDMs delayed VEPs during early infancy could represent neurophysiologic markers for subsequent neurodevelopmental risk. To test this hypothesis, we are carrying on repeated longitudinal recordings and clinical examinations of this sample. Delayed VEPs appeared significantly related to poor metabolic control during pregnancy, especially in type-1 diabetes, while lower DQ scores were more closely related to pregnancy complications. Moreover, in infants of type-1 diabetic mothers delayed VEPs were significantly related to some indexes of poor metabolic control during pregnancy but not to Apgar scores; on the contrary, in the GDM group, delayed VEPs were more closely related to indexes of perinatal distress. These findings might be explained by different effects of both factors (poor metabolic control and complications) on the brain growth and maturation, depending on the period of their occurrence during pregnancy (Jovanovic et al., 1998; Silverman et al., 1998; Duvanel et al., 1999). Beside, the correlations among delayed VEPs and parameters of poor metabolic control showed inter-hemispheric differences, and were not found in all three studied components. Several explanations could account for these data. It may be hypothesized that abnormalities of metabolic regulation and its consequences may have different regional effects on brain maturation, affecting some structures more than others. In malnourished infants, Bartel et al. (1978) found significantly longer latencies of some VEP components measured from the right hemisphere (O2), while no significant differences were found for left hemisphere. Regional differences were also noted in the distribution of hypoglycaemic brain damage; neuronal necrosis may occur in the dentate gyrus of the hippocampus and in the superficial layers of the cortex, while cerebellum and brainstem are universally spared (Auer, 2004). Furthermore, experimental studies in newborn rats showed differences on regional vulnerability to hypoglycemic insult of the cortex, dentate gyrus of the hippocampus, the thalamus, and the hypothalamus (Zhou et al., 2008). Other significant factors may be related to the asynchronous nature of brain maturation in the early stage, as supported by EEG studies in very premature infants (Selton et al., 2000), by the asynchrony of sleep spindles before the age of two years (Grigg-Damberger et al., 2007), and by data recently obtained by diffusion tensor imaging (Provenzale et al., 2007; Dubois et al., 2008). Additional studies on the relationships between VEPs and neurodevelopment processes in the early phase of brain maturation are needed to further elucidate these aspects. In conclusion, at the age of two months IDMs have a mean global score of psychomotor development within normal limits, even if lower values may occur in same cases, but their VEPs are delayed. The increase of latencies appears significantly related to poor control of antepartum maternal metabolism in pre-gestational diabetes, and to delivery complications in gestational diabetes. These findings suggest that maternal diabetes may have subtle negative effects on brain functions of the offspring, and VEPs seem to be more sensitive than psychometric test to detect these effects. References American Electroencephalographic Society. American Electroencephalographic Society guidelines in electroencephalography, evoked potentials, and polysomnography. J Clin Neurophysiol 1994;11:1–147. Auer RN. Hypoglycemic brain damage. Metab Brain Dis 2004;19(3–4):169–75. Bartel PR, Burnett LS, Griesel RD, Freiman I, Rosen EU, Geefhuysen J. The visual evoked potential in children after kwashiorkor. S Afr Med J 1978;54(21):857–60.

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