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1.
Diabetes Metab Syndr ; 17(5): 102768, 2023 May.
Article in English | MEDLINE | ID: mdl-37178514

ABSTRACT

BACKGROUND AND AIM: T1DM has a significant effect on brain structure and function. Age of onset of diabetes may be a critical factor mediating this impairment. We evaluated young adults with T1DM, stratified by the age of onset, for structural brain changes, hypothesizing that there may be a spectrum of white matter damage in these participants, compared to controls. METHODS: We recruited adult patients (20-50 years of age at the time of study enrolment) with onset of T1DM before 18 years of age and at least ten years of schooling, along with controls having normoglycaemia. We compared the Diffusion Tensor Imaging parameters between patients and controls and evaluated their correlations with cognitive z scores, and glycemic measures. RESULTS: We evaluated 93 individuals, 69 [age: 24.1 (±4.5) years, gender: 47.8% men, education: 14.7 ± 1.6 years] with T1DM and 24 [age: 27.8 (±5.4) years, gender: 58.3% men, education: 14.6 ± 1.9 years] without T1DM (controls). We did not find any significant correlation of fractional anisotropy (FA) with age at T1D diagnosis, duration of diabetes, current glycemic status, or domain-wise cognitive z scores. The FA was lower (but not statistically significant) in participants with T1DM when evaluated for the whole brain, individual lobes, hippocampi and amygdala. CONCLUSION: Participants with T1DM do not show a significant difference in the brain white matter integrity when evaluated in a cohort of young adults with relatively few microvascular complications compared to controls.


Subject(s)
Diabetes Mellitus, Type 1 , Male , Young Adult , Humans , Adult , Infant , Female , Diabetes Mellitus, Type 1/complications , Diabetes Mellitus, Type 1/psychology , Cross-Sectional Studies , Diffusion Tensor Imaging/methods , Brain/diagnostic imaging , Cognition
2.
Adv Ther ; 39(4): 1711-1723, 2022 04.
Article in English | MEDLINE | ID: mdl-35182367

ABSTRACT

INTRODUCTION: Type 1 diabetes (T1DM) is associated with cognitive deficits, and age at diagnosis is thought to play a substantial role. However, there are limited data for the cognitive performance in young adults, in relation to the age of diabetes onset. The lack of information is particularly striking in the context of developing regions. METHODS: This cross-sectional study was performed from August 2018 to July 2020. We included adult participants with T1DM, stratified by the age of diabetes onset (till 6 years of age, between 7 to 12 years of age, and 13 to < 18 years of age) and compared them with the control group (no diabetes or pre-diabetes). We filled a structured case record proforma for all participants and recorded relevant socio-demographic and medical details. Detailed neuropsychological assessment with 13 psychological tests representing four cognitive domains was carried-(1) attention, working memory and executive functions; (2) learning and memory; (3) visuoperceptual functions; and (4) information processing speed. RESULTS: We evaluated 100 individuals, 73 (men 48.0%) with T1DM and 27 (men 51.9%) without T1DM. After adjustment for age, gender and education, the mean differences in composite Z scores (for the four cognitive domains) between participants with T1DM and without T1DM were 0.08 for attention, working memory and executive functions (p = 0.614); 0.07 for learning and memory (p = 0.694); 0.05 for visuoperceptual (p = 0.784); and 0.22 for information processing speed (p = 0.305). No significant differences were found for the three subgroups of individuals with T1DM, when compared with the control group. Effect size (Cohen's d) for the individual tests (n = 13) ranged from - 0.36 to + 0.39, and none of the comparisons were statistically significant. Amongst the participants with T1DM, higher education had a significant positive association with three of the four cognitive domains evaluated. CONCLUSIONS: To conclude, our findings suggest minimal differences in the cognitive functioning of patients with T1DM with different age of onset of diabetes compared to healthy controls, when evaluated in early adulthood. This is possibly the first study from South Asia with an in-depth and comprehensive assessment of cognitive functions in patients with T1DM, using a detailed neuropsychological battery.


Subject(s)
Cognition Disorders , Cognitive Dysfunction , Diabetes Mellitus, Type 1 , Adult , Child , Cognition , Cognition Disorders/etiology , Cognitive Dysfunction/complications , Cross-Sectional Studies , Diabetes Mellitus, Type 1/complications , Humans , Male , Young Adult
3.
J Diabetes Complications ; 35(8): 107970, 2021 08.
Article in English | MEDLINE | ID: mdl-34119405

ABSTRACT

AIM: The aim of this study was to evaluate the association of cognitive impairment with sleep quality, depression, and cardiometabolic risk factors among participants with type 2 diabetes mellitus. METHODS: Subjects underwent clinical interview to capture socio-demographic details, medical history, sleep quality, presence of depression, along with anthropometric and biochemical measurements. A detailed neuropsychological assessment [Montreal cognitive assessment scale (MoCA), Trail making A and B, Digit span, Spatial span, Letter Number Sequencing] was done. Cognitive impairment was defined as MoCA score of <23. RESULTS: Participants (n=250, 50% women, 63.6% middle-age) had a mean (±SD) age of 53.6 (±9.1) years and HbA1c of 55.1±6.8mmol/mol (7.2±0.6%). Cognitive impairment was present in 57 (22.8%) participants. In the middle-age subgroup, cognitive impairment was higher (23.9%) than those in the fourth decade (6.3%), but comparable (24.0%) to the older age (60-70years) individuals. Diabetes-related vascular complications [Odds ratio (95% CI) 2.03 (1.05, 3.94)]; hypertension [2.00 (1.04, 3.84)], depression [2.37 (1.24, 4.55)] and lower education [2.73 (1.42, 5.23)] had a significant association with cognitive impairment on multivariate logistic regression analysis. CONCLUSION: The high burden of cognitive impairment calls for an urgent need to establish longitudinal cohorts in midlife to understand this population's cognitive trajectories and see the influence of various bio-psychosocial variables.


Subject(s)
Cardiometabolic Risk Factors , Cognitive Dysfunction , Depression , Diabetes Mellitus, Type 2 , Sleep Quality , Adult , Aged , Cognitive Dysfunction/complications , Cognitive Dysfunction/epidemiology , Cross-Sectional Studies , Depression/complications , Depression/epidemiology , Diabetes Mellitus, Type 2/complications , Diabetes Mellitus, Type 2/epidemiology , Female , Humans , Male , Middle Aged
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