Cognitive impairment in type 2 diabetes and its impact on daily living and self-care: A case - Control study in Kanpur, North India

Association of vitamin D and cognition in people with type 2 diabetes: a systematic review

CONTEXT

There is a high prevalence of vitamin D deficiency and impaired cognitive function in people with type 2 diabetes mellitus (T2DM).

OBJECTIVE

To critically and systematically review the literature on the association between vitamin D status and cognitive performance in people with type 2 diabetes.

DATA SOURCES

This review was conducted according to PRISMA recommendations. MEDLINE, SCOPUS, the Cochrane Library, and Web of Science databases were searched using the terms "Diabetes Mellitus, Type 2", "Cognitive Function", and "Vitamin D".

DATA EXTRACTION

Eight observational and 1 randomized study were included, containing data of 14 648 adult and elderly individuals (19-74 y). All extracted data were compiled, compared, and critically analyzed.

DATA ANALYSIS

There is no strong evidence that lower serum concentrations of vitamin D and vitamin D-binding protein are associated with worsening cognitive function in individuals with T2DM. Vitamin D supplementation (12 wk) improved the scores of some executive functioning tests, although there was no difference between low doses (5000 IU/wk) and high doses (50 000 IU/wk).

CONCLUSIONS

There is no high-quality evidence demonstrating an association between vitamin D status and cognitive function, or clinical benefits on cognition from vitamin D supplementation in individuals with T2DM. Future studies are needed. Systematic Review Registration: PROSPERO registration no. CRD42021261520.

Predictive model for identifying mild cognitive impairment in patients with type 2 diabetes mellitus: A CHAID decision tree analysis

BACKGROUND

As the population ages, mild cognitive impairment (MCI) and type 2 diabetes mellitus (T2DM) become common conditions that often coexist. Evidence has shown that MCI could lead to reduced treatment compliance, medication management, and self-care ability in T2DM patients. Therefore, early identification of those with increased risk of MCI is crucial from a preventive perspective. Given the growing utilization of decision trees in prediction of health-related outcomes, this study aimed to identify MCI in T2DM patients using the decision tree approach.

METHODS

This hospital-based case-control study was performed in the Endocrinology Department of Xiangya Hospital affiliated to Central South University between March 2021 and December 2022. MCI was defined based on the Petersen criteria. Demographic characteristics, lifestyle factors, and T2DM-related information were collected. The study sample was randomly divided into the training and validation sets in a 7:3 ratio. Univariate and multivariate analyses were performed, and a decision tree model was established using the chi-square automatic interaction detection (CHAID) algorithm to identify key predictor variables associated with MCI. The area under the curve (AUC) value was used to evaluate the performance of the established decision tree model, and the performance of multivariate regression model was also evaluated for comparison.

RESULTS

A total of 1001 participants (705 in the training set and 296 in the validation set) were included in this study. The mean age of participants in the training and validation sets was 60.2  ±  10.3 and 60.4  ±  9.5 years, respectively. There were no significant differences in the characteristics between the training and validation sets (p > .05). The CHAID decision tree analysis identified six key predictor variables associated with MCI, including age, educational level, household income, regular physical activity, diabetic nephropathy, and diabetic retinopathy. The established decision tree model had 15 nodes composed of 4 layers, and age is the most significant predictor variable. It performed well (AUC = .75 [95% confidence interval (CI): .71-.78] and .67 [95% CI: .61-.74] in the training and validation sets, respectively), was internally validated, and had comparable predictive value compared to the multivariate logistic regression model (AUC = .76 [95% CI: .72-.80] and .69 [95% CI: .62-.75] in the training and validation sets, respectively).

CONCLUSION

The established decision tree model based on age, educational level, household income, regular physical activity, diabetic nephropathy, and diabetic retinopathy performed well with comparable predictive value compared to the multivariate logistic regression model and was internally validated. Due to its superior classification accuracy and simple presentation as well as interpretation of collected data, the decision tree model is more recommended for the prediction of MCI in T2DM patients in clinical practice.

Berberine attenuates cognitive dysfunction and hippocampal apoptosis in rats with prediabetes

The cognitive dysfunction caused by prediabetes causes great difficulties in human life, and the terrible thing is that the means to prevent the occurrence of this disease are very limited at present, Berberine has shown the potential to treat diabetes and cognitive dysfunction, but it still needs to be further explored to clarify the mechanism of its therapeutic effect. Therefore, the aim of this study was to investigate the effects and mechanisms of Berberine on prediabetes-induced cognitive dysfunction. Prediabetes rat model was induced by a high-fat diet and a normal diet was used as a control. They were fed for 20 weeks. At week 13, the model rats were given 100 mg/kg Berberine by gavage for 7 weeks. The cognitive function of rats was observed. At the same time, OGTT, fasting blood glucose, blood lipids, insulin and other metabolic parameters, oxidative stress, and apoptosis levels were measured. The results showed that the model rats showed obvious glucose intolerance, elevated blood lipids, and insulin resistance, and the levels of oxidative stress and apoptosis were significantly increased. However, after the administration of Berberine, the blood glucose and lipid metabolism of prediabetic rats were significantly improved, and the oxidative stress level and apoptosis level of hippocampal tissue were significantly reduced. In conclusion, Berberine can alleviate the further development of diabetes in prediabetic rats, reduce oxidative stress and apoptosis in hippocampal tissue, and improve cognitive impairment in prediabetic rats.

The impact of neuropsychological functions on self-care/self-management of type 2 diabetes in middle-aged people: a scoping review and meta-analysis

INTRODUCTION

This study aimed to investigate the impact of neuropsychological functions on self-care/self-management in middle-aged individuals with type 2 diabetes (T2DM).

AREAS COVERED

A comprehensive literature search was conducted from January 2012 to April 2023 across multiple databases. Ten articles were included in the scoping review, and 3 articles were included in the meta-analysis. The findings consistently indicated an association between reduced neuropsychological functions and poor self-care/self-management in this population. Memory functions, executive functions, and other domains were found to be significantly related to self-care/self-management, including diet management, exercise, blood glucose monitoring, and foot care.

EXPERT OPINION

This study highlights the importance of considering neuropsychological factors in understanding and improving diabetes management outcomes. The findings underscore the need for comprehensive neuropsychological assessments and the development of targeted interventions to address specific vulnerable domains. Future research should focus on elucidating underlying mechanisms, addressing methodological inconsistencies, and exploring the effectiveness of interventions targeting neuropsychological impairments. Incorporating technology and personalized approaches into diabetes management can enhance self-care/self-management and clinical outcomes in individuals with T2DM.

The use of nomogram for detecting mild cognitive impairment in patients with type 2 diabetes mellitus

BACKGROUND

Type 2 diabetes mellitus (T2DM) is highly prevalent worldwide and may lead to a higher rate of cognitive dysfunction. This study aimed to develop and validate a nomogram-based model to detect mild cognitive impairment (MCI) in T2DM patients.

METHODS

Inpatients with T2DM in the endocrinology department of Xiangya Hospital were consecutively enrolled between March and December 2021. Well-qualified investigators conducted face-to-face interviews with participants to retrospectively collect sociodemographic characteristics, lifestyle factors, T2DM-related information, and history of depression and anxiety. Cognitive function was assessed using the Mini-Mental State Examination scale. A nomogram was developed to detect MCI based on the results of the multivariable logistic regression analysis. Calibration, discrimination, and clinical utility of the nomogram were subsequently evaluated by calibration plot, receiver operating characteristic curve, and decision curve analysis, respectively.

RESULTS

A total of 496 patients were included in this study. The prevalence of MCI in T2DM patients was 34.1% (95% confidence interval [CI]: 29.9%-38.3%). Age, marital status, household income, diabetes duration, diabetic retinopathy, anxiety, and depression were independently associated with MCI. Nomogram based on these factors had an area under the curve of 0.849 (95% CI: 0.815-0.883), and the threshold probability ranged from 35.0% to 85.0%.

CONCLUSIONS

Almost one in three T2DM patients suffered from MCI. The nomogram, based on age, marital status, household income, duration of diabetes, diabetic retinopathy, anxiety, and depression, achieved an optimal diagnosis of MCI. Therefore, it could provide a clinical basis for detecting MCI in T2DM patients.

Cognitive Behavioral Therapy for self-care behaviors with type 2 diabetes mellitus patients: A systematic review

BACKGROUND AND AIMS

Self-care behavior is associated with the risk of microvascular and macrovascular complications. Self-care behaviors can be improved through positive thinking, attitude, and knowledge. Cognitive behavioral therapy (CBT) can be one of the interventions for improving self-care behaviors. However, the ideal model and duration of the intervention and an effective assessment instrument to measure the improvement in self-care behaviors remain unidentified. Therefore, this review aimed to assess the effectiveness of CBT, including its models, duration, and instruments, in improving self-care behaviors in patients with type 2 diabetes mellitus (T2DM).

METHODS

The Scopus, Cochrane Library, PubMed, EBSCO Host, Directory of Open Access Journals, GARUDA, Taylor & Francis, and Gray Literature databases were systematically searched to identify studies that were in English and published in 2011-2021. The quality of the identified articles was assessed using The Critical Appraisal Skill Programme.

RESULTS

We found 368 patients in seven randomized controlled trials. CBT was significantly effective in improving overall self-care behavior, including blood glucose monitoring, physical activity, and medication compliance.

CONCLUSION

Individual and group CBT interventions applied face-to-face, via telephone, and via internet show an increase in self-care behavior in patients with T2DM. The duration of treatment had a significant effect at 3 months to 1 year with 12-21 sessions. CBT is performed by a CBT licensed nurse or psychiatrist, nutritionist, CBT psychologist with experience in diabetes care, doctors, research students.

Type 2 diabetes mellitus-associated cognitive dysfunction: Advances in potential mechanisms and therapies

Type 2 diabetes (T2D) and its target organ injuries cause distressing impacts on personal health and put an enormous burden on the healthcare system, and increasing attention has been paid to T2D-associated cognitive dysfunction (TDACD). TDACD is characterized by cognitive dysfunction, delayed executive ability, and impeded information-processing speed. Brain imaging data suggest that extensive brain regions are affected in patients with T2D. Based on current findings, a wide spectrum of non-specific neurodegenerative mechanisms that partially overlap with the mechanisms of neurodegenerative diseases is hypothesized to be associated with TDACD. However, it remains unclear whether TDACD is a consequence of T2D or a complication that co-occurs with T2D. Theoretically, anti-diabetes methods are promising neuromodulatory approaches to reduce brain injury in patients with T2D. In this review, we summarize potential mechanisms underlying TDACD and promising neurotropic effects of anti-diabetes methods and some neuroprotective natural compounds. Constructing screening or diagnostic tools and developing targeted treatment and preventive strategies would be expected to reduce the burden of TDACD.