Association between trajectory of severe hypoglycemia and dementia in patients with type 2 diabetes: A population-based study

Association of hypoglycemic events with cognitive impairment in patients with type 2 diabetes mellitus: Protocol for a dose-response meta-analysis

INTRODUCTION

With an incidence rate as high as 46%-58%, hypoglycemia is a common complication of glycemic management among those suffering from type 2 diabetes mellitus(T2DM). According to preclinical research, hypoglycemia episodes may impair cognition by harming neurons. However, there is still controversy regarding the clinical evidence for the relationship between hypoglycemic events and the likelihood of cognitive impairment. Furthermore, little research has been done on the dose-response association between hypoglycemia incidents and the possibility of cognitive impairment. To address these knowledge gaps, the present research intends to update the comprehension of the association among hypoglycemic events and the risk of cognitive impairment and to clarify the correlation between dose and response by incorporating the most recent investigations.

METHOD AND ANALYSIS

This work has developed a protocol for a systematic review and meta-analysis that will examine, via a well-organized assessment of several databases, the relationship between the incidence of hypoglycemia and the probability of cognitive impairment. Observational studies investigating the connection between hypoglycemia episodes and cognitive impairment will be included. The databases that will be searched are PubMed, Web of Science, the Chinese Biomedical Literature Database (CBM), Cochrane Library, Embase, the China National Knowledge (CNKI), Wan Fang, the Chinese Science and Technology Periodical Database (VIP), and Du Xiu. Literature from the establishment of each database to December 2023 will be included in the search. Two researchers will independently screen the studies that satisfy the requirements for both inclusion and exclusion. A third researcher will be asked to mediate any disputes. The methodological caliber of the studies included will be assessed utilizing the Newcastle-Ottawa Scale (NOS) or the Joanna Briggs Institute (JBI) critical appraisal method. With regard to GRADE, which stands for Grading of Recommendations, Assessment, Development, and Evaluation, the quality of the evidence will be evaluated. ROBIS Tool will be used to evaluate the risk of bias in the development of the systematic review. If the data is accessible, meta-analysis and dose-response curve analysis will be employed by Stata software. However, if the data does not allow for such analysis, a descriptive review will be performed.

DISCUSSION AND CONCLUSION

Hypoglycemic episodes may raise the likelihood of cognitive impairment, according to earlier investigations. This study will update the relevant evidence and explore the dose-response connection between hypoglycemic episodes and cognitive impairment. The results of this review will have significant effects on decision-making by individuals with diabetes, healthcare providers, and government policy institutions.

TRIAL REGISTRATION

Prospero registration number: CRD42023432352.

Systemic Metabolism and Mitochondria in the Mechanism of Alzheimer's Disease: Finding Potential Therapeutic Targets

Elderly people over the age of 65 are those most likely to experience Alzheimer's disease (AD), and aging and AD are associated with apparent metabolic alterations. Currently, there is no curative medication against AD and only several drugs have been approved by the FDA, but these drugs can only improve the symptoms of AD. Many preclinical and clinical trials have explored the impact of adjusting the whole-body and intracellular metabolism on the pathogenesis of AD. The most recent evidence suggests that mitochondria initiate an integrated stress response to environmental stress, which is beneficial for healthy aging and neuroprotection. There is also an increasing awareness of the differential risk and potential targeting strategies related to the metabolic level and microbiome. As the main participants in intracellular metabolism, mitochondrial bioenergetics, mitochondrial quality-control mechanisms, and mitochondria-linked inflammatory responses have been regarded as potential therapeutic targets for AD. This review summarizes and highlights these advances.

Type 2 diabetes mellitus and cognitive function: understanding the connections

PURPOSE OF REVIEW

To review the connection between type 2 diabetes and cognitive dysfunction, including its epidemiology, potential mechanisms of pathophysiology, risk factors, possible prevention, and treatment considerations.

RECENT FINDINGS

Diabetes is a risk factor for mild cognitive decline, in addition to Alzheimer's disease and vascular dementia. Duration of diabetes, concomitant vascular or associated co-morbidities, hyper- and hypoglycemia may lead to worsening cognitive dysfunction. Unfortunately, there is a lack of evidence-based guidance on the prevention of cognitive dysfunction in the diabetes population. Studies of diabetes medications, including metformin, glucagon-like peptide-1 (GLP-1) receptor agonists, and sodium-glucose cotransporter-2 inhibitors (SGLT2) have shown some benefit with cardiovascular morbidity and may affect cognition. In the absence of clearly defined preventive tools, diabetes practice guidelines recommend annual cognitive screening as standard of care in adults with diabetes aged 65 years or older.

SUMMARY

People living with diabetes are at risk for significant decline in cognitive function. Epidemiology and risk factors are well defined. Prevention and treatment strategies are limited and require further study.

Great diversity in the utilization and reporting of latent growth modeling approaches in type 2 diabetes: A literature review

Introduction

The progression of complications of type 2 diabetes (T2D) is unique to each patient and can be depicted through individual temporal trajectories. Latent growth modeling approaches (latent growth mixture models [LGMM] or latent class growth analysis [LCGA]) can be used to classify similar individual trajectories in a priori non-observed groups (latent groups), sharing common characteristics. Although increasingly used in the field of T2D, many questions remain regarding the utilization of these methods.

Objective

To review the literature of longitudinal studies using latent growth modeling approaches to study T2D.

Methods

MEDLINE (Ovid), EMBASE, CINAHL and Wb of Science were searched through August 25^th, 2021. Data was collected on the type of latent growth modeling approaches (LGMM or LCGA), characteristics of studies and quality of reporting using the GRoLTS-Checklist and presented as frequencies.

Results

From the 4,694 citations screened, a total of 38 studies were included. The studies were published beetween 2011 and 2021 and the length of follow-up ranged from 8 weeks to 14 years. Six studies used LGMM, while 32 studies used LCGA. The fields of research varied from clinical research, psychological science, healthcare utilization research and drug usage/pharmaco-epidemiology. Data sources included primary data (clinical trials, prospective/retrospective cohorts, surveys), or secondary data (health records/registries, medico-administrative). Fifty percent of studies evaluated trajectory groups as exposures for a subsequent clinical outcome, while 24% used predictive models of group membership and 5% used both. Regarding the quality of reporting, trajectory groups were adequately presented, however many studies failed to report important decisions made for the trajectory group identification.

Conclusion

Although LCGA were preferred, the contexts of utilization were diverse and unrelated to the type of methods. We recommend future authors to clearly report the decisions made regarding trajectory groups identification.

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There is a growing body of literature on trajectory modeling in type 2 diabetes.

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Latent class growth analysis can be used in many different contexts.

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The current reporting of methods used should be improved.

Dysmetabolism and Neurodegeneration: Trick or Treat?

Accumulating evidence suggests the existence of a strong link between metabolic syndrome and neurodegeneration. Indeed, epidemiologic studies have described solid associations between metabolic syndrome and neurodegeneration, whereas animal models contributed for the clarification of the mechanistic underlying the complex relationships between these conditions, having the development of an insulin resistance state a pivotal role in this relationship. Herein, we review in a concise manner the association between metabolic syndrome and neurodegeneration. We start by providing concepts regarding the role of insulin and insulin signaling pathways as well as the pathophysiological mechanisms that are in the genesis of metabolic diseases. Then, we focus on the role of insulin in the brain, with special attention to its function in the regulation of brain glucose metabolism, feeding, and cognition. Moreover, we extensively report on the association between neurodegeneration and metabolic diseases, with a particular emphasis on the evidence observed in animal models of dysmetabolism induced by hypercaloric diets. We also debate on strategies to prevent and/or delay neurodegeneration through the normalization of whole-body glucose homeostasis, particularly via the modulation of the carotid bodies, organs known to be key in connecting the periphery with the brain.

Association between hypoglycemia and dementia in patients with diabetes: a systematic review and meta-analysis of 1.4 million patients

BACKGROUND

Diabetes mellitus (DM) is known to be a risk factor for dementia. However, it is unclear if hypoglycemic events play a role in the risk of dementia. We aimed to systematically review evidence on the risk of dementia in DM patients based on prior hypoglycemic events.

METHODS

PubMed, Embase, ScienceDirect, CENTRAL, and Google Scholar databases were searched till 15th November 2021 for cohort studies assessing the risk of dementia based on prior hypoglycemic events in DM patients. Adjusted data were pooled in a random-effects model.

RESULTS

Ten studies with a total of 1,407,643 patients were included. Pooled analysis of all ten studies indicated that hypoglycemic episodes were associated with a statistically significant increase in the risk of dementia in DM patients as compared to those not experiencing hypoglycemic episodes (HR: 1.44 95% CI: 1.26, 1.65 I² = 89% p < 0.00001). The results did not change on the exclusion of any study. Sub-group analysis based on the study population, type of study, adjustment for glycated hemoglobin, gender, and the number of hypoglycemic episodes also presented similar results.

CONCLUSIONS

Evidence from observational studies with a large sample size indicates that DM patients with hypoglycemic episodes are at increased risk of dementia. Anti-hyperglycemic drugs should be adequately tailored in these patients to avoid the risk of dementia.