Factors associated with cognitive decline in older adults with type 2 diabetes mellitus during a 6-year observation

The association of insulin responses and insulin sensitivity with cognition in adults with pre-diabetes: The Diabetes Prevention Program Outcomes Study

OBJECTIVE

Dysglycemia is a significant risk factor for cognitive impairment. However, which pathophysiologic determinant(s) of dysglycemia, impaired insulin sensitivity (ISens) or the islet β-cell's response (IResp), contribute to poorer cognitive function, independent of dysglycemia is not established. Among 1052 adults with pre-diabetes from the Diabetes Prevention Program Outcomes Study (DPPOS), we investigated the relationship between IResp, ISens and cognitive function.

RESEARCH DESIGN AND METHODS

IResp was estimated by the insulinogenic index (IGI; pmol/mmol) and ISens as 1/fasting insulin from repeated annual oral glucose tolerance tests. The mean IResp and mean ISens were calculated over approximately 12 years of follow-up. Verbal learning (Spanish-English Verbal Learning Test [SEVLT]) and executive function (Digital Symbol Substitution Test [DSST]) were assessed at the end of the follow-up period. Linear regression models were run for each cognitive outcome and were adjusted for dysglycemia and other factors.

RESULTS

Higher IResp was associated with poorer performance on the DSST (-0.69 points per 100 unit increase in IGI, 95 % CI: -1.37, -0.01). ISens was not associated with DSST, nor were IResp or ISens associated with performance on the SEVLT.

CONCLUSIONS

These results suggest that a greater β-cell response in people at high risk for type 2 diabetes is associated with poorer executive function, independent of dysglycemia and ISens.

Unveiling peripheral neuropathy and cognitive dysfunction in diabetes: an observational and proof-of-concept study with video games and sensor-equipped insoles

Background

Proactive screening for cognitive dysfunction (CD) and peripheral neuropathy (PNP) in elderly patients with diabetes mellitus is essential for early intervention, yet clinical examination is time-consuming and prone to bias.

Objective

We aimed to investigate PNP and CD in a diabetes cohort and explore the possibility of identifying key features linked with the respective conditions by machine learning algorithms applied to data sets obtained in playful games controlled by sensor-equipped insoles.

Methods

In a cohort of patients diagnosed with diabetes (n=261) aged over 50 years PNP and CD were diagnosed based on complete physical examination (neuropathy symptom and disability scores, and Montreal Cognitive Assessment). In an observational and proof-of-concept study patients performed a 15 min lasting gaming session encompassing tutorials and four video games with 5,244 predefined features. The steering of video games was solely achieved by modulating plantar pressure values, which were measured by sensor-equipped insoles in real-time. Data sets were used to identify key features indicating game performance with correlation regarding CD and PNP findings. Thereby, machine learning models (e.g. gradient boosting and lasso and elastic-net regularized generalized linear models) were set up to distinguish patients in the different groups.

Results

PNP was diagnosed in 59% (n=153), CD in 34% (n=89) of participants, and 23% (n=61) suffered from both conditions. Multivariable regression analyses suggested that PNP was positively associated with CD in patients with diabetes (adjusted odds ratio = 1.95; 95% confidence interval: 1.03-3.76; P=0.04). Predictive game features were identified that significantly correlated with CD (n=59), PNP (n=40), or both (n=59). These features allowed to set up classification models that were enriched by individual risk profiles (i.e. gender, age, weight, BMI, diabetes type, and diabetes duration). The obtained models yielded good predictive performance with the area under the receiver-operating-characteristic curves reaching 0.95 for CD without PNP, 0.83 for PNP without CD, and 0.84 for CD and PNP combined.

Conclusions

The video game-based assessment was able to categorize patients with CD and/or PNP with high accuracy. Future studies with larger cohorts are needed to validate these results and potentially enhance the discriminative power of video games.

Association Between Antidiabetic Drugs and Delirium: A Study Based on the Adverse Drug Event Reporting Database in Japan

BACKGROUND AND OBJECTIVE

Several associations between diabetes mellitus and delirium have been reported; however, they have been inconsistent, and evidence on the effects of antidiabetic medications on delirium is also limited. This study aimed to investigate whether the use of antidiabetic drugs is a risk factor for delirium development.

METHODS

Using the Japanese Adverse Event Reporting Database, we analyzed 662,899 reports between 2004 and 2022. Reporting odds ratios (RORs) and 95% confidence intervals (CIs) for delirium associated with diabetes and using each antidiabetic medication were calculated after adjusting for potential confounders.

RESULTS

Overall, 8892 of the reports analyzed were associated with delirium. A comparison of the incidence of delirium between patients with and without diabetes showed no significant difference, with 1.34% in patients without diabetes and 1.37% in those with diabetes. In each antidiabetic medication, signals for delirium were detected for sulfonylurea (crude ROR, 1.35; 95% CI 1.21-1.51) and insulin (crude ROR, 1.28; 95% CI 1.13-1.44). These results were maintained even after adjusting for factors with potential confounders (sulfonylurea: adjusted ROR, 1.75; 95% CI 1.54-2.00, insulin: adjusted ROR, 1.35; 95% CI 1.20-1.54).

CONCLUSIONS

Our results suggest no association between diabetes and delirium; however, using sulfonylurea and insulin may be associated with delirium development. Nonetheless, these findings should be validated in future studies.

Dementia in Diabetes: The Role of Hypoglycemia

Hypoglycemia, a common consequence of diabetes treatment, is associated with severe morbidity and mortality and has become a major barrier to intensifying antidiabetic therapy. Severe hypoglycemia, defined as abnormally low blood glucose requiring the assistance of another person, is associated with seizures and comas, but even mild hypoglycemia can cause troubling symptoms such as anxiety, palpitations, and confusion. Dementia generally refers to the loss of memory, language, problem-solving, and other cognitive functions, which can interfere with daily life, and there is growing evidence that diabetes is associated with an increased risk of both vascular and non-vascular dementia. Neuroglycopenia resulting from a hypoglycemic episode in diabetic patients can lead to the degeneration of brain cells, with a resultant cognitive decline, leading to dementia. In light of new evidence, a deeper understating of the relationship between hypoglycemia and dementia can help to inform and guide preventative strategies. In this review, we discuss the epidemiology of dementia among patients with diabetes, and the emerging mechanisms thought to underlie the association between hypoglycemia and dementia. Furthermore, we discuss the risks of various pharmacological therapies, emerging therapies to combat hypoglycemia-induced dementia, as well as risk minimization strategies.

The predictive value of fibrinogen in the occurrence of mild cognitive impairment events in patients with diabetic peripheral neuropathy

BACKGROUND

Research suggests that fibrinogen (Fib) is related to mild cognitive impairment (MCI) and diabetic peripheral neuropathy (DPN) and the risk of MCI in patients with DPN is greatly increased, although no studies have evaluated the predictive value of Fib for the risk of MCI in patients with DPN.

METHODS

This prospective observational clinical study enrolled 207 type 2 diabetes mellitus (T2DM) patients, who were divided into diabetes with no neuropathy (102 cases) and diabetes with neuropathy (105 cases) groups. Meanwhile, 90 healthy unrelated subjects were recruited as controls. The incidence of MCI in the DPN patients was followed up for 2 years. Divide patients in the DPN group into subgroups according to whether MCI occur, use multivariate logistic regression to analyze independent factors of MCIs in DPN patients within 2 years, and use ROC curve to analyze the predictive value of Fib for MCI in DPN patients.

RESULTS

Fib levels were significantly higher in diabetic subjects with neuropathy compared with those without (P < 0.001). In further subgroup analysis of DPN patients who were divided according to the occurrence of MCI, baseline data of the MCI subgroup showed Fib levels were higher than that in the non-MCI group while education levels declined (P < 0.001). The education level and increased Fib levels were independent factors for the occurrence of MCI within 2 years after the onset of DPN (OR = 0.769, 95% CI: 0.605 ~ 0.968, P = 0.037; OR = 2.674, 95% CI: 1.094 ~ 3.168, P = 0.002). The ROC curve indicated that the predictive value of Fib was (AUC = 0.764, 95% CI: 0.671 ~ 0.842, P < 0.001).

CONCLUSIONS

Fib may function as a predictor for assessing the risk of MCI in DPN patients.

Diagnostic, Prognostic, and Mechanistic Biomarkers of Diabetes Mellitus-Associated Cognitive Decline

Cognitive dysfunctions such as mild cognitive impairment (MCI), Alzheimer's disease (AD), and other forms of dementia are recognized as common comorbidities of type 2 diabetes mellitus (T2DM). Currently, there are no disease-modifying therapies or definitive clinical diagnostic and prognostic tools for dementia, and the mechanisms underpinning the link between T2DM and cognitive dysfunction remain equivocal. Some of the suggested pathophysiological mechanisms underlying cognitive decline in diabetes patients include hyperglycemia, insulin resistance and altered insulin signaling, neuroinflammation, cerebral microvascular injury, and buildup of cerebral amyloid and tau proteins. Given the skyrocketing global rates of diabetes and neurodegenerative disorders, there is an urgent need to discover novel biomarkers relevant to the co-morbidity of both conditions to guide future diagnostic approaches. This review aims to provide a comprehensive background of the potential risk factors, the identified biomarkers of diabetes-related cognitive decrements, and the underlying processes of diabetes-associated cognitive dysfunction. Aging, poor glycemic control, hypoglycemia and hyperglycemic episodes, depression, and vascular complications are associated with increased risk of dementia. Conclusive research studies that have attempted to find specific biomarkers are limited. However, the most frequent considerations in such investigations are related to C reactive protein, tau protein, brain-derived neurotrophic factor, advanced glycation end products, glycosylated hemoglobin, and adipokines.

Kidney Function and Risk of Physical and Cognitive Impairment in Older Persons with Type 2 Diabetes at an Outpatient Clinic with Geriatric Assessment Implementation

PURPOSE

Diabetes is associated with an increased risk of cognitive and physical functional decline that may impede disease self-management. By incorporating cognitive and physical function assessment, this study aimed to evaluate prevalence and factors associated with cognitive and physical dysfunction in older diabetic people.

METHODS

The cross-sectional study was performed from August 1, 2017 to November 30, 2018. The patients aged 65 years or older with type 2 diabetes mellitus were enrolled and the disease was routinely evaluated by blood hemoglobin A1c (A1C), blood pressure, lipids, and kidney function measured by estimated glomerular filtration rate (eGFR) and urinary albumin-creatinine rate (UACR). Besides, cognitive dysfunction through Mini-mental State Examination (MMSE), and functional disabilities by Activities of Daily Living (ADL) questionnaire were assessed simultaneously.

RESULTS

Among 863 patients (48.3% men) with a median age of 72.0 years (interquartile range or IQR: 67.0-78.0 years), 159 (18.5%) had cognitive impairment assessed by MMSE, while 40 (4.6%) experienced at least one problem in ADL. With different A1C stratifications, it was shown that both MMSE and ADL scores were associated with glycemic control. Patients with impaired MMSE and ADL scores were older, had lower eGFR, lower blood pressure, and higher UACR levels. After adjustment of possible confounders, it was shown that age and eGFR predicted MMSE and ADL score impairment.

CONCLUSION

By incorporating physical and cognitive function screening program into routine care at a diabetes outpatient clinic, our study found that both cognitive and physical function impairment were common in older diabetic patients, and their relevant factors, including older age, and lower eGFR. It was recommended that in older individuals with diabetes, particularly those with risk factors, an additional assessment of cognitive and physical functions can be integrated into routine clinical process to provide more comprehensive management plans.

Cognitive impairment in type 2 diabetes patients with and without diabetic peripheral neuropathy: a mismatch negativity study

OBJECTIVES

To assess the cognitive impairment in patients with type 2 diabetes mellitus (T2DM) using mismatch negativity (MMN) and to explore the relationship between cognitive impairment and diabetic peripheral neuropathy (DPN).

METHODS

Sixty-six T2DM patients and 40 healthy controls were included. For each participant, mini-mental state examination (MMSE) was applied to assess the general cognitive function and MMN was elicited. T2DM patients were divided into two subgroups: subgroup DPN-, patients without DPN; subgroup DPN+, patients with DPN. The MMSE scores, MMN amplitudes and latencies were compared between the T2DM group and the control group using univariate analysis of variance procedures, and also among the controls, subgroup DPN- and subgroup DPN+. Pearson's correlation coefficients (r) were used to analyze potential confounding clinical factors associated with MMN.

RESULTS

T2DM patients had significantly lower MMSE scores compared with controls (23.25 ± 2.86 vs. 27.15 ± 1.83; P < 0.01), whereas those of the two subgroups were not significantly different. Both subgroup DPN+ and DPN- had longer latencies and lower amplitudes of MMN than the controls. The latencies of MMN were significantly longer in subgroup DPN+ compared with subgroup DPN-. The latency of MMN was positively correlated with the duration of the disease.

CONCLUSION

Cognitive decline exists in patients with T2DM irrespective of the presence of DPN. Patients with DPN may have more severe cognitive dysfunction than those without DPN. MMN may be a promising tool for evaluating cognitive function.

Oxidative stress and endothelial dysfunction are associated with reduced cognition in type 2 diabetes

OBJECTIVE

Type 2 diabetes is associated with cognitive dysfunction, but the mechanisms are unknown. We assessed the relationships of biomarkers of oxidation, endothelial function and inflammation with cognition in participants of the CAROLINA^® trial (CARdiovascular Outcome Trial of LINAgliptin Versus Glimepiride in Type 2 Diabetes).

METHODS

Baseline circulating biomarkers of oxidation (8-iso-prostaglandin F2α), endothelial function (asymmetric dimethylarginine, endothelin-1) and inflammation (C-reactive protein, interleukin-6, tumour necrosis factor-α), based on linear regression, were related to cognition on five domains, as measured with an automated battery.

RESULTS

In 37 patients (mean age 66.7 ± 8.7 years, median HbA1c 6.9%/52 mmol/mol), 8-iso-prostaglandin F2α was associated with reduced mental flexibility and attention (standardised regression coefficients -0.47, -0.34), whereas asymmetric dimethylarginine was associated with reduced psychomotor speed and attention (standardised regression coefficients -0.39, -0.34). No significant associations were observed between biomarkers of inflammation and cognition.

CONCLUSION

Elevated biomarkers of oxidation and endothelial function are associated and may play a role in reduced psychomotor speed, mental flexibility and attention in type 2 diabetes.

Impact of pharmacological treatment of diabetes mellitus on dementia risk: systematic review and meta-analysis

BACKGROUND

The association between diabetes mellitus (DM) treatment and dementia is not well understood.

OBJECTIVE

To investigate the association between treatment of diabetes, hypoglycemia, and dementia risk.

RESEARCH DESIGN AND METHODS

We performed a systematic review and meta-analysis of pharmacological treatment of diabetes and incident or progressive cognitive impairment. We searched Ovid MEDLINE, Embase, Cochrane Central Registry of Controlled Trials, and PsychINFO from inception to 18 October 2017. We included cross-sectional, case-control, cohort, and randomized controlled studies. The study was registered with PROSPERO (ID CRD42017077953).

RESULTS

We included 37 studies into our systematic review and 13 into our meta-analysis. Ten studies investigated any antidiabetic treatment compared with no treatment or as add-on therapy to prior care. Treatment with an antidiabetic agent, in general, was not associated with incident dementia (risk ratio (RR) 1.01; 95% CI 0.93 to 1.10). However, we found differential effects across drug classes, with a signal of harm associated with insulin therapy (RR 1.21; 95% CI 1.06 to 1.39), but potentially protective effects with thiazolidinedione exposure (RR 0.71; 95% CI 0.55 to 0.93). Severe hypoglycemic episodes were associated with a nearly twofold increased likelihood of incident dementia (RR 1.77; 95% CI 1.35 to 2.33). Most studies did not account for DM duration or severity.

CONCLUSIONS AND LIMITATIONS

The association between treatment for diabetes and dementia is differential according to drug class, which is potentially mediated by hypoglycemic risk. Not accounting for DM duration and/or severity is a major limitation in the available evidence base.

Potential Risk Factors of the Cognitive Dysfunction in Patients with Type 2 Diabetes Mellitus

It is known that the aged persons with type 2 diabetes mellitus present a high risk for developing neurocognitive disorders and in order to explain this phenomenon we have proposed some potential risk factors. They can be involved in the causality patterns or can act as useful markers of the cerebrovascular lesions (or both) and for which there are strong proofs, including the poor glycemic control, hypoglycemia, microvascular diseases, inflammation or depression. For the macrovascular affections, the association with the cognitive disorders seems to devolve on the examined vascular system. It is put into discussion that for the next researches it is important to analyze how exactly the interrelations between the risk factors can contribute to cognitive disorders.

Inflammation: the link between comorbidities, genetics, and Alzheimer's disease

Alzheimer’s disease (AD) is a neurodegenerative disorder, most cases of which lack a clear causative event. This has made the disease difficult to characterize and, thus, diagnose. Although some cases are genetically linked, there are many diseases and lifestyle factors that can lead to an increased risk of developing AD, including traumatic brain injury, diabetes, hypertension, obesity, and other metabolic syndromes, in addition to aging. Identifying common factors and trends between these conditions could enhance our understanding of AD and lead to the development of more effective treatments. Although the immune system is one of the body’s key defense mechanisms, chronic inflammation has been increasingly linked with several age-related diseases. Moreover, it is now well accepted that chronic inflammation has an important role in the onset and progression of AD. In this review, the different inflammatory signals associated with AD and its risk factors will be outlined to demonstrate how chronic inflammation may be influencing individual susceptibility to AD. Our goal is to bring attention to potential shared signals presented by the immune system during different conditions that could lead to the development of successful treatments.

Relationship between Insulin Levels and Nonpsychotic Dementia: A Systematic Review and Meta-Analysis

Objectives

To explore the relationship between insulin levels and nonpsychotic dementia.

Methods

Six electronic databases (PubMed, Cochrane, SCI, CNKI, VIP, and Wanfang) were searched from January 1, 2007, to March 1, 2017. Experimental or observational studies that enrolled people with nonpsychotic dementia or abnormal insulin levels in which insulin levels or MMSE scores (events in nonpsychotic dementia) were the outcome measures. Random-effects models were chosen for this meta-analysis. Sample size, mean, s.d., and events were primarily used to generate effect sizes (with the PRIMA registration number CRD42017069860).

Results

50 articles met the final inclusion criteria. Insulin levels in cerebrospinal fluid were lower (Hedges' g = 1.196, 95% CI = 0.238 to 2.514, and P = 0.014), while the levels in peripheral blood were higher in nonpsychotic dementia patients (Hedges' g = 0.853 and 95% CI = 0.579 to 1.127), and MMSE scores were significantly lower in the high insulin group than in the healthy control group (Hedges' g = 0.334, 95% CI = 0.249 to 0.419, and P = 0.000).

Conclusions

Our comprehensive results indicate that blood insulin levels may increase in patients with nonpsychotic dementia.

High Hemoglobin A1c and Diabetes Predict Memory Decline in the Health and Retirement Study

BACKGROUND

Type 2 diabetes (T2D) is an established risk factor for dementia, but evidence for T2D and memory decline is less consistent. Understanding how T2D and blood glucose relate to memory decline is crucial to elucidating the mechanisms linking T2D and dementia.

MATERIALS AND METHODS

For 8888 Health and Retirement Study participants aged 50+, glycosylated hemoglobin (HbA1c) was measured in either 2006 or 2008 and physician's diagnosis of diabetes was self-reported in the same year. Composite memory (z scored) was assessed biennially through 2012 using immediate and delayed word list recall or the Informant Questionnaire for Cognitive Decline. Marginal mean regression models for repeated outcomes were specified to predict memory decline as a function of diabetes or HbA1c, using age as the timescale and adjusting for health and social confounders.

RESULTS

Diabetes was associated with a 10% faster rate of memory decline [β=-0.04 per decade; 95% confidence interval (CI), -0.06 to -0.01). A 1 U increase in HbA1c corresponded with a 0.05 SD decrease in memory score per decade (95% CI, -0.08 to -0.03). Even among individuals with HbA1c<6.5% (threshold for diabetes), higher HbA1c was associated with memory decline (β=-0.05 per decade; 95% CI, -0.08 to -0.03).

DISCUSSION

Diabetes accelerated memory loss and higher HbA1c predicted memory decline even in nondiabetics.

Obese adolescents with type 2 diabetes perform worse than controls on cognitive and behavioral assessments

BACKGROUND

Children with type 1 diabetes demonstrate worse cognitive performance compared with their peers. Little is known regarding the cognitive and behavioral performance in obese adolescents with type 2 diabetes.

METHODS

Cross sectional evaluation of 20 obese adolescents with type 2 diabetes and 20 healthy adolescents was performed in Cincinnati, Ohio. Cognitive tests that included measures of processing speed, working memory, verbal and semantic fluency and parent reports of executive function and problem behavior were compared. Academic achievement and the relationship between cognitive/behavioral scores and diabetes duration and diabetes control (hemoglobin A1c) were assessed in the type 2 diabetes group only.

RESULTS

The type 2 diabetes group had mean duration of diabetes of 2.8 ± 2.2 yr and hemoglobin A1c of 7.9 ± 2.2%. Adolescents with type 2 diabetes scored lower than controls on tests of working and verbal memory and processing speed (all p < 0.05) and worse for Internalizing, Externalizing, and Total Problems behaviors on the Child Behavior Checklist (all p < 0.05). Adolescents with type 2 diabetes scored below the population mean in academic achievement, most notably calculation. Working memory and processing speed were negatively correlated with duration of diabetes (r = -0.50 and -0.47, respectively, p < 0.05).

CONCLUSIONS

Obese youth with type 2 diabetes score poorly compared with controls on multiple assessments of cognitive function and adaptive behavior. Further work is needed to determine if these effects are driven by obesity, diabetes or other demographic and socioeconomic risk factors.

Low serum HDL-cholesterol concentrations in mid-life predict late-life cognitive impairment in type 2 diabetes: The Fremantle diabetes study

In a study involving patients with type 2 diabetes assessed annually over 5years, serum HDL-cholesterol was the sole mid-life metabolic predictor of late-life cognitive impairment.

Insulin resistance and cognitive performance in type 2 diabetes - The Maastricht study

AIMS

Type 2 diabetes, hyperinsulinemia, and insulin resistance are associated with cognitive impairment. Experimental studies indicate that insulin signaling in the brain is related to cognitive performance. Here we evaluated whether insulin-related variables contribute to the variance in cognitive performance among individuals with type 2 diabetes.

METHODS

A total of 806 individuals with type 2 diabetes (mean age 62±8years, HbA1c 6.9±1.1%) completed a neuropsychological test battery. Insulin-related variables evaluated were: fasting plasma insulin, C-peptide, and the Homeostasis Model Assessment (HOMA2-IR; in individuals without insulin treatment; n=641). The unadjusted coefficient of determination (R²), obtained from multiple linear regression analyses, was used to estimate the proportion of variance in cognition explained by insulin-related variables.

RESULTS

Sex, age, and educational level together explained 18.0% (R²) of the variance in memory function, 26.5% in information processing speed, and 22.8% in executive function and attention. Fasting insulin, C-peptide, or HOMA2-IR did not increase the explained variance (maximum ΔR² 0.3%, P≥0.14). Similar results were obtained when insulin-related variables were added to models that additionally included glycemic control, cardiovascular risk factors, and depression.

CONCLUSIONS

Our results show that measures of peripheral insulin resistance are unrelated to cognitive performance among individuals with adequately controlled type 2 diabetes.

Gender differences in cognitive deficits in schizophrenia with and without diabetes

This study investigated gender differences in cognition in schizophrenia with and without diabetes. Cognition was assessed in 263 individuals with schizophrenia with age range (40-68): 67 males and 34 females with schizophrenia with diabetes; and 125 males and 37 females with schizophrenia without diabetes according to the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). Fasting glucose, hemoglobin A1c (HbA1c) and lipid levels were measured. Results showed that male individuals performed worse on most cognitive tasks, especially attention, in schizophrenia with than without diabetes. This result was not observed in female individuals. Also, individuals of both genders showed higher fasting glucose and HbA1c in schizophrenia with than without diabetes. In schizophrenia with diabetes, males had significantly worse cognition than females in all cognitive domains. Higher HbA1c, lower high-density lipoprotein, and an earlier age of onset of schizophrenia were found in males compared with female individuals. HbA1c was negatively associated with attention and the RBANS total score for males but not for females. In schizophrenia without diabetes, males showed worse performance in immediate and delayed memory than females. This study support cognition was worse for males with schizophrenia irrespective of whether they have diabetes. However, diabetes exemplified the gender differences, especially in attention.

Cardiovascular risk factors and cognitive decline in older people with type 2 diabetes

AIMS/HYPOTHESIS

The aim of this work was to assess the role of well-established cardiovascular risk factors in the late-life cognitive decline of patients with type 2 diabetes.

METHODS

Data from 831 participants (aged 60-75 years) attending the 4 year follow-up of the Edinburgh Type 2 Diabetes Study (ET2DS) were used. Smoking history (pack-years), BP, HbA1c, plasma glucose and cholesterol were determined at baseline clinics (single time measurements) and/or from serial data recorded on a clinical management database from diagnosis until recruitment ('historical' data). Principal component analysis derived a factor, g, of general ability from seven cognitive tests. Linear regression models of follow-up g were adjusted for baseline g to represent 4 year cognitive change. 'Accelerated late-life cognitive decline' was defined as scoring in the lowest tertile of '4 year cognitive change' regression scores. Analyses controlled for age and sex.

RESULTS

A baseline history of moderate/heavy smoking (≥ 10 pack-years) and a 1% increased historical HbA1c (equivalent to an increase by 11 mmol/mol) predicted a 64% (OR 1.64; 95% CI 1.14, 2.34; p = 0.007) and 21% (OR 1.21; 95% CI 1.00, 1.45; p = 0.046) increased risk of accelerated cognitive decline, respectively. When treated as continuous measures, higher pack-years, historical HbA1c and historical BP emerged as significant independent predictors of 4 year decline in g (standardised β range -0.07 to -0.14; all p ≤ 0.05).

CONCLUSIONS/INTERPRETATION

Increased smoking and poorer glycaemic control (with relatively weaker findings for BP) during the life-course were independently associated with accelerated late-life cognitive decline. Where possible, evaluation is warranted of these risk factors as targets for intervention to reduce the burden of cognitive impairment in diabetes.

The impact of diabetes on cognitive decline: potential vascular, metabolic, and psychosocial risk factors

Older people with type 2 diabetes are at increased risk of developing cognitive impairment, for which several potential risk factors have been proposed. The present article reviews evidence in people with type 2 diabetes for associations of cognitive impairment with a range of vascular, metabolic, and psychosocial risk factors, many of which have a higher prevalence in people with type 2 diabetes than in non-diabetic adults of a similar age. Definitive research studies in this field are few in number. The risk factors may be involved in causal pathways or may act as useful markers of cerebrovascular damage (or both), and for which relatively consistent evidence is available, include poor glycemic control, hypoglycemia, microvascular disease, inflammation, and depression. For macrovascular disease, the strength of the association with cognitive impairment appears to depend on which vascular system has been examined. A role for pre-morbid ability in young adulthood as influencing the risk of both diabetes and cognitive impairment has also been suggested. The importance of considering inter-relationships between risk factors when investigating their potential contribution to cognitive impairment in future investigations is discussed.

Is cognitive impairment associated with the presence and severity of peripheral neuropathy in patients with type 2 diabetes mellitus?

BACKGROUND

Peripheral Diabetic Neuropathy (PDN) and cognitive impairment are complications of Diabetes Mellitus (DM) that seem to share several underlying mechanisms. The aim of this study was to investigate whether diabetic patients would have worse cognitive function than non diabetic individuals and within diabetic patients, whether those with PDN would present an even more significant cognitive impairment.

FINDINGS

Ninety four (94) outpatients with Type 2 DM were sequentially evaluated. Also, Fifty four (54) healthy individuals were sequentially selected to match the diabetic group. For the assessment of neuropathy, Portuguese versions of the Neuropathy Disability Score (NDS) and Neuropathy Symptom Score (NSS) were used. Global cognitive function was assessed by using the Portuguese Version of the Mini-Mental State Examination (MMSE), Trail Making Tests A and B and Verbal Fluency Test. Significantly lower scores were found in the Type 2 DM group in comparison to control group in the MMSE (25.7 [16-30] vs 27.6 [19-30]; p <0.001). Within T2DM group, forty five (45) patients were diagnosed with PDN. No differences were found between patients with and without PDN in all cognitive tests (p >0.05 in all comparison). No correlation was also found among NSS, NDS and any of the cognitive tests.

CONCLUSION

Although diabetic patients do have a worse cognitive function, this impairment does not seem to be related to the presence and/or severity of PDN.