Effects of glycemic variability and hyperglycemia in acute ischemic stroke on post-stroke cognitive impairments

Cognitive impairment and hippocampal degeneration in aged rat models of type 2 diabetes with induced glycemic fluctuation: A pilot study

OBJECTIVE

Effective methods for establishing an aged animal model of diabetes and glycemic fluctuation have rarely been investigated. The aim of the study was to explore the feasibility of inducing glycemic fluctuation in aged Sprague-Dawley rats and to evaluate the corresponding changes in cognitive function.

METHODS

Male rats aged 48 weeks were fed a high-fat and high-glucose diet and given streptozotocin intraperitoneally to establish a rat model of type 2 diabetes mellitus (T2DM). Then, glycemic fluctuation was induced via three different protocols: (1) intraperitoneal injection of glucose; (2) sequential fasting, insulin injection, and normal diet; and (3) intermittent intraperitoneal injections of glucose and insulin.

RESULTS

All three protocols were effective at inducing glycemic fluctuation in aged rats with T2DM, with successful modeling rates of 60 %, 90 %, and 70 %, respectively. Aged T2DM rats with glycemic fluctuation showed significant increases in glycemic variability compared with controls, including in the mean blood glucose, postprandial glycemic excursion, largest amplitude of glycemic excursion, and standard deviation of blood glucose values (all P < 0.05). Additionally, rats with glycemic fluctuation had more severe insulin resistance and dyslipidemia (P < 0.05). Morris water maze testing showed a trend of longer escape latency in the navigation test for rats in the glycemic fluctuation groups, suggesting impaired cognitive function. Pathological analysis showed degenerative changes in the CA1 hippocampal region of rats in the glycemic fluctuation groups. Finally, differential gene expression analysis revealed 1323 significantly altered genes in the GV group, with 691 upregulated and 632 downregulated. The dysregulated genes were predominantly associated with the axon guidance pathway and potassium channel regulation.

CONCLUSIONS

The proposed protocols were effective at establishing an aged T2DM rat model with glycemic fluctuation, and rats with glycemic fluctuation exhibited diminished cognitive function.

Evaluation of Glycemic Variability and Discharge Outcomes in Patients with Ischemic Stroke Following Thrombolysis

Background and Purpose

Hyperglycemia following acute ischemic stroke (AIS) is associated with adverse outcomes including, hemorrhagic conversion and increased length of stay; however, the impact of glycemic variability is largely unknown. This study aims to evaluate the effect of glycemic variability on discharge outcomes in patients treated with alteplase for AIS.

Methods

A retrospective review of ischemic stroke patients who presented within 4.5 hours from symptom onset and received alteplase was completed. Patients hospitalized for at least 48 hours were included. Glycemic variability was measured using J-index. Groups were defined by normal or abnormal J-indices. Logistic regression models were developed to determine odds ratios for select clinical characteristics, NIHSS score, mRS, and disposition at discharge.

Results

Of the 229 patients, 97 (42%) had an abnormal J-index. In the univariate analysis, abnormal J-index was associated with worse outcomes in terms of NIHSS score, mRS, and discharge disposition compared to a normal J-index. In the unadjusted multivariate analysis, abnormal J-index was associated with higher odds of unfavorable mRS (3-6) at discharge (OR 2.1; 95% CI 1.2 - 3.5, P = .009). In the adjusted multivariate analysis, patients with an abnormal J-index had higher odds of hemorrhagic transformation (OR 5.7; 95% CI 2.1 - 15.6, P < .0001). There was no difference in mortality.

Conclusion

Glycemic variability with abnormal J-index following AIS is associated with adverse functional outcomes at discharge and increased odds of hemorrhagic conversion in patients treated with alteplase. Additional studies validating glycemic variability indices post-ischemic stroke are needed to determine the full clinical impact.

Effect of glycemic variability on infectious outcomes in critically Ill burn patients

After acute burn injury, patients experience a hypermetabolic state often complicated by a stress-induced hyperglycemia. Recent research points towards glycemic variability as a contributing factor in adverse outcomes in critically ill patients. In burn patients, greater glycemic variability has been associated with increased rates of mortality and sepsis. However, no studies to date have examined the impact of glycemic variability on rates of infection in this population or determined which measure may be most useful. Infection, and subsequent sepsis, remains the leading contributor to morbidity and mortality after burn injury. The primary objective of this study is to evaluate the relationship between different measures of glycemic variability and infectious complications in burn patients. This retrospective study included patients admitted to a single American Burn Association-verified burn center between January 1, 2020 and December 31, 2020 with burn or inhalation injury. The primary outcome was a composite of autograft loss, mortality, and proven infection. Secondary outcomes included hospital length of stay and a further analysis of the proven infection component of the composite primary outcome. In addition to mean glucose, several different measures of glycemic variability were used for comparison, including standard deviation, coefficient of variation, mean amplitude of glycemic excursions, and J-index. Outcomes were analyzed using multiple logistic regression analysis while controlling for revised Baux score. A quantile analysis was performed to do determine the optimal mean threshold. Three hundred and ninety-two patients were admitted and screened for inclusion during the study period. Most patients were excluded due to a LOS less than 72 h. 112 patients were included in the study. Of the 112 patients, 22.3% experienced an infectious complication (25 patients with 28 complications). Mean glucose (OR 1.024; 95% CI 1.004-1.045) and J-index (OR 1.044; 95% CI 1.003-1.087) were associated with occurrence of infectious complications. Regarding target mean glucose threshold, a daily mean glucose above 150 mg/dL showed the strongest association with infectious complications (OR 3.634; 95% CI 1.008-13.101). Mean glucose, standard of deviation, and J-index were all independently associated with proven infection.

Network analysis of neuropsychiatric, cognitive, and functional complications of stroke: implications for novel treatment targets

AIM

Recovery from stroke is adversely affected by neuropsychiatric complications, cognitive impairment, and functional disability. Better knowledge of their mutual relationships is required to inform effective interventions. Network theory enables the conceptualization of symptoms and impairments as dynamic and mutually interacting systems. We aimed to identify interactions of poststroke complications using network analysis in diverse stroke samples.

METHODS

Data from 2185 patients were sourced from member studies of STROKOG (Stroke and Cognition Consortium), an international collaboration of stroke studies. Networks were generated for each cohort, whereby nodes represented neuropsychiatric symptoms, cognitive deficits, and disabilities on activities of daily living. Edges characterized associations between them. Centrality measures were used to identify hub items.

RESULTS

Across cohorts, a single network of interrelated poststroke complications emerged. Networks exhibited dissociable depression, apathy, fatigue, cognitive impairment, and functional disability modules. Worry was the most central symptom across cohorts, irrespective of the depression scale used. Items relating to activities of daily living were also highly central nodes. Follow-up analysis in two studies revealed that individuals who worried had more densely connected networks than those free of worry (CASPER [Cognition and Affect after Stroke: Prospective Evaluation of Risks] study: S = 9.72, P = 0.038; SSS [Sydney Stroke Study]: S = 13.56, P = 0.069).

CONCLUSION

Neuropsychiatric symptoms are highly interconnected with cognitive deficits and functional disabilities resulting from stroke. Given their central position and high level of connectedness, worry and activities of daily living have the potential to drive multimorbidity and mutual reinforcement between domains of poststroke complications. Targeting these factors early after stroke may have benefits that extend to other complications, leading to better stroke outcomes.

Relationship between acute glucose variability and cognitive decline in type 2 diabetes: A systematic review and meta-analysis

BACKGROUND

Cognitive decline is one of the most widespread chronic complications of diabetes, which occurs in more than half of the patients with type 2 diabetes (T2DM). Emerging evidences have suggested that glucose variability (GV) is associated with the pathogenesis of diabetic complications. However, the influence of acute GV on cognitive dysfunction in T2DM is still controversial. The aim of the study was to evaluate the association between acute GV and cognitive defect in T2DM, and provide a most recent and comprehensive summary of the evidences in this research field.

METHODS

PubMed, Cochrane library, EMBASE, Web of science, Sinomed, China National Knowledge Infrastructure (CNKI), and Wanfang were searched for articles that reported on the association between acute GV and cognitive impairment in T2DM.

RESULTS

9 eligible studies were included, with a total of 1263 patients with T2DM involved. Results showed that summary Fisher's z value was -0.23 [95%CI (-0.39, -0.06)], suggesting statistical significance (P = 0.006). Summary r value was -0.22 [95%CI (-0.37, -0.06)]. A lower cognitive performance was found in the subjects with greater glucose variation, which has statistical significance. Mean amplitude of glycemic excursions (MAGE) was associated with a higher risk of poor functional outcomes. Fisher's z value was -0.35 [95%CI (-0.43, -0.25)], indicating statistical significance (P = 0.011). Sensitivity analyses by omitting individual studies showed stability of the results.

CONCLUSIONS

Overall, higher acute GV is associated with an increased risk of cognitive impairment in patients with T2DM. Further studies should be required to determine whether targeted intervention of reducing acute GV could prevent cognitive decline.

Prediction of post-stroke cognitive impairment after acute ischemic stroke using machine learning

BACKGROUND AND OBJECTIVES

Post-stroke cognitive impairment (PSCI) occurs in up to 50% of patients with acute ischemic stroke (AIS). Thus, the prediction of cognitive outcomes in AIS may be useful for treatment decisions. This PSCI cohort study aimed to determine the applicability of a machine learning approach for predicting PSCI after stroke.

METHODS

This retrospective study used a prospective PSCI cohort of patients with AIS. Demographic features, clinical characteristics, and brain imaging variables previously known to be associated with PSCI were included in the analysis. The primary outcome was PSCI at 3-6 months, defined as an adjusted z-score of less than - 2.0 standard deviation in at least one of the four cognitive domains (memory, executive/frontal, visuospatial, and language), using the Korean version of the Vascular Cognitive Impairment Harmonization Standards-Neuropsychological Protocol (VCIHS-NP). We developed four machine learning models (logistic regression, support vector machine, extreme gradient boost, and artificial neural network) and compared their accuracies for outcome variables.

RESULTS

A total of 951 patients (mean age 65.7 ± 11.9; male 61.5%) with AIS were included in this study. The area under the curve for the extreme gradient boost and the artificial neural network was the highest (0.7919 and 0.7365, respectively) among the four models for predicting PSCI according to the VCIHS-NP definition. The most important features for predicting PSCI include the presence of cortical infarcts, mesial temporal lobe atrophy, initial stroke severity, stroke history, and strategic lesion infarcts.

CONCLUSION

Our findings indicate that machine-learning algorithms, particularly the extreme gradient boost and the artificial neural network models, can best predict cognitive outcomes after ischemic stroke.

Glycemic variability correlates with medial temporal lobe atrophy and decreased cognitive performance in patients with memory deficits

Background

In the past, researchers have observed a significant link between glycemia and dementia. Medial temporal atrophy (MTA) is regarded as a common marker of dementia. The correlation between glycemic variability and MTA is unclear, and it has not been determined whether glycemic variability can be utilized as a biomarker of MTA and cognitive performance.

Methods

The patients in a memory clinic who underwent brain MRI scans and cognitive assessments within the first week of their hospital visit, were enrolled. All participants underwent three fasting blood glucose and one HBA1c assessments on three self-selected days within 1 week of their first visit. The variability independent of the mean (VIM) was employed. Validated visual scales were used to rate the MTA results. The mini-mental state examination (MMSE) and Montreal Cognitive Assessment (MoCA) scales were employed to assess the cognitive functions of the participants. Spearman's correlation and regression models were used to examine the relationship between the MMSE and MoCA scales, and also determine the link between the MRI characteristics and cognitive status, where vascular risk factors, educational status, age, gender, and mean glucose parameters served as covariates.

Results

Four hundred sixty-one subjects completed the MMSE scale, while 447 participants completed the MoCA scale. Data analysis revealed that 47.72% of the participants were men (220/461), and the median age of the patients was 69.87 ± 5.37 years. The findings of Spearman's correlation analysis exhibited a strong negative relationship between the VIM and MMSE score (r = -0.729, P < 0.01), and the MoCA score (r = -0.710, P < 0.01). The VIM was regarded as an independent risk factor for determining cognitive impairment in both the MMSE and MoCA assessments. The results were unaffected by sensitivity analysis. In addition, a non-linear relationship was observed between the VIM and MTA scores.

Conclusion

The variability in the blood glucose levels, which was presented as VIM, was related to the reduced cognitive function, which was reflected by MMSE and MoCA scales. The relationship between the VIM and the MTA score was non-linear. The VIM was positively related to the MTA score when the VIM was less than 2.42.

Nonlinear relationship between glycated hemoglobin and cognitive impairment after acute mild ischemic stroke

BACKGROUND

Stroke is the second most common cause of morbidity and mortality. Even mild stroke survivors have an increased risk of cognitive impairment. Studies have been conducted on the relationship between glycated hemoglobin (HbA1c) and cognitive decline, but the findings have been inconsistent. Therefore, this study examined the link between HbA1c levels and cognitive impairment following acute mild ischemic stroke.

METHODS

Data from 311 patients with acute mild ischemic stroke admitted to Suining Central Hospital, Sichuan Province, China, from January 1, 2015, to December 31, 2018, were evaluated. Fasting venous blood was taken to assess HbA1c levels on the day after admission. Cognitive function was assessed using the Chinese version of the Montreal Cognitive Assessment Scale (MoCA) 3-6 months after stroke onset. We used a generalized additive model and smooth curve fitting (penalty spline method) to assess the nonlinear relationship between HbA1c and poststroke cognitive impairment (PSCI).

RESULTS

This study included 311 patients aged 23 to 96 years old (mean age: 67.37 ± 11.92 years), of whom 198 (63.67%) were men. Among the 311 stroke patients, 120 (38.59%) had PSCI. After adjusting for potential confounders, there was a nonlinear relationship between HbA1c and PSCI, with an inflection point of 8.2. To the left of the inflection point, the effect size, 95% confidence interval, and P value were 0.87, 0.58 to 1.31, and 0.5095, respectively; however, to the right of the inflection point, these numbers were 1.96, 1.08 to 3.58, and 0.0280.

CONCLUSION

We found a nonlinear relationship between HbA1c and PSCI. When HbA1c was greater than 8.2%, HbA1c was positively correlated with PSCI.

The Association of Glucose Variability and Dementia Incidence in Latinx Adults with Type 2 Diabetes: A Retrospective Study

Latinx adults with both cognitive dysfunction and type 2 diabetes mellitus (T2DM) are significantly more likely than Latinx adults with diabetes alone to have complications such as cardiovascular disease. Glucose variability may be a risk for dementia, but the course of glucose variability in the time before a dementia diagnosis for Latinx adults with T2DM has not been examined. We used a 10-year retrospective cohort of medical records of Latinx patients with T2DM who had at least one use of a continuous glucose monitor. The objective was to examine how glucose variability was associated with future dementia diagnoses. A total of 116 charts were included. Mean of daily differences and mean amplitude of glycemic excursions were more strongly associated with dementia diagnoses than other variability indices (p < .01). Understanding the relationships between cognitive function, glucose variability, and barriers to health care can translate into improved interventions to enhance diabetes care.

A review of stress-induced hyperglycaemia in the context of acute ischaemic stroke: Definition, underlying mechanisms, and the status of insulin therapy

The transient elevation of blood glucose produced following acute ischaemic stroke (AIS) has been described as stress-induced hyperglycaemia (SIH). SIH is common even in patients with AIS who have no previous diagnosis of diabetes mellitus. Elevated blood glucose levels during admission and hospitalization are strongly associated with enlarged infarct size and adverse prognosis in AIS patients. However, insulin-intensive glucose control therapy defined by admission blood glucose for SIH has not achieved the desired results, and new treatment ideas are urgently required. First, we explore the various definitions of SIH in the context of AIS and their predictive value in adverse outcomes. Then, we briefly discuss the mechanisms by which SIH arises, describing the dual effects of elevated glucose levels on the central nervous system. Finally, although preclinical studies support lowering blood glucose levels using insulin, the clinical outcomes of intensive glucose control are not promising. We discuss the reasons for this phenomenon.

Association between diabetes mellitus and post-stroke cognitive impairment

Stroke survivors suffer from various physical, emotional, and cognitive impairments. These changes are dynamic and depend on multiple factors, including underlying diseases, baseline brain function and pathology, the site of the stroke and the post-stroke inflammation, neurogenesis as well as the subsequent remodeling of the neuro-network. First we review the structural and pathological changes of the brain in stroke survivors with diabetes mellitus, which may lead to post-stroke cognitive dysfunction. Second, we provide evidence of hyperglycemia, diabetes mellitus, hypoglycemia, and their relationship with post-stroke cognitive impairment (PSCI) and post-stroke dementia (PSD). In addition to conventional biomarkers, such as HbA1c, we also provide other novel tools to predict PSCI/PSD, such as glycemic variability, receptor for advanced glycation end products, and gut microbiota. Finally, we attempt to provide some modifying methods for glycemic control, focusing on the prevention of PSCI/PSD.

Clinical relevance of glucose metrics during the early brain injury period after aneurysmal subarachnoid hemorrhage: An opportunity for continuous glucose monitoring

Hyperglycaemia, hypoglycaemia and higher glucose variability during the Early Brain Injury (EBI) period of aneurysmal subarachnoid hemorrhage (aSAH) have been associated with poor clinical outcome. However, it is unclear whether these associations are due to direct glucose-driven injury or if hyperglycaemia simply acts as a marker of initial severity. Actually, strict glucose control with intensive insulin therapy has not been demonstrated as an effective strategy for improving clinical outcomes after aSAH. Currently published studies describing an association between hyperglycaemia and prognosis in aSAH patients have been based on isolated glucose measurements and did not incorporate comprehensive dynamic evaluations, such as those derived from subcutaneous continuous glucose monitoring devices (CMG). Arguably, a more accurate knowledge on glycaemic patterns during the acute phase of aSAH could increase our understanding of the relevance of glycaemia as a prognostic factor in this disease as well as to underpin its contribution to secondary focal and diffuse brain injury. Herein, we have summarized the available evidence on the diagnostic and prognostic relevance of glucose metrics during the acute phase of cerebrovascular diseases, focusing in the EBI period after aSAH. Overall, obtaining a more precise scope of acute longitudinal glucose profiles could eventually be useful for improving glucose management protocols in the setting of acute aSAH and to advance toward a more personalized management of aSAH patients during the EBI phase.

An Untargeted Lipidomics Study of Acute Ischemic Stroke with Hyperglycemia Based on Ultrahigh-Performance Liquid Chromatography-Mass Spectrometry

Patients with type 2 diabetes have twice as much of the risk of acute ischemic stroke (AIS) occurrence as healthy individuals, and the AIS patients with type 2 diabetes have a higher risk of death and a poorer prognosis. This study was to investigate the interrelationship between hyperglycemia and AIS and provided a reference for blood glucose management of AIS patients. The blood glucose level of AIS patients of the present study was controlled by insulin below 180 mg/dL (standard group) and between 80 and 130 mg/dL (management group). And the fasting venous blood samples were collected for determination of blood glucose level, homeostasis model assessment of insulin resistance (HOMA-IR), peptide C, and basal insulin level. Furthermore, lipids of the blood samples were detected using metabolomics, so as to clarify the similarities and differences in metabolic patterns in AIS patients with diabetes after the intervention of different glycemic strategies. The results revealed that compared to the standard group, the blood glucose level and HOMA-IR in the management group were significantly decreased, and levels of peptide C and basal insulin level were greatly increased. Through lipidomics detection, 83, 50, and 44 types of significantly upregulated differential lipids were detected in the standard vs. normal groups, the standard vs. management groups, and the management vs. normal groups, respectively, with triacylglycerol dominated. This study preliminarily revealed metabolic differences among AIS patients with hyperglycemia after different blood glucose intervention methods, hoping to provide a theoretical basis for clinical prevention and treatment of this disease.

Relationships Among Perception of Cognitive Function, Diabetes Self-Management, and Glucose Variability in Older Adults: A Mixed Methods Study

The aim of the current study was to explore relationships among perceived cognitive function, glucose variability, and self-management in older adults with type 2 diabetes mellitus (T2DM). A mixed methods design was used with data from: (a) questionnaires on perceived cognitive function and diabetes self-management; (b) continuous glucose monitoring (CGM) reports; and (c) semi-structured interviews. Thirty adults with T2DM (47% female; mean age = 68.5 [SD = 5.2] years) participated. Those who exercised more days per week had more stable glucose. Those who reported fewer days of diet adherence had more hypoglycemia. Participants who reported higher levels of memory dissatisfaction exhibited higher levels of glucose variability. Findings point to the potential of glucose variability as a target to reduce the effect of diabetes on cognitive function. Instruction in recognition of glucose patterns found via CGM can be integrated into self-management education to improve self-management and subsequent glucose control and cognitive function. [Research in Gerontological Nursing, xx(x), xx-xx.].

Acute Glycemic Variability and Functional Outcome in Patients with Acute Ischemic Stroke: A Meta-Analysis

Dysglycemia are involved in the development of functional impairment after acute ischemic stroke (AIS). The aim of the study was to evaluate the association between acute glycemic variability and functional outcome in patients with AIS. Cohort studies were obtained by search Medline, Web of Science, Embase, Wanfang, and China National Knowledge Infrastructure databases from inception to November, 2021. A random-effect model which incorporates the intra-study heterogeneity was chosen to pool the results. Ten cohort studies including 3038 patients were included, and 1319 (43.4%) had poor functional outcome (modified Rankin Scale >2) up to three months after disease onset. Pooled results showed that higher acute GV was associated with an increased risk of poor functional outcome, as evidenced by GV evaluated by the standard deviation of blood glucose (SDBG, OR: 1.91, 95% CI: 1.38 to 2.65, I2=60%, p<0.001), the coefficient of variation of blood glucose (OR: 2.03, 95% CI: 1.15 to 3.58, I2=17%, p=0.02), the range of glucose (OR: 1.43, 95% CI: 1.11 to 1.83, I2=22%, p=0.005), and the mean amplitude of glycemic excursion (OR: 1.59, 95% CI: 1.10 to 2.31, I2=0%, p=0.01). Subgroup analyses did not support that difference in study design, treatments for AIS, mean age of the patients, duration for GV measuring, or study quality would significantly affect the association between SDBG and functional outcome after AIS. In conclusion, higher acute glycemic variability may predict poor functional outcome within 3 months after AIS.

Acute glycemic variability and mortality of patients with acute stroke: a meta-analysis

BACKGROUND

Increased glucose fluctuation has been related to poor prognosis in patients with critical illnesses, while its prognostic role in patients with acute stroke remains unknown. The meta-analysis aimed to evaluate the association between the acute glycemic variation (GV) and mortality risk in patients with acute stroke.

METHODS

Cohort studies were obtained by searching Medline, Web of Science, Embase, Wanfang and CNKI databases. A random-effect model which incorporates the intra-study heterogeneity was chosen to pool the results.

RESULTS

Ten cohort studies with 1433 patients were included, and 280 (19.5%) of them died within 90 days of disease onset. Results of the meta-analyses showed that a higher acute GV was associated with an increased risk of early mortality in patients with acute stroke, as indicated by GV measured with the coefficient of variation of blood glucose (CVBG, odds ratio [OR]: 2.24, 95% CI 1.40 to 3.58, p < 0.001, I2 = 73%), the standard deviation of blood glucose (SDBG, OR: 2.31, 95% CI 1.70 to 3.13, p < 0.001, I2 = 50%), and the mean amplitude of glycemic excursion (OR: 3.57, 95% CI 1.44 to 8.85, p = 0.006, I2 = 23%). For acute GV measured with CVBG and SDBG, subgroup analyses showed consistent results in patients with acute ischemic and hemorrhagic stroke, and for studies reporting 28-day and 90-day all-cause mortality (p for subgroup analysis all > 0.05).

CONCLUSIONS

Higher acute GV may be an independent risk factor of early mortality in patients with acute stroke.

A New Nomogram Model for Individualized Prediction of Cognitive Impairment in Patients with Acute Ischemic Stroke

BACKGROUND

Cognitive impairment is a common symptom after ischemic stroke. Such symptom can cause effect on rehabilitation of patients and their quality of life and. As stroke rapidly growth on nowadays, a reliable scoring tool to detect the risk of cognitive impairment after stroke is now being put on the first place.

METHODS

We enrolled patients with acute ischemic stroke (AIS) as samples and hospitalized all at the First Affiliated Hospital of Soochow University between October 2018 and June 2020. All patients were assessed by the Montreal Cognitive Assessment (MoCA) scales and MoCA score < 26 was defined as standard to have having cognitive impairment. All patients were randomly (7:3) divided into two cohorts: the primary ones and the validated ones. Based on multivariate logistic model, the independent predictors of cognitive impairment in the acute phase were identified. The predictive nomogram was generated and evaluated by Harrell's concordance index (C-index) and calibration plot both in two cohorts, respectively.

RESULTS

A total of 191 patients were enrolled, of whom 135 comprised the primary cohort and 56 comprised the validated cohort. Gender, age, baseline NIHSS score, hyperhomocysteinemia (HHcy) and multiple lesions were independently associated with acute cognitive impairment after stroke and included to construct the nomogram. The nomogram derived from the primary cohort had an Area Under Curve (AUC) of 0.773 and the validated ones had an AUC of 0.859. Calibration plot revealed adequate fit of the nomogram in predictive value.

CONCLUSION

The new nomogram based on gender, age, baseline NIHSS score, HHcy and multiple lesions gave rise to an accurate and comprehensive prediction for cognitive impairment in AIS patients. After further validation, it could potentially be a reliable forecasting tool.

Post-Stroke Cognitive Impairment: Epidemiology, Risk Factors, and Management

Stroke, characterized as a neurological deficit of cerebrovascular cause, is very common in older adults. Increasing evidence suggests stroke contributes to the risk and severity of cognitive impairment. People with cognitive impairment following stroke often face with quality-of-life issues and require ongoing support, which have a profound effect on caregivers and society. The high morbidity of post-stroke cognitive impairment (PSCI) demands effective management strategies, in which preventive strategies are more appealing, especially those targeting towards modifiable risk factors. In this review article, we attempt to summarize existing evidence and knowledge gaps on PSCI: elaborating on the heterogeneity in current definitions, reporting the inconsistent findings in PSCI prevalence in the literature, exploring established or less established predictors, outlining prevention and treatment strategies potentially effective or currently being tested, and proposing promising directions for future research.

Role of diabetes in stroke: Recent advances in pathophysiology and clinical management

The increasing prevalence of diabetes and stroke is a major global public health concern. Specifically, acute stroke patients, with pre-existing diabetes, pose a clinical challenge. It is established that diabetes is associated with a worse prognosis after acute stroke and the various biological factors that mediate poor recovery profiles in diabetic patients is unknown. The level of association and impact of diabetes, in the setting of reperfusion therapy, is yet to be determined. This article presents a comprehensive overview of the current knowledge of the role of diabetes in stroke, therapeutic strategies for primary and secondary prevention of cardiovascular disease and/or stroke in diabetes, and various therapeutic considerations that may apply during pre-stroke, acute, sub-acute and post-stroke stages. The early diagnosis of diabetes as a comorbidity for stroke, as well as tailored post-stroke management of diabetes, is pivotal to our efforts to limit the burden. Increasing awareness and involvement of neurologists in the management of diabetes and other cardiovascular risk factors is desirable towards improving stroke prevention and efficacy of reperfusion therapy in acute stroke patients with diabetes.

Nutritional Impact on Metabolic Homeostasis and Brain Health

Aging in modern societies is often associated with various diseases including metabolic and neurodegenerative disorders. In recent years, researchers have shown that both dysfunctions are related to each other. Although the relationship is not fully understood, recent evidence indicate that metabolic control plays a determinant role in neural defects onset. Indeed, energy balance dysregulation affects neuroenergetics by altering energy supply and thus neuronal activity. Consistently, different diets to help control body weight, blood glucose or insulin sensitivity are also effective in improving neurodegenerative disorders, dampening symptoms, or decreasing the risk of disease onset. Moreover, adapted nutritional recommendations improve learning, memory, and mood in healthy subjects as well. Interestingly, adjusted carbohydrate content of meals is the most efficient for both brain function and metabolic regulation improvement. Notably, documented neurological disorders impacted by specific diets suggest that the processes involved are inflammation, mitochondrial function and redox balance as well as ATP production. Interestingly, processes involving inflammation, mitochondrial function and redox balance as well as ATP production are also described in brain regulation of energy homeostasis. Therefore, it is likely that changes in brain function induced by diets can affect brain control of energy homeostasis and other brain functions such as memory, anxiety, social behavior, or motor skills. Moreover, a defect in energy supply could participate to the development of neurodegenerative disorders. Among the possible processes involved, the role of ketone bodies metabolism, neurogenesis and synaptic plasticity, oxidative stress and inflammation or epigenetic regulations as well as gut-brain axis and SCFA have been proposed in the literature. Therefore, the goal of this review is to provide hints about how nutritional studies could help to better understand the tight relationship between metabolic balance, brain activity and aging. Altogether, diets that help maintaining a metabolic balance could be key to both maintain energy homeostasis and prevent neurological disorders, thus contributing to promote healthy aging.

The Rate of Decrease in Brain Perfusion in Progressive Supranuclear Palsy and Corticobasal Syndrome May Be Impacted by Glycemic Variability-A Pilot Study

Progressive supranuclear palsy (PSP) and corticobasal syndrome (CBS) are tauopathic parkinsonian syndromes, presently lacking disease-modifying treatments. Patients affected by these diseases suffer due to multidimensional deteriorations resulting in motor and cognitive impairment. Previously published research has confirmed risk factors that may impact the course of PSP and CBS, among them hypertension and diabetes. Less data is available regarding prediabetes and glycemic variability. In this study, 26 patients with clinical diagnoses of PSP and CBS were examined using glycated hemoglobin and perfusion single-photon emission tomography (SPECT). Patients were divided into two groups-PSP/CBS patients with glycated hemoglobin (HbA1c) below and above 5.7%. The results of the perfusion evaluation were compared with the values from healthy volunteers from the software's database. A decrease in perfusion in certain regions of interest was observed among patients affected by increased glycemic variability. A more pronounced decrement in perfusion was observed only in some regions of interest-the hippocampus, pons, left thalamus, right insula. The results indicated that, among PSP/CBS patients, individuals with more pronounced glycemic variability had more severe hypoperfusion in certain brain regions in comparison with PSP/CBS patients without carbohydrate metabolism disorders. Due to the fact that PSP and CBS are associated with cognitive impairment, an additional decrease in perfusion in the hippocampal area may impact the rate of cognitive deterioration.

Glycemic variability of acute stroke patients and clinical outcomes: a continuous glucose monitoring study

Introduction:

Glycemic variability (GV) has been associated with worse prognosis in critically ill patients. We sought to evaluate the potential association between GV indices and clinical outcomes in acute stroke patients.

Methods:

Consecutive diabetic and nondiabetic, acute ischemic or hemorrhagic stroke patients underwent regular, standard-of-care finger-prick measurements and continuous glucose monitoring (CGM) for up to 96 h. Thirteen GV indices were obtained from CGM data. Clinical outcomes during hospitalization and follow-up period (90 days) were recorded. Hypoglycemic episodes disclosed by CGM but missed by finger-prick measurements were also documented.

Results:

A total of 62 acute stroke patients [48 ischemic and 14 hemorrhagic, median NIHSS score: 9 (IQR: 3–16) points, mean age: 65 ± 10 years, women: 47%, nondiabetic: 79%] were enrolled. GV expressed by higher mean absolute glucose (MAG) values was associated with a lower likelihood of neurological improvement during hospitalization before and after adjusting for potential confounders (OR: 0.135, 95% CI: 0.024–0.751, p = 0.022). There was no association of GV indices with 3-month clinical outcomes. During CGM recording, 32 hypoglycemic episodes were detected in 17 nondiabetic patients. None of these episodes were identified by the periodic blood glucose measurements and therefore they were not treated.

Conclusions:

Greater GV of acute stroke patients may be related to lower odds of neurological improvement during hospitalization. No association was disclosed between GV indices and 3-month clinical outcomes.

High Neutrophil-Lymphocyte Ratio Predicts Post-stroke Cognitive Impairment in Acute Ischemic Stroke Patients

Background and Aims: Systemic inflammation is associated with an increased risk of cognitive impairment and dementia, but the associations between them in stroke patients are less clear. We examined the impact of systemic inflammation represented as the neutrophil-lymphocyte ratio (NLR) on the development of post-stroke cognitive impairment (PSCI) and domain-specific cognitive outcomes 3-month after ischemic stroke. Methods: Using prospective stroke registry data, we consecutively enrolled 345 participants with ischemic stroke whose cognitive functions were evaluated 3-month after stroke. Their cognition was assessed with the Korean version of the Vascular Cognitive Impairment Harmonization Standards and the Korean-Mini Mental Status Examination. PSCI was defined as a z-score of < -2 standard deviations for age, sex, and education adjusted means in at least one cognitive domain. The participants were categorized into five groups according to the quintiles of NLR (lowest NLR, Q1). The cross-sectional association between NLR and PSCI was assessed using multiple logistic regression, adjusting for age, sex, education, vascular risk factors, and stroke type. Results: A total of 345 patients were enrolled. The mean age was 63.0 years and the median NIHSS score and NLR were 2 [1-4] and 2.26 [1.65-2.91], respectively. PSCI was identified in 71 (20.6%) patients. NLR was a significant predictor for PSCI both as a continuous variable (adjusted OR, 1.14; 95% CI, 1.00-1.31) and as a categorical variable (Q5, adjusted OR, 3.26; 95% CI, 1.17-9.08). Patients in the Q5 group (NLR ≥ 3.80) showed significantly worse performance in global cognition and in visuospatial and memory domains. Conclusions: NLR in the acute stage of ischemic stroke was independently associated with PSCI at 3 months after stroke, and high NLR was specifically associated with cognitive dysfunction in the memory and visuospatial domains. Thus, systemic inflammation may be a modifiable risk factor that may influence cognitive outcomes after stroke.

Effects of Glycemic Gap on Post-Stroke Cognitive Impairment in Acute Ischemic Stroke Patients

Background: Post-stroke hyperglycemia is a frequent finding in acute ischemic stroke patients and is associated with poor functional and cognitive outcomes. However, it is unclear as to whether the glycemic gap between the admission glucose and HbA1c-derived estimated average glucose (eAG) is associated with post-stroke cognitive impairment (PSCI). Methods: We enrolled acute ischemic stroke patients whose cognitive functions were evaluated three months after a stroke using the Korean version of the vascular cognitive impairment harmonization standards neuropsychological protocol (K-VCIHS-NP). The development of PSCI was defined as having z-scores of less than −2 standard deviations in at least one cognitive domain. The participants were categorized into three groups according to the glycemic gap status: non-elevated (initial glucose − eAG ≤ 0 mg/dL), mildly elevated (0 mg/dL < initial glucose − eAG < 50 mg/dL), and severely elevated (50 mg/dL ≤ initial glucose − eAG). Results: A total of 301 patients were enrolled. The mean age was 63.1 years, and the median National Institute of Health Stroke Scale (NIHSS) score was two (IQR: 1–4). In total, 65 patients (21.6%) developed PSCI. In multiple logistic regression analyses, the severely elevated glycemic gap was a significant predictor for PSCI after adjusting for age, sex, education level, initial stroke severity, Trial of Org 10172 in Acute Stroke Treatment (TOAST) classification, and left hemispheric lesion (aOR: 3.65, p-value = 0.001). Patients in the severely elevated glycemic gap group showed significantly worse performance in the frontal and memory domains. Conclusions: In conclusion, our study demonstrated that an elevated glycemic gap was significantly associated with PSCI three months after a stroke, with preferential involvement of frontal and memory domain dysfunctions.

Short-term glycemic variability and hemorrhagic transformation after successful endovascular thrombectomy

BACKGROUND

Glycemic variability (GV) is a risk factor for poor outcomes after ischemic stroke. However, its effect on hemorrhagic transformation after endovascular recanalization therapy (ERT) remains to be elucidated.

METHODS

Patients with acute ischemic stroke due to large vessel occlusion with successful recanalization after ERT (modified thrombolysis in cerebral infarction 2b or 3) were enrolled between January 2013 and November 2019. Blood glucose level data were obtained during the first 36 h after ERT, and ten GV parameters including time rate (TR) of glucose variation were assessed. The TR of glucose variation reflects the speed of glucose fluctuations over time (mg/dL/hour) during the monitoring period. Symptomatic intracerebral hemorrhage (sICH) and unfavorable outcomes at 3 months after ERT were analyzed. The sICH was defined as parenchymal hematoma type 2 with a neurological deterioration of 4 points or more on the National Institute of Health Stroke Scale. Moreover, a modified Rankin Scale of 3-6 at 3 months was considered an unfavorable outcome.

RESULTS

Among all patients (n = 176; mean age, 69.3 years; 47.7 % female), sICH developed after successful ERT in 16 (9.1%) patients. In addition, 54% (n = 95) patients had an unfavorable outcome at 3 months. Patients with sICH and unfavorable outcome had higher the TR of glucose variation. After adjusting for potential confounders, the TR of glucose (per 1 mg/dL/h increase) variation was independently associated with sICH (odds ratio, 1.17; 95% confidence interval [CI], 1.012-1.343) and 3-month unfavorable outcome (OR 1.14, 95% CI, 1.000-1.297).

CONCLUSIONS

Time-related GV during the first 36 h after successful ERT has a stronger correlation with sICH and poor functional outcomes compared to any GV parameters. This suggests that maintaining stable glucose may be an important factor in the prevention of sICH after undergoing successful ERT.

Glycemic Variability and CNS Inflammation: Reviewing the Connection

Glucose is the primary energy source for the brain, and exposure to both high and low levels of glucose has been associated with numerous adverse central nervous system (CNS) outcomes. While a large body of work has highlighted the impact of hyperglycemia on peripheral and central measures of oxidative stress, cognitive deficits, and vascular complications in Type 1 and Type 2 diabetes, there is growing evidence that glycemic variability significantly drives increased oxidative stress, leading to neuroinflammation and cognitive dysfunction. In this review, the latest data on the impact of glycemic variability on brain function and neuroinflammation will be presented. Because high levels of oxidative stress have been linked to dysfunction of the blood-brain barrier (BBB), special emphasis will be placed on studies investigating the impact of glycemic variability on endothelial and vascular inflammation. The latest clinical and preclinical/in vitro data will be reviewed, and clinical/therapeutic implications will be discussed.

Glycemic variability: prognostic impact on acute ischemic stroke and the impact of corrective treatment for hyperglycemia. The GLIAS-III translational study

Introduction

Glycemic variability (GV) represents the amplitude of oscillations in glucose levels over time and is associated with higher mortality in critically ill patients. Our aim is to evaluate the impact of GV on acute ischemic stroke (IS) outcomes in humans and explore the impact of two different insulin administration routes on GV in an animal model.

Methods

This translational study consists of two studies conducted in parallel: The first study is an observational, multicenter, prospective clinical study in which 340 patients with acute IS will be subcutaneously implanted a sensor to continuously monitor blood glucose levels for 96 h. The second study is a basic experimental study using an animal model (rats) with permanent occlusion of the middle cerebral artery and induced hyperglycemia (through an intraperitoneal injection of nicotinamide and streptozotocin). The animal study will include the following 6 groups (10 animals per group): sham; hyperglycemia without IS; IS without hyperglycemia; IS and hyperglycemia without treatment; IS and hyperglycemia and intravenous insulin; and IS and hyperglycemia and subcutaneous insulin. The endpoint for the first study is mortality at 3 months, while the endpoints for the animal model study are GV, functional recovery and biomarkers.

Discussion

The GLIAS-III study will be the first translational approach analyzing the prognostic influence of GV, evaluated by the use of subcutaneous glucose monitors, in acute stroke.

Trial registrationhttps://www.clinicaltrials.gov (NCT04001049)

Mens Sana in Corpore Sano: Does the Glycemic Index Have a Role to Play?

Although diet interventions are mostly related to metabolic disorders, nowadays they are used in a wide variety of pathologies. From diabetes and obesity to cardiovascular diseases, to cancer or neurological disorders and stroke, nutritional recommendations are applied to almost all diseases. Among such disorders, metabolic disturbances and brain function and/or diseases have recently been shown to be linked. Indeed, numerous neurological functions are often associated with perturbations of whole-body energy homeostasis. In this regard, specific diets are used in various neurological conditions, such as epilepsy, stroke, or seizure recovery. In addition, Alzheimer’s disease and Autism Spectrum Disorders are also considered to be putatively improved by diet interventions. Glycemic index diets are a novel developed indicator expected to anticipate the changes in blood glucose induced by specific foods and how they can affect various physiological functions. Several results have provided indications of the efficiency of low-glycemic index diets in weight management and insulin sensitivity, but also cognitive function, epilepsy treatment, stroke, and neurodegenerative diseases. Overall, studies involving the glycemic index can provide new insights into the relationship between energy homeostasis regulation and brain function or related disorders. Therefore, in this review, we will summarize the main evidence on glycemic index involvement in brain mechanisms of energy homeostasis regulation.

Donepezil Improves Gait Performance in Patients with an Acute Cerebral Infarction: A Prospective Observational Cohort Study

Background:

Hemiplegia is a common symptom after acute cerebral infarction.

Objective:

This study aimed to explore the influence factors of gait performance and investigate whether donepezil could improve gait performance in patients with an acute cerebral infarction.

Methods:

A total of 107 patients who experienced unilateral paresis after an acute cerebral infarction incident were enrolled in this prospectively observational study. Participants underwent a 3- month assessment. At the study's conclusion, patients were divided into 2 groups-those who received donepezil daily (observation Group) and those who did not (Control Group).

Results:

There was a significant difference (t=3.269, P=0.001) of Wisconsin Gait Scale (WGS) score between single site infarction (27.11±6.65) and multiple sites infarction (31.54±6.42). For gender, smoking, drinking, hypertension, hyperlipidemia and diabetes, there was no difference in WGS scores between subgroups (P>0.05), respectively. The patient's admission National Institute of Health Stroke Scale(NIHSS) score had a strongly positive correlation with WGS score (r=0.850, P<0.001). Besides, age (r=0.218, P=0.024), glycosylated hemoglobin (r=0.274, P=0.004), MMSE (r=-0.261, P=0.007) and Montreal Cognitive Assessment (MoCA) (r=-0.272, P=0.005) had a weak correlation with WGS scores. Multivariate analysis showed age (95% CI: 0.042~0.188, P=0.002), admission NIHSS score (95% CI: 2.405~3.137, P<0.001) and multiple sites infarction (95% CI: 0.044~2.983, P=0.044) were independent risk factors of WGS scores. WGS scores of both observation and control groups gradually decreased after admission (P<0.001). At 3 months after admission, WGS score of the observation group was significantly lower than the control group (t=2.468, P=0.015). There were no significant differences between observation and control group at admission and 1 month after admission (P>0.05) and WGS scores of both single site and multiple sites infarction gradually decreased at one month and three months after admission (P<0.001), while there was no significant difference between two groups (P>0.05).

Conclusion:

Admission NIHSS score, age and multiple sites infarction were independent risk factors of WGS score. Donepezil could improve gait performance in patients with acute cerebral infarction.

The treament of hyperglycemia in acute ischemic stroke with incretin-based drugs

Stroke is a major cause of mortality and morbidity worldwide. Considerable experimental and clinical evidence suggests that both diabetes mellitus (DM) and post-stroke hyperglycemia are associated with increased mortality rate and worsened clinical conditions in acute ischemic stroke (AIS) patients. Insulin treatment does not seem to provide convincing benefits for these patients, therefore prompting a change of strategy. The selective agonists of Glucagon-Like Peptide-1 Receptors (GLP-1Ras) and the Inhibitors of Dipeptidyl Peptidase-IV (DPP-IVIs, gliptins) are two newer classes of glucose-lowering drugs used for the treatment of DM. This review examines in detail the rationale for their development and the physicochemical, pharmacokinetic and pharmacodynamic properties and clinical activities. Emphasis will be placed on their neuroprotective effects at cellular and molecular levels in experimental models of acute cerebral ischemia. In perspective, an adequate basis does exist for a novel therapeutic approach to hyperglycemia in AIS patients through the additive treatment with GLP-1Ras plus DPP-IVIs.

Type 2 diabetes mellitus and cardiovascular disease: focus on the effect of antihyperglycemic treatments on cardiovascular outcomes

Introduction: Type 2 diabetes mellitus and cardiovascular disease contribute to significant morbidity, mortality, and health-care resource expenditure. The pathophysiological and clinical associations between diabetes and cardiovascular disease have been the subject of multiple studies, most recently culminating in large trials of several new antiglycemic agents being found to confer additional cardiovascular risk reduction. Understanding the potential cardiovascular benefits of antiglycemic medications offers the unique opportunity to reduce the morbidity and mortality presented by both diseases at once.Areas covered: The literature search was comprised of a Pubmed search querying 'cardiovascular outcomes' and 'diabetes'. This article reviews the pathophysiology of cardiovascular complications in type 2 diabetes and the cardiovascular outcome trials related to newer antiglycemic medications.Expert opinion: The treatment of patients with type 2 diabetes mellitus and cardiovascular disease is rapidly advancing. In particular, the sodium-glucose cotransporter-2 (SGLT2) inhibitors and glucagon-like peptide-1 (GLP-1) receptor agonists have demonstrated cardiovascular benefit by reducing major adverse cardiovascular events and cardiovascular mortality. Future directions of the treatment of type 2 diabetes and cardiovascular disease will focus on targeting and preventing diabetic cardiomyopathy and further defining the role of SGLT2 inhibitors and of GLP-1 receptor agonists in additional patient populations.

Recombinant Human Growth Hormone Ameliorates Cognitive Impairment in Stroke Patients

OBJECTIVE

We aimed to determine the effects of recombinant human growth hormone (rhGH) replacement on cognitive function in subjects with poststroke cognitive impairment using resting-state functional magnetic resonance imaging.

METHODS

We included 60 patients with a first-ever stroke for 3 months and a diagnosis of cognitive impairment who were randomized 1:1 to receive either rhGH subcutaneously or placebo injection for 6 months. All subjects were required to receive the same rehabilitative therapy program. Both groups were subjected to pretreatment and posttreatment neuropsychological assessment using the Montreal Cognitive Assessment, serum neurotrophic factors, biomarkers of glucose and lipid metabolism, and functional magnetic resonance imaging during 6 months of the study period. The pattern of brain activity was determined by examining the functional connectivity and amplitude of low-frequency fluctuations (ALFF) of blood oxygen level dependent signal.

RESULTS

Forty-three (82.7%) completed the study. Treatment with rhGH reduced levels of triglycerides and low-density lipoprotein cholesterol but did not significantly altered plasma concentrations of glucose and glycated hemoglobin. We found a significant increase in serum insulin-like growth factor 1 levels (32.6%; P < 0.001) in the rhGH-treated group compared with that in the controls. After 6 months of rhGH treatment, mean Montreal Cognitive Assessment score improved from 16.31 (5.32) to 21.19 (6.54) (P < 0.001). The rhGH group showed significant increased area of activation with increased ALFF values in the regions of the frontal lobe, putamen, temporal lobe, and thalamus (P < 0.05), relative to the baseline conditions. The correlation analysis revealed that the ALFF and functional connectivity of default mode network was positively correlated with the ΔMoCA score and ΔIGF-1 levels; that is, the more the scale score increased, the higher the functional connection strength. No undesirable adverse effects were observed.

CONCLUSIONS

The rhGH replacement has a significant impact on global and domain cognitive functions in poststroke cognitive impairment.

A View Beyond HbA1c: Role of Continuous Glucose Monitoring

Hemoglobin A1C (HbA1c) is used as an index of average blood glucose measurement over a period of months and is a mainstay of blood glucose monitoring. This metric is easy to measure and relatively inexpensive to obtain, and it predicts diabetes-related microvascular complications. However, HbA1c provides only an approximate measure of glucose control; it does not address short-term glycemic variability (GV) or hypoglycemic events. Continuous glucose monitoring (CGM) is a tool which helps clinicians and people with diabetes to overcome the limitations of HbA1c in diabetes management. Time spent in the glycemic target range and time spent in hypoglycemia are the main CGM metrics that provide a more personalized approach to diabetes management. Moreover, the glucose management indicator (GMI), which calculates an approximate HbA1c level based on the average CGM-driven glucose level, facilitates individual decision-making when the laboratory-measured HbA1c and estimated HbA1c are discordant. GV, on the other hand, is a measure of swings in blood glucose levels over hours or days and may contribute to diabetes-related complications. In addition, addressing GV is a major challenge during the optimization of glycemia. The degree of GV is associated with the frequency, duration, and severity of the hypoglycemic events. Many factors affect GV in a patient, including lifestyle, diet, the presence of comorbidities, and diabetes therapy. Recent evidence supports the use of some glucose-lowering agents to improve GV, such as the new ultra-long acting insulin analogs, as these agents have a smoother pharmacodynamic profile and improve glycemic control with fewer fluctuations and fewer nocturnal hypoglycemic events. These newer glucose-lowering agents (such as incretin hormones or sodium-glucose cotransporter 2 inhibitors) can also reduce the degree of GV. However, randomized trials are needed to evaluate the effect of GV on important diabetes outcomes. In this review, we discuss the role of HbA1c as a measure of glycemic control and its limitations. We also explore additional glycemic metrics, with a focus on time (duration) in glucose target range, time (duration) in hypoglycemia, GV, GMI, and their correlation with clinical outcomes.