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

Differential impact of TyG and TyG-BMI indices on short- and long-term mortality in critically ill ischemic stroke patients

BACKGROUND

Ischemic stroke is a major contributor to global morbidity and mortality, particularly in critically ill patients in intensive care units (ICUs). While advances in stroke management have improved outcomes, predicting mortality remains challenging due to the involvement of complex metabolic and cardiovascular factors. The triglyceride-glucose (TyG) index, a marker for insulin resistance, has gained attention for its potential to predict adverse outcomes in stroke patients. Furthermore, the TyG-BMI index, which combines TyG with body mass index (BMI), may offer a more comprehensive measure by accounting for obesity-related metabolic burden. However, the comparative impact of these indices on short- and long-term mortality among critically ill ischemic stroke patients remains unclear.

METHODS

This retrospective cohort study analyzed data from the Medical Information Mart for Intensive Care IV (MIMIC-IV 3.0) database, including 1,334 critically ill ischemic stroke patients. The patients were divided into four groups based on TyG and TyG-BMI quartiles, respectively. Cox proportional hazards models were employed to assess the association of these indices with 30-day, 90-day, 180-day, and 1-year all-cause mortality (ACM). Kaplan-Meier survival analysis was used to compare survival rates across different index levels. We utilized restricted cubic splines (RCS) to examine the association between the TyG, TyG-BMI index and the specified outcomes. Furthermore, TyG and TyG-BMI index were utilized to establish logistic regression models for mortality across different time periods, and corresponding Receiver Operating Characteristic (ROC) curves were generated.

RESULTS

Kaplan-Meier survival analysis show that Higher TyG levels were associated with significantly increased mortality risk at all time points, with patients in the highest TyG quartile exhibiting the greatest risk. Conversely, patients having a lower TyG-BMI level faced a heightened risk of long-term ACM. The RCS analysis results demonstrated that the TyG index did not exhibit a statistically significant nonlinear relationship with mortality across all time points. However, a significant nonlinear relationship was observed between the TyG index and long-term mortality. From the ROC curve, it can be observed that TyG performs better in predicting short-term mortality. Conversely, TyG-BMI demonstrates superior performance in predicting long-term mortality. The analysis revealed that while the TyG index alone is a strong predictor of mortality, the TyG-BMI index enhances the ability to predict long-term outcomes.

CONCLUSION

This finding suggests both the TyG and TyG-BMI indices serve as valuable predictors of mortality in critically ill ischemic stroke patients. However, significant differences were observed across the various follow-up periods. Based on the distinct characteristics of these two indicators, future research should focus on the selective integration of TyG and TyG-BMI indices into clinical risk assessment models, tailored to the metabolic profiles of ischemic stroke patients in the ICU. This approach could enhance the precision of mortality risk stratification and optimize patient management strategies.

The impact of chronic kidney disease on prognosis in acute stroke: unraveling the pathophysiology and clinical complexity for optimal management

BACKGROUND

Chronic kidney disease (CKD) significantly increases stroke risk and severity, posing challenges in both acute management and long-term outcomes. CKD contributes to cerebrovascular pathology through systemic inflammation, oxidative stress, endothelial dysfunction, vascular calcification, impaired cerebral autoregulation, and a prothrombotic state, all of which exacerbate stroke risk and outcomes.

METHODS

This review synthesizes evidence from peer-reviewed literature to elucidate the pathophysiological mechanisms linking CKD and stroke. It evaluates the efficacy and safety of acute reperfusion therapies-intravenous thrombolysis and endovascular thrombectomy-in CKD patients with acute ischemic stroke. Considerations, such as renal function, drug dosage adjustments, and the risk of contrast-induced nephropathy, are critically analyzed. Evidence-based recommendations and research priorities are drawn from an analysis of current practices and existing knowledge gaps.

RESULTS

CKD influences stroke outcomes through systemic and local pathophysiological changes, necessitating tailored therapeutic approaches. Reperfusion therapies are effective in CKD patients but require careful monitoring of renal function to mitigate risks, such as contrast-induced nephropathy and thrombolytic complications. The bidirectional relationship between stroke and CKD highlights the need for integrated management strategies to address both conditions. Early detection and optimized management of CKD significantly reduce stroke-related morbidity and mortality.

CONCLUSION

Optimizing stroke care in CKD patients requires a comprehensive understanding of their pathophysiology and clinical management challenges. This article provides evidence-based recommendations, emphasizing individualized treatment decisions and coordinated care. It underscores the importance of integrating renal considerations into stroke treatment protocols and highlights the need for future research to refine therapeutic strategies, address knowledge gaps, and consider tailored interventions to improve outcomes and quality of life for this high-risk population.

Diabetes Mellitus and Risk of Future Stroke: Evidence From CHARLS and Mendelian Randomization Analyses

OBJECTIVES

This study leveraged the China Health and Retirement Longitudinal Study (CHARLS) to explore the association between diabetes and stroke in middle-aged and older adults in East Asia and assess the causality of this relationship using Mendelian randomization.

METHODS

Data from the 2011-2020 CHARLS cohort identified individuals with diabetes at baseline. Stroke incidence was self-reported through standardized questionnaires. Logistic regression and restricted cubic spline analysis examined the relationship between diabetes and stroke risk alongside nonlinear correlations between glucose levels and stroke. Mendelian randomization clarified the causal link and analyzed the mediating effect between diabetes and stroke using genetic methods.

RESULTS

In the study population aged 45 and above, stroke incidence was 5.99% in normoglycemic, 6.82% in prediabetic, and 9.93% in diabetic individuals. Over 7 years, 473 strokes occurred. Diabetes was associated with a 1.35-fold increased stroke risk compared to normoglycemia (OR = 1.35; 95% CI: 1.03-1.79). Subgroup analyses highlighted higher stroke risks in middle-aged women, nonsmokers, and nondrinkers. Mendelian randomization supports a genetic causal relationship between diabetes and stroke. Diabetes may indirectly lead to stroke through the mediating effects of hypertension and high cholesterol.

CONCLUSION

The findings confirm a significant association and causal link between diabetes and stroke risk in an East Asian population. In addition, the results indicate that controlling blood glucose in prediabetic individuals reduces stroke risk, with no similar benefits in diabetes.

Treatments, medical expenses and complications of hospital outpatient healthcare associated with stroke in patients with diabetes in China: a retrospective analysis of the Beijing Municipal Medical Insurance Database

OBJECTIVES

Diabetes is closely associated with risk of stroke and its adverse sequelae. Approximately 20%-33% of patients with stroke have diabetes. In China, however, it is unclear how stroke affects healthcare utilisation, medications and complications among people with diabetes. This study aimed to analyse the clinical characteristics, treatment options, medical expenses and complications of hospital outpatient healthcare associated with stroke in patients with diabetes in China.

DESIGN

A retrospective, multicentre, observational study.

SETTING

Beijing Municipal Medical Insurance Database, with data from 2016 to 2018.

PARTICIPANTS

The study included patients with diabetes whose data included 2016-2018 outpatient medication records and who had Beijing medical insurance. Patients who did not have continuous prescription records for more than 2 months were excluded from the analysis. In total, 2 853 036 people with diabetes were included, and patients who had and did not have a stroke were compared.

RESULTS

In our study, 19.75%-22.30% of patients with diabetes suffered from stroke between 2016 and 2018. The average annual medical cost for a patient diagnosed with diabetes is ¥9606.65, and the cost increases to ¥13 428.39 when diabetes was combined with stroke; thus, stroke increases the medical cost for patients with diabetes by 39.78% (p<0.0001). Among patients with diabetes who had a stroke, 4.76 medications were used (1.8 hypoglycaemic drugs and 2.97 non-hypoglycaemic drugs); these numbers were significantly greater than for patients with diabetes who did not have a stroke receiving both hypoglycaemic drugs and non-hypoglycaemic drugs (p<0.0001). Among patients with diabetes who did not have a stroke, 3.58 medications were used (1.66 hypoglycaemic drugs and 1.92 non-hypoglycaemic drugs). Patients with diabetes who had a stroke also had significantly greater incidences of diabetic peripheral neuropathy, diabetic kidney disease, diabetic retinopathy and diabetic angiopathy than those who did not have a stroke (p<0.0001). These drugs and costs increased with the number of complications (p<0.0001). The increased medical costs for each specific complication are also listed. We also analysed the medical costs and medication regimens stratified by sex, age group and complications.

CONCLUSIONS

Stroke is associated with a significant increase in complications and medications for patients with diabetes and greatly adds to the economic burden of these patients. Early identification of stroke risk factors in patients with diabetes, as well as targeted poststroke diabetes management, is crucial from a socioeconomic perspective for a comprehensive management and treatment of stroke in patients with diabetes.

Healthy Sleep Pattern, Metabolic Diseases, and Risk of Stroke: The Kailuan Cohort Study

Background

Sleep complaints were reported to be associated with stroke, however, the evidence on the association between healthy sleep pattern and stroke risk in Chinese is limited.

Objective

The aim of this study was to investigate the association between healthy sleep pattern and stroke in Chinese, and the influence of metabolic diseases on the association.

Methods

A total of 11,851 participants from the Kailuan study in China without stroke at baseline were included. We calculated a healthy sleep score according to four sleep factors, and defined the low-risk groups as follows: no insomnia, no excessive daytime sleepiness, no frequent snoring, and sleep 7-8h/d. Each low-risk sleep factor was assigned a score of 1. Cox proportional hazard models were used to assess the association between healthy sleep score and stroke. Mediation analysis was used to estimate the role of metabolic diseases (obesity, diabetes, and hypertension) in the healthy sleep score-stroke association.

Results

During a mean follow-up period of 7.7 years, 504 cases of stroke were identified. A higher healthy sleep score was associated with a lower risk of stroke in a dose-response manner (P-trend=0.03). The adjusted hazard ratio (HR) for participants with a healthy sleep score of 4 versus ≤2 was 0.75 (95% confidence interval [CI]: 0.56, 0.96). In addition, obesity, diabetes, and hypertension collectively explained 21.9% (95% CI: 17.2, 26.5) of the association between healthy sleep score and stroke.

Conclusion

Adherence to healthy sleep pattern was associated with a lower risk of stroke, and the favorable association was partially mediated by metabolic diseases.

Analysis and projections of disease burden for different risk factors and sexes of ischemic stroke in young adults in China

To estimate the rate of death, and disability-adjusted life years (DALYs) and project the disease burden of ischemic stroke due to relevant risk factors in young adults age 20-49 years by sex in China. Data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 were used. The age-standardized mortality (ASMR), age-standardized DALYs rate (ASDR), and estimated annual percentage changes (EAPC) were calculated to evaluate the temporal trends from 1990 to 2019. We also used the NORDPRED model to predict ASMR for ischemic stroke due to related risk factors in Chinese young adults over the next 10 years. From 1990 to 2019, the general age-standardized mortality [from 2.39 (1.97 to 2.99) in 1990 to 1.8 (1.41 to 2.18) in 2019, EAPC = - 1.23] and DALYs rates (from 171.7 (140.34 to 212.36) in 1990 to 144.4 (114.29 to 177.37) in 2019, EAPC = - 0.86) decreased for ischemic stroke in young adults in China. ASMR and ASDR decreased for all level 1 risk factors (including behavioral, environmental/occupational, and metabolic) from 1990 to 2019, with the slightest decrease for metabolic risks [ASMR from 1.86 (1.39 to 2.41) in 1990 to 1.53 (1.15 to 1.92) in 2019, ASDR from 133.68 (99.96 to 173.89) in 1990 to 123.54 (92.96 to 156.98) in 2019] and the largest decrease for environmental/occupational risks [ASMR from 1.57 (1.26 to 1.98) in 1990 to 1.03 (0.78 to 1.29) in 2019, ASDR from 110.91 (88.44 to 138.34) in 1990 to 80.03 (61.87 to 100.33) in 2019]. In general, high body-mass index, high red meat intake, and ambient particulate matter pollution contributed to the large increase in ASMR and ASDR between 1990 and 2019. Significant reductions in ASMR and ASDR were observed in low vegetables intake, household air pollution from solid fuels, lead exposure, and low fiber intake. In addition, there were sex differences in the ranking of ASMR attributable to risks in ischemic stroke. The disease burden of ischemic stroke attributable to relevant risk factors in young adults in China is greater and has a faster growth trend or a slower decline trend in males than in females (except for secondhand smoke). The apparent increasing trend of ASMR attributable to high fasting plasma glucose, high systolic blood pressure, high body-mass index, and high red meat intake was observed in males but not in females. The projected analysis showed an increasing trend in ASMR between 1990 and 2030 for all specific metabolic risks for males, but a decreasing trend for females. ASMR attributable to ambient particulate matter pollution showed an increasing trend from 1990 to 2030 for both males and females. The burden of ischemic stroke in young adults in China showed a downward trend from 1990 to 2019. Specific risk factors associated with the burden of ischemic stroke varied between the sexes. Corresponding measures need to be developed in China to reduce the disease burden of ischemic stroke among young adults.

Post-stroke diabetes management: a qualitative study

Introduction

Diabetes is associated with an increased risk of stroke. In many cases, a diabetes diagnosis may predate a stroke; however, diabetes is often diagnosed during the hospital admission following a stroke. To explore the experiences of stroke survivors as they cope with a new diabetes diagnosis, particularly regarding developing an effective strategy for managing the disease.

Methods

A qualitative grounded theory approach was used that employed focus group interviews with participants, including clinicians and stroke survivors, to develop a holistic understanding of primary and secondary stroke care services and the experiences of those accessing them.

Results

Clinicians believed they were not optimally equipped to manage diabetes as a condition. They believed more emphasis should be placed on self-management, which would be better managed by lifestyle changes than medication alone. Conversely, stroke survivors with diabetes experienced an additional burden associated with the diagnoses but relied on clinicians to manage their diabetes and believed the clinicians were failing if they were unwilling or unable to achieve this.

Discussion

The research highlights the tensions between stroke survivors and healthcare professionals. Stroke survivors relied on the healthcare teams to provide the optimal treatment when they had recently undergone a significant health event where they had experienced a stroke and received a diabetes diagnosis. However, the healthcare teams, while recognizing the importance of a holistic and comprehensive treatment package, struggled to provide it due to resource limitations. To optimize post-stroke diabetes self-management education, a strategic framework that prioritizes patient empowerment and interdisciplinary collaboration is paramount. Tailoring educational interventions to align with individual patient profiles-considering their unique health status, personal preferences, and cultural context-is essential for fostering self-efficacy. Such a strategy not only empowers patients to take an active role in managing their diabetes post-stroke but also contributes to superior health outcomes and an elevated standard of living.

MicroRNA Regulatory Pattern in Diabetic Mouse Cortex at Different Stages Following Ischemic Stroke

After ischemic stroke, microRNAs (miRNAs) participate in various processes, including immune responses, inflammation, and angiogenesis. Diabetes is a key factor increasing the risk of ischemic stroke; however, the regulatory pattern of miRNAs at different stages of diabetic stroke remains unclear. This study comprehensively analyzed the miRNA expression profiles in diabetic mice at 1, 3, and 7 days post-reperfusion following the middle cerebral artery occlusion (MCAO). We identified differentially expressed (DE) miRNAs in diabetic stroke and found significant dysregulation of some novel miRNAs (novel_mir310, novel_mir89, and novel_mir396) post-stroke. These DEmiRNAs were involved in apoptosis and the formation of tight junctions. Finally, we identified three groups of time-dependent DE miRNAs (miR-6240, miR-135b-3p, and miR-672-5p). These have the potential to serve as biomarkers of diabetic stroke. These findings provide a new perspective for future research, emphasizing the dynamic changes in miRNA expression after diabetic stroke and offering potential candidates as biomarkers for future clinical applications.

Recurrent vascular events partially explain association between diabetes and poor prognosis in young ischemic stroke patients

BACKGROUND AND AIMS

Stroke is the second leading cause of death and third leading cause of disability worldwide. There is an increasing incidence of stroke among the young. In this study, we aimed to identify factors associated with poor long-term prognosis in young stroke patients.

METHODS

In this longitudinal observational study, we recruited 147 young ischemic stroke patients within one week of ischemic stroke and followed them up for functional outcome (modified Rankin score (mRS)), recurrent vascular events, and recurrent hospitalisation. Poor function was labelled as mRS score of 3 and above. We performed univariate and multivariable logistic regression analyses to determine factors associated with poor long term functional outcome.

RESULTS

At a median follow-up of 7-years, 32 (22%) of the 147 patients had poor functional outcome. In multivariable analyses, diabetes mellitus (OR = 9.01, CI 3.15 to 26.92), was the only independent predictor of poor function. In analyses stratified by diabetic status, recurrent vascular events (OR = 4.47, CI 1.40 to 14.28) were associated with poor functional outcome within young diabetic patients but not in non-diabetic patients.

CONCLUSIONS

Our findings suggest that diabetes mellitus affects long-term functional outcome in young ischemic stroke and that its effect is mediated partly by recurrent vascular events.

DATA ACCESS STATEMENT

Data obtained from Multi-Centre Retinal study (MCRS), Singapore site. Data cannot be made publicly available due to potentially identifiable research participant information.

From Admission to Discharge: Predicting National Institutes of Health Stroke Scale Progression in Stroke Patients Using Biomarkers and Explainable Machine Learning

As a result of social progress and improved living conditions, which have contributed to a prolonged life expectancy, the prevalence of strokes has increased and has become a significant phenomenon. Despite the available stroke treatment options, patients frequently suffer from significant disability after a stroke. Initial stroke severity is a significant predictor of functional dependence and mortality following an acute stroke. The current study aims to collect and analyze data from the hyperacute and acute phases of stroke, as well as from the medical history of the patients, in order to develop an explainable machine learning model for predicting stroke-related neurological deficits at discharge, as measured by the National Institutes of Health Stroke Scale (NIHSS). More specifically, we approached the data as a binary task problem: improvement of NIHSS progression vs. worsening of NIHSS progression at discharge, using baseline data within the first 72 h. For feature selection, a genetic algorithm was applied. Using various classifiers, we found that the best scores were achieved from the Random Forest (RF) classifier at the 15 most informative biomarkers and parameters for the binary task of the prediction of NIHSS score progression. RF achieved 91.13% accuracy, 91.13% recall, 90.89% precision, 91.00% f1-score, 8.87% FNrate and 4.59% FPrate. Those biomarkers are: age, gender, NIHSS upon admission, intubation, history of hypertension and smoking, the initial diagnosis of hypertension, diabetes, dyslipidemia and atrial fibrillation, high-density lipoprotein (HDL) levels, stroke localization, systolic blood pressure levels, as well as erythrocyte sedimentation rate (ESR) levels upon admission and the onset of respiratory infection. The SHapley Additive exPlanations (SHAP) model interpreted the impact of the selected features on the model output. Our findings suggest that the aforementioned variables may play a significant role in determining stroke patients' NIHSS progression from the time of admission until their discharge.

Comparative effectiveness of acupuncture and pharmacological interventions in treating diabetic stroke: A protocol for a systematic review and network meta-analysis

BACKGROUND

There is a close and causative correlation between stroke and diabetes, and the complication of the 2 diseases seriously harms human health and currently becomes a topic of clinical importance. To date, the common methods of treating diabetic stroke include acupuncture and pharmacological interventions. However, there is no high-quality or direct evidence of their comparative effectiveness. This review aims to provide a network meta-analysis to compare the efficacy of acupuncture and pharmacological interventions in treating diabetic stroke.

METHODS

Databases such as PubMed, Cochrane Central Register of Controlled Trials, EMBASE, China National Knowledge Infrastructure, China Biology Medicine Disc will be searched for relevant randomized controlled trials to obtain literatures on the treatment of diabetic stroke, and clinical randomized controlled trials will be screened out from their inception to December 30, 2022. The participant intervention comparator outcomes of this study are as flowing: P, patients with diabetic stroke; I, acupuncture and pharmacological interventions; C, no treatment, pharmacological placebo, or sham acupuncture groups; O, primary outcome will be blood glucose levels, glycosylated hemoglobin levels, and the rate of stroke recurrence; secondary outcomes will include fasting and post-load blood glucose levels, cholesterol, triglycerides, and quality of life scale scores. Cochrane Risk of Bias Tool will be used in assessing literature's quality. Review Manager software 5.3 and Stata 15.1 will be used in data analysis.

RESULT

This systematic review and network meta-analysis will provide evidence of the efficacy of different therapeutic methods in treating diabetic stroke, to show which forms of therapy are more commonly used with higher effectiveness.

CONCLUSION

The results will systematically provide suggestions for medical practitioners to choose the effective, time-saving and economical therapeutic strategy for diabetic stroke.

Diabetes and the treatment of ischemic stroke

This white paper examines the current challenges for treating ischemic stroke in diabetic patients. The need for a greater understanding of the mechanisms that underlie the relationship between diabetes and the cerebral vascular responses to ischemia is discussed. The critical need to improve the efficacy and safety of thrombolysis is addressed, as is the need for a better characterization the off-target actions of tPA, the only currently approved thrombolytic for the treatment of ischemic stroke.

Identification of distinct circulating microRNAs in acute ischemic stroke patients with type 2 diabetes mellitus

Stroke is the second leading cause of global mortality and continued efforts aim to identify predictive, diagnostic, or prognostic biomarkers to reduce the disease burden. Circulating microRNAs (miRNAs) have emerged as potential biomarkers in stroke. We performed comprehensive circulating miRNA profiling of ischemic stroke patients with or without type 2 diabetes mellitus (T2DM), an important risk factor associated with worse clinical outcomes in stroke. Serum samples were collected within 24 h of acute stroke diagnosis and circulating miRNAs profiled using RNA-Seq were compared between stroke patients with T2DM (SWDM; n = 92) and those without T2DM (SWoDM; n = 98). Our analysis workflow involved random allocation of study cohorts into discovery (n = 96) and validation (n = 94) datasets. Five miRNAs were found to be differentially regulated in SWDM compared to SWoDM patients. Hsa-miR-361-3p and -664a-5p were downregulated, whereas miR-423-3p, -140-5p, and -17-3p were upregulated. We also explored the gene targets of these miRNAs and investigated the downstream pathways associated with them to decipher the potential pathways impacted in stroke with diabetes as comorbidity. Overall, our novel findings provide important insights into the differentially regulated miRNAs, their associated pathways and potential utilization for clinical benefits in ischemic stroke patients with diabetes.

Quercetin targets VCAM1 to prevent diabetic cerebrovascular endothelial cell injury

Introduction

Endothelial cells play important roles in neurodegenerative diseases caused by diabetes, therefore, we aimed at investigating the mechanisms through which endothelial cells are involved in diabetes development.

Methods

Single cell analysis was performed to identify the major endothelial cell subtypes in cardiovascular tissues that are involved in diabetes development. A cell-cell communication approach was then used to identify ligand-receptor interaction pairs between these cell types. Differential expression analysis between the two experimental groups [standard chow diet group and diabetogenic diet with cholesterol (DDC) group] was used to identify diabetes-related differentially expressed genes (DEGs). The upregulated genes were used to identify candidate ligands or receptors, as well as the corresponding cell types. Cell trajectory inference was performed to identify the stage of cell development and changes in expression of candidate ligands or receptors during cell development. Gene set enrichment analysis (GSEA) was conducted to investigate the biological functions of genes of purpose. Finally, molecular dynamics simulations (MDSs) were used to predict potential drugs with the ability to target the proteins of purpose.

Results

Seven cell types, including five endothelial cell subtypes (EC_1, EC_2, EC_3, EC_4, and EC_EndMT), were identified from endothelial cell-enriched single cell samples from the heart and aorta of mice. Cell-cell communication analysis revealed the potential ligand-receptor interactions between these cell types while five important ligand-receptor-associated genes, including Fn1, Vcam1, Fbn1, Col4a1, and Col4a2, were established by differential expression analysis. Among them, Vcam1 is mainly expressed in EC_EndMT and is involved in interactions between EC_EndMT and other cells. Cell trajectory extrapolation analysis revealed a shift from EC_2/EC_4 to EC_EndMT and a shift from EC_EndMT to EC_3/EC_1 during the progression of diabetes. GSEA analysis revealed that upregulation of VCAM1 may have inhibitory effects on cell growth and energy metabolism.

Conclusion

EC_EndMT subtypes have a complex role in neurodegenerative diseases caused by diabetes. Through mechanisms involved in cell-cell communication, Vcam1 may play an important role in dysregulation of biological functions of EC_ EndMT. Molecular docking results of the quercetin-VCAM1 complex suggest that quercetin may be an effective drug for targeting this protein.