Hypertension and diabetes mellitus as a predictive risk factors for stroke

Unravelling pharmacological mechanisms and effects of Tianma Siwu Decoction-derived compounds on ischemic stroke by multidimensional network pharmacological analysis

ETHNOPHARMACOLOGICAL RELEVANCE

Ischemic stroke (IS) a complex pathological event emerging as one of the most serious threats with huge economic impact in the 21st century. Following IS, multiple cascades and pathways are stimulated, culminating in long term consequences. One of Chinese Traditional Medicine, Tianma Siwu Decoction (TSD), is known to have sedative-hypnotic, anticonvulsant and anti-inflammatory effects, which is usually used to treat migraine and ischemic stroke, but its potential pharmacological mechanism remains unclear.

AIM OF THE STUDY

This study is aimed to identify the active principles from TSD that has strong pharmacological effect on the treatment of IS.

MATERIALS AND METHODS

Based on liquid chromatography-triple quadrupole mass spectrometry (LC-Q-MS/MS) technology, a new three-step-based approach integrating concentration parameters and Quality marker (Q-marker) with network pharmacology and bioactivity evaluation to explore the therapeutic effects and mechanisms of TSD on ischemic stroke. Ultimately, as the main herb of the TSD, high-concentration compounds from Gastrodia elata Blume (GEB) were identified and collected by LC-Q-MS/MS, and an optimized analytical model in multidimensional network pharmacology was introduced to more accurately explore the potential mechanisms by which TSD affects IS.

RESULTS

The results showed that 280 overlapping targets of TSD were obtained after the introduction of compound concentration parameters into the multidimensional network pharmacology analysis. Additionally, TSD might regulate IS through the AGE-RAGE and Rap1 signaling pathways. Through an in vitro hypoxia-reoxygenation injury cell model, it was discovered that as the Q-markers of GEB, gastrodin and parishin could effectively reduce neuronal hypoxic injury by modulating the expression levels of p-JNK and p-p38 proteins. According to the results of molecular docking, gastrodin and baicalin exhibits strong binding affinity to GAPDH and MAPK3, respectively (≦-7 kcal/mol).

CONCLUSION

We discovered that compound concentration is a key factor that influence the activity of substances, affects the accuracy and reliability of predictive outcomes. Consequently, the study enhances the network pharmacology model by incorporating concentration factors, aiming for a more accurate understanding of the potential mechanisms behind TSD anti-ischemic stroke actions.

An intelligent learning system based on electronic health records for unbiased stroke prediction

Stroke has a negative impact on people's lives and is one of the leading causes of death and disability worldwide. Early detection of symptoms can significantly help predict stroke and promote a healthy lifestyle. Researchers have developed several methods to predict strokes using machine learning (ML) techniques. However, the proposed systems have suffered from the following two main problems. The first problem is that the machine learning models are biased due to the uneven distribution of classes in the dataset. Recent research has not adequately addressed this problem, and no preventive measures have been taken. Synthetic Minority Oversampling (SMOTE) has been used to remove bias and balance the training of the proposed ML model. The second problem is to solve the problem of lower classification accuracy of machine learning models. We proposed a learning system that combines an autoencoder with a linear discriminant analysis (LDA) model to increase the accuracy of the proposed ML model for stroke prediction. Relevant features are extracted from the feature space using the autoencoder, and the extracted subset is then fed into the LDA model for stroke classification. The hyperparameters of the LDA model are found using a grid search strategy. However, the conventional accuracy metric does not truly reflect the performance of ML models. Therefore, we employed several evaluation metrics to validate the efficiency of the proposed model. Consequently, we evaluated the proposed model's accuracy, sensitivity, specificity, area under the curve (AUC), and receiver operator characteristic (ROC). The experimental results show that the proposed model achieves a sensitivity and specificity of 98.51% and 97.56%, respectively, with an accuracy of 99.24% and a balanced accuracy of 98.00%.

Cardiovascular Effectiveness and Safety of Antidiabetic Drugs in Patients with Type 2 Diabetes and Peripheral Artery Disease: Systematic Review

Peripheral artery disease (PAD) is an atherosclerotic condition commonly complicating type 2 diabetes (T2D), leading to poor quality of life and increased risk of major adverse lower-limb (MALE) and cardiovascular (CV) events (MACE). Therapeutic management of PAD in T2D patients is much more arduous, often due to bilateral, multi-vessel, and distal vascular involvement, in addition to increased systemic polyvascular atherosclerotic burden. On the other hand, the pathophysiological link between PAD and T2D is very complex, involving mechanisms such as endothelial dysfunction and increased subclinical inflammation in addition to chronic hyperglycemia. Therefore, the clinical approach should not ignore vascular protection with the aim of reducing limb and overall CV events besides a mere glucose-lowering effect. However, the choice of the best medications in this setting is challenging due to low-grade evidence or lacking targeted studies in PAD patients. The present review highlighted the strong relationship between T2D and PAD, focusing on the best treatment strategy to reduce CV risk and prevent PAD occurrence and worsening in patients with T2D. The Medline databases were searched for studies including T2D and PAD up to June 2024 and reporting the CV effectiveness and safety of the most used glucose-lowering agents, with no restriction on PAD definition, study design, or country. The main outcomes considered were MACE-including nonfatal acute myocardial infarction, nonfatal stroke, and CV death-and MALE-defined as lower-limb complications, amputations, or need for revascularization. To the best of our current knowledge, GLP-1 receptor agonists and SGLT2 inhibitors represent the best choice to reduce CV risk in T2D and PAD settings, but a personalized approach should be considered. GLP-1 receptor agonists should be preferred in subjects with prevalent atherosclerotic burden and a history of previous MALE, while SGLT2 inhibitors should be used in those with heart failure if overall CV benefits outweigh the risk of lower-limb complications.

Exploring the link between brain topological resilience and cognitive performance in the context of aging and vascular risk factors: A cross-ethnicity population-based study

Brain aging is typically associated with a significant decline in cognitive performance. Vascular risk factors (VRF) and subsequent atherosclerosis (AS) play a major role in this process. Brain resilience reflects the brain's ability to withstand external perturbations, but the relationship of brain resilience with cognition during the aging process remains unclear. Here, we investigated how brain topological resilience (BTR) is associated with cognitive performance in the face of aging and vascular risk factors. We used data from two cross-ethnicity community cohorts, PolyvasculaR Evaluation for Cognitive Impairment and Vascular Events (PRECISE, n = 2220) and Sydney Memory and Ageing Study (MAS, n = 246). We conducted an attack simulation on brain structural networks based on k-shell decomposition and node degree centrality. BTR was defined based on changes in the size of the largest subgroup of the network during the simulation process. Subsequently, we explored the negative correlations of BTR with age, VRF, and AS, and its positive correlation with cognitive performance. Furthermore, using structural equation modeling (SEM), we constructed path models to analyze the directional dependencies among these variables, demonstrating that aging, AS, and VRF affect cognition by disrupting BTR. Our results also indicated the specificity of this metric, independent of brain volume. Overall, these findings underscore the supportive role of BTR on cognition during aging and highlight its potential application as an imaging marker for objective assessment of brain cognitive performance.

The action mechanism by which C1q/tumor necrosis factor-related protein-6 alleviates cerebral ischemia/reperfusion injury in diabetic mice

JOURNAL/nrgr/04.03/01300535-202409000-00034/figure1/v/2024-01-16T170235Z/r/image-tiff Studies have shown that C1q/tumor necrosis factor-related protein-6 (CTRP6) can alleviate renal ischemia/reperfusion injury in mice. However, its role in the brain remains poorly understood. To investigate the role of CTRP6 in cerebral ischemia/reperfusion injury associated with diabetes mellitus, a diabetes mellitus mouse model of cerebral ischemia/reperfusion injury was established by occlusion of the middle cerebral artery. To overexpress CTRP6 in the brain, an adeno-associated virus carrying CTRP6 was injected into the lateral ventricle. The result was that oxygen injury and inflammation in brain tissue were clearly attenuated, and the number of neurons was greatly reduced. In vitro experiments showed that CTRP6 knockout exacerbated oxidative damage, inflammatory reaction, and apoptosis in cerebral cortical neurons in high glucose hypoxia-simulated diabetic cerebral ischemia/reperfusion injury. CTRP6 overexpression enhanced the sirtuin-1 signaling pathway in diabetic brains after ischemia/reperfusion injury. To investigate the mechanism underlying these effects, we examined mice with depletion of brain tissue-specific sirtuin-1. CTRP6-like protection was achieved by activating the sirtuin-1 signaling pathway. Taken together, these results indicate that CTRP6 likely attenuates cerebral ischemia/reperfusion injury through activation of the sirtuin-1 signaling pathway.

Missed opportunities for hypertension screening of older people in the Philippines: cross-sectional analysis of nationally representative individual-level data

Background

Guidelines recommend routine blood pressure measurement at health facilities. We estimated the potential for opportunistic screening for hypertension at health facilities to change the level and distribution of diagnosed hypertension in the older population of the Philippines.

Methods

We used a representative, nationwide sample of Filipinos aged 60 years and older and classified respondents as a) hypertensive if they had high (≥140/90 mm Hg) blood pressure (BP) or were taking BP medication, b) diagnosed if told have high BP by a doctor, and c) a missed opportunity for diagnosis if they were hypertensive, undiagnosed and had an outpatient visit to a health facility in the past 12 months. We assumed c) would be diagnosed if health facilities operated opportunistic screening. We estimated percentages of hypertensives diagnosed and with a missed opportunity overall, by wealth quintile and covariates, with age-sex and, then, full adjustment.

Findings

We estimated that opportunistic screening at health facilities would increase the percentage of hypertensives diagnosed from 62.7% (95% CI: 58.2, 67.0) to 74.4% (95% CI: 70.9, 77.6). The increase would be larger in richer groups due to lower (private) healthcare utilization by poorer, undiagnosed hypertensives.

Interpretation

Opportunistic screening for hypertension, if effectively implemented at health facilities, would substantially increase diagnosis but exacerbate inequality unless barriers discouraging poorer, older Filipinos from accessing outpatient and primary care were lowered.

Funding

Economic Research Institute for ASEAN and East Asia, Swiss Agency for Development and Cooperation/Swiss National Science Foundation grant 400640_160374.

Predictors of Ischemic Stroke After Acute Coronary Syndrome: A Retrospective Analysis

Background Ischemic stroke (IS) is a fatal complication of acute coronary syndrome (ACS). Factors that speed up IS development after ACS are understudied, especially in developing countries like Pakistan. Thus, this study was designed to identify the potential risk factors of IS in patients with a preceding episode of ACS. Methodology This retrospective study was performed on 208 patients whose ACS and its consequent complications such as IS were managed in the cardiac and neurology units of Benazir Bhutto Hospital, Rawalpindi, from January 2022 to March 2023. Patients were enrolled via consecutive sampling and pre-defined inclusion and exclusion criteria. Before data collection, informed consent and ethical approval were obtained. Data were retrieved from the medical records of the patients. A self-structured proforma was applied to collect data. SPSS version 25 (IBM Corp., Armonk, NY, USA) was used for data analysis. The study variables between patients with and without IS were compared using descriptive and inferential statistics. The association between IS and its possible risk factors in patients who had previously experienced ACS was determined using multivariate logistic regression. Results Of the 208 enrolled patients, 24 (11.54%) had IS following ACS. Sedentary lifestyle (odds ratio (OR) = 3.099, 95% confidence interval (CI) = 1.025~4.219, p = 0.009), hypertension (OR = 3.060, 95% CI = 1.798~4.876, p = 0.002), diabetes mellitus (OR = 2.899, 95% CI = 1.126~4.112, p = 0.009), dyslipidemia (OR = 2.907, 95% CI = 1.332~4.254, p = 0.007), history of smoking (OR = 2.760, 95% CI = 1.234~4.122, p = 0.018), and non-adherence to ACS medication (OR = 2.966, 95% CI = 1.300~4.266, p = 0.030), were the risk factors of IS among patients with preceding ACS. Conclusions In the study population, the incidence of IS following ACS was significant. Sedentary lifestyle, hypertension, diabetes mellitus, dyslipidemia, smoking history, and non-compliance with ACS therapy all played a significant role in the development of IS in patients with prior ACS. Proper management of ACS and associated risk factors could lead to the prevention of serious complications such as IS.

Association between Bilateral Vertebral Artery Blood Flow Changes and Posterior Circulation Infarction in Patients with Severe Intracranial Stenosis

INTRODUCTION

The objective of this study was to explore the association between net vertebral artery flow volume (NVAFV), calculated through color duplex ultrasonography, and posterior circulation infarction (PCI) in patients with severe intracranial vertebral artery (VA) stenosis.

METHODS

234 patients with severe intracranial VA stenosis (≥70%) were categorized into the PCI group (n = 139) and the non-PCI group (n = 95) based on cranial MRI diagnosis. The correlation between NVAFV and CT perfusion data was analyzed, and the occurrence of PCI under diverse PCI mechanisms was also investigated. Multifactorial logistic regression and stratified analysis was performed to analyze the association between NVAFV and PCI. Lastly, generalized additive models and smooth curve fitting was utilized to outline relationship between NVAFV and PCI.

RESULTS

NVAFV showed a significant correlation with cerebral blood flow, mean transmit time, and time to peak. In the large artery atherosclerosis mechanism, a reduction in NVAFV correlated with a gradual rise in PCI cases (p = 0.002), while this trend lacked significance in the branch artery occlusive disease mechanism (p = 0.993). In the fully adjusted model, each 10 mL/min increase in NVAFV reduced PCI incidence by 11% (OR 0.890, 95% CI 0.840-0.943, p < 0.001), Sensitivity analysis showed similar results; NVAFV presented different PCI risks among various glucose level subgroups, the OR (95% CI) for PCI was 0.788 (0.684, 0.906) in low-glucose group (T1), 0.968 (0.878, 1.066) in moderate-glucose group (T2), and 0.886 (0.801, 0.979) in high-glucose group (T3). Smooth curve fitting demonstrated a linear negative association between NVAFV and PCI.

CONCLUSION

NVAFV demonstrated an association with PCI in patients with severe intracranial VA stenosis, it can serve as a reference for identifying high-risk populations of PCI; however, it must be considered in combination with glucose.

Assessment of knowledge and awareness of stroke among the Syrian population: unveiling the current landscape in Syria through the first nationally representative study

Stroke is a global public health concern, contributing to high rates of morbidity and mortality. In Syria, the current conflict and associated challenges have had a profound impact on healthcare infrastructure, including education and awareness programs related to stroke. An essential aspect of preventing stroke is the awareness of individuals. The study aimed to investigate factors associated with knowledge and awareness of stroke among Syrian people. A cross-sectional national representative study was conducted in Syria. The questionnaire was created on Google form and disseminated as a link through online platform social media like Facebook, WhatsApp, and Twitter. The population of the study was divided using proportionate random sampling into the 14 governorates. A random sample was selected from each area. The STROBE reporting guideline for cross-sectional studies was followed. Logistic regression analysis was performed to identify the factors associated with poor knowledge of stroke. A total of 1013 Syrian adults participated in the study. With more than half of them were females (53.5%) and employed (55.6%). Significant associations were found between ability to identify at least one correct risk factor and employability status (p = 0.029), single group (p = 0.036) and smokers (p < 0.001). In addition, significant associations were found between identifying at least one correct stroke symptom and smokers (p < 0.001) and no-obese people (p = 0.048). Furthermore, younger age group (below 30 years) were significantly able to list at least one correct stroke consequence compared to the older age groups (p = 0.025). Moreover, a significantly higher number of smokers compared to non-smokers correctly identified at least one stroke consequence (p = 0.019). The study revealed that there is a relatively weak understanding of the preventable nature of stroke among Syrian population. The overall awareness is still inadequate and varies depending on lifestyle factors and employment status.

Risk factors of acute ischemic stroke and the role of angiotensin I in predicting prognosis of patients undergoing endovascular thrombectomy

Purpose

The interaction between the renin-angiotensin system (RAS) and the acute ischemic stroke (AIS) is definite but not fully understood. This study aimed to analyze the risk factors of AIS and explore the role of serum indicators such as angiotensin I (Ang I) in the prognosis of patients undergoing endovascular thrombectomy (EVT).

Patients and methods

Patients with AIS who underwent EVT and healthy controls were retrospectively enrolled in this study, and the patients were divided into a good or a poor prognosis group. We compared Ang I, blood routine indexes, biochemical indexes, electrolyte indexes, and coagulation indexes between patients and controls. We used univariate and multivariate logistic regression analyses to evaluate possible risk factors for AIS and the prognosis of patients undergoing EVT. Independent risk factors for the prognosis of patients undergoing EVT were identified through multifactorial logistic regression analyses to construct diagnostic nomograms, further assessed by receiver operating characteristic curves (ROC).

Results

Consistent with previous studies, advanced age, high blood glucose, high D-dimer, and high prothrombin activity are risk factors for AIS. In addition, Ang I levels are lower in AIS compared to the controls. The level of Ang I was higher in the good prognosis group. Furthermore, we developed a nomogram to evaluate its ability to predict the prognosis of AIS after EVT. The AUC value of the combined ROC model (Ang I and albumin-globulin ratio (AGR)) was 0.859.

Conclusions

In conclusion, advanced age, high blood glucose, high D-dimer, and high prothrombin activity are risk factors for AIS. The combined Ang I and AGR model has a good predictive ability for the prognosis of AIS patients undergoing arterial thrombectomy.

Cognitive dysfunction in diabetes-related foot complications: A cohort study

Objective

Mild-moderate cognitive impairment has been identified in general diabetes, and early evidence indicates cognitive reductions may be more pronounced in those with diabetes-related foot complications (DRFC). Cognitive difficulties may impede treatment engagement and self-management. This requires further explication to optimise patient care and outcomes. The current study aimed to characterise cognitive function in people with DRFC using comprehensive cognitive measures.

Method

This cross-sectional cohort study recruited 80 adult participants (M age  = 63.38, SD = 11.40, range = 30 - 89) from the Royal Melbourne Hospital Diabetic Foot Unit in Victoria, Australia, all with DRFC. Each completed a comprehensive cognitive battery (memory, attention, executive functions) and scores were calculated using age-matched population norms, where available.

Results

On the majority of tasks, DRFC participants performed significantly worse than age-matched norms, with the largest decrements seen in inhibition control, verbal memory, verbal abstract reasoning and working memory. Small to moderate reductions were also seen in visual learning, verbal fluency, processing speed and premorbid functioning. Demographic (lower education, male gender) and clinical factors (higher HbA1c, macrovascular and microvascular disease, longer diabetes duration) were associated with poorer cognitive functioning.

Conclusions

Marked reductions in cognitive functioning were found in individuals with DRFC, predominantly in the domains of verbal memory and executive functioning. Lower education, male gender and indicators of diabetes severity, such as vascular disease, are associated with heightened risk for poorer cognitive functioning. As DRFCs are a serious complication with devastating outcomes if not successfully managed, cognitive barriers to self-management must be addressed to optimise treatment.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40200-023-01381-4.

Genetically identified mediators associated with increased risk of stroke and cardiovascular disease in individuals with autism spectrum disorder

Growing evidence suggested that individuals with autism spectrum disorder (ASD) associated with stroke and cardiovascular disease (CVD). However, the causal association between ASD and the risk of stroke and CVD remains unclear. To validate this, we performed two-sample Mendelian randomization (MR) and two-step mediation MR analyses, using relevant genetic variants sourced from the largest genome-wide association studies (GWASs). Two-sample MR evidence indicated causal relationships between ASD and any stroke (OR = 1.1184, 95% CI: 1.0302-1.2142, P < 0.01), ischemic stroke (IS) (OR = 1.1157, 95% CI: 1.0237-1.2160, P = 0.01), large-artery atherosclerotic stroke (LAS) (OR = 1.2902, 95% CI: 1.0395-1.6013, P = 0.02), atrial fibrillation (AF) (OR = 1.0820, 95% CI: 1.0019-1.1684, P = 0.04), and heart failure (HF) (OR = 1.1018, 95% CI: 1.0007-1.2132, P = 0.05). Additionally, two-step mediation MR suggested that type 2 diabetes mellitus (T2DM) partially mediated this effect (OR = 1.14, 95%CI: 1.02-1.28, P = 0.03). The mediated proportion were 10.96% (95% CI: 0.58%-12.10%) for any stroke, 11.77% (95% CI: 10.58%-12.97%) for IS, 10.62% (95% CI: 8.04%-13.20%) for LAS, and 7.57% (95% CI: 6.79%-8.36%) for HF. However, no mediated effect was observed between ASD and AF risk. These findings have implications for the development of prevention strategies and interventions for stroke and CVD in patients with ASD.

Early-life tobacco smoke exposure and stroke risk: a prospective study of 341,783 and 352,737 UK Biobank participants

INTRODUCTION

Stroke is a life-threatening condition that causes a major medical burden globally. The currently used methods for the prevention or prediction of stroke have certain limitations. Exposure to tobacco in early life, including smoking during adolescence and maternal smoking during pregnancy, can affect adolescent development and lead to several negative outcomes. However, the association between early-life tobacco exposure and stroke is not known.

METHODS

In this prospective cohort study, for the analyses involving exposure to maternal smoking during pregnancy and age of smoking initiation, we included 304,984 and 342,893 participants, respectively., respectively from the UK Biobank. Cox proportional hazard regression model and subgroup analyses were performed to investigate the association between early-life tobacco exposure and stroke. Mediation analyses were performed to identify the mediating role of biological aging in the association between early tobacco exposure and stroke.

RESULTS

Compared with participants whose mothers did not smoke during pregnancy, participants whose mothers smoked during pregnancy showed an 11% increased risk of stroke (HR: 1.11, 95% CI: 1.05-1.18, P < 0.001). Compared with participants who never smoked, participants who smoked during adulthood, adolescence and childhood showed a 22%, 24%, and 38% increased risk of stroke during their adulthood, respectively. Mediation analysis indicated that early-life tobacco exposure can cause stroke by increasing biological aging.

CONCLUSION

This study reveals that exposure to tobacco during early life is associated with an increased risk of experiencing a stroke, and increased biological aging can be the underlying mechanism.

Improved hypertensive stroke classification based on multi-scale feature fusion of head axial CT angiogram and multimodal learning

PURPOSE

Strokes are severe cardiovascular and circulatory diseases with two main types: ischemic and hemorrhagic. Clinically, brain images such as computed tomography (CT) and computed tomography angiography (CTA) are widely used to recognize stroke types. However, few studies have combined imaging and clinical data to classify stroke or consider a factor as an Independent etiology.

METHODS

In this work, we propose a classification model that automatically distinguishes stroke types with hypertension as an independent etiology based on brain imaging and clinical data. We first present a preprocessing workflow for head axial CT angiograms, including noise reduction and feature enhancement of the images, followed by an extraction of regions of interest. Next, we develop a multi-scale feature fusion model that combines the location information of position features and the semantic information of deep features. Furthermore, we integrate brain imaging with clinical information through a multimodal learning model to achieve more reliable results.

RESULTS

Experimental results show our proposed models outperform state-of-the-art models on real imaging and clinical data, which reveals the potential of multimodal learning in brain disease diagnosis.

CONCLUSION

The proposed methodologies can be extended to create AI-driven diagnostic assistance technology for categorizing strokes.

Advanced Nano-Drug Delivery Systems in the Treatment of Ischemic Stroke

In recent years, the frequency of strokes has been on the rise year by year and has become the second leading cause of death around the world, which is characterized by a high mortality rate, high recurrence rate, and high disability rate. Ischemic strokes account for a large percentage of strokes. A reperfusion injury in ischemic strokes is a complex cascade of oxidative stress, neuroinflammation, immune infiltration, and mitochondrial damage. Conventional treatments are ineffective, and the presence of the blood-brain barrier (BBB) leads to inefficient drug delivery utilization, so researchers are turning their attention to nano-drug delivery systems. Functionalized nano-drug delivery systems have been widely studied and applied to the study of cerebral ischemic diseases due to their favorable biocompatibility, high efficiency, strong specificity, and specific targeting ability. In this paper, we briefly describe the pathological process of reperfusion injuries in strokes and focus on the therapeutic research progress of nano-drug delivery systems in ischemic strokes, aiming to provide certain references to understand the progress of research on nano-drug delivery systems (NDDSs).

Findings of Angiography and Carotid Vessel Wall Imaging Associated with Post-Procedural Clinical Events after Carotid Artery Stenting

PURPOSE

Vessel wall imaging (VWI) for carotid plaque is better for detecting unstable carotid plaque such as intraplaque hemorrhage (IPH), lipid-rich necrotic core (LRNC), and thin/ruptured fibrous cap. However, the role of VWI before carotid artery stenting (CAS) is unclear. Thus, this study aimed to determine the findings of symptomatic carotid stenosis before CAS on angiography and carotid VWI and to evaluate the imaging findings associated with post-procedural clinical events after CAS.

MATERIALS AND METHODS

This retrospective study included 173 consecutive patients who underwent carotid VWI, CAS, and post-procedural diffusion-weighted imaging (DWI) after CAS. Findings of unstable plaque on carotid VWI and unstable findings on angiography were analyzed. We also analyzed the incidence of post-procedural clinical events, any stroke, myocardial infarction (MI), and death within 30 days of CAS.

RESULTS

Of 173 patients, 101 (58.4%) had initial ischemic symptoms and positive findings on DWI. Symptomatic patients were significantly higher in patients with IPH than in patients without IPH (62.4% vs. 45.8%, P=0.031). Degree of stenosis, thrombus of the stenotic lesion, flow delay of internal carotid artery, and flow arrest by filter thrombus had significantly higher prevalence in the symptomatic group. Twenty patients (11.6%) had post-procedural clinical events such as any stroke, clinical symptoms, and/or MI. Hyperlipidemia and intraluminal thrombus on angiography were identified as significant factors influencing post-procedural events after CAS.

CONCLUSION

An intraluminal thrombus on angiography was identified as a significant factor influencing post-procedural clinical events after CAS.

Protective mechanism of Paeonol on central nervous system

Cerebrovascular diseases involve neuronal damage, resulting in degenerative neuropathy and posing a serious threat to human health. The discovery of effective drug components from natural plants and the study of their mechanism are a research idea different from chemical synthetic medicines. Paeonol is the main active component of traditional Chinese medicine Paeonia lactiflora Pall. It widely exists in many medicinal plants and has pharmacological effects such as anti-atherosclerosis, antiplatelet aggregation, anti-oxidation, and anti-inflammatory, which keeps generally used in the treatment of cardiovascular and cerebrovascular diseases. Based on the therapeutic effects of Paeonol for cardiovascular and cerebrovascular diseases, this article reviewed the pharmacological effects of Paeonol in Alzheimer's disease, Parkinson's disease, stroke, epilepsy, diabetes encephalopathy, and other neurological diseases, providing a reference for the research of the mechanism of Paeonol in central nervous system diseases.

Mitochondrial-derived peptides: Antidiabetic functions and evolutionary perspectives

Mitochondrial-derived peptides (MDPs) are a novel class of bioactive microproteins encoded by short open-reading frames (sORF) in mitochondrial DNA (mtDNA). Currently, three types of MDPs have been identified: Humanin (HN), MOTS-c (Mitochondrial ORF within Twelve S rRNA type-c), and SHLP1-6 (small Humanin-like peptide, 1 to 6). The 12 S ribosomal RNA (MT-RNR1) gene harbors the sequence for MOTS-c, whereas HN and SHLP1-6 are encoded by the 16 S ribosomal RNA (MT-RNR2) gene. Special genetic codes are used in mtDNA as compared to nuclear DNA: (i) ATA and ATT are used as start codons in addition to the standard start codon ATG; (ii) AGA and AGG are used as stop codons instead of coding for arginine; (iii) the standard stop codon UGA is used to code for tryptophan. While HN, SHLP6, and MOTS-c are encoded by the H (heavy owing to high guanine + thymine base composition)-strand of the mtDNA, SHLP1-5 are encoded by the L (light owing to less guanine + thymine base composition)-strand. MDPs attenuate disease pathology including Type 1 diabetes (T1D), Type 2 diabetes (T2D), gestational diabetes, Alzheimer's disease (AD), cardiovascular diseases, prostate cancer, and macular degeneration. The current review will focus on the MDP regulation of T2D, T1D, and gestational diabetes along with an emphasis on the evolutionary pressures for conservation of the amino acid sequences of MDPs.

Stroke after Cardiac Surgery: A Risk Factor Analysis of 580,117 Patients from UK National Adult Cardiac Surgical Audit Cohort

Cerebrovascular accident is the most ominous complication observed after cardiac surgery, carrying an increased risk of morbidity and mortality. Analysis of the problem shows its multidimensional nature. In this study, we aimed to identify major determinants among classic variables, either demographic, clinical or type of surgical procedure, based on the analysis of a large dataset of 580,117 patients from the UK National Adult Cardiac Surgical Audit (NACSA). For this purpose, univariate and multivariate logistic regression models were utilized to determine associations between predictors and dependent variable (Stroke after cardiac surgery). Odds ratios (ORs) and 95% confidence intervals (CIs) were constructed for each independent variable. Statistical analysis allows us to confirm with greater certainty the predictive value of some variables such as age, gender, diabetes mellitus (diabetes treated with insulin OR = 1.37, 95%CI = 1.23-1.53), and systemic arterial hypertension (OR = 1.11, 95%CI = 1.05-1.16);, to emphasize the role of preoperative atrial fibrillation (OR = 1.10, 95%CI = 1.03-1.16) extracardiac arteriopathy (OR = 1.70, 95%CI = 1.58-1.82), and previous cerebral vascular accident (OR 1.71, 95%CI = 1.6-1.9), and to reappraise others like smoking status (crude OR = 1.00, 95%CI = 0.93-1.07 for current smokers) or BMI (OR = 0.98, 95%CI = 0.97-0.98). This could allow for better preoperative risk stratification. In addition, identifying those surgical procedures (for example thoracic aortic surgery associated with a crude OR of 3.72 and 95%CI = 3.53-3.93) burdened by a high risk of neurological complications may help broaden the field of preventive and protective techniques.

Causal relationship between atrial fibrillation and stroke risk: a Mendelian randomization

OBJECTIVES

This study aimed to investigate the causal relationship between Atrial Fibrillation (AF) and the risk of Stroke using a Mendelian randomization (MR) approach.

METHODS

A two-sample MR analysis was conducted using publicly available genome-wide association study (GWAS) summary statistics data. In this analysis, genetic variants associated with AF were used as instrumental variables to estimate the causal effect. The inverse-variance weighted (IVW) method, weighted median estimator, and MR-Egger regression were employed for estimation. Additionally, sensitivity analysis was performed using the leave-one-out method.

RESULTS

The analysis included 87 single nucleotide polymorphisms (SNPs) associated with AF. The results from the IVW method indicated a positive association between genetic predisposition to AF and the risk of stroke (OR 1.002, 95 % CI 1.001-1.003, P < 0.001). The weighted median and MR-Egger methods showed consistent results (weighted median: OR 1.001, 95 % CI 1.000-1.002, P = 0.034; MR-Egger: OR 1.001, 95 % CI 1.000-1.003, P = 0.086). Sensitivity analysis demonstrated that no individual SNP significantly influenced the causal inference.

CONCLUSIONS

This study provides evidence of a causal relationship between AF and an elevated risk of stroke. These findings emphasize the significance of managing AF in order to prevent and treat strokes. Additional research is required to better understand the underlying mechanisms of this causal association.

Association of Dietary Magnesium Intake with the Risk of Stroke among Adults

The relationship between dietary magnesium intake and the risk of stroke is controversial. This study aimed to examine the association of dietary magnesium intake with the risk of stroke among American adults.The relationship between dietary magnesium intake and the risk of stroke was analyzed using the National Health and Nutrition Examination Survey (NHANES) 2007-2018 data with 29,653 adults. The amount of magnesium from the diet was assessed by two 24-hour dietary recalls. Stroke outcomes were defined using the results of the self-reported questionnaires. The association between dietary magnesium intake and the risk of stroke was evaluated using logistic regression models and restricted cubic spline.In our study, an inverse association between dietary magnesium intake and the risk of stroke was found. For the highest versus lowest quartile of dietary magnesium intake, the multivariate-adjusted odds ratio (95% confidence interval) of stroke was 0.56 (0.36-0.86). The magnesium intake of women was negatively associated with stroke risk, but this negative association was not found in men. Then, the inverse association was statistically significant among the 40-59 year-old group. The results from the dose-response analysis show a linear relationship between dietary magnesium intake and the risk of stroke.Dietary magnesium intake was inversely associated with the risk of stroke, especially in women. Therefore, our study emphasizes the importance of appropriately increasing dietary magnesium intake.

Association between the intake of dietary n3 and n6 fatty acids and stroke in US adults: A cross-sectional study of NHANES 2007-2018

BACKGROUND

The association between the intake of dietary n3 and n6 fatty acids and the risk of stroke is subject to debate. The primary objective of the present research was to establish the correlation in a large sample of American adults.

METHODS

Using data from the National Health and Nutrition Examination Survey (NHANES) between 2007 and 2018, the association of the intake of dietary n3 and n6 fatty acids with stroke events was analyzed in a sample of 29,459 adults. The intake of n3 and n6 fatty acids intake was assessed though two 24-h dietary recalls. Stroke outcomes were identified based on the responses provided in self-reported questionnaire. Logistic regression was fitted to evaluate the correlation of dietary n3, n6 fatty acids intake with stroke events.

RESULTS

Subjects in the highest tertile (T3) of dietary n3 (OR: 0.67, 95% CI: 0.49-0.93), n6 (OR: 0.65, 95% CI: 0.45-0.95) fatty acids intake were found to have obviously lower risk of stroke compared to those in the lowest tertile (T1), but the n6:n3 ratio was not found to be associated with a stroke event. Results from stratified analysis demonstrated that dietary n3 fatty acids had an inverse correlation of stroke in both male and female, but dietary n6 fatty acids only had this correlation in male. Moreover, findings were made that the interaction was significant in terms of age in the subgroup analysis, and the negative relationship between the intake of dietary n3 and n6 fatty acids and stroke event were particularly pronounced among participants aged ≥60.

CONCLUSIONS

The present results suggested that increased dietary n3, n6 fatty acids intake correlated with a lower risk of stroke.

Meta-analysis of the effects of inert gases on cerebral ischemia-reperfusion injury

Recently, noble gas has become a hot spot within the medical field like respiratory organ cerebral anemia, acute urinary organ injury and transplantation. However, the shield performance in cerebral ischemia-reperfusion injury (CIRI) has not reached an accord. This study aims to evaluate existing evidence through meta-analysis to determine the effects of inert gases on the level of blood glucose, partial pressure of oxygen, and lactate levels in CIRI. We searched relevant articles within the following both Chinese and English databases: PubMed, Web of science, Embase, CNKI, Cochrane Library and Scopus. The search was conducted from the time of database establishment to the end of May 2023, and two researchers independently entered the data into Revman 5.3 and Stata 15.1. There were total 14 articles were enclosed within the search. The results showed that the amount of partial pressure of blood oxygen in the noble gas cluster was beyond that in the medicine gas cluster (P < 0.05), and the inert gas group had lower lactate acid and blood glucose levels than the medical gas group. The partial pressure of oxygen (SMD = 1.51, 95% CI 0.10 ~ 0.91 P = 0.04), the blood glucose level (SMD = - 0.59, 95% CI - 0.92 ~ - 0.27 P = 0.0004) and the lactic acid level (SMD = - 0.42, 95% CI - 0.80 ~ - 0.03 P = 0.03) (P < 0.05). These results are evaluated as medium-quality evidence. Inert gas can effectively regulate blood glucose level, partial pressure of oxygen and lactate level, and this regulatory function mainly plays a protective role in the small animal ischemia-reperfusion injury model. This finding provides an assessment and evidence of the effectiveness of inert gases for clinical practice, and provides the possibility for the application of noble gases in the treatment of CIRI. However, more operations are still needed before designing clinical trials, such as the analysis of the inhalation time, inhalation dose and efficacy of different inert gases, and the effective comparison of the effects in large-scale animal experiments.

Causal Paradigm Between Common Comorbidities of Cardiovascular and Metabolism-Related Diseases in Elderly: Evidence from Cross-Sectional and Mendelian Randomization Studies

Background

Comorbidity is a common problem among elderly people, significantly damaging individuals' health and healthcare systems. However, observational studies may be susceptible to residual confounding factors and bias. The present study aimed to assess the causal effect of common chronic disease comorbidity using the Mendelian randomization (MR) approach.

Methods

Data for the present study were obtained from a community survey conducted between 2018 and 2020 in four counties in Ganzhou City, southern China. A cross-sectional survey was conducted using a multi-stage stratified random sampling method. A total of 1756 valid questionnaires were collected to analyze common chronic disease comorbidities. Genetic variants associated with hypertension, diabetes, stroke, and hyperlipidemia-related factors were selected as instrumental variables for univariate and multivariate MR analyses.

Results

The self-reported prevalence of chronic disease in the older adult population in Southern China was 68.1%, with hypertension (46.1%), diabetes (10.5%), and hyperlipidemia (8.5%) being the three most common conditions. The prevalence of chronic disease comorbidity was 20.7% among the 12 chronic diseases studied. Hypertension was identified as a predictor of diabetes (OR [95% CI]: 1.114 [1.049, 1.184], p < 0.001), and diabetes mellitus was equally identified as a risk factor for hypertension (OR [95% CI]: 1.118 [1.069, 1.187], p < 0.001). Furthermore, high triglyceride levels were identified as a risk factor for hypertension (OR [95% CI]: 1.262 [1.129, 1.411], p < 0.001). In contrast to intracranial hemorrhages, hypertension had a significant impact on ischemic stroke (OR [95% CI]: 1.299 [1.161, 1.454], p < 0.001).

Conclusion

The causal association between multiple cardiovascular and metabolism-related diseases is mediated by hypertension, with a bidirectional cause-and-effect relationship between hypertension and diabetes. Hypertension is a risk factor for ischemic stroke, and the hyperlipidemia-related factor triglycerides (TG) influence hypertension. Therefore, prioritizing hypertension prevention and control in the elderly is critical for effective chronic disease management.

Train-your-brain program to reduce depression, anxiety, and stress in stroke survivors: a pilot community-based cognitive intervention study

Introduction

Stroke is a major cause of death and disability worldwide, and it often results in depression, anxiety, stress, and cognitive impairment in survivors. There is a lack of community-based cognitive interventions for stroke survivors. This pilot single trial aimed to assess the feasibility, acceptability, and perceived effectiveness of a community-based cognitive intervention program called Train-Your-Brain (TYB) for stroke survivors and caregivers. The study focused on improvements in emotional and psychological well-being, as well as cognitive functioning.

Methods

A quasi-experimental design was used in this study. A total of 48 participants were recruited and assessed using Depression, Anxiety, Stress Scale - 21 items (DASS-21), Montreal Cognitive Assessment (MoCA) and Symbol Digits Modality Test (SDMT) before and after the intervention. The TYB program consisted of nine sessions and was conducted via the Zoom software application. Participants provided feedback on the program, highlighting areas for improvement.

Results

Twenty-seven stroke survivors and 21 caregivers completed the program. Participants expressed high satisfaction with the TYB program but recommended avoiding assessments in December and customizing the program for stroke survivors and caregivers. Stroke survivors showed significant improvements in depression and stress scores, while caregivers experienced no significant improvements after the program. While there was a slight improvement in stroke survivors' cognitive scores after the program, it was not statistically significant. Caregivers, however, experienced a significant decline in cognitive scores.

Discussion

The TYB program provided group support and validation, resulting in improved mood and reduced stress among stroke survivors. Cultural collectivism played a significant role in fostering group cohesion. However, the program's limited focus on caregivers and timing of assessments during the December holidays may have affected the outcomes. The TYB program demonstrated feasibility and potential effectiveness in alleviating psychological distress and enhancing cognitive function among stroke survivors. Future research should explore long-term effects, larger sample sizes, and non-English-speaking populations to enhance generalizability. Tailored interventions for caregivers are necessary.

Association Between Sleep Duration and Stroke in Different Status of Metabolic Syndrome: A Cross-Sectional Study in Shanghai Adult Residents

Purpose

This study aimed to investigate the relationship between sleep duration (SD) and stroke, and examine the effects of SD on stroke with or without metabolic syndrome (Mets) and its components among the adult residents in Shanghai, China.

Participants and Methods

A total of 20,245 participants (51.72% male, mean age 44.66 years) were included from Shanghai Chronic Disease and Risk Factors Surveillance (SCDRFS) in 2017. The weighted logistic regressions were performed to examine the associations between SD and stroke in different status of Mets and its components.

Results

The mean SD was 7.51±0.03 h/d. After adjusting for all the potential factors, SD<6 h/d (OR=1.73, 95% CI: 1.35-2.20) or ≥10 h/d (OR=1.66, 95% CI: 1.08-2.57) was significantly positively associated with stoke in the total participants; moreover, in the non-Mets group, only SD<6 h/d (OR=1.77, 95% CI: 1.19, 2.64) significantly increased the risk of stroke; while, in the Mets group, SD<6 h/d (OR=1.80, 95% CI:1.17-2.76) and ≥10 h/d (OR=1.97, 95% CI: 1.00-3.88) both had a positive significantly association with stoke. In addition, the effects of SD<6 h/d on stroke were more pronounced among those with high WC (OR=2.24, 95% CI: 1.40-3.58) and high TG (OR=2.60, 95% CI: 1.86-3.62), and the effects of SD≥10 h/d on stroke were more evident among those with high TG (OR=2.28, 95% CI: 1.02-5.08) and high FBG (OR=2.58, 95% CI: 1.30-5.10).

Conclusion

Both short and long SD were significantly positively associated with stroke in the total participants, and the associations were stronger in the Mets group; conversely, in the non-Mets group, only short SD was significantly positively associated with stroke, and no significant association was observed between long SD and stroke. Therefore, more precise sleep measures may be needed to prevent stroke according to the different status of Mets.

Development, validation, and visualization of a novel nomogram to predict stroke risk in patients

Background

Stroke is the second leading cause of death worldwide and a major cause of long-term neurological disability, imposing an enormous financial burden on families and society. This study aimed to identify the predictors in stroke patients and construct a nomogram prediction model based on these predictors.

Methods

This retrospective study included 11,435 participants aged >20 years who were selected from the NHANES 2011-2018. Randomly selected subjects (n = 8531; 75%) and the remaining subjects comprised the development and validation groups, respectively. The least absolute shrinkage and selection operator (LASSO) binomial and logistic regression models were used to select the optimal predictive variables. The stroke probability was calculated using a predictor-based nomogram. Nomogram performance was assessed by the area under the receiver operating characteristic curve (AUC) and the calibration curve with 1000 bootstrap resample validations. Decision curve analysis (DCA) was performed to evaluate the clinical utility of the nomogram.

Results

According to the minimum criteria of non-zero coefficients of Lasso and logistic regression screening, older age, lower education level, lower family income, hypertension, depression status, diabetes, heavy smoking, heavy drinking, trouble sleeping, congestive heart failure (CHF), coronary heart disease (CHD), angina pectoris and myocardial infarction were independently associated with a higher stroke risk. A nomogram model for stroke patient risk was established based on these predictors. The AUC (C statistic) of the nomogram was 0.843 (95% CI: 0.8186-0.8430) in the development group and 0.826 (95% CI: 0.7811, 0.8716) in the validation group. The calibration curves after 1000 bootstraps displayed a good fit between the actual and predicted probabilities in both the development and validation groups. DCA showed that the model in the development and validation groups had a net benefit when the risk thresholds were 0-0.2 and 0-0.25, respectively.

Discussion

This study effectively established a nomogram including demographic characteristics, vascular risk factors, emotional factors and lifestyle behaviors to predict stroke risk. This nomogram is helpful for screening high-risk stroke individuals and could assist physicians in making better treatment decisions to reduce stroke occurrence.

Co-occurrence of hypertension and type 2 diabetes: prevalence and associated factors among Haramaya University employees in Eastern Ethiopia

Background

Both hypertension (HTN) and diabetes are public health concerns in low- and middle-income countries, particularly in sub-Saharan African countries. The co-occurrence of HTN and diabetes is associated with an increased risk of mortality, morbidity, and reduced productivity in the working force. In Ethiopia, there is limited evidence on the co-occurrence of HTN and type 2 diabetes (T2DM). Therefore, this study was conducted to assess the co-occurrence of HTN and T2DM and their associated factors among Haramaya University employees in Eastern Ethiopia.

Methods

A cross-sectional survey was conducted among 1,200 employees at Haramaya University using a simple random sampling technique from December 2018 to February 2019. Demographic and behavioral factors were collected on a semi-structured questionnaire, followed by measurement of anthropometry and blood pressure. Blood glucose and lipid profile measurements were performed by collecting 6 ml of venous blood samples after 8 h of overnight fasting. Data were entered into EpiData 3.1 version and analyzed using Stata 16 software. Bivariable and multivariable logistic regressions were applied to observe the association between independent variables with co-occurrence of HPN and T2DM using odds ratio, 95% confidence interval (CI), and p-values of ≤ 0.05 were considered statistically significant.

Results

The prevalence of HTN and T2DM was 27.3 and 7.4%, respectively. The co-occurrence of HTN and T2DM was 3.8%. The study found that being older (AOR = 3.97; 95 % CI: 1.80-8.74), khat chewing (AOR = 2.76; 95 % CI: 1.23-6.18), body mass index ≥ 25 kg/m² (AOR = 5.11; 95 % CI: 2.06-12.66), and sedentary behavior ≥8 h per day (AOR = 6.44; 95 % CI: 2.89-14.34) were statistically associated with co-occurrence of HTN and T2DM. On the other hand, consuming fruits and vegetables (AOR = 0.10; 95 % CI: 0.04-0.22) and a higher level of education (AOR = 0.39; 95% CI: 0.17-0.89) were negatively statistically associated with the co-occurrence of HTN and T2DM.

Conclusion

The co-occurrence of HTN and T2DM was prevalent among the study participants. This may create a substantial load on the healthcare system as an end result of increased demand for healthcare services. Therefore, rigorous efforts are needed to develop strategies for screening employees to tackle the alarming increase in HTN and T2DM in university employees.

Use and misuse of random forest variable importance metrics in medicine: demonstrations through incident stroke prediction

BACKGROUND

Machine learning tools such as random forests provide important opportunities for modeling large, complex modern data generated in medicine. Unfortunately, when it comes to understanding why machine learning models are predictive, applied research continues to rely on 'out of bag' (OOB) variable importance metrics (VIMPs) that are known to have considerable shortcomings within the statistics community. After explaining the limitations of OOB VIMPs - including bias towards correlated features and limited interpretability - we describe a modern approach called 'knockoff VIMPs' and explain its advantages.

METHODS

We first evaluate current VIMP practices through an in-depth literature review of 50 recent random forest manuscripts. Next, we recommend organized and interpretable strategies for analysis with knockoff VIMPs, including computing them for groups of features and considering multiple model performance metrics. To demonstrate methods, we develop a random forest to predict 5-year incident stroke in the Sleep Heart Health Study and compare results based on OOB and knockoff VIMPs.

RESULTS

Nearly all papers in the literature review contained substantial limitations in their use of VIMPs. In our demonstration, using OOB VIMPs for individual variables suggested two highly correlated lung function variables (forced expiratory volume, forced vital capacity) as the best predictors of incident stroke, followed by age and height. Using an organized analytic approach that considered knockoff VIMPs of both groups of features and individual features, the largest contributions to model sensitivity were medications (especially cardiovascular) and measured medical risk factors, while the largest contributions to model specificity were age, diastolic blood pressure, self-reported medical risk factors, polysomnography features, and pack-years of smoking. Thus, we reach very different conclusions about stroke risk factors using OOB VIMPs versus knockoff VIMPs.

CONCLUSIONS

The near-ubiquitous reliance on OOB VIMPs may provide misleading results for researchers who use such methods to guide their research. Given the rapid pace of scientific inquiry using machine learning, it is essential to bring modern knockoff VIMPs that are interpretable and unbiased into widespread applied practice to steer researchers using random forest machine learning toward more meaningful results.

Time trajectories of key cardiometabolic parameters and of cardiovascular risk in subjects with diabetes in a real world setting

BACKGROUND AND AIMS

Diabetes is associated with increased cardiovascular risk. Glycated haemoglobin (HbA_1c), lipid parameters and blood pressure are known risk factors for adverse outcome. The aim of the study was to explore the time trajectories of these key parameters and of the associated cardiovascular risk.

METHODS

We linked the diabetes electronic health records to the laboratory information system so as to investigate the trajectories of key metabolic parameters from 3 years prior to the diagnosis of diabetes to 10 years after diagnosis. We calculated the cardiovascular risk at the different time points during this period using the United Kingdom Prospective Study (UKPDS) risk engine.

RESULTS

The study included 21,288 patients. The median age at diagnosis was 56 years and 55.3% were male. There was a sharp decrease in HbA_1c after diagnosis of diabetes, but there was a progressive rise thereafter. All lipid parameters after diagnosis also improved in the year of diagnosis, and these improvements persisted even up to 10 years post-diagnosis. There was no discernible trend in mean systolic or diastolic blood pressures following diagnosis of diabetes. There was a slight decrease in the UKPDS-estimated cardiovascular risk after diagnosis of diabetes followed by a progressive increase. Estimated glomerular filtration rate declined at an average rate of 1.33 ml/min/1.73 m²/year.

CONCLUSIONS

Our data suggest that lipid control should be tightened with increasing duration of diabetes since this is more readily achievable than HbA_1c lowering and since other factors such as age and duration of diabetes are unmodifiable.

Acute Brain Infarction in Antineutrophil Cytoplasmic Antibody-Associated Vasculitis: A Korean Single-Center Study

OBJECTIVES

This study investigated the clinical and radiological features of antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) patients with acute brain infarction, using a cohort of Korean patients with AAV.

METHODS

This study included 263 patients with AAV. Acute brain infarction was defined as infarction that occurred within 7 days or less. The brain territories affected by acute brain infarction were investigated. Active AAV was arbitrarily defined as the highest tertile of Birmingham Vasculitis Activity Score (BVAS).

RESULTS

The median age at diagnosis was 59.0 years, and 35.4% were male. Fourteen cases of acute brain infarction occurred in 12 patients (4.6%), which was calculated as 1332.2 per 100,000 patient-years and 10 times higher than the incidence rate in the Korean general population. Patients with AAV with acute brain infarction exhibited significantly older age, increased BVAS at diagnosis, and a more frequent history of prior brain infarction compared with those without. The brain territories affected in AAV patients were middle cerebral artery (50.0%), multiple territories (35.7%), and posterior cerebral artery (14.3%). Lacunar infarction and microhemorrhage were observed in 42.9% and 71.4% of cases, respectively. Prior brain infarction and BVAS at diagnosis were independently associated with acute brain infarction (hazard ratios, 7.037 and 1.089). Patients with AAV with prior brain infarction or BVAS for active AAV exhibited significantly lower cumulative acute brain infarction-free survival rates than those without.

CONCLUSION

Acute brain infarction was observed in 4.6% of AAV patients, and both prior brain infarction and BVAS at diagnosis were independently associated with acute brain infarction.

Recurrent/Subsequent Stroke and Associated Outcomes in Geriatric Patients with OSA and Prior Stroke Events: A Retrospective Study Using the 2019 National Inpatient Sample

Background: Obstructive sleep apnea (OSA) increases the risk of stroke and cardiovascular diseases. However, its impact on geriatric patients with a prior history of stroke/transient ischemic attack (TIA) has not been adequately studied. Methods: We utilized the 2019 National Inpatient Sample in the US to identify geriatric patients with OSA (G-OSA) who had a prior history of stroke/TIA. We then compared subsequent stroke (SS) rates among sex and race subgroups. We also compared the demographics and comorbidities of SS+ and SS- groups and utilized logistic regression models to assess outcomes. Results: Out of 133,545 G-OSA patients admitted with a prior history of stroke/TIA, 4.9% (6520) had SS. Males had a higher prevalence of SS, while Asian-Pacific Islanders and Native Americans had the highest prevalence of SS, followed by Whites, Blacks, and Hispanics. The SS+ group had higher all-cause in-hospital mortality rates, with Hispanics showing the highest rate compared to Whites and Blacks (10.6% vs. 4.9% vs. 4.4%, p < 0.001), respectively. Adjusted analysis for covariates showed that complicated and uncomplicated hypertension (aOR 2.17 [95% CI 1.78-2.64]; 3.18 [95% CI 2.58-3.92]), diabetes with chronic complications (aOR 1.28 [95% CI 1.08-1.51]), hyperlipidemia (aOR 1.24 [95% CI 1.08-1.43]), and thyroid disorders (aOR 1.69 [95% CI 1.14-2.49]) were independent predictors of SS. The SS+ group had fewer routine discharges and higher healthcare costs. Conclusions: Our study shows that about 5% of G-OSA patients with a prior history of stroke/TIA are at risk of hospitalization due to SS, which is associated with higher mortality and healthcare utilization. Complicated and uncomplicated hypertension, diabetes with chronic complications, hyperlipidemia, thyroid disorders, and admission to rural hospitals predict subsequent stroke.

A-Tuning Ensemble Machine Learning Technique for Cerebral Stroke Prediction

A cerebral stroke is a medical problem that occurs when the blood flowing to a section of the brain is suddenly cut off, causing damage to the brain. Brain cells gradually die because of interruptions in blood supply and other nutrients to the brain, resulting in disabilities, depending on the affected region. Early recognition and detection of symptoms can aid in the rapid treatment of strokes and result in better health by reducing the severity of a stroke episode. In this paper, the Random Forest (RF), Extreme Gradient Boosting (XGBoost), and light gradient-boosting machine (LightGBM) were used as machine learning (ML) algorithms for predicting the likelihood of a cerebral stroke by applying an open-access stroke prediction dataset. The stroke prediction dataset was pre-processed by handling missing values using the KNN imputer technique, eliminating outliers, applying the one-hot encoding method, and normalizing the features with different ranges of values. After data splitting, synthetic minority oversampling (SMO) was applied to balance the stroke samples and no-stroke classes. Furthermore, to fine-tune the hyper-parameters of the ML algorithm, we employed a random search technique that could achieve the best parameter values. After applying the tuning process, we stacked the parameters to a tuning ensemble RXLM that was analyzed and compared with traditional classifiers. The performance metrics after tuning the hyper-parameters achieved promising results with all ML algorithms.

The Association between Diabetes Mellitus and its Management with Outcomes following Endovascular Repair for Descending Thoracic Aortic Aneurysm

OBJECTIVE

Prior literature is conflicted regarding the effect of diabetes mellitus (DM) on outcomes following endovascular repair of aortic aneurysms. In this study, we aimed to examine the association between DM and outcomes following TEVAR for TAA.

METHODS

We identified patients who underwent TEVAR for TAA of the descending thoracic aorta in the VQI between 2014-2022. We created two cohorts, DM and non-DM, based on the patient's preoperative DM status, and secondarily sub-stratified DM patients by management strategy: dietary management, non-insulin medications, and insulin therapy cohorts. Outcomes included perioperative and 5-year mortality, in-hospital complications, indications for repair, and one-year sac dynamics, which were analyzed with multivariable cox regression, multivariable logistic regression, and chi-square tests, respectively.

RESULTS

We identified 2,637 patients, of which 473 (18%) had DM preoperatively. Among DM patients, 25% were diet controlled, 54% non-insulin medications, and 21% insulin therapy. Within patients who underwent TEVAR for TAA, the proportions of ruptured presentation were higher in the dietary (11.1%) and insulin (14.3%) managed cohorts relative to non-insulin therapy (6.6%) and non-DM (6.9%). Following multivariable regression analysis, we found that DM was associated with similar perioperative mortality (OR: 1.14 [95% CI: 0.70-1.81]) and 5-year mortality compared with non-DM patients (HR: 1.15 [95% CI: 0.91-1.48]). Furthermore, all in-hospital complications were comparable between DM patients and non-DM patients. Compared with non-DM patients, dietary management of DM was significantly associated with higher adjusted perioperative mortality (OR: 2.16 [95% CI: 1.03-4.19]) and higher 5-year mortality (HR: 1.50 [95% CI: 1.03-2.20]), though this was not the case for other DM subgroups. All cohorts displayed similar one-year sac dynamics, with sac regression occurring in 47% of non-DM patients vs 46% of DM patients (P= 0.27).

CONCLUSION

Preoperatively, DM patients that underwent TEVAR had a higher proportion of ruptured presentation when treated with diet or insulin medications than when treated with non-insulin medications. Following TEVAR for descending TAA, DM was associated with a similar risk of perioperative and 5-year mortality to non-DM. In contrast, dietary therapy for DM was associated with significantly higher perioperative mortality and 5-year mortality.

Benefits of intensified reductions in blood glucose and in blood pressure for patients with type 2 diabetes

Adequate blood glucose and blood pressure control is paramount for the prevention of microvascular and macrovascular complications in patients with type 2 diabetes (T2D). This review article summarises the important advances in blood glucose and blood pressure lowering from the last three decades, with a focus on the evidence from large scale randomized clinical trials and meta-analyses. This paper focuses on evidence supporting specific blood glucose and blood pressure targets, and the importance of long-term sustained risk factor control. Novel therapies including the glucagon-like peptide-1 receptor agonists (GLP1-RA) and the sodium glucose co-transporter 2 inhibitors (SGLT2i) have revolutionized the treatment of type 2 diabetes and highlighted the importance of approaches that deliver benefits beyond glucose or blood pressure lowering. This article provides an overview of contemporary management of T2D with an emphasis on tailoring treatment plans to the individual.

Awareness of Stroke Risk Factors, Warning Signs, and Preventive Behaviour Among Diabetic Patients in Al-Ahsa, Saudi Arabia

Objectives This study aims to measure the level of awareness about stroke symptoms, risk factors, and preventive health practices that could be taken to reduce the risk of stroke among diabetic patients in Al-Ahsa, Saudi Arabia. Methods A cross-sectional study was conducted in Al-Ahsa, Saudi Arabia in 2020. The sample included a total of 202 male and female Saudi adults aged 18-65 years, with either type 1 or type 2 diabetes mellitus, and living in Al Ahsa, Saudi Arabia. The information was collected randomly through an online questionnaire distributed among patients after getting their contact information from relevant governmental and private diabetes clinics and after signing the informed consent. For awareness and knowledge items, each correct answer was scored one point and the total summation of the discrete scores of the different items was calculated. A diabetic patient with a score less than 60% of the total score was considered to have poor awareness while a score of 60% or more of the total score was considered a good level of awareness. Results A total of 87 (43.1%) participants had an overall good awareness level, while 115 (56.9%) had poor awareness levels. Around 40.6% of the study patients had heard about stroke, 61.9% knew that stroke affects the brain, and 24.3% reported that stroke is higher among males. As for factors associated with stroke, the most reported was high blood pressure (71.8%), followed by diabetes mellitus (69.3%). Exactly 65.8% of participants knew about the mechanism of ischemic stroke and 42.6% reported hemorrhagic stroke. A high percentage of patients (73.1%) realize that they could reduce their risk of stroke. Conclusion The findings of the current study showed that less than half (43.1%) of the Saudi patients with DM had a good awareness level regarding stroke and its related risk factors and warning signs. Older patients (aged 50-65 years) with high social levels (high education and income) and those with a family history of stroke had significantly higher awareness levels. Hypertension, DM, and smoking are the highest reported known risk factors of stroke, and speech disorders are the highest known stroke presentation to the respondents.

Utility of atherosclerosis-associated serum antibodies against colony-stimulating factor 2 in predicting the onset of acute ischemic stroke and prognosis of colorectal cancer

Introduction

Autoantibodies against inflammatory cytokines may be used for the prevention of atherosclerosis. Preclinical studies consider colony-stimulating factor 2 (CSF2) as an essential cytokine with a causal relationship to atherosclerosis and cancer. We examined the serum anti-CSF2 antibody levels in patients with atherosclerosis or solid cancer.

Methods

We measured the serum anti-CSF2 antibody levels via amplified luminescent proximity homogeneous assay-linked immunosorbent assay based on the recognition of recombinant glutathione S-transferase-fused CSF2 protein or a CSF2-derived peptide as the antigen.

Results

The serum anti-CSF2 antibody (s-CSF2-Ab) levels were significantly higher in patients with acute ischemic stroke (AIS), acute myocardial infarction (AMI), diabetes mellitus (DM), and chronic kidney disease (CKD) compared with healthy donors (HDs). In addition, the s-CSF2-Ab levels were associated with intima-media thickness and hypertension. The analyzes of samples obtained from a Japan Public Health Center-based prospective study suggested the utility of s-CSF2-Ab as a risk factor for AIS. Furthermore, the s-CSF2-Ab levels were higher in patients with esophageal, colorectal, gastric, and lung cancer than in HDs but not in those with mammary cancer. In addition, the s-CSF2-Ab levels were associated with unfavorable postoperative prognosis in colorectal cancer (CRC). In CRC, the s-CSF2-Ab levels were more closely associated with poor prognosis in patients with p53-Ab-negative CRC despite the lack of significant association of the anti-p53 antibody (p53-Ab) levels with the overall survival.

Conclusion

S-CSF2-Ab was useful for the diagnosis of atherosclerosis-related AIS, AMI, DM, and CKD and could discriminate poor prognosis, especially in p53-Ab-negative CRC.

Predicting transient ischemic attack risk in patients with mild carotid stenosis using machine learning and CT radiomics

Objective

This study aims to establish a radiomics-based machine learning model that predicts the risk of transient ischemic attack in patients with mild carotid stenosis (30-50% North American Symptomatic Carotid Endarterectomy Trial) using extracted computed tomography radiomics features and clinical information.

Methods

A total of 179 patients underwent carotid computed tomography angiography (CTA), and 219 carotid arteries with a plaque at the carotid bifurcation or proximal to the internal carotid artery were selected. The patients were divided into two groups; patients with symptoms of transient ischemic attack after CTA and patients without symptoms of transient ischemic attack after CTA. Then we performed random sampling methods stratified by the predictive outcome to obtain the training set (N = 165) and testing set (N = 66). 3D Slicer was employed to select the site of plaque on the computed tomography image as the volume of interest. An open-source package PyRadiomics in Python was used to extract radiomics features from the volume of interests. The random forest and logistic regression models were used to screen feature variables, and five classification algorithms were used, including random forest, eXtreme Gradient Boosting, logistic regression, support vector machine, and k-nearest neighbors. Data on radiomic feature information, clinical information, and the combination of these pieces of information were used to generate the model that predicts the risk of transient ischemic attack in patients with mild carotid artery stenosis (30-50% North American Symptomatic Carotid Endarterectomy Trial).

Results

The random forest model that was built based on the radiomics and clinical feature information had the highest accuracy (area under curve = 0.879; 95% confidence interval, 0.787-0.979). The combined model outperformed the clinical model, whereas the combined model showed no significant difference from the radiomics model.

Conclusion

The random forest model constructed with both radiomics and clinical information can accurately predict and improve discriminative power of computed tomography angiography in identifying ischemic symptoms in patients with carotid atherosclerosis. This model can aid in guiding the follow-up treatment of patients at high risk.

Analyzing and predicting the risk of death in stroke patients using machine learning

Background

Stroke is an acute disorder and dysfunction of the focal neurological system that has long been recognized as one of the leading causes of death and severe disability in most regions globally. This study aimed to supplement and exploit multiple comorbidities, laboratory tests and demographic factors to more accurately predict death related to stroke, and furthermore, to make inferences about the heterogeneity of treatment in stroke patients to guide better treatment planning.

Methods

We extracted data from the Medical Information Mart from the Intensive Care (MIMIC)-IV database. We compared the distribution of the demographic factors between the control and death groups. Subsequently, we also developed machine learning (ML) models to predict mortality among stroke patients. Furthermore, we used meta-learner to recognize the heterogeneity effects of warfarin and human albumin. We comprehensively evaluated and interpreted these models using Shapley Additive Explanation (SHAP) analysis.

Results

We included 7,483 patients with MIMIC-IV in this study. Of these, 1,414 (18.9%) patients died during hospitalization or 30 days after discharge. We found that the distributions of age, marital status, insurance type, and BMI differed between the two groups. Our machine learning model achieved the highest level of accuracy to date in predicting mortality in stroke patients. We also observed that patients who were consistent with the model determination had significantly better survival outcomes than the inconsistent population and were better than the overall treatment group.

Conclusion

We used several highly interpretive machine learning models to predict stroke prognosis with the highest accuracy to date and to identify heterogeneous treatment effects of warfarin and human albumin in stroke patients. Our interpretation of the model yielded a number of findings that are consistent with clinical knowledge and warrant further study and verification.

Serum Fatty Acids Are Associated with a Higher Risk of Ischemic Stroke

Stroke prevention, a significant public-health concern, begins with recognizing and addressing risk factors. Interventions targeted at modifiable risk factors can effectively prevent ischemic stroke, while Omega-3 fatty acids have been shown to improve stroke outcomes. Our study aimed to investigate the relationship between ischemic-stroke risk factors and fatty acids using a prospective observational study with 274 patients. We collected clinical data on risk factors and measured fatty-acid levels using high-performance liquid chromatography coupled with mass spectrometry. We found that several risk factors, including age, sex, smoking, atrial fibrillation, dyslipidemia, and previous stroke history, had a direct relationship with fatty acids. Of these, smoking had the most significant impact, negatively impacting levels of docosahexaenoic and eicosapentaenoic acid. Conversely, dyslipidemia and atrial fibrillation positively correlated with fatty acids, particularly in female patients and those with recurrent strokes. Age was found to directly correlate with other risk factors and variations in fatty-acid ratios. The stroke rate was higher in males than females before the age of 70, but this trend reversed. Our findings suggest that better management of risk factors, particularly modifiable lifestyle factors, could improve fatty-acid profiles and the balance of Omega-3 and Omega-6 in patients with ischemic stroke.

Dissecting the Spectrum of Stroke Risk Factors in an Apparently Healthy Population: Paving the Roadmap to Primary Stroke Prevention

We aimed to investigate, for the first time, the spectrum of stroke risk factors specific to the population of the Republic of Moldova. The subjects were examined according to a pre-established protocol of risk factor estimation. The study involved 300 subjects, including 60% women and 40% men, with a mean age of 49.9 ± 14.5 years. The most common risk factor was abdominal obesity, identified in 75% of subjects; general obesity was detected in 48%, while 32% of subjects were overweight and 20% were normally weighted. Hypertension was observed in 44%; 8% of those examined had atrial fibrillation, and 9% had diabetes mellitus. Left myocardial hypertrophy on ECG was present in 53% of subjects, and acute ischemic changes in 2%. Laboratory observations detected that glycosylated hemoglobin increased by 7%, and >50% had dyslipidemia. Total cholesterol was significantly elevated by 58%, LDL-cholesterol was increased by 32%, and HDL-cholesterol was decreased by 9%. Homocysteine was increased in 55% and high-sensitivity C-reactive protein in 28% of subjects. These results indicate the presence of modifiable risk factors and the necessity to elaborate on the primary prevention strategies aimed at minimizing the burden of stroke in the population of the Republic of Moldova.

A Cross-Sectional Study: Determining Factors of Functional Independence and Quality of Life of Patients One Month after Having Suffered a Stroke

(1) Background: loss of quality of life (QoL) and functional independence are two of the most common consequences of suffering a stroke. The main objective of this research is to study which factors are the greatest determinants of functional capacity and QoL a month after suffering a stroke so that they can be considered in early interventions. (2) Methods: a cross-sectional study was conducted which sample consisted of 81 people who had previously suffered a stroke. The study population was recruited at the time of discharge from the Neurology Service and Stroke Unit of the hospitals of Burgos and Córdoba, Spain, through a consecutive sampling. Data were collected one month after participants experienced a stroke, and the main study variables were quality of life, measured with the Stroke-Specific Quality of Life Measure (NEWSQOL), and functional independence, measured with the Functional Independence Measure-Functional Assessment Measure (FIM-FAM). (3) Results: the factors associated with a worse QoL and functional capacity one month after having suffered a stroke were living in a different dwelling than the usual flat or house (p < 0.05), a worse cognitive capacity (p < 0.001) and a worse functional capacity of the affected upper limb (p < 0.001). A higher age was related to a worse functional capacity one month after suffering a stroke (p = 0.048). (4) Conclusions: the type of dwelling, age, cognitive ability and functional capacity of the affected upper limb are determining aspects in functional independence and QoL during the first weeks after a stroke.

Risk factors for cerebral complications in patients with pulmonary arteriovenous malformations: A multicenter retrospective cohort study

OBJECTIVE

Pulmonary arteriovenous malformation (PAVM) is a rare pulmonary disease. Although most patients with PAVMs are asymptomatic, cerebral complications associated with PAVMs are often fatal. This study aimed to evaluate the risk factors for cerebral complications in patients with PAVMs.

METHODS

We retrospectively reviewed the medical charts of patients with PAVMs between 2003 and 2021 at two tertiary referral hospitals and one secondary hospital.

RESULTS

Fifty-five patients diagnosed with PAVMs were enrolled in this study. Most patients were female (89.1%), and the median age was 53 years. Thirty patients (54.5%) had incidentally detected PAVMs without symptoms. Twenty-four patients (43.7%) with PAVMs were treated with embolotherapy or surgery. Thirteen patients (23.6%) had cerebral complications. There was no significant difference in the development of cerebral complications according to treatment; however, older age (≥ 65 years) was associated with the development of new cerebral complications in untreated patients with PAVMs (odds ratio, 17.09; 95% confidence interval, 1.16-250.31; P = 0.038).

CONCLUSION

Older age (≥ 65 years) was a risk factor for the development of cerebral complications in patients with PAVMs; therefore, treatment should be considered in older patients with PAVMs.

Effectiveness of exercise in reducing cerebral stroke risk factors: A systematic review and meta-analysis

OBJECTIVES

This study aimed to explore the relationship between exercise and cerebral stroke and provide evidence for the prevention of cerebral stroke.

MATERIALS/METHODS

All clinical trials of exercise intervention for atherosclerosis were systematically reviewed. Five major databases were searched to retrieve relevant studies from their inception to May 2022. According to the magnitude of heterogeneity, the random and fixed-effect models were used to test reasonably.

RESULTS

According to the inclusion and exclusion criteria, 1341 articles were screened and 13 articles involving 825 patients were identified. The result showed that in the randomized controlled trials carotid intima-media thickness index was lower in the exercise group (-0.04 mm, 95% confidence interval: -0.07 to -0.01). All were statistically significant (P < .005) and subgroup analysis showed that the intervention period and paper quality are sources of heterogeneity.

CONCLUSIONS

The results of this systematic review suggest that exercise is associated with a slow increase in carotid intima-media thickness, which may provide evidence that exercise helps reduce cerebral stroke.

An Integrated Classification and Association Rule Technique for Early-Stage Diabetes Risk Prediction

The number of diabetic patients is increasing yearly worldwide, requiring the need for a quick intervention to help these people. Mortality rates are higher for diabetic patients with other serious health complications. Thus, early prediction for such diseases positively impacts healthcare quality and can prevent serious health complications later. This paper constructs an efficient prediction system for predicting diabetes in its early stage. The proposed system starts with a Local Outlier Factor (LOF)-based outlier detection technique to detect outlier data. A Balanced Bagging Classifier (BBC) technique is used to balance data distribution. Finally, integration between association rules and classification algorithms is used to develop a prediction model based on real data. Four classification algorithms were utilized in addition to an a priori algorithm that discovered relationships between various factors. The named algorithms are Artificial Neural Network (ANN), Decision Trees (DT), Support Vector Machines (SVM), and K Nearest Neighbor (KNN) for data classification. Results revealed that KNN provided the highest accuracy of 97.36% compared to the other applied algorithms. An a priori algorithm extracted association rules based on the Lift matrix. Four association rules from 12 attributes with the highest correlation and information gain scores relative to the class attribute were produced.

Significance of Edaravone Combined with Emotion Management Model in Promoting the Recovery Process and Improving Negative Psychology in Patients with Type 2 Diabetes Mellitus Combined with Stroke

Methods

Eighty-one patients with T2DM combined with CS who attended our hospital and received rehabilitation treatment from March 2020 to May 2021 were enrolled to a prospective nonrandomized controlled analysis. Among them, 46 patients received EDA combined with emotional management model and were regarded as the observation group (OG), and 35 received EDA combined with conventional care and were seen as the control group (CG). The clinical efficacy and glycemic function of the two groups were compared, and the scores of the Activities of Daily Living (ADL), Pittsburgh Sleep Quality Index (PSQI), and Self-Assessment Scale for Anxiety and Depression (SAS and SDS) were investigated before and after treatment. At the time of discharge, patient satisfaction with care was counted. Within six months after prognosis, T2DM self-management behavior and CS self-management behavior score surveys were conducted.

Results

There was no difference in clinical efficacy between both groups (P > 0.05); The posttreatment glucose, PSQI, SAS, and SDS scores were lower in the OG than in the CG, while ADL and emotional management scores were higher than in the CG (P < 0.05). In addition, both nursing satisfaction and prognosis disease self-management behavior scores were also higher in the OG than in the CG (P < 0.05).

Conclusion

The EDA combined with emotion management model can effectively promote the recovery process of patients with type II T2DM combined with CS, while improving their negative psychology and enhancing their self-management ability, which has high potential for clinical application.

Glucose-activatable insulin delivery with charge-conversional polyelectrolyte multilayers for diabetes care

One of the most effective treatments for diabetes is to design a glucose-regulated insulin (INS) delivery system that could adjust the INS release time and rate to reduce diabetes-related complications. Here, mixed multiple layer-by-layer (mmLbL)-INS microspheres were developed for glucose-mediated INS release and an enhanced hypoglycemic effect for diabetes care. To achieve ultrafast glucose-activated INS release, glucose oxidase (GOx) was assembled with a positively charged polymer and modified on INS LbL. The mmLbL-INS microspheres were constructed with one, two, and four layers of the polyelectrolyte LbL assembly at a ratio of 1:1:1. Under hyperglycemia, GOx converts a change in the hyperglycemic environment to a pH stimulus, thus providing sufficient hydrogen ion. The accumulated hydrogen ion starts LbL charge shifting, and anionic polymers are converted to cationic polymers through hydrolytic cleavage of amine-functionalized side chains. The results of in vitro INS release suggested that glucose can modulate the mmLbL-INS microspheres in a pulsatile profile. In vivo studies validated that this formulation enhanced the hypoglycemic effect in STZ-induced diabetic rats within 2 h of subcutaneous administration and facilitated stabilization of blood glucose levels for up to 2 days. This glucose-activatable LbL microsphere system could serve as a powerful tool for constructing a precisely controlled release system.

The use of self-management strategies for stroke rehabilitation: a scoping review

INTRODUCTION

Self-management is generally considered a dynamic and collaborative process by individuals and caregivers to manage a chronic condition. Self-management has recently emerged as a promising strategy for stroke rehabilitation. This scoping review aims to examine and summarize self-management strategies utilized by stroke survivors for stroke rehabilitation.

METHODS

PubMed, Scopus, CINAHL (EBSCO), Embase, and ProQuest were searched for articles published between January 2010 and December 2021. Studies were selected if they were published in English in a peer-reviewed journal, utilized a non-experimental research design, and focused on adult stroke survivors. All relevant information from the included articles was extracted in a systematic way using a pre-developed data extraction form. Two authors performed data extraction and quality evaluation independently. All issues were resolved through discussion among the authors.

RESULTS

We narratively summarized the findings of 15 quantitative, qualitative, and mixed-method studies, including a total of 1,494 stroke survivors. The stroke survivors used a range of self-management strategies for their stroke rehabilitation, including domains related to lifestyle, social support, communication, knowledge and information, and goal-setting. Gender, age, stroke-related disability, fatigue, self-management education, social support, and communication with others were found to be associated with self-management use in stroke rehabilitation.

CONCLUSIONS

This scoping review provides an important overview on stroke survivors' use of self-management strategies and their experience. Their use of self-management strategies is complicated and multifaceted, comprising several domains and involving a diverse range of approaches and personal experiences. However, we identified several gaps in the literature and more research is required.

Association between diabetes duration and 1-year prognosis of stroke: A national registry study

BACKGROUND AND PURPOSE

Diabetes mellitus is a strong independent risk factor for stroke recurrence. However, the association between diabetes duration and the prognosis of stroke remains uncertain. We aimed to characterize whether an association exists between diabetes duration and stroke outcomes in patients with ischemic stroke or transient ischemic attack (TIA).

METHODS

Between 2015 and 2018, 14,674 patients with ischemic stroke or TIA within 7 days and older than 18 years from the Third China National Stroke Registry (CNSR-III) were included in this analysis. Diabetes duration at baseline was collected by face-to-face interviews and further categorized into groups of without diabetes, diabetes < 4, 4 to <8 and ≥8 years. The association between diabetes duration and clinical outcomes, including stroke recurrence, poor function outcome (modified Rankin Scale score of 3-6), and all-cause mortality at the 1-year follow-up after stroke onset, was evaluated by a multivariable Cox proportional hazard regression model, competing risk model and logistic regression model with adjustment for demographic and clinical features.

RESULTS

Among the 14,674 patients included, the average age was 62.0 years, and 68.5% were male. There were 1419 (9.7%) patients who had stroke recurrence, 1912 (13.0%) who had poor function outcome, and 478 (3.3%) who had all-cause mortality at the 1-year follow-up. After adjusting for potential covariates, a diabetes duration ≥8 years was associated with an increased risk of 1-year stroke recurrence (adjusted hazards ratio [HR], 1.31; 95% CI, 1.05-1.64; p = .02) in comparison to those without Diabetes mellitus. Using a competing risk regression model, a diabetes duration ≥8 years was a significant risk factor for stroke recurrence (HR, 1.31; 95% CI, 1.12-1.53). In contrast, there was no significant association between diabetes duration < 4, 4 to <8 years and clinical outcomes.

CONCLUSIONS

Long-term diabetes duration (≥8 years), but not short-term diabetes duration, was associated with an increased risk of 1-year stroke recurrence in patients with ischemic stroke or TIA.

A Five-Year Retrospective Cohort Study of Survivality and Functional Outcomes of Stroke Patients Following Hospital Admission

Background

Stroke is the fourth leading cause of death in India. Data on long-term outcomes of patients with stroke in India are relatively sparse.

Objective

To document survival and long-term functional outcomes of patients with acute stroke and to assess the measures taken for secondary prevention of stroke.

Methods and Material

A five-year retrospective cohort study involving 118 patients with acute stroke was conducted. Details about five years’ survival, functional outcomes (modified Rankin Scale [mRS], Barthel index [BI], and Hamilton Depression Rating Scale [HDRS]), and secondary prevention measures were investigated.

Results

Among the patients, 38.1% were diagnosed with ischemic stroke and 61.8% were diagnosed with hemorrhagic stroke. Hypertension was observed to be the predominant risk factor in a majority of the admitted patients. About 30.5% of patients died in the hospital within zero to four weeks after the index event, while 27.1% died during the follow-up period of five years. Approximately 21.1% of patients experienced a recurrent stroke over the next five years which turned out fatal. The quality of life was seriously affected in 32.4% of survivors. It was seen that 40.5% of survivors were fully independent and 45.9% were able to return to their occupation after five years poststroke. Prevalence of severe and very severe depression was observed in 3.4% and 1.7% of survivors, respectively. The majority of the survivors (93.9%) were aware of the risk of recurrent stroke. Physical activities as measures for the prevention of stroke were undertaken by 60.6% of survivors.

Conclusion

Effective strategies for secondary prevention and also for long-term survival after stroke should be initiated as early as possible after the onset of the initial stroke. Stroke survivors should be closely monitored for their functional recovery and behavioral and emotional improvement poststroke.