Risk Factor For Stroke Research Articles

Association between serum triglycerides and stroke type, severity, and prognosis. Analysis in 6558 patients

Background and objectivesHypertriglyceridemia (HT) may increase the risk of stroke. Limited studies have shown that stroke severity and infarction size are smaller in patients with HT. We explored the relationship between triglyceride levels and stroke risk factors, severity and outcome in a large prospective database.DesignProspective Cross-sectional study.SettingWe retrospectively interrogated the Qatar Stroke Database in all patients admitted between 2014-2022 with acute ischemic stroke and evaluated the relationship between triglyceride, diabetes, stroke severity (measured on NIHSS), stroke type (TOAST classification) and the short- (mRS at 90 days) and long-term outcomes (MACE at 1 year) in patients with HT.ParticipantsSix thousand five hundred fifty-eight patients ≥20 years were included in this studyResultsSix thousand five hundred fifty-eight patients with ischemic stroke [mean age 54.6 ± 12. 9; male 82.1%) were included. Triglyceride levels upon admission were low-normal (≤1.1 mmol/L) in 2019 patients, high-normal (1.2-1.7 mmol/L) in 2142 patients, borderline-high (1.8-2.2 mmol/L) in 1072 patients and high (≥2.3 mmol/L) in 1325 patients. Higher triglyceride levels were associated with stroke and increased likelihood of having diabetes, obesity, active smoking, and small vessel/lacunar stroke type. An inverse relationship was noted whereby higher triglyceride levels were associated with lower stroke severity and reduced likelihood of poorer outcome (mRS 3-6) at discharge and 90 days. Long-term MACE events were less frequent in patients with higher triglyceride levels. After adjusting age, gender, diabetes, prior stroke, CAD, and obesity, multivariate analysis showed that hypertension and triglyceride levels were higher in mild ischemic strokes patients.ConclusionsIncreasing triglycerides are associated with higher risk of small vessel disease and requires further prospective cohort studies for confirmation.

Investigation of telomere length in young age ischemic stroke patients

Background & Objective: Telomere length is frequently accepted as a marker of biological aging. Various studies examine the relationship between telomere length, accepted as a marker of biological aging, and stroke, but this relationship has not been clearly demonstrated. The objective of this study is to determine whether short DNA telomere length is an independent risk factor for stroke. Methods: Our study examined telomere length in young patients with ischemic stroke. The study included 60 patients with a history of ischemic stroke at a young age within the last 3 years and a control group consisting of 40 volunteers with similar age, gender, and disease history defined as risk factors for stroke. Results: In our study, the mean telomere length of the patient group was significantly higher than the mean telomere length of the control group. However, the telomere length of the patients in the study did not show a significant difference between socio-demographic and risk factors defined for ischemic stroke. Conclusion: Our study is very important in being the first to show such a relationship between telomere length and young age ischemic stroke. The low sample size may partially explain this result compared to other studies, as well as the study’s design, the study population’s age, ethnicity, and methods of studying telomere length. More studies with a larger sample size with younger patients are needed to better understand the relationship between telomere length and stroke in the future.

Risk Factors for Stroke in Children with Tuberculous Meningitis: A Prospective Observational Study

Objective: The purpose of the study is to establish the prevalence of stroke as well as the clinical and radiological correlates of stroke in children with tuberculous meningitis (TBM). Methods and Materials: A prospective observational study was conducted at the Pediatric Department, King George’s Medical University (KGMU), Lucknow, Uttar Pradesh, India. Using a computed tomography (CT) scan/brain magnetic resonance imaging (MRI), patients were divided into stroke and non-stroke groups. Demographic characteristics, clinical presentations, cerebrospinal fluid examination, basal meningeal enhancement, hydrocephalus, tuberculoma, and clinical outcome were compared between the two groups. Results: Seventy-eight TBM patients, aged between 6 months and 14 years, were included. Out of 78 enrolled patients, 3 (3.8%) had definite TBM, 73 (91%) had probable TBM, and 4 (5.1%) had possible TBM (LCS). As per the Medical Research Council (MRC) staging, 13% had Stage 1 TBM, 26% had stage 2, and 61% had stage 3 TBM. Out of 78 patients with chest X-ray findings, 42 (53%) had findings suggestive of tuberculosis (TB), which included 33 (42%) with hilar lymphadenopathy and 9 (11%) with a miliary pattern. On neuroimaging, hydrocephalous was seen in 62.8% of cases, basal meningeal enhancement in 64.1%, tuberculoma in 6.4% of cases, and infarction in 53.8% of cases. There was no statistically significant association found between the staging of TBM and the presence of infarction as the majority of cases involved were in stage 3 of the disease (61.5%). TBM patients with stroke had poor clinical outcomes. Conclusion: Age, altered sensorium, focal neurological deficits, vomiting, and basal meningeal enhancement can predict the occurrence of stroke in young adults with TBM.

Unlocking stroke prediction: Harnessing projection-based statistical feature extraction with ML algorithms

Non-communicable diseases, such as cardiovascular disease, cancer, chronic respiratory diseases, and diabetes, are responsible for approximately 71% of all deaths worldwide. Stroke, a cerebrovascular disorder, is one of the leading contributors to this burden among the top three causes of death. Early recognition of symptoms can encourage a balanced lifestyle and provide essential information for stroke prediction. To identify a stroke patient and risk factors, machine learning (ML) is a key tool for physicians. Due to different data measurement scales and their probability distributional assumptions, ML-based algorithms struggle to detect risk factors. Furthermore, when dealing with risk factors with high-dimensional features, learning algorithms struggle with complexity. In this study, rigorous statistical tests are used to identify risk factors, and PCA-FA (Integration of Principal Components and Factors) and FPCA (Factor Based PCA) approaches are proposed for projecting suitable feature representations for improving learning algorithm performances. The study dataset consists of different clinical, lifestyle, and genetic attributes, allowing for a comprehensive analysis of potential risk factors associated with stroke, which contains 5110 patient records. Using significant test (P-value <0.05), chi-square and independent sample t-test identified age, heart_disease, hypertension, work_type, ever_married, bmi, and smoking_status as risk factors for stroke. To develop the predicting model with proposed feature extraction techniques, random forests approach provides the best results when utilizing the PCA-FA method. The best accuracy rate for this approach is 92.55%, while the AUC score is 98.15%. The prediction accuracy has increased from 2.19% to 19.03% compared to the existing work. Additionally, the prediction results is robustified and reproducible with a stacking ensemble-based classification algorithm. We also developed a web-based application to help doctors diagnose stroke risk based on the findings of this study, which could be used as an additional tool to help doctors diagnose.

The predictive value of the hs-CRP/HDL-C ratio, an inflammation-lipid composite marker, for cardiovascular disease in middle-aged and elderly people: evidence from a large national cohort study

Background and aimsCardiovascular disease (CVD) is associated with inflammation and abnormal lipid metabolism. However, a single inflammatory index or a single lipid index cannot accurately predict the prognosis of CVD independently because it is prone to be affected by various confounding factors.MethodsThis population-based cohort study included 6,554 participants from the China Health and Retirement Longitudinal Study (CHARLS) to investigate correlations. In the present study, the occurrence of CVD events such as stroke and heart disease was evaluated by considering self-reported diagnoses at the beginning of the study and during wave 4, and a restricted cubic spline model was used to investigate potential nonlinear relationships in addition to multivariate logistic regression models. Stratified analyses were performed to examine how sociodemographic characteristics may influence the results.ResultsSeven years of follow-up (2011–2018) revealed that 786 people (11.99%) developed CVD. According to the adjusted model, the high-sensitivity C-reactive protein (hs-CRP)-to-high-density lipoprotein cholesterol (HDL-C) ratio is a contributing factor to CVD risk (OR 1.31, 95% CI 1.05–1.64). In addition, a nonlinear relationship was observed between the hs-CRP/HDL-C ratio and the occurrence of new CVD, stroke, or cardiac issues (Poverall <0.05, Pnonlinear <0.05). Moreover, noteworthy associations between the hs-CRP/HDL-C ratio and age were detected in the stratified analysis (P = 0.048), indicating that younger participants had more negative effects of a high hs-CRP/HDL-C ratio.ConclusionsAccording to the present cohort study, a high hs-CRP/HDL-C ratio is a significant risk factor for CVD, new stroke, and heart problems. Early intervention in patients with increased hs-CRP/HDL-C ratios may further reduce the incidence of CVD, in addition to focusing on independent lipid markers or independent inflammatory markers.

The discovery of GGT1 as a novel gene for ischemic stroke conferring protection against disease risk in non-smokers and non-abusers of alcohol

ObjectivesIncreased plasma gamma-glutamyl transferase (GGT1) has been identified as a robust and independent risk factor for ischemic stroke (IS), but the molecular mechanisms of the enzyme-disease association are unclear. The present study investigated whether polymorphisms in the GGT1 gene contribute to IS susceptibility. Materials and MethodsDNA samples obtained from 1288 unrelated individuals (600 IS patients and 688 controls) were genotyped for common single nucleotide polymorphisms of GGT1 using the MassArray-4 platform. ResultsThe rs5751909 polymorphism was significantly associated with decreased risk of ischemic stroke regardless sex and age (Pperm≤0.01, dominant genetic model). The haplotype rs4820599A-rs5760489A-rs5751909A showed strong protection against ischemic stroke (OR 0.53, 95%CI 0.36 - 0.77, Pperm≤0.0001). The protective effect of SNP rs5751909 in the stroke phenotype was successfully replicated in the UK Biobank, SiGN, and ISGC cohorts (P≤0.01). GGT1 polymorphisms showed joint (epistatic) effects on the risk of ischemic stroke, with some known IS-associated GWAS loci (e.g., rs4322086 and rs12646447) investigated in our population. In addition, SNP rs5751909 was found to be strongly associated with a decreased risk of ischemic stroke in non-smokers (OR 0.54 95%CI 0.39-0.75, Pperm=0.0002) and non-alcohol abusers (OR 0.43 95%CI 0.30-0.61, Pperm=2.0 × 10−6), whereas no protective effects of this SNP against disease risk were observed in smokers and alcohol abusers (Pperm<0.05). ConclusionsWe propose mechanisms underlying the observed associations between GGT1 polymorphisms and ischemic stroke risk. This pilot study is the first to demonstrate that GGT1 is a novel susceptibility gene for ischemic stroke and provides additional evidence of the genetic contribution to impaired redox homeostasis underlying disease pathogenesis.

Trends in American Indian/Alaskan native self-reported stroke prevalence and associated modifiable risk factors in the United States from 2011-2021

BackgroundStroke prevalence varies by race/ethnicity, as do the risk factors that elevate the risk of stroke. Prior analyses have suggested that American Indian/Alaskan Natives (AI/AN) have higher rates of stroke and vascular risk factors. MethodsWe included biyearly data from the 2011-2021 Behavioral Risk Factor Surveillance System (BRFSS) surveys of adults (age ≥18) in the United States. We describe survey-weighted prevalence of stroke per self-report by race and ethnicity. In patients with self-reported stroke (SRS), we also describe the prevalence of modifiable vascular risk factors. ResultsThe weighted number of U.S. participants represented in BRFSS surveys increased from 237,486,646 in 2011 to 245,350,089 in 2021. SRS prevalence increased from 2.9% in 2011 to 3.3% in 2021 (p<0.001). Amongst all race/ethnicity groups, the prevalence of stroke was highest in AI/AN at 5.4% and 5.6% in 2011 and 2021, compared to 3.0% and 3.4% for White adults (p<0.001). AI/AN with SRS were also the most likely to have four or more vascular risk factors in both 2011 and 2021 at 23.9% and 26.4% compared to 18.2% and 19.6% in White adults (p<0.001). ConclusionFrom 2011-2021 in the United States, AI/AN consistently had the highest prevalence of self-reported stroke and highest overall burden of modifiable vascular risk factors. This persistent health disparity leaves AI/AN more susceptible to both incident and recurrent stroke.

Risk Factors and Stroke Symptoms Knowledge among Diabetes Mellitus, Hypertension and Heart Disease Patients: Literature Review

Stroke is the leading cause of disability and the second leading cause of death in the world and the biggest cause of death in Indonesia. Knowledge of stroke risk factors and symptoms can improve stroke prevention measures so as to reduce the risk of disability and death. This study aims to analyze the description of knowledge about risk factors and symptoms of stroke in patients with diabetes mellitus, hypertension, and heart disease. The research was carried out using google scholar search engine and electronic databases, such as Pubmed and Science Direct. The English keywords used are knowledge AND “risk factors” AND “stroke symptoms”. Meanwhile, the Indonesian keywords are: pengetahuan DAN “faktor risiko” DAN “gejala stroke”. The inclusion criteria of the articles collected were articles in English and Indonesian, full text, the Cross-Sectional Study method or descriptive, and publication year between 2012-2022. This research obtained 8 articles which would then be analyzed. All articles analyzed were overseas research reports (two african continent countries and three asia continent countries) and in English. It is shown that knowledge about the risk factors and symptoms of stroke in patients with diabetes mellitus, hypertension, and heart disease is still lacking. There are 2 studies that report 56 and 77% of respondents do not know the risk factors for stroke. Knowledge of stroke symptoms in the form of decreased consciousness was found to be very poor (7.6% of respondents).

Clinical and imaging markers for the prognosis of acute ischemic stroke.

Significant differences in the outcomes observed in patients with acute ischemic stroke (AIS) have led to research investigations for identifying the predictors. In this retrospective study, we aimed to investigate the relationship of different clinical and imaging factors with the prognosis of AIS. All clinical and imaging metrics were compared between the good and poor prognosis groups according to the modified Rankin Scale (mRS) score at 90 days after discharge. Clinical factors included gender, age, NIHSS scores at admission, and other medical history risk factors. Imaging markers included the lesion's size and location, diffusion, and perfusion metrics of infarction core and peripheral regions, and the state of collateral circulation. Spearman's correlations were analyzed for age and imaging markers between the different groups. The Chi-square test and Cramer's V coefficient analysis were performed for gender, collateral circulation status, NIHSS score, and other stroke risk factors. A total of 89 patients with AIS were divided into the good (mRS score ≤ 2) and poor prognosis groups (mRS score ≥ 3). There were differences in NIHSS score at the admission; relative MK (rMK), relative MD (rMD), relative CBF (rCBF) of the infarction core; relative mean transit time (rMTT), relative time to peak (rTTP), and relative CBF (rCBF) of peripheral regions; and collateral circulation status between the two groups (p < 0.05). Among them, the rMK of infarction lesions had the strongest correlation with the mRS score at 90 days after discharge (r = 0.545, p < 0.001). Perfusion and diffusion metrics could reflect the microstructure and blood flow characteristics of the lesion, which were the key factors for the salvage ability and prognosis of the infarction tissue. The characteristics of the infarction core and peripheral regions have different effects on the outcomes. Diffusion of infarction core has strong relations with the prognosis, whereas the time metrics (MTT, TTP) were more important for peripheral regions. MK had a more significant association with prognosis than MD. These factors were the primary markers influencing the prognosis of cerebral infarction patients.

The SGLT2 inhibitor Empagliflozin promotes post-stroke functional recovery in diabetic mice

Type-2 diabetes (T2D) worsens stroke recovery, amplifying post-stroke disabilities. Currently, there are no therapies targeting this important clinical problem. Sodium-glucose cotransporter 2 inhibitors (SGLT2i) are potent anti-diabetic drugs that also efficiently reduce cardiovascular death and heart failure. In addition, SGLT2i facilitate several processes implicated in stroke recovery. However, the potential efficacy of SGLT2i to improve stroke recovery in T2D has not been investigated. Therefore, we determined whether a post-stroke intervention with the SGLT2i Empagliflozin could improve stroke recovery in T2D mice. T2D was induced in C57BL6J mice by 8 months of high-fat diet feeding. Hereafter, animals were subjected to transient middle cerebral artery occlusion and treated with vehicle or the SGLTi Empagliflozin (10 mg/kg/day) starting from 3 days after stroke. A similar study in non diabetic mice was also conducted. Stroke recovery was assessed using the forepaw grip strength test. To identify potential mechanisms involved in the Empagliflozin-mediated effects, several metabolic parameters were assessed. Additionally, neuronal survival, neuroinflammation, neurogenesis and cerebral vascularization were analyzed using immunohistochemistry/quantitative microscopy. Empagliflozin significantly improved stroke recovery in T2D but not in non-diabetic mice. Improvement of functional recovery was associated with lowered glycemia, increased serum levels of fibroblast growth factor-21 (FGF-21), and the normalization of T2D-induced aberration of parenchymal pericyte density. The global T2D-epidemic and the fact that T2D is a major risk factor for stroke are drastically increasing the number of people in need of efficacious therapies to improve stroke recovery. Our data provide a strong incentive for the potential use of SGLT2i for the treatment of post-stroke sequelae in T2D.

Correlation Between HbA1c and Body Mass Index Among Patients with High Lipid Profile Attending Johns Hopkins Aramco Healthcare Hospital in Saudi Arabia

BACKGROUND AND OBJECTIVES: Dyslipidemia is a modifiable risk factor for cardiovascular diseases, diabetes, and stroke. The primary objective of this study was to examine the relationship between HbA1C and body mass index (BMI) among patients with high lipid profiles. METHODS: This retrospective, hospital-based study was conducted at Johns Hopkins Aramco Healthcare Facilities. Data were extracted from medical health records and included demographics, lipid profiles, and HBA1c measurements. The study included 2368 participants, and DATAtab was used to analyse the data. RESULTS: The participants were 57.05% male and 78.42% Saudi. The mean age was 41.48±12.1 years, and the mean body mass index (BMI) was 28.44±5.53. There was a statistically significant relationship between the use of lipid lowering medicine and HbA1c (P&lt;0.001). There was a very weak positive but statistically significant relationship between HbA1c and BMI (r = 0.18, P&lt;0.001). HbA1c and systolic blood pressure appeared to have a statistically significant positive association (r = 0.16, P&lt; 0.001). There was no correlation between HbA1c and low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), or diastolic blood pressure. There was an inverse correlation between HbA1c and high-density lipoprotein cholesterol (HDL-C) (r = -0.11, P&lt; 0.001). Regression was performed using a linear multivariable analysis with HbA1c as the dependent variable, and the age (B 0.192, P&lt;0.001), BMI (B 0.119, P&lt;0.001), HDL (B -0.058, P&lt;0.005), Triglyceride (B 0.093, P&lt;0.001), lipid lowering medication (B 0.104, P&lt;0.001), systolic BP (B 0.060, P&lt; 0.003) as independents variables.  CONCLUSION: The results indicated that HbA1c is linked to BMI, age, systolic blood pressure, triglycerides, and HDL-C levels. There was no correlation between HbA1c and LDL-C, TC, and diastolic blood pressure.

The paradigm change from reactive medical services to 3PM in ischemic stroke: a holistic approach utilising tear fluid multi-omics, mitochondria as a vital biosensor and AI-based multi-professional data interpretation

Worldwide stroke is the second leading cause of death and the third leading cause of death and disability combined. The estimated global economic burden by stroke is over US$891 billion per year. Within three decades (1990–2019), the incidence increased by 70%, deaths by 43%, prevalence by 102%, and DALYs by 143%. Of over 100 million people affected by stroke, about 76% are ischemic stroke (IS) patients recorded worldwide. Contextually, ischemic stroke moves into particular focus of multi-professional groups including researchers, healthcare industry, economists, and policy-makers. Risk factors of ischemic stroke demonstrate sufficient space for cost-effective prevention interventions in primary (suboptimal health) and secondary (clinically manifested collateral disorders contributing to stroke risks) care. These risks are interrelated. For example, sedentary lifestyle and toxic environment both cause mitochondrial stress, systemic low-grade inflammation and accelerated ageing; inflammageing is a low-grade inflammation associated with accelerated ageing and poor stroke outcomes. Stress overload, decreased mitochondrial bioenergetics and hypomagnesaemia are associated with systemic vasospasm and ischemic lesions in heart and brain of all age groups including teenagers. Imbalanced dietary patterns poor in folate but rich in red and processed meat, refined grains, and sugary beverages are associated with hyperhomocysteinaemia, systemic inflammation, small vessel disease, and increased IS risks. Ongoing 3PM research towards vulnerable groups in the population promoted by the European Association for Predictive, Preventive and Personalised Medicine (EPMA) demonstrates promising results for the holistic patient-friendly non-invasive approach utilising tear fluid-based health risk assessment, mitochondria as a vital biosensor and AI-based multi-professional data interpretation as reported here by the EPMA expert group. Collected data demonstrate that IS-relevant risks and corresponding molecular pathways are interrelated. For examples, there is an evident overlap between molecular patterns involved in IS and diabetic retinopathy as an early indicator of IS risk in diabetic patients. Just to exemplify some of them such as the 5-aminolevulinic acid/pathway, which are also characteristic for an altered mitophagy patterns, insomnia, stress regulation and modulation of microbiota-gut-brain crosstalk. Further, ceramides are considered mediators of oxidative stress and inflammation in cardiometabolic disease, negatively affecting mitochondrial respiratory chain function and fission/fusion activity, altered sleep–wake behaviour, vascular stiffness and remodelling. Xanthine/pathway regulation is involved in mitochondrial homeostasis and stress-driven anxiety-like behaviour as well as molecular mechanisms of arterial stiffness. In order to assess individual health risks, an application of machine learning (AI tool) is essential for an accurate data interpretation performed by the multiparametric analysis. Aspects presented in the paper include the needs of young populations and elderly, personalised risk assessment in primary and secondary care, cost-efficacy, application of innovative technologies and screening programmes, advanced education measures for professionals and general population—all are essential pillars for the paradigm change from reactive medical services to 3PM in the overall IS management promoted by the EPMA.

Many Models, Little Adoption-What Accounts for Low Uptake of Machine Learning Models for Atrial Fibrillation Prediction and Detection?

(1) Background: Atrial fibrillation (AF) is a major risk factor for stroke and is often underdiagnosed, despite being present in 13-26% of ischemic stroke patients. Recently, a significant number of machine learning (ML)-based models have been proposed for AF prediction and detection for primary and secondary stroke prevention. However, clinical translation of these technological innovations to close the AF care gap has been scant. Herein, we sought to systematically examine studies, employing ML models to predict incident AF in a population without prior AF or to detect paroxysmal AF in stroke cohorts to identify key reasons for the lack of translation into the clinical workflow. We conclude with a set of recommendations to improve the clinical translatability of ML-based models for AF. (2) Methods: MEDLINE, Embase, Web of Science, Clinicaltrials.gov, and ICTRP databases were searched for relevant articles from the inception of the databases up to September 2022 to identify peer-reviewed articles in English that used ML methods to predict incident AF or detect AF after stroke and reported adequate performance metrics. The search yielded 2815 articles, of which 16 studies using ML models to predict incident AF and three studies focusing on ML models to detect AF post-stroke were included. (3) Conclusions: This study highlights that (1) many models utilized only a limited subset of variables available from patients' health records; (2) only 37% of models were externally validated, and stratified analysis was often lacking; (3) 0% of models and 53% of datasets were explicitly made available, limiting reproducibility and transparency; and (4) data pre-processing did not include bias mitigation and sufficient details, leading to potential selection bias. Low generalizability, high false alarm rate, and lack of interpretability were identified as additional factors to be addressed before ML models can be widely deployed in the clinical care setting. Given these limitations, our recommendations to improve the uptake of ML models for better AF outcomes include improving generalizability, reducing potential systemic biases, and investing in external validation studies whilst developing a transparent modeling pipeline to ensure reproducibility.

Classification of Stroke Disease at Dr. Drs. M. Hatta Brain Hospital Bukittinggi With Decision Tree Algorithm C4.5

Stroke is a health condition that has vascular disorders where brain  function is related to problems with blood vessels that carry blood to the brain. Several factors that can influence stroke include unhealthy eating habits, lack of physical activity, smoking behavior, alcohol consumption, and obesity. The symptoms experienced are headache, nausea, vomiting, blurred vision and difficulty swallowing. The researcher’s aim is to determine the risk faktors that affect the incidence of stroke hospitalization based on stroke diagnoses at the DR. Drs. M. Hatta Brain Hospital Bukittinggi city by classifying each variable using a decision tree. A decision tree is a flowchart that resembles a branching tree. The C4.5 algorithm is used in this research, which can process numerical and categorical data, can handle missing attribute values, and produces rules that are easy to interpret. The results of the analysis show that the attribute that is a risk factor for stroke is the heart. The model created using the C4.5 algorithm was tested using a counfusion matrix resulting in an accuracy of 64.54%, a precision of 53.34% for classifying ischemic stroke patients correctly, and a recall of 72.73% for classifying hemorrhagic patients correctly.

Migraine and atrial fibrillation: a systematic review and meta-analysis.

Patients with migraines, particularly those with auras, may present with stroke. Atrial fibrillation is a known risk factor for stroke. With common pathophysiological factors between migraines and atrial fibrillation, we aimed to clarify the association between migraine and atrial fibrillation in this systematic review and meta-analysis. A literature search was conducted in EMBASE, PubMed, Scopus and Cochrane electronic bibliographic databases from inception to 5 September 2022 with the following inclusion criteria: (a) cohort or cross-sectional studies; (b) studies that included only patients aged ≥18 years; and (c) studies that examined the association between atrial fibrillation and migraines. Exclusion criteria were case-control studies and the studies that included patients with previous diagnosis of atrial fibrillation or nonmigrainous headache. The Newcastle-Ottawa Scale was used to assess the quality of studies. Six studies were included, demonstrating a pooled prevalence of atrial fibrillation of 1.61% (95% confidence interval [CI] 0.51, 3.29) in migraine with aura and 1.32% (95% CI 0.17, 3.41) in migraine without aura. The overall prevalence of atrial fibrillation in migraine was 1.39% (95% CI 0.24, 3.46). In this systematic review and meta-analysis, the overall prevalence of atrial fibrillation in patients with migraine was low. Further studies are needed to clarify this relationship.

Comparing Stroke Risk Factors Among Sexual Minority Groups in Texas.

Knowledge gaps remain on stroke risk and disparities between sexual minority (SM) subgroups. In this study, stroke risk between SM subgroups, specifically gay/bisexual men and lesbian/bisexual women (G/BM and L/BW), was assessed. Data were collected in June 2022 using a bilingual (English and Spanish) cross-sectional paper-and-pen survey distributed among 183 SM individuals attending the 2022 Houston Pride Parade and Festival, as well as across Texas via phone call or online format. Relevant sociodemographic and stroke risk factors were compared between G/BM and L/BW using chi-square (or Fisher's exact, when appropriate) and two-sample t-tests. Sexual orientation was used to predict stroke risk using multiple binomial logistic regression, adjusting for other sociodemographic determinants. While comparing the stroke risk factors between G/BW and L/BW, statistically significant differences were found in hypertension (p = 0.047), age (p < 0.001), smoking status (p = 0.043), cholesterol level (p < 0.001), and HIV (p = 0.038). G/BM were 2.79 times more likely to have a higher stroke risk compared to L/BW (aOR = 2.79; CI, 1.11-6.05, p = 0.032), after adjusting for other sociodemographic factors. This pilot study, conducted in Texas, adds to the existing scientific literature on stroke risk among the SM population and revealed that G/BM might have a higher stroke risk compared to L/BW. These findings can inform future research and intervention designs tailored to G/BM and L/BW communities and improve their overall health.

Risk and sex-specific trends of dementia and stroke in Italy Compared to European and high-income countries and the world: global implications.

Understanding the increasing trends in Italy may inform new prevention strategies and better treatments. We investigated trends and risk factors of dementia, stroke, and ischemic heart disease (IHD) in Italy with the second-oldest population globally, compared to European and high-income countries and the world. We analyzed the Global Burden of Disease Study (GBD) 2019 estimates on incidence and burden (i.e., disability and death combined) of the three conditions in both sexes. We also analyzed the burden attributable to 12 modifiable risk factors and their changes during 1990-2019. In 2019, Italy had 186,108 new dementias (123,885 women) and 94,074 new strokes (53,572 women). Women had 98% higher crude dementia and 24% higher crude stroke burdens than men. The average age-standardized new dementia rate was 114.7 per 100,000 women and 88.4 per 100,000 men, both higher than Western Europe, the European Union, high-income countries, and the world. During 1990-2019, this rate increased in both sexes (4%), despite a decline in stroke (- 45%) and IHD (- 17%) in Italy. Dementia burden attributable to tobacco decreased in both sexes (- 12.7%) during 1990-2019, while high blood glucose and high body mass index combined burden increased (25.4%). Stroke and IHD had similar trends. While decreases in new strokes and IHDs are encouraging, new approaches to their joint prevention are required to reverse the rising dementia trends, especially among women. Life course approaches to promoting holistic brain health should be implemented at the community, national, and international levels before the growing trends become overwhelming.

Bilateral nephrectomy impairs cardiovascular function and cerebral perfusion in a rat model of acute hemodilutional anemia.

Anemia and renal failure are independent risk factors for perioperative stroke, prompting us to assess the combined impact of acute hemodilutional anemia and bilateral nephrectomy (2Nx) on microvascular brain Po2 (PBro2) in a rat model. Changes in PBro2 (phosphorescence quenching) and cardiac output (CO, echocardiography) were measured in different groups of anesthetized Sprague-Dawley rats (1.5% isoflurane, n = 5-8/group) randomized to Sham 2Nx or 2Nx and subsequently exposed to acute hemodilutional anemia (50% estimated blood volume exchange with 6% hydroxyethyl starch) or time-based controls (no hemodilution). Outcomes were assessed by ANOVA with significance assigned at P < 0.05. At baseline, 2Nx rats demonstrated reduced CO (49.9 ± 9.4 vs. 66.3 ± 19.3 mL/min; P = 0.014) and PBro2 (21.1 ± 2.9 vs. 32.4 ± 3.1 mmHg; P < 0.001) relative to Sham 2Nx rats. Following hemodilution, 2Nx rats demonstrated a further decrease in PBro2 (15.0 ± 6.3 mmHg, P = 0.022). Hemodiluted 2Nx rats did not demonstrate a comparable increase in CO after hemodilution compared with Sham 2Nx (74.8 ± 22.4 vs. 108.9 ± 18.8 mL/min, P = 0.003) that likely contributed to the observed reduction in PBro2. This impaired CO response was associated with reduced fractional shortening (33 ± 9 vs. 51 ± 5%) and increased left ventricular end-systolic volume (156 ± 51 vs. 72 ± 15 µL, P < 0.001) suggestive of systolic dysfunction. By contrast, hemodiluted Sham 2Nx animals demonstrated a robust increase in CO and preserved PBro2. These data support the hypothesis that the kidney plays a central role in maintaining cerebral perfusion and initiating the adaptive increase in CO required to optimize PBro2 during acute anemia.NEW & NOTEWORTHY This study has demonstrated that bilateral nephrectomy acutely impaired cardiac output (CO) and microvascular brain Po2 (PBro2), at baseline. Following acute hemodilution, nephrectomy prevented the adaptive increase in CO associated with acute hemodilution leading to a further reduction in PBro2, accentuating the degree of cerebral tissue hypoxia. These data support a role for the kidney in maintaining PBro2 and initiating the increase in CO that optimized brain perfusion during acute anemia.

Evaluation of stroke awareness and risk factor prevalence among students at a public sector university in Quetta

Background and Objective:&#x0D;  Stroke is the leading cause of death and disability. Improving stroke knowledge among medical students will help to improve stroke care and its prevention. This study aims to evaluate the prevalence of risk factors and stroke awareness among university students.&#x0D; Methods:&#x0D; This cross-sectional study was conducted among students at Sardar Bahadur Khan Women's University in Quetta. An eleven-question multiple-choice survey was administered to assess participants' knowledge of stroke-related concepts. The initial study was conducted using descriptive statistics. Additionally, a supplementary screening for common risk factors linked to stroke was included in the study, which involved blood pressure, blood sugar, and cholesterol measures. Data were coded, entered into SPSS, and screened for missing values and outliers. Descriptive analyses were conducted, including frequency tables and graphical representations using pie charts.&#x0D; Results:&#x0D; In our survey of 255 female students, the vast majority (94.9%) correctly classified stroke as a brain disease, whereas a lesser percentage (1.6%) confused it with heart (0.8%), kidney (0.8%), or lung diseases (0.8%) problems. Notably, 74.1% of participants were aware of the precise cause of stroke, but 58.8% identified arm and leg weakness as a symptom. Other symptoms that were recognized by participants included difficulties speaking (25.5%), headache (9.8%), vertigo (2.4%), and chest pain (3.4%). Moreover, 94.9% of participants recognized that stroke is preventable. The most often diagnosed risk factor was hypertension (58.4%), which was followed by high cholesterol (11.8%), diabetes (9.0%), migraine (8.2%), advanced age (7.8%), and smoking (4.7%).&#x0D; Conclusion&#x0D; Our study shows a very good knowledge about stroke among the students at Sardar Bahadur Khan University but our results are biased due to addressing only an educated group of people.

Meat and meat products - a scoping review for Nordic Nutrition Recommendations 2023.

Meat is not only a source of several nutrients but also a proposed risk factor for several non-communicable diseases. Here, we describe the totality of evidence for the role of meat intake for chronic disease outcomes, discuss potential mechanistic pathways, knowledge gaps, and limitations of the literature. Use of the scoping review is based on a de novo systematic review (SR) and meta-analysis on the association between poultry intake and cardiovascular disease (CVD) and type 2 diabetes (T2D), qualified SRs (as defined in the Nordic Nutrition Recommendations 2023 project) on meat intake and cancer by the World Cancer Research Fund (WCRF), the International Agency for Research on Cancer (IARC), and a systematic literature search of SRs and meta-analyses. The quality of the SRs was evaluated using a modified AMSTAR 2 tool, and the strength of evidence was evaluated based on a predefined criteria developed by the WCRF. The quality of the SRs was on average critically low. Our findings indicate that the evidence is too limited for conclusions for most of the chronic disease outcomes. However, findings from qualified SRs indicate strong evidence that processed meat increases the risk of colorectal cancer and probable evidence that red meat (unprocessed, processed, or both) increases the risk. The evidence suggests that both unprocessed red meat and processed meat (also including processed poultry meat) are probable risk factors for CVD mortality and stroke, and that total red meat and processed meat are risk factors for CHD. We found no sufficient evidence suggesting that unprocessed red meat, processed red meat, total red meat, or processed meat (including red and white meat) would be protective of any chronic disease. There was also no sufficient evidence to conclude on protective effect of poultry on any chronic diseases; effects on the risk of CVD, stroke, and T2D, to any direction, were regarded as unlikely.