Association between serum calcium and prognosis in patients with acute ischemic stroke in ICU: analysis of the MIMIC-IV database.

BACKGROUND: While serum Ca has proven to be a reliable predictor of mortality across various diseases, its connection with the clinical outcomes of ischemic stroke (IS) remains inconclusive. Our research aimed to explore the relationships between serum total Ca (tCa) and serum ionized Ca (iCa) and mortality among acute IS (AIS) patients. METHODS: We gathered data from 1773 AIS patients in the Medical Information Mart for Intensive Care Database IV, including baseline demographic data, comorbidities, vital signs, laboratory-based data, and scoring systems. Endpoints for the study encompassed 30-d, 90-d, and 365-d all-cause mortalities. Employing restricted cubic spline Cox regression, we explored potential nonlinear relationships between admission serum iCa and tCa levels and mortality. Participants were categorized into four groups based on serum iCa and tCa quartiles. Multivariable Cox regression analysis was then conducted to evaluate the independent association of iCa and tCa quartiles with all-cause mortality. RESULTS: The restricted cubic spline revealed a U-shaped association between iCa and 30-d and 90-d mortality (P<0.05), while the relationship between iCa and 365-d mortality was linear (P<0.05). After adjusting for confounders, multivariable Cox analysis demonstrated that the lowest serum iCa level quartile was independently associated with increased risks of 30-d, 90-d, and 365-d mortality. Similarly, the highest serum iCa level quartile was independently associated with increased risks of 30-d and 90-d mortality, but not 365-d mortality. Notably, serum tCa level showed no association with increased risks of 30-d, 90-d, and 365-d mortality. CONCLUSIONS: Our findings suggest that serum iCa, rather than tCa, is linked to ischemic stroke prognosis. Both high and low serum iCa levels are associated with poor short-term prognosis, while only low serum iCa is associated with poor long-term prognosis in AIS patients.

Lipoprotein(a) as a blood marker for large artery atherosclerosis stroke etiology: validation in a prospective cohort from a swiss stroke center.

BACKGROUND: Lipoprotein (a) [Lp(a)] serum levels are highly genetically determined and promote atherogenesis. High Lp(a) levels are associated with increased cardiovascular morbidity. Serum Lp(a) levels have recently been associated with large artery atherosclerosis (LAA) stroke. We aimed to externally validate this association in an independent cohort. METHODS: This study stems from the prospective multicentre CoRisk study (CoPeptin for Risk Stratification in Acute Stroke patients [NCT00878813]), conducted at the University Hospital Bern, Switzerland, between 2009 and 2011, in which Lp(a) plasma levels were measured within the first 24 hours after stroke onset. We assessed the association of Lp(a) with LAA stroke using multivariable logistic regression and performed interaction analyses to identify potential effect modifiers. RESULTS: Of 743 patients with ischaemic stroke, 105 (14%) had LAA stroke aetiology. Lp(a) levels were higher for LAA stroke than non-LAA stroke patients (23.0 nmol/l vs 16.3 nmol/l, p = 0.01). Multivariable regression revealed an independent association of log10and#xA0;Lp(a) with LAA stroke aetiology (aOR 1.47 [95% CI 1.03and#x2013;2.09], p = 0.03). The interaction analyses showed that Lp(a) was not associated with LAA stroke aetiology among patients with diabetes. CONCLUSIONS: In a well-characterised cohort of patients with ischaemic stroke, we validated the association of higher Lp(a) levels with LAA stroke aetiology, independent of traditional cardiovascular risk factors. These findings may inform randomised clinical trials investigating the effect of Lp(a) lowering agents on cardiovascular outcomes. The CoRisk (CoPeptin for Risk Stratification in Acute Patients) study is registered on ClinicalTrials.gov. REGISTRATION NUMBER: NCT00878813.

Development and validation of a nomogram for predicting 28-day mortality in patients with ischemic stroke.

BACKGROUND/AIM: We aimed to construct a validated nomogram model for predicting short-term (28-day) ischemic stroke mortality among critically ill populations. MATERIALS AND METHODS: We collected raw data from the Medical Information Mart for Intensive Care IV database, a comprehensive repository renowned for its depth and breadth in critical care information. Subsequently, a rigorous analytical framework was employed, incorporating a 10-fold cross-validation procedure to ensure robustness and reliability. Leveraging advanced statistical methodologies, specifically the least absolute shrinkage and selection operator regression, variables pertinent to 28-day mortality in ischemic stroke were meticulously screened. Next, binary logistic regression was utilized to establish nomogram, then applied concordance index to evaluate discrimination of the prediction models. Predictive performance of the nomogram was assessed by integrated discrimination improvement (IDI) and net reclassification index (NRI). Additionally, we generated calibration curves to assess calibrating ability. Finally, we evaluated the nomogram's net clinical benefit using decision curve analysis (DCA), in comparison with scoring systems clinically applied under common conditions. RESULTS: A total of 2089 individuals were identified and assigned into training (n = 1443) or validation (n = 646) cohorts. Various identified risk factors, including age, ethnicity, marital status, underlying metastatic solid tumor, Charlson comorbidity index, heart rate, Glasgow coma scale, glucose concentrations, white blood cells, sodium concentrations, potassium concentrations, mechanical ventilation, use of heparin and mannitol, were associated with short-term (28-day) mortality in ischemic stroke individuals. A concordance index of 0.834 was obtained in the training dataset, indicating that our nomogram had good discriminating ability. Results of IDI and NRI in both cohorts proved that our nomogram had positive improvement of predictive performance, compared to other scoring systems. The actual and predicted incidence of mortality showed favorable concordance on calibration curves (P > 0.05). DCA curves revealed that, compared with scoring systems clinically used under common conditions, the constructed nomogram yielded a greater net clinical benefit. CONCLUSIONS: Utilizing a comprehensive array of fourteen readily accessible variables, a prognostic nomogram was meticulously formulated and rigorously validated to provide precise prognostication of short-term mortality within the ischemic stroke cohort.

Machine learning identifies novel coagulation genes as diagnostic and immunological biomarkers in ischemic stroke.

BACKGROUND: Coagulation system is currently known associated with the development of ischemic stroke (IS). Thus, the current study is designed to identify diagnostic value of coagulation genes (CGs) in IS and to explore their role in the immune microenvironment of IS. METHODS: Aberrant expressed CGs in IS were input into unsupervised consensus clustering to classify IS subtypes. Meanwhile, key CGs involved in IS were further selected by weighted gene co-expression network analysis (WGCNA) and machine learning methods, including random forest (RF), support vector machine (SVM), generalized linear model (GLM) and extreme-gradient boosting (XGB). The diagnostic performance of key CGs were evaluated by receiver operating characteristic (ROC) curves. At last, quantitative PCR (qPCR) was performed to validate the expressions of key CGs in IS. RESULTS: IS patients were classified into two subtypes with different immune microenvironments by aberrant expressed CGs. Further WGCNA, machine learning methods and ROC curves identified ACTN1, F5, TLN1, JMJD1C and WAS as potential diagnostic biomarkers of IS. In addition, their expressions were significantly correlated with macrophages, neutrophils and/or T cells. GSEA also revealed that those biomarkers may regulate IS via immune and inflammation. Moreover, qPCR verified the expressions of ACTN1, F5 and JMJD1C in IS. CONCLUSIONS: The current study identified ACTN1, F5 and JMJD1C as novel coagulation-related biomarkers associated with IS immune microenvironment, which enriches our knowledge of coagulation-mediated pathogenesis of IS and sheds light on next-step in vivo and in vitro experiments to elucidate the relevant molecular mechanisms.

The systemic inflammation score is a prognostic factor for patients with ischemic stroke who have not undergone intravenous thrombolysis or endovascular thrombectomy therapy.

BACKGROUND: The systemic inflammation score (SIS) has been utilised as a representative biomarker for evaluating nutritional and inflammation status. However, the predictive value of SIS has not been reported in patients with acute ischemic stroke (AIS). We aimed to evaluate whether SIS is associated with prognosis in stroke. METHODS: A total of 4801 patients with AIS were included in the study. The primary outcome was a modified Rankin Scale score>2 at the 3-month follow-up. A total of 4801 patients were randomly allocated into training (n=3361) and validation cohorts (n=1440) at a ratio of 7:3. Model performance was validated using the receiver operating characteristic (ROC) curve and calibration curve. Additionally, a comparison was made between the nomogram and the THRIVE score in regards to their respective predictive capabilities. RESULTS: Overall, 1091(32.5%) patients in the training cohort and 446 (31.0%) patients in the validation cohort experienced an unfavorable outcome. The multivariate logistic regression analysis revealed that a high SIS, age, NIHSS, diabetes and prior stroke were associated with unfavorable outcome. Our nomogram was developed based on the variables mentioned above. The area under the curve (AUC) of the training set and the validation set are 0.702 and 0.708, respectively, indicating that the model has modest agreement and discrimination. The results of AUC, net reclassification improvement (NRI) and integrated discrimination improvement (IDI) showed that nomogram had significantly higher predictive value than THRIVE scores (all P<0.001). However, unlike the THRIVE publication, all patients who had undergone intravenous thrombolysis or endovascular thrombectomy therapy were excluded in our study. In consequence, our derived THRIVE scores cannot be compared to those in the original THRIVE study. CONCLUSION: The SIS exhibits potential as a simple prognostic biomarker, and the nomogram, which utilizes the SIS, may serve as a valuable tool for clinicians in the early identification of patients at heightened risk for unfavorable outcomes.

Revolutionizing Ischemic Stroke Diagnosis and Treatment: The Promising Role of Neurovascular Unit-Derived Extracellular Vesicles.

Ischemic stroke is a fatal and disabling disease worldwide and imposes a significant burden on society. At present, biological markers that can be conveniently measured in body fluids are lacking for the diagnosis of ischemic stroke, and there are no effective treatment methods to improve neurological function after ischemic stroke. Therefore, new ways of diagnosing and treating ischemic stroke are urgently needed. The neurovascular unit, composed of neurons, astrocytes, microglia, and other components, plays a crucial role in the onset and progression of ischemic stroke. Extracellular vesicles are nanoscale lipid bilayer vesicles secreted by various cells. The key role of extracellular vesicles, which can be released by cells in the neurovascular unit and serve as significant facilitators of cellular communication, in ischemic stroke has been extensively documented in recent literature. Here, we highlight the role of neurovascular unit-derived extracellular vesicles in the diagnosis and treatment of ischemic stroke, the current status of extracellular vesicle engineering for ischemic stroke treatment, and the problems encountered in the clinical translation of extracellular vesicle therapies. Extracellular vesicles derived from the neurovascular unit could provide an important contribution to diagnostic and therapeutic tools in the future, and more studies in this area should be carried out.

Cardiomyopathy in Patients With Acute Ischemic Stroke and Methamphetamine Use: Relevance for Cardioembolic Stroke and Outcome.

BACKGROUND: Methamphetamine use has emerged as a major risk factor for cardiovascular and cerebrovascular disease in young adults. The aim of this study was to investigate a possible association of methamphetamine use with cardioembolic stroke. METHODS AND RESULTS: We performed a retrospective study of patients with acute ischemic stroke admitted at our medical center between 2019 and 2022. All patients were screened for methamphetamine use and cardiomyopathy, defined as left ventricular ejection fraction ≤45%. Among 938 consecutive patients, 46 (4.9%) were identified as using methamphetamine. Compared with the nonmethamphetamine group (n=892), the methamphetamine group was significantly younger (52.8±9.6 versus 69.7±15.2 years; P<0.001), included more men (78.3% versus 52.8%; P<0.001), and had a significantly higher rate of cardiomyopathy (30.4% versus 14.0%; P<0.01). They were also less likely to have a history of atrial fibrillation (8.7% versus 33.4%; P<0.01) or hyperlipidemia (28.3% versus 51.7%; P<0.01). Compared with patients with cardiomyopathy without methamphetamine use, the patients with cardiomyopathy with methamphetamine use had significantly lower left ventricular ejection fraction (26.0±9.59% versus 32.47±9.52%; P<0.01) but better functional outcome at 3 months, likely attributable to significantly younger age and fewer comorbidities. In the logistic regression model of clinical variables, methamphetamine-associated cardiomyopathy was found to be significantly associated with cardioembolic stroke (odds ratio, 1.79 [95% CI, 1.04-3.06]; P<0.05). CONCLUSIONS: We demonstrate that methamphetamine use is significantly associated with cardiomyopathy and cardioembolic stroke in young adults.

Baseline Uric Acid Levels and Intravenous Thrombolysis Outcomes in Patients With Acute Ischemic Stroke: A Prospective Cohort Study.

BACKGROUND: The study aimed to investigate the relationship between uric acid (UA) levels and functional outcomes at 3 months in patients with acute ischemic stroke (AIS) who underwent intravenous thrombolysis (IVT). METHODS AND RESULTS: This prospective cohort study included 1001 consecutive patients with AIS who underwent IVT. The correlation between UA levels and post-IVT AIS outcomes was examined. Any nonlinear relationship was assessed using a restricted cubic spline function. The nonlinear P value for the association of UA levels with favorable (modified Rankin Scale [mRS] score ≤2) and excellent (mRS score ≤1) outcomes at 3 months post-IVT were <0.001 and 0.001, respectively. However, for patients with and without hyperuricemia, no evident nonlinear relationship was observed between UA levels and favorable 3-month post-IVT outcomes, with nonlinear P values of 0.299 and 0.207, respectively. The corresponding interaction analysis yielded a P value of 0.001, indicating significant heterogeneity. Similar results were obtained for excellent outcomes at 3 months post-IVT. In the hyperuricemia group, increased UA levels by 50 µmol/L reduced the odds of a favorable 3-month post-AIS outcome (odds ratio [OR], 0.75 [95% CI, 0.57-0.97]). Conversely, in the nonhyperuricemia group, a similar UA increase was linked to higher favorable outcome odds (OR, 1.31 [95% CI, 1.15-1.50]). CONCLUSIONS: An inverted U-shaped nonlinear relationship was observed between UA levels and favorable and excellent outcomes at 3 months in patients with AIS who underwent IVT. Higher UA levels predict favorable outcomes in patients without hyperuricemia but unfavorable outcomes in those with hyperuricemia.

Development and Validation of Machine Learning Algorithms to Predict 1-Year Ischemic Stroke and Bleeding Events in Patients with Atrial Fibrillation and Cancer.

In this study, we leveraged machine learning (ML) approach to develop and validate new assessment tools for predicting stroke and bleeding among patients with atrial fibrillation (AFib) and cancer. We conducted a retrospective cohort study including patients who were newly diagnosed with AFib with a record of cancer from the 2012-2018 Surveillance, Epidemiology, and End Results (SEER)-Medicare database. The ML algorithms were developed and validated separately for each outcome by fitting elastic net, random forest (RF), extreme gradient boosting (XGBoost), support vector machine (SVM), and neural network models with tenfold cross-validation (train:test = 7:3). We obtained area under the curve (AUC), sensitivity, specificity, and F2 score as performance metrics. Model calibration was assessed using Brier score. In sensitivity analysis, we resampled data using Synthetic Minority Oversampling Technique (SMOTE). Among 18,388 patients with AFib and cancer, 523 (2.84%) had ischemic stroke and 221 (1.20%) had major bleeding within one year after AFib diagnosis. In prediction of ischemic stroke, RF significantly outperformed other ML models [AUC (0.916, 95% CI 0.887-0.945), sensitivity 0.868, specificity 0.801, F2 score 0.375, Brier score = 0.035]. However, the performance of ML algorithms in prediction of major bleeding was low with highest AUC achieved by RF (0.623, 95% CI 0.554-0.692). RF models performed better than CHA2DS2-VASc and HAS-BLED scores. SMOTE did not improve the performance of the ML algorithms. Our study demonstrated a promising application of ML in stroke prediction among patients with AFib and cancer. This tool may be leveraged in assisting clinicians to identify patients at high risk of stroke and optimize treatment decisions.

Peripheral blood syndecan-1 levels after mechanical thrombectomy can predict the clinical prognosis of patients with acute ischemic stroke.

BACKGROUND: Previously, we revealed noticeable dynamic fluctuations in syndecan-1 levels in the peripheral blood of post-stroke patients. We further investigated the clinical prognostic value of syndecan-1 as a biomarker of glycoprotein damage in patients with acute ischaemic stroke (AIS). METHODS: We examined 105 patients with acute large vessel occlusion in the anterior circulation, all of whom underwent mechanical thrombectomy (MT). Peripheral blood syndecan-1 levels were measured 1 day after MT, and patients were categorised into favourable and unfavourable prognostic groups based on the 90-day modified Rankin Scale (mRS) score. Additionally, we compared the clinical outcomes between groups with high and low syndecan-1 concentrations. RESULTS: The findings revealed a significantly lower syndecan-1 level in the group with an unfavourable prognosis compared to those with a favourable prognosis (p < 0.01). In the multivariable logistic regression analysis, lower syndecan-1 levels were identified as a predictor of unfavourable prognosis (odds ratio (OR) = 0.965, p = 0.001). Patients displaying low syndecan-1 expression in the peripheral blood (< 29.51 ng/mL) experienced a > twofold increase in the rates of unfavourable prognosis and mortality. CONCLUSIONS: Our study demonstrates that syndecan-1, as an emerging, easily detectable stroke biomarker, can predict the clinical outcomes of patients with AIS. After MT, low levels of syndecan-1 in the peripheral blood on the first day emerged as an independent risk factor for an unfavourable prognosis, suggesting that lower syndecan-1 levels might signify worse clinical presentation and outcomes in stroke patients undergoing this procedure.

Enhancing the evaluation of acute ischemic stroke risk in individuals with non-valvular atrial fibrillation by including laboratory indicators.

To investigate the clinical significance of the CHA2DS2-VASc-60 score, lipoprotein (a) [Lp(a)], red blood cell distribution width (RDW), and their combined effect in patients with non-valvular atrial fibrillation (NVAF) who experience acute ischemic stroke (AIS). This retrospective analysis was conducted on the clinical data of hospitalized patients with NVAF at the Third Affiliated Hospital of Anhui Medical University between April 1, 2020, and April 1, 2023. Based on the diagnosis of acute ischemic stroke (AIS), the patients were divided into two groups: the AIS group (150 cases of NVAF patients with comorbid AIS) and the non-AIS group (163 cases of NVAF patients without AIS). We performed CHA2DS2-VASc-60 scoring for all patients and collected their laboratory indicators and echocardiographic indicators during hospitalization. The study comprised 313 individuals with NVAF in total. There is a statistically significant difference (P < 0.05) in the comparison of CHA2DS2-VASc-60 score (5.68 ± 1.12 vs. 3.67 ± 1.47), Lp(a) [23.98 (13.28, 42.22) vs. 14.32 (7.96, 21.91)] and RDW (13.67 ± 1.25 vs. 12.94 ± 0.76) between NVAF patients with and without concomitant AIS. The results of the Spearman correlation analysis demonstrate a positive association between Lp(a) and RDW levels and both the CHA2DS2-VASc score and the CHA2DS2-VASc-60 score in patients with NVAF. Multivariate logistic regression analysis revealed that CHA2DS2-VASc-60 score [OR = 6.549, 95% CI: 4.110-10.433, P < 0.05], Lp(a) [OR = 1.023, 95% CI: 1.005-1.041, P < 0.05], and RDW [OR = 1.644, 95% CI: 1.071-2.525, P < 0.05] were independent risk factors for AIS in patients with non-valvular atrial fibrillation (NVAF). The receiver operator characteristic (ROC) curves showed that the area under the curve of CHA2DS2-VASc-60 score, Lp(a), RDW, and CHA2DS2-VASc-60 score combined with Lp(a) and RDW predicted that NVAF patients with AIS were 0.881 [95% CI: 0.804-0.906], 0.685 [95% CI: 0.626-0.744], 0.695 [95% CI: 0.637-0.754], and 0.906 [95% CI: 0.845-0.921], respectively. The CHA2DS2-VASc-60 score, Lp(a), and RDW were significantly increased in NVAF patients with AIS, which were independent risk factors for NVAF patients with AIS. The combination of the three has a high predictive capacity for NVAF patients with AIS.

Effect of Postoperative Prolonged sedation with Dexmedetomidine after successful reperfusion with Endovascular Thrombectomy on long-term prognosis in patients with acute ischemic stroke (PPDET): study protocol for a randomized controlled trial.

BACKGROUND: Endovascular thrombectomy (EVT) is a standard treatment for acute ischemic stroke (AIS) with large vessel occlusion. Hypertension and increased blood pressure variability within the first 24 h after successful reperfusion are related to a higher risk of symptomatic intracerebral hemorrhage and higher mortality. AIS patients might suffer from ischemia-reperfusion injury following reperfusion, especially within 24 h. Dexmedetomidine (DEX), a sedative commonly used in EVT, can stabilize hemodynamics by inhibiting the sympathetic nervous system and alleviate ischemia-reperfusion injury through anti-inflammatory and antioxidative properties. Postoperative prolonged sedation for 24 h with DEX might be a potential pharmacological approach to improve long-term prognosis after EVT. METHODS: This single-center, open-label, prospective, randomized controlled trial will include 368 patients. The ethics committee has approved the protocol. After successful reperfusion (modified thrombolysis in cerebral infarction scores 2b-3, indicating reperfusion of at least 50% of the affected vascular territory), participants are randomly assigned to the intervention or control group. In the intervention group, participants will receive 0.1~1.0 µg/kg/h DEX for 24 h. In the control group, participants will receive an equal dose of saline for 24 h. The primary outcome is the functional outcome at 90 days, measured with the categorical scale of the modified Rankin Scale, ranging from 0 (no symptoms) to 6 (death). The secondary outcome includes (1) the changes in stroke severity between admission and 24 h and 7 days after EVT, measured by the National Institute of Health Stroke Scale (ranging from 0 to 42, with higher scores indicating greater severity); (2) the changes in ischemic penumbra volume/infarct volume between admission and 7 days after EVT, measured by neuroimaging scan; (3) the length of ICU/hospital stay; and (4) adverse events and the all-cause mortality rate at 90 days. DISCUSSION: This randomized clinical trial is expected to verify the hypothesis that postoperative prolonged sedation with DEX after successful reperfusion may promote the long-term prognosis of patients with AIS and may reduce the related socio-economic burden. TRIAL REGISTRATION: ClinicalTrials.gov NCT04916197. Prospectively registered on 7 June 2021.

Machine Learning-Based Clinical Prediction Models for Acute Ischemic Stroke Based on Serum Xanthine Oxidase Levels.

OBJECTIVE: Early prediction of the onset, progression and prognosis of acute ischemic stroke (AIS) is helpful for treatment decision-making and proactive management. Although several biomarkers have been found to predict the progression and prognosis of AIS, these biomarkers have not been widely used in routine clinical practice. Xanthine oxidase (XO) is a form of xanthine oxidoreductase (XOR), which is widespread in various organs of the human body and plays an important role in redox reactions and ischemia‒reperfusion injury. Our previous studies have shown that serum XO levels on admission have certain clinical predictive value for AIS. The purpose of this study was to utilize serum XO levels and clinical data to establish machine learning models for predicting the onset, progression, and prognosis of AIS. METHODS: We enrolled 328 consecutive patients with AIS and 107 healthy controls from October 2020 to September 2021. Serum XO levels and stroke-related clinical data were collected. We established 5 machine learning models-the logistic regression (LR), support vector machine (SVM), decision tree, random forest, and K-nearest neighbor (KNN) models-to predict the onset, progression, and prognosis of AIS. The area under the receiver operating characteristic curve (AUROC), accuracy, sensitivity, specificity, negative predictive value, and positive predictive value were used to evaluate the predictive performance of each model. RESULTS: Among the 5 machine learning models predicting AIS onset, the AUROC values of 4 prediction models were over 0.7, while that of the KNN model was lower (AUROC = 0.6708, 95% CI 0.576-0.765). The LR model showed the best AUROC value (AUROC = 0.9586, 95% CI 0.927-0.991). Although the 5 machine learning models showed relatively poor predictive value for the progression of AIS (all AUROCs <0.7), the LR model still showed the highest AUROC value (AUROC = 0.6543, 95% CI 0.453-0.856). We compared the value of 5 machine learning models in predicting the prognosis of AIS, and the LR model showed the best predictive value (AUROC = 0.8124, 95% CI 0.715-0.910). CONCLUSIONS: The tested machine learning models based on serum levels of XO could predict the onset and prognosis of AIS. Among the 5 machine learning models, we found that the LR model showed the best predictive performance. Machine learning algorithms improve accuracy in the early diagnosis of AIS and can be used to make treatment decisions.

Bioinformatics identification of potential biomarkers and therapeutic targets for ischemic stroke and vascular dementia.

Ischemic stroke and vascular dementia, as common cerebrovascular diseases, with the former causing irreversible neurological damage and the latter causing cognitive and memory impairment, are closely related and have long received widespread attention. Currently, the potential causative genes of these two diseases have yet to be investigated, and effective early diagnostic tools for the diseases have not yet emerged. In this study, we screened new potential biomarkers and analyzed new therapeutic targets for both diseases from the perspective of immune infiltration. Two gene expression profiles on ischemic stroke and vascular dementia were obtained from the NCBI GEO database, and key genes were identified by LASSO regression and SVM-RFE algorithms, and key genes were analyzed by GO and KEGG enrichment. The CIBERSORT algorithm was applied to the gene expression profile species of the two diseases to quantify the 24 subpopulations of immune cells. Moreover, logistic regression modeling analysis was applied to illustrate the stability of the key genes in the diagnosis. Finally, the key genes were validated using RT-PCR assay. A total of 105 intersecting DEGs genes were obtained in the 2 sets of GEO datasets, and bioinformatics functional analysis of the intersecting DEGs genes showed that GO was mainly involved in the purine ribonucleoside triphosphate metabolic process，respiratory chain complex，DNA-binding transcription factor binding and active transmembrane transporter activity. KEGG is mainly involved in the Oxidative phosphorylation, cAMP signaling pathway. The LASSO regression algorithm and SVM-RFE algorithm finally obtained three genes, GAS2L1, ARHGEF40 and PFKFB3, and the logistic regression prediction model determined that the three genes, GAS2L1 (AUC: 0.882), ARHGEF40 (AUC: 0.867) and PFKFB3 (AUC: 0.869), had good diagnostic performance. Meanwhile, the two disease core genes and immune infiltration were closely related, GAS2L1 and PFKFB3 had the highest positive correlation with macrophage M1 (p < 0.001) and the highest negative correlation with mast cell activation (p = 0.0017); ARHGEF40 had the highest positive correlation with macrophage M1 and B cells naive (p < 0.001), the highest negative correlation with B cell memory highest correlation (p = 0.0047). RT-PCR results showed that the relative mRNA expression levels of GAS2L1, ARHGEF40, and PFKFB3 were significantly elevated in the populations of both disease groups (p < 0.05). Immune infiltration-based models can be used to predict the diagnosis of patients with ischemic stroke and vascular dementia and provide a new perspective on the early diagnosis and treatment of both diseases.

Balloon-mounting stent versus balloon angioplasty for intracranial arterial stenosis: A systematic review and meta-analysis.

BACKGROUND: Intracranial artery atherosclerotic stenosis (ICAS) is a major cause of stroke, especially in Asian countries. Current treatment options, including balloon-mounted stent (BMS) and balloon angioplasty (BA), lack sufficient evidence to determine a preferred approach. This systematic review and meta-analysis aimed to compare the efficacy and safety of BMS and BA in treating ICAS. METHODS: Following PRISMA 2020 guidelines, we conducted a comprehensive search in PubMed, Web of Science, and Scopus up to December 1, 2023. Eligible studies compared BMS with BA in patients diagnosed with ICAS. Primary outcomes included the success rate and occurrence of stroke (ischemic or hemorrhagic). Secondary outcomes were perforator occlusion, in-stent thrombosis, death, and restenosis. Statistical analysis was conducted using R software version 4.3.1, employing a random-effects model. RESULTS: Five high-quality studies involving 707 patients (515 males, 192 females) were included. BMS had a significantly higher success rate compared to BA (Risk Ratio [RR]: 1.13; CI: 1.03 to 1.24, p < 0.01; I2 = 14 %). The overall risk for stroke (ischemic and hemorrhagic) was significantly higher in BMS (RR: 2.97; CI: 1.32 to 6.67, p < 0.01; I2 = 0 %). However, no significant difference was found between BMS and BA regarding ischemic stroke (RR: 2.33; CI: 0.80 to 6.74, p = 0.12; I2 = 0 %). Additionally, no significant differences were observed in terms of perforator occlusion, in-stent thrombosis, dissection, minor and major strokes, and mortality rates. BMS was associated with a lower risk of restenosis (RR: 0.31; 95 % CI: 0.12 to 0.83, p = 0.02; I2 = 0 %). CONCLUSION: Our results indicate that BMS might be associated with higher success and lower restenosis rates than BA in the treatment of ICAS but with an increased overall risk of stroke. No significant differences were observed in ischemic stroke, perforator occlusion, in-stent thrombosis, dissection, minor and major strokes, and mortality rates. The choice of treatment should consider these findings, alongside the technical challenges and desired angiographic outcomes. Future randomized controlled trials are necessary to further elucidate these results.

Ischemic stroke as an initial performance of polycythemia vera in young adults: A case report and literature review.

INTRODUCTION: As the second leading cause of death and disability worldwide, stroke is mainly caused by atherosclerosis and cardiac embolism, particularly in older individuals. Nevertheless, in young and otherwise healthy individuals, the causes of stroke can be more diverse and may include conditions such as patent foramen ovale, vasculitis, coagulopathies, genetic factors, or other undetermined causes. Although these other causes of stroke account for a relatively small proportion compared to ischemic stroke, they are becoming increasingly common in clinical practice and deserve attention. Here, we present a rare female patient with polycythemia vera (PV) who was admitted to the hospital as a stroke patient without any previous medical history. PATIENT CONCERNS: A 40-year-old young woman felt sudden dizziness and slow response. After 4 days of being admitted, she developed blurry vision on the right. DIAGNOSES: Cranial magnetic resonance imaging revealed aberrant signals in the left temporal and parietal lobe, as well as multiple small focal signal abnormalities were observed in the left frontal lobe. Magnetic resonance angiography revealed partial stenosis of the left internal carotid artery. The patient's blood routine examination revealed a significant elevation in complete blood counts, particularly the increase in red blood cells, as well as prolonged clotting time. An abdominal ultrasound and abdomen computed tomography showed splenomegaly. The outcome of the genetic testing was positive for the Janus kinase JAK2 exon V617F mutation (JAK2/V617F). The patient was diagnosed with PV-related stroke. INTERVENTIONS: The patient was treated with phlebotomy, cytoreductive therapy, and low-dose aspirin antiplatelet therapy and was regularly followed up in hematology and neurology clinics after discharge. OUTCOMES: The patient's red blood cell, leukocyte, and thrombocyte counts had fully normalized, with her hemoglobin level measuring at 146 g/L and hematocrit value at 43%. Furthermore, there had been a significant improvement in neurological symptoms. LESSONS: PV, a rare hematological disorder, can present with ischemic stroke as the initial performance, and the diagnosis mainly relies on routine blood tests, bone marrow biopsies, and genetic test. Therefore, clinicians should pay attention to PV, a low-prevalence disease, when encountering stroke in youth.

ECG predictors of AF: A systematic review (predicting AF in ischaemic stroke-PrAFIS).

In 25% of patients presenting with embolic stroke, a cause is not determined. Atrial fibrillation (AF) is a commonly identified mechanism of stroke in this population, particularly in older patients. Conventional investigations are used to detect AF, but can we predict AF in this population and generally? We performed a systematic review to identify potential predictors of AF on 12-lead electrocardiogram (ECG). METHOD: We conducted a search of EMBASE and Medline databases for prospective and retrospective cohorts, meta-analyses or case-control studies of ECG abnormalities in sinus rhythm predicting subsequent atrial fibrillation. We assessed quality of studies based on the Newcastle-Ottawa scale and data were extracted according to PRISMA guidelines. RESULTS: We identified 44 studies based on our criteria. ECG patterns that predicted the risk of developing AF included interatrial block, P-wave terminal force lead V1, P-wave dispersion, abnormal P-wave-axis, abnormal P-wave amplitude, prolonged PR interval, left ventricular hypertrophy, QT prolongation, ST-T segment abnormalities and atrial premature beats. Furthermore, we identified that factors such as increased age, high CHADS-VASC, chronic renal disease further increase the positive-predictive value of some of these parameters. Several of these have been successfully incorporated into clinical scoring systems to predict AF. CONCLUSION: There are several ECG abnormalities that can predict AF both independently, and with improved predictive value when combined with clinical risk factors, and if incorporated into clinical risk scores. Improved and validated predictive models could streamline selection of patients for cardiac monitoring and initiation of oral anticoagulants.

Association between uric acid levels and the risk of futile reperfusion in stroke after thrombectomy: A propensity score matching study.

INTRODUCTION: Currently, futile reperfusion (FR) is becoming a major challenge in the endovascular treatment of patients with acute ischemic stroke (AIS). The relationship between serum uric acid (SUA) and FR has not been investigated. This study aims to determine the relationship between SUA and FR using propensity score matching (PSM) analysis. METHODS: A total of 441 patients with AIS undergoing mechanical thrombectomy (MT) between August 2017 and January 2023 were included and divided into two groups based on the median SUA (297.4 µmol/L). Two groups were balanced using PSM analysis at a 1:1 ratio. The standardized mean difference (SMD) were used to assess the efficacy of the matching. Finally, 158 patients with low SUA (≤ 297.4 µmol/L) were matched with 158 patients with high SUA (>297.4 µmol/L). Predictors of FR were analyzed by multivariate logistic regression analysis in the PSM cohort. RESULTS: After PSM, patients with low SUA (≤ 297.4 µmol/L) had a significant higher incidence of FR (72.8 %, 115/158) than patients with high SUA (>297.4 µmol/L) (48.1 %, 76/158) (P<0.001). Multivariate logistic regression analysis in the PSM cohort showed that low SUA (≤ 297.4 µmol/L) was an independent risk factor for the efficacy of reperfusion (OR: 6.403, 95 % CI: 3.123-13.129, P<0.001), suggesting that patients with SUA ≤ 297.4 µmol/L have a 6.403 times higher risk of FR than patients with SUA>297.4 µmol/L. CONCLUSION: The results of this study suggest that low SUA (≤ 297.4 µmol/L) at admission increases the risk of FR in AIS patients undergoing MT by PSM analysis.

Prevalence of Fabry disease and GLA variants in young patients with acute stroke: The challenge to widen the screening. The Fabry-Stroke Italian Registry.

BACKGROUND: Fabry disease (FD) is a treatable X-linked lysosomal storage disorder caused by GLA gene variants leading to alpha-galactosidase A deficiency. FD is a rare cause of stroke, and it is still controversial whether in stroke patients FD should be searched from the beginning or at the end of the diagnostic workup (in cryptogenic strokes). METHODS: Fabry-Stroke Italian Registry is a prospective, multicentric screening involving 33 stroke units. FD was sought by measuring α-galactosidase A activity (males) and by genetic tests (males with reduced enzyme activity and females) in patients aged 18-60 years hospitalized for TIA, ischemic stroke, or intracerebral hemorrhage. We diagnosed FD in patients with 1) already known pathogenic GLA variants; 2) novel GLA variants if additional clinical, laboratory, or family-derived criteria were present. RESULTS: Out of 1906 patients, we found a GLA variant in 15 (0.79%; 95%CI 0.44-1.29) with a certain FD diagnosis in 3 (0.16%; 95%CI 0.03-0.46) patients, none of whom had hemorrhage. We identified 1 novel pathogenic GLA variant. Ischemic stroke etiologies in carriers of GLA variants were: cardioaortic embolism (33%), small artery occlusion (27%), other causes (20%), and undetermined (20%). Mild severity, recurrence, previous TIA, acroparesthesias, hearing loss, and small artery occlusion were predictors of GLA variant. CONCLUSION: In this large multicenter cohort the frequency of FD and GLA variants was consistent with previous reports. Limiting the screening for GLA variants to patients with cryptogenic stroke may miss up to 80% of diagnoses. Some easily recognizable clinical features could help select patients for FD screening.

Platelet indices as prognostic markers of ischemic stroke and their correlation with lipid profile.

OBJECTIVE: Stroke is the cause of one in eight deaths and adds a dreadful burden of disability for the patients. Ischemic stroke is caused by a loss of blood supply to brain due to sudden occlusion of the arterial system, caused by an emboli or thrombus. Our aim was to correlate platelet indices, total cholesterol ratio, and various comorbidities with stroke. METHODS: A cross-sectional study was performed from 2020-2022 with 132 stroke patients admitted to the SRM Medical College Hospital and Research Center, India. Detailed clinical examination was performed. Venous blood samples were drawn at the time of admission to estimate platelet count, mean platelet volume (MPV), platelet distribution width (PDW), and platelet crit (PCT). Overnight fasting serum samples were obtained for lipid profiling. RESULTS: Among the participants in our study, maximum belonged to the age group 50 to 59 years (34.1%) and majority were males (79.5%). In terms of comorbidities, 85.6% of the participants had diabetes, 42.4% had hypertension and 22% had dyslipaedemia. All platelet and lipid parameters were found to be similar between patients with and without comorbidities. While all platelet indices increased with the increase in severity of stroke, we found that PDW is most reliable in predicting stroke with an area under the receiver operator curve of 0.942, with a sensitivity and specificity of 92.1% at cut-off value 14. All platelet parameters also significantly increased in patients with severe lipid dysfuction, establishing a correlation between lipid profile, platelet indices and stroke. CONCULSION: We found a significant relationship between all platelet parameters and stroke. Thus, we believe that patients with risk factors for atherosclerosis should have their platelet indices assessed periodically before the development of cerebrovascular events. Furthermore, dyslipidemia if properly treated, is a modifiable risk factor for stroke, which can decrease morbidity and mortality leading to a healthier society.