Outcome In Ischemic Stroke Patients Research Articles

Biomarkers — predictors of mortality in patients with ischemic stroke

BACKGROUND: Stroke is a global health problem and the second leading cause of death worldwide, with ischemic stroke accounting for the majority of acute cerebrovascular accidents. Predicting outcomes in patients with ischemic stroke is challenging due to the limited prognostic performance of existing models. The lack of reliable and predictive biomarkers of ischemic stroke used in clinical practice provides a rationale for studies to address this issue.
 AIM: The aim of this study was to identify clinical, demographic, neuroimaging and molecular biomarkers of ischemic stroke associated with the fatal outcome of the disease.
 MATERIALS AND METHODS: We retrospectively analyzed cases of ischemic stroke confirmed by computed tomography of the brain with a duration of 3 months or less. As factors potentially related to the outcome of ischemic stroke, we considered (1) clinical and demographic characteristics, including sex, age, history of acute cerebrovascular accident, time from stroke to hospitalization, phase and type of stroke, neurological status on admission (level of consciousness, FOUR coma scale), comorbidities (diabetes mellitus, infectious complications, oncological diseases); (2) molecular biomarkers including blood glucose and neuron-specific enolase (NSE) levels at different phases of stroke; (3) neuroimaging biomarkers such as number and location of stroke lesion, total infarct volume, signs of edema, hemorrhagic component according to computed tomography.
 RESULTS: 38 patients with ischemic stroke were included in the study. Lesion volume was larger in non-survivors: 123 [44.6–206.2] versus 42.7 [8.2–88.7] ml3 (p=0.032), and cerebral edema was detected significantly more often on admission CT scan than in survivors: 7 (77.8%) versus 10 (34.5%), p=0.022. Stroke lesion volume was a predictor of mortality (AUC 0.739; 95% CI 0.542–0.937; p=0.032). The optimal cut-off for stroke lesion volume was found to be 90 ml3.
 CONCLUSION: Signs of edema/brain stem dislocation and cerebral lesion volume 90 ml3 documented at hospital admission are predictors of fatal outcome. Therefore, neuroimaging biomarkers can be used for risk stratification of fatal outcome in ischemic stroke patients.

Deep Learning-Based Extraction of Biomarkers for the Prediction of the Functional Outcome of Ischemic Stroke Patients.

Accurately predicting functional outcomes in stroke patients remains challenging yet clinically relevant. While brain CTs provide prognostic information, their practical value for outcome prediction is unclear. We analyzed a multi-center cohort of 743 ischemic stroke patients (<72 h onset), including their admission brain NCCT and CTA scans as well as their clinical data. Our goal was to predict the patients' future functional outcome, measured by the 3-month post-stroke modified Rankin Scale (mRS), dichotomized into good (mRS ≤ 2) and poor (mRS > 2). To this end, we developed deep learning models to predict the outcome from CT data only, and models that incorporate other patient variables. Three deep learning architectures were tested in the image-only prediction, achieving 0.779 ± 0.005 AUC. In addition, we created a model fusing imaging and tabular data by feeding the output of a deep learning model trained to detect occlusions on CT angiograms into our prediction framework, which achieved an AUC of 0.806 ± 0.082. These findings highlight how further refinement of prognostic models incorporating both image biomarkers and clinical data could enable more accurate outcome prediction for ischemic stroke patients.

Predicting stroke outcome: A case for multimodal deep learning methods with tabular and CT Perfusion data

Motivation:Acute ischemic stroke is one of the leading causes of morbidity and disability worldwide, often followed by a long rehabilitation period. To improve and personalize stroke rehabilitation, it is essential to provide a reliable prognosis to caregivers and patients. Deep learning techniques might improve the predictions by incorporating different data modalities. We present a multimodal approach to predict the functional status of acute ischemic stroke patients after their discharge based on tabular data and CT perfusion imaging. Methods:We conducted experiments on tabular, imaging, and multimodal deep learning architectures to predict dichotomized mRS scores 3 months after the event. The dataset was collected from a Dutch hospital and includes 98 CVA patients with a visible occlusion on their CT perfusion scan. Tabular data is based on the Dutch Acute Stroke Audit data, and imaging data consists of summed-up CT perfusion maps. Results:On the tabular data, TabNet outperformed our baselines with an AUC of 0.71, while ResNet-10 on the imaging data performed comparably with an AUC of 0.70. Our implementation of the multimodal DAFT architecture outperforms baselines as well as comparable studies by achieving an 0.75 AUC, and 0.80 F1 score. This was achieved with a final model of less than a hundred thousand optimizable parameters, and a dataset less than half the size of reference papers. Conclusion:Overall, we demonstrate the feasibility of predicting the functional outcome for ischemic stroke patients and the usability of multimodal deep learning architectures for this purpose.

Serum uric acid and prognosis of ischemic stroke: Cohort study, meta-analysis and Mendelian randomization study.

The role of serum uric acid (UA) levels in the functional recovery of ischemic stroke remains uncertain. To evaluate whether UA could predict clinical outcomes in patients with ischemic stroke. A three-stage study design was employed, combining a large-scale prospective cohort study, a meta-analysis and a Mendelian randomization (MR) analysis. Firstly, we conducted a cohort study using data from the Nanjing Stroke Registry Program (NSRP) to assess the association between UA levels and 3-month functional outcomes in ischemic stroke patients. Secondly, the meta-analysis was conducted to integrate currently available cohort evidence. Lastly, MR analysis was utilized to explore whether genetically determined UA had a causal link to the functional outcomes of ischemic stroke using summary data from the CKDGen and GISCOME datasets. In the first stage, the cohort study included 5631 patients and found no significant association between UA levels and functional outcomes at 3 months after ischemic stroke. In the second stage, the meta-analysis, including 10 studies with 14,657 patients, also showed no significant association between UA levels and stroke prognosis. Finally, in the third stage, MR analysis using data from 6165 patients in the GISCOME study revealed no evidence of a causal relationship between genetically determined UA and stroke functional outcomes. Our comprehensive triangulation approach found no significant association between UA levels and functional outcomes at 3 months after ischemic stroke.

Association of nutritional screening tools with 6-month outcomes in ischemic stroke patients: A retrospective study

ObjectiveNutritional screening tools based on laboratory examinations are relatively objective and available indicators. However, few studies have investigated whether malnutrition severity might be associated with adverse outcomes at the platform recovery period of 6 mo and differentiated in acute ischemic stroke patients with or without intravenous thrombolysis. Therefore, we assessed the association between malnutrition and 6-mo outcomes in both intravenous thrombolysis and non-intravenous thrombolysis patients. MethodsWe retrospectively recruited 138 acute ischemic stroke patients who received intravenous thrombolysis and 311 who did not. The Geriatric Nutritional Risk Index, prognostic nutritional index, and Controlling Nutritional Status were used to assess nutritional status. The concordance between the 3 malnutrition screening tools was investigated with the κ statistic. Subgroups analyses were conducted to assess the correlation between malnutrition and functional outcomes in intravenous thrombolysis and non-intravenous thrombolysis patients. ResultsA total of 17 (6.44%) patients were suffering from malnutrition, as indicated by the Geriatric Nutritional Risk Index, prognostic nutritional index, and Controlling Nutritional Status jointly. Moderate–severe malnutrition evaluated by the Geriatric Nutritional Risk Index was significantly associated with poor functional outcome (odds ratio = 4.074; P = 0.003). Patients in the good functional outcome group (modified Rankin scale scores = 0 to 2) had a higher proportion of intravenous thrombolysis treatment (32.79% versus 21.25%; P = 0.043). Furthermore, subgroup analyses found no significant interactions between malnourished levels and intravenous thrombolysis treatment (P interaction > 0.05). ConclusionThe Geriatric Nutritional Risk Index, over ≤24 h, compared with the prognostic nutritional index and Controlling Nutritional Status, provided timely signals to improve acute ischemic stroke patients’ nutritional status. Also, nutritional status might not lead todifferent 6-mo outcomes, whether or not patients received intravenous thrombolysis treatment.

Role of artificial intelligence and machine learning in the diagnosis of cerebrovascular disease.

Cerebrovascular diseases are known to cause significant morbidity and mortality to the general population. In patients with cerebrovascular disease, prompt clinical evaluation and radiographic interpretation are both essential in optimizing clinical management and in triaging patients for critical and potentially life-saving neurosurgical interventions. With recent advancements in the domains of artificial intelligence (AI) and machine learning (ML), many AI and ML algorithms have been developed to further optimize the diagnosis and subsequent management of cerebrovascular disease. Despite such advances, further studies are needed to substantively evaluate both the diagnostic accuracy and feasibility of these techniques for their application in clinical practice. This review aims to analyze the current use of AI and MI algorithms in the diagnosis of, and clinical decision making for cerebrovascular disease, and to discuss both the feasibility and future applications of utilizing such algorithms. We review the use of AI and ML algorithms to assist clinicians in the diagnosis and management of ischemic stroke, hemorrhagic stroke, intracranial aneurysms, and arteriovenous malformations (AVMs). After identifying the most widely used algorithms, we provide a detailed analysis of the accuracy and effectiveness of these algorithms in practice. The incorporation of AI and ML algorithms for cerebrovascular patients has demonstrated improvements in time to detection of intracranial pathologies such as intracerebral hemorrhage (ICH) and infarcts. For ischemic and hemorrhagic strokes, commercial AI software platforms such as RapidAI and Viz.AI have bene implemented into routine clinical practice at many stroke centers to expedite the detection of infarcts and ICH, respectively. Such algorithms and neural networks have also been analyzed for use in prognostication for such cerebrovascular pathologies. These include predicting outcomes for ischemic stroke patients, hematoma expansion, risk of aneurysm rupture, bleeding of AVMs, and in predicting outcomes following interventions such as risk of occlusion for various endovascular devices. Preliminary analyses have yielded promising sensitivities when AI and ML are used in concert with imaging modalities and a multidisciplinary team of health care providers. The implementation of AI and ML algorithms to supplement clinical practice has conferred a high degree of accuracy, efficiency, and expedited detection in the clinical and radiographic evaluation and management of ischemic and hemorrhagic strokes, AVMs, and aneurysms. Such algorithms have been explored for further purposes of prognostication for these conditions, with promising preliminary results. Further studies should evaluate the longitudinal implementation of such techniques into hospital networks and residency programs to supplement clinical practice, and the extent to which these techniques improve patient care and clinical outcomes in the long-term.

Potential and limitations of computed tomography images as predictors of the outcome of ischemic stroke events: a review

The prediction of functional outcome after a stroke remains a relevant, open problem. In this article, we present a systematic review of approaches that have been proposed to predict the most likely functional outcome of ischemic stroke patients, as measured by the modified Rankin scale. Different methods use a variety of clinical information and features extracted from brain computed tomography (CT) scans, usually obtained at the time of hospital admission. Most studies have concluded that CT data contains useful information, but the use of this information by models does not always translate into statistically significant improvements in the quality of the predictions.

Correlation between Atherogenic Index of Plasma and Lipid Profile with Cognitive Function and Their Effect on Outcome in Ischemic Stroke Patients

Dyslipidemia is one of the main risk factors for both ischemic stroke and cognitive impairment. Atherogenic index of plasma (AIP) has been shown to correlate with mortality and clinical outcomes in stroke, but studies about its association with cognitive impairment in ischemic stroke is still limited. We aimed to determine the correlation between AIP and lipid profile and cognitive function and their effect on outcome in ischemic stroke patients. A cross-sectional study involving 50 ischemic stroke patients in the Haji Adam Malik General Hospital was conducted from August 2021 to March 2022. We measured the cholesterol level and calculated the AIP then divided them into 3 risk categories which were high (AIP&gt;0.21); intermediate (AIP&gt;0.11and ≤0.21) and low (≤0.11). We performed cognitive assessment and stroke outcome at the 7th day of stroke onset. Data analysis was conducted with Spearman correlation test. The subjects were predominantly male (60%) with median age of 55 (34-68) years. Most of the subjects had AIP level of high risk (54%) and were cognitively impaired (66%). There was no significant association between AIP and both global cognition and each cognitive domain. However, there were significant negative correlations between total cholesterol (r=-0.31, p=0.03) and LDL-C level (r=-0.30, p=0.03) and attention. There was also a significant negative correlation between cognitive function and stroke outcome (r=-0.61, p=0.01). Higher total cholesterol and LDL-C levels showed negative correlation with cognitive function, mainly attention. Poorer cognitive function correlated with worse outcome in ischemic stroke patients.

Seasonal Variation in Neurological Severity and Clinical Outcomes in Ischemic Stroke Patients - A 9-Year Study of 5,238 Patients.

Because the effects of extreme weather conditions on stroke severity and outcomes are unclear, we evaluated seasonal variations in stroke severity and clinical outcomes.Methods and Results: Between 2012 and 2020 we enrolled 5,238 patients with acute ischemic stroke, who were divided into 4 seasons according to stroke onset: spring, summer, autumn and winter. We analyzed the effect of season on the severity and outcomes of all subjects. Multivariable analysis showed that the winter group had 1.234-fold increased risk of moderate-to-severe neurological deficits than the summer group (95% confidence interval (CI): 1.034-1.472, P=0.020). Compared with the summer group, the winter and the spring groups experienced 1.243- and 1.251-fold the risk of suffering from worse outcomes among all patients at 6-month follow-up (95% CI 1.008-1.534, P=0.042, 95% CI 1.013-1.544, P=0.037). The 1-year follow-up revealed similar results. Further comparison of each season in the 2012-2015 and 2016-2020 periods found that the proportion of poor outcomes in the latter autumn group was lower than that in the former time period, with significant differences in both 6-month and 1-year follow-up. The onset season was related to the severity and clinical outcomes of ischemic stroke. Patients with winter onset had more severe neurological deficits and worse outcomes than those with summer onset.

Association of underlying untreated cardiovascular risk factors with mortality and functional outcome in ischaemic stroke patients

ObjectivesThe study aimed to determine the prevalence of untreated pharmacologically modifiable cardiovascular risk factors (PMRF) among patients with ischaemic stroke and the association with in-hospital mortality and functional outcome. MethodsWe analysed the data from ischaemic stroke cases admitted to Sarawak General Hospital between June 2013 and June 2021. We matched the underlying PMRFs with prior medications and categorised them as treated, untreated, or no PMRF. We calculated the prevalence and assessed the association between untreated PMRFs and in-hospital mortality or favourable functional outcome (FFO) at discharge, which was adjusted for age, sex, and other covariates in multivariable models. ResultsWe included 1963 patients [65.4% male, 59.8 (SD 13.4) years]; 43.8% who had at least one untreated PMRF had triple the odds of in-hospital mortality [adjusted OR (aOR) 2.86, (95%CI 1.44, 5.70)], whereas 30.2% who had all PMRFs treated showed no significant association. Untreated hypertension [aOR 2.19 (95%CI 1.21, 3.98)], treated [aOR 3.02 (95%CI 1.32, 6.92)], and untreated atrial fibrillation [aOR 1.89 (95%CI 1.18, 3.03)] were significantly associated with more in-hospital death, whereas treated prior stroke was associated with fewer in-hospital death [aOR 0.31 (95%CI 0.11, 0.84)]. Treated diabetes [aOR 0.66 (95%CI 0.49, 0.88)] and untreated prior stroke [aOR 0.53 (95%CI 0.33, 0.83)] were associated with fewer FFO. ConclusionThe high prevalence of untreated underlying PMRFs was significantly associated with poorer outcomes among Malaysian patients with ischaemic stroke in Sarawak. Efforts are needed to promote early screening and treatment of cardiovascular risk factors to reduce the burdens and improve stroke outcomes in this region.

Development and validation of a nomogram model for predicting unfavorable functional outcomes in ischemic stroke patients after acute phase.

Prediction of post-stroke functional outcome is important for personalized rehabilitation treatment, we aimed to develop an effective nomogram for predicting long-term unfavorable functional outcomes in ischemic stroke patients after acute phase. We retrospectively analyzed clinical data, rehabilitation data, and longitudinal follow-up data from ischemic stroke patients who underwent early rehabilitation at multiple centers in China. An unfavorable functional outcome was defined as a modified Rankin Scale (mRS) score of 3-6 at 90 days after onset. Patients were randomly allocated to either a training or test cohort in a ratio of 4:1. Univariate and multivariate logistic regression analyses were used to identify the predictors for the development of a predictive nomogram. The area under the receiver operating characteristic curve (AUC) was used to evaluate predictive ability in both the training and test cohorts. A total of 856 patients (training cohort: n = 684; test cohort: n = 172) were included in this study. Among them, 518 patients experienced unfavorable outcomes 90 days after ischemic stroke. Trial of ORG 10172 in Acute Stroke Treatment classification (p = 0.024), antihypertensive agents use [odds ratio (OR) = 1.86; p = 0.041], 15-day Barthel Index score (OR = 0.930; p < 0.001) and 15-day mRS score (OR = 13.494; p < 0.001) were selected as predictors for the unfavorable outcome nomogram. The nomogram model showed good predictive performance in both the training (AUC = 0.950) and test cohorts (AUC = 0.942). The constructed nomogram model could be a practical tool for predicting unfavorable functional outcomes in ischemic stroke patients underwent early rehabilitation after acute phase.

Association between blood pressure and different antihypertensive drugs with outcome after ischemic stroke: A Mendelian randomization study.

Observational studies suggest an association between blood pressure (BP) and functional outcomes in ischemic stroke patients but whether this is causal or due to confounding is uncertain. We used Mendelian randomization (MR) to assess causality, and also explore whether particular classes of anti-hypertensives were associated with a better outcome after ischemic stroke. We selected genetic variants associated with systolic and diastolic BP and BP-lowering variants in genes encoding antihypertensive drugs from genome-wide association studies (GWAS) on 757,601 individuals. The primary outcome was 3-month dependence or death defined as a modified Rankin Scale (mRS) of 3-6. The secondary outcome was disability or death after 90 days defined as mRS 2-6. Cochran's Q statistic in the inverse variance weighted (IVW) model, the weighted median, MR-Egger regression, leave-one-single-nucleotide polymorphism (SNP)-out analysis, MR-Pleiotropy Residual Sum and Outlier methods were adopted as sensitivity analyses. To validate our primary results, we performed independent repeat analyses and Bi-directional MR analyses. Genetic predisposition to higher systolic and diastolic BP was associated with disability or death after ischemic stroke in univariable IVW MR analysis (odds ratio (OR) 1.29, 95% confidence interval (CI): 1.05-1.59, p = 0.014; OR 1.27, 95% CI: 1.07-1.51, p = 0.006, respectively). Pulse pressure was associated with both dependence or death and disability or death after ischemic stroke (OR = 1.05, 95% CI: 1.02-1.08, p = 0.002; OR = 1.04, 95% CI = 1.01-1.07, p = 0.009, respectively). Angiotensin-converting enzyme inhibitor (ACEI) and calcium channel blocker (CCB) were significantly associated with improved functional outcomes (dependence or death, OR 0.76, 95% CI: 0.62-0.94, p = 0.009; OR 0.89, 95% CI: 0.83-0.97, p = 0.005). Proxies for β-blockers, angiotensin receptor blockers (ARB), and thiazides failed to show associations with functional outcomes (p > 0.05). We provide evidence for an association of genetic predisposition to higher BP with a higher risk of 3-month functional dependence after ischemic stroke. Our findings support ACEI and CCB as promising antihypertensive drugs for improving functional outcomes in ischemic stroke.

Functional outcomes of ischemic stroke patients aged over 80 years treated with acute revascularization therapy according to pre-morbid disability: a PARADISE study.

Aging population leads to changes in the profile of patients with acute ischemic stroke (IS), and older adults were largely excluded from randomized clinical trials of acute revascularization therapy. This study aimed to assess functional outcomes of treated IS patients > 80 years old according to prior disability and identify associated factors. Consecutively older patients with acute IS treated with either IV thrombolysis and/or mechanical thrombectomy were enrolled between 2016 and 2019. Pre-morbid disability was assessed using the modified Rankin Scale (mRS) score, and patients were classified as being independent (mRS score, 0-2) or having pre-existing disability (mRS score, 3-5). A multivariable logistic regression analysis was performed to assess factors associated with a poor functional outcome (mRS score > 3) at 3 and 12 months in each group of patients. Among 300 included patients (mean age: 86.3 ± 4.6 years, 63% women, median NIHSS score: 14, IQR: 8-19), 100 had a pre-existing disability. In patients with a pre-morbid mRS score of 0-2, 51% had mRS >3 including 33% of deaths at 3 months. At 12 months, 50% had a poor outcome including 39% of deaths. In patients with a pre-morbid mRS score of 3-5, 71% had a poor outcome at 3 months including 43% of deaths, and at 12 months, 76% had mRS >3 including 52% of deaths. In multivariable models, the NIHSS score at 24 h was independently associated with poor outcomes at 3 and 12 months in both patients with (OR = 1.32; 95% CI: 1.16-1.51, p < 0.001 for 12 months outcome) or without (OR = 1.31; 95% CI: 1.19-1.44, p < 0.001 for 12 months outcome) pre-morbid disability. Although a large proportion of older patients with a pre-existing disability had a poor functional outcome, they did not differ from their non-impaired counterparts regarding prognostic factors. This means that there were no factors in our study that would help clinicians identify patients at risk of poor functional outcomes after revascularization therapy among those with prior disability. Further studies are needed to better understand the post-stroke trajectory of older IS patients with a pre-morbid disability.

Frequency of Hyponatremia and Its Impact on Prognosis in Ischemic Stroke.

Background Hyponatremia, often encountered in hospitalized patients, is associated with adverse outcomes in ischemic stroke patients. In this study, we investigated the frequency of hyponatremia and its impact on prognosis and clinical outcomes in ischemic stroke patients from a tertiary care hospital. Methodology A total of 289 patients admitted to the hospital with ischemic stroke from September 2022 to February 2023 were considered in this cross-sectional study. Serum sodium level was measured on admission, and hyponatremia was defined as sodium less than 135 mmol/L. The primary outcome of the study was assessed by the National Institutes of Health Stroke Scale (NIHSS) score on admission and discharge and inpatient mortality. Data were analyzed using SPSS version 20 (IBM Corp., Armonk, NY, USA), and multivariate logistic regressions were conducted using variables identified as having a relationship with hyponatremia. Results Our study shows that among 289 patients with ischemic stroke, the mean age was 61 ± 8.53 years. Hyponatremia was observed in 101 (35%) patients, and all baseline characteristics and risk factors for stroke were similar between patients with and without hyponatremia. The patients with hyponatremia had higher NIHSS scores on admission (p = 0.041) and at discharge (p = 0.039). In the resultant multivariate analysis, hyponatremia was an independent predictor of mortality rates during the hospital stay. The cumulative incidence rates of in-hospital mortality for hyponatremia and normal sodium level were 16.8% and 10.1%, respectively. Conclusions Hyponatremia is prevalent in ischemic stroke and is independently associated with in-hospital mortality and worse NIHSS scores at admission and discharge.

Hypercoagulability on Thromboelastography Can Predict the Functional Outcomes in Patients with Acute Ischemic Stroke.

We investigated the association between the reaction time (R), a thromboelastography (TEG) parameter for hypercoagulability, and functional outcomes based on the occurrence of hemorrhagic transformation (HT) and early neurological deterioration (END). We enrolled ischemic stroke patients and performed TEG immediately after the patients' arrival. The baseline characteristics, occurrence of HT and END, stroke severity, and etiology were compared according to the R. END was defined as an increase of ≥1 point in motor or ≥2 points in the total National Institute of Health Stroke Scale within 3 days after admission. The outcome was the achievement of functional independence (modified Rankin scale [mRS]: 0-2) at 3 months after stroke. Logistic regression analyses were performed to verify the association between R and outcome. HT and END were frequently observed in patients with an R of <5 minutes compared with the group with an R of ≥5 minutes (15 [8.1%] vs. 56 [21.0%], p < 0.001; 16 [8.6%] vs. 65 [24.3%], p = 0.001, respectively). In multivariable analysis, an R of <5 minutes was associated with decreased odds of achieving functional independence (0.58 [0.34-0.97], p = 0.038). This association was maintained when the outcome was changed to disability free (mRS 0-1) and when mRS was analyzed as an ordinal variable. Hypercoagulability on TEG (R <5 minutes) may be a negative predictor for functional outcome of stroke after 3 months, with more frequent HT, END, and different stroke etiologies. This study highlights the potential of TEG parameters as biomarkers for predicting functional outcomes in ischemic stroke patients.

The Role of Circular RNAs in Ischemic Stroke.

Ischemic stroke (IS), a devastating condition characterized by intracranial artery stenosis and middle cerebral artery occlusion leading to insufficient oxygen supply to the brain, is a major cause of death and physical disability worldwide. Recent research has demonstrated the critical role of circular RNAs (circRNAs), a class of covalently enclosed noncoding RNAs that are widespread in eukaryotic cells, in regulating various physiological and pathophysiological cellular processes, including cell apoptosis, autophagy, synaptic plasticity, and neuroinflammation. In the past few years, circRNAs have attracted extensive attention in the field of IS research. This review summarizes the current understanding of the mechanisms underlying the involvement of circRNAs in IS development. A better understanding of circRNA-mediated pathogenic mechanisms in IS may pave the way for translating circRNA research into clinical practice, ultimately improving the clinical outcomes of IS patients.

Characteristics of the platelet profile as a predictor of 30-day clinical outcome in ischemic stroke patients

Objective. Investigate the relationship between platelet profiles, in this case PDW and MPV at hospital admission, which can be predictors of clinical outcome 30 days after ischemic stroke. Methods. This research is an analytic study with a retrospective cohort method. Secondary data in the form of medical records at the neuro polyclinic of Bethesda Hospital Yogyakarta in 2019 - 2020. The number of subjects was 74, grouped as good outcome (mRS 0-2) and poor outcome (mRS 3-6). Data analysis used was t-test, Pearson’s test, Fisher’s test, ROC, and multivariable logistic regression model. Results. In this study, both PDW (p = 0.982) and MPV (p = 0.174) were not significantly associated (p &gt; 0.05) with poor outcomes on the chi-square test. ROC curve analysis showed that the PDW cutoff value was &gt;11.1 fl [(Area Under Curve (AUC) ROC was 0.638, with 95% CI = 0.518-0.746, and p-value 0.835)] and the MPV cutoff value was ≤9,8 fl [(Area Under Curve (AUC) ROC was 0.521, with 95% CI = 0.402-0.639, and p-value 0.137)] which was also not statistically significant (p &gt; 0.05). From these results, multivariable logistic regression analysis was performed which found that MPV ≤9,8 fl was associated with a small 30-day clinical outcome [(Odds Ratio (OR) = 0.110, 95% CI = 0.013-0.953, p = 0.007)]. While PDW &gt;11.1 fl did not have a significant relationship after regression analysis was carried out where p &gt; 0.05 was obtained. Conclusion. Increased PDW and MPV values at hospital admission did not increase the risk of 30-day disability in ischemic stroke patients.

Circulating lipocalin-2 as a novel biomarker for early neurological deterioration and unfavorable prognosis after acute ischemic stroke.

Lipocalin-2 (LCN2) is an acute-phase protein that could mediate neuroinflammation after brain injury. We aimed to evaluate if LCN2 level was associated with early neurological deterioration (END) in acute ischemic stroke patients, thus hindering clinical recovery. We conducted a prospective study of acute ischemic stroke patients between June 2021 and February 2022. Serum LCN2 concentration was measured after admission using an enzyme-linked immunosorbent assay. Outcomes included END and 90-day poor functional outcome (modified Rankin Scale 3-6). The National Institutes of Health Stroke Scale increment ≥4 points within 72h after admission was defined as END. A total of 253 acute ischemic stroke patients (mean age, 65.2±13.4 years; 64.0% male) were recruited. In the multivariate adjustment, increased serum LCN2 levels (per 1-SD increase of LCN2) were associated with a higher risk of END (odds ratio [OR], 1.64; 95% confidence interval [CI], 1.20-2.25; p=.002) and 90-day poor outcome (OR, 1.73; 95% CI, 1.22-2.45; p=.002). Restricted cubic splines found a linear relationship between LCN2 level and 90-day unfavorable outcome (END, p=.001 for linearity; 90-day poor outcome, p=.013 for linearity). Subgroup analysis further confirmed the significant association of LCN2 with clinical outcomes. This study demonstrated that higher circulating LCN2 level was associated with an increased risk of early clinical worsening and 90-day unfavorable outcomes in ischemic stroke patients.

Plasma growth differentiation factor − 8 / Myostatin level as prognostic biomarker of patients with ischemic stroke and acute revascularization therapy. PARADISE study

BackgroundIdentifying biological markers of ischemic stroke (IS) is an important research approach to develop innovative therapeutic strategies. This study aimed to assess the association between plasma Growth Differentiation Factor-8 (GDF-8)/Myostatin levels and outcome of IS patients. MethodsConsecutive patients with acute IS treated with either intravenous thrombolysis and/or mechanical thrombectomy at Dijon University Hospital, France were prospectively included. Clinical variables were recorded, and plasma GDF-8 was collected just after the revascularization procedure. Primary endpoint was functional outcome at 3 months assessed by the modified Rankin Scale (mRS) score. Secondary endpoints included mRS scores at 6 and 12 months, and overall mortality over 1-year of follow-up. ResultsAmong the 173 included patients (median age: 76 years, Interquartile range (IQR): 66–85; 49% women), median plasma GDF-8 levels at admission were significantly lower in those with a poor outcome at 3 months defined as a mRS score > 2 (2073 (IQR: 1564-2757) pg/mL versus 1471 (1192-2241) pg/mL, p < 0.001). Lower GDF-8 levels at admission were associated with higher 3-months mRS score in multivariable ordinal logistic regression analysis (OR = 0.9995; 95% CI: 0.9991–0.9999, p = 0.011). The association was also observed with 6- and 12-month mRS scores. Although mortality was higher in patients with lower GDF-8 levels, the association was not significant in multivariable Cox analysis. ConclusionLower plasma GDF-8 levels were associated with a poorer functional outcome in IS patients treated with acute revascularization therapy. Underlying pathophysiological mechanisms involving GDF-8 in post-stroke outcome remain to be elucidated.

Hypertension as Risk Factor of Poor Functional Outcome in Primary Ischemic Stroke Patients

Survival rate of ischemic stroke has been improving which increases long-term disability in consequences. GBD 2017 shows stroke as the third most common cause of morbidity. Hypertension is the most common risk factor for ischemic stroke incidence and affecting long-term functional outcome. Therefore, hypertension control in ischemic stroke is expected to improve functional outcome and quality of life. Therefore, this study was conducted to know the role of hypertension as risk factor of poor functional outcome in primary ischemic stroke patients. Study was conducted by observational retrospective cohort from May 2018 until April 2019 in 7 hospitals in D.I. Yogyakarta. Functional outcome of primary ischemic stroke patients was assessed by physician at day 30 by using Barthel Index. Bivariate analysis was analyzed by using Chi-Square with 95% CI and p-value &lt;0.05 indicated statistical significance. Based on the study, there were increased risk for having dependent functional outcome in hypertension (RR=1.12, 95% CI=0.74-1.69), diabetes mellitus (RR=1.041, 95% CI=0.71-1.53) but these results were not statistically significant (p&gt;0.05). From the study it can be concluded that hypertension is one of the most common risk factors of stroke but hypertension has no role in predicting functional outcome. However, hypertension increases risk for having poor functional outcome in ischemic stroke patients.