Measure Of Stroke Severity Research Articles

Evaluating the concordance between International Classification of Diseases, Tenth Revision Code and stroke severity as measured by the National Institutes of Health Stroke Scale

BackgroundThe National Institutes of Health Stroke Scale (NIHSS) scores have been used to evaluate acute ischaemic stroke (AIS) severity in clinical settings. Through the International Classification of Diseases, Tenth Revision...

Validation of the Passive Surveillance Stroke Severity score in three Canadian provinces

ObjectiveAdjusting for stroke severity is critical in stroke outcomes research. The Passive Surveillance Stroke SeVerity (PaSSV) score is an administrative data-based measure of stroke severity, initially derived in Ontario, Canada using data between 2002-2013. We assessed its geographical and temporal external validity in British Columbia (BC), Nova Scotia (NS), and Ontario, Canada. MethodsIn each province, we identified adult in-patients with ischemic stroke or intracerebral hemorrhage and admitted from an emergency department between 2014-2019 and calculated their PaSSV score using linked administrative data. We used Cox proportional hazards models to evaluate the association between the PaSSV score and the hazard of death over 30 days and the cause-specific hazard of admission to long-term care over 365 days. We assessed the models’ discriminative values using Uno’s c-statistic, comparing models with versus without PaSSV. ResultsWe included 86,142 patients (n=18,387 in BC, n=65,082 in Ontario, n=2,673 in NS). The mean and median PaSSV were similar across provinces. Higher PaSSV score, reflecting lower stroke severity, was associated with a lower mortality (hazard ratio and 95% confidence intervals 0.70 [0.68-0.71] in BC, 0.69 [0.68-0.69] in Ontario, 0.72 [0.68-0.75] in NS) and long-term care admission (0.77 [0.76-0.79] in BC, 0.84 [0.83-0.85] in Ontario, 0.86 [0.79-0.93] in NS). Including PaSSV in the multivariable models improved model fit according to the c-statistics. ConclusionWe showed that PaSSV has geographical and temporal validity. It is a useful tool for risk-adjustment in multi-jurisdiction stroke outcomes research, and a valuable addition to be included in the national algorithm inventory.

Evaluating Serum Copeptin as a Promising Biomarker for Predicting Acute Ischaemic Stroke Severity: A Hospital-Based Study on Strokes.

Stroke is the second cause of mortality and the foremost leading cause of disability globally. Many potential biomarkers have been described to contribute to prognosticating the severity in the acute phase of stroke as well as help with risk stratification. Copeptin, an inactive peptide that is produced in an equimolar ratio to arginine vasopressin and adequately mirrors an individual's stress response to acute illnesses like acute ischaemic stroke as evidenced by elevated or increasing levels is being explored in this study to determine its relationship with acute stroke severity and infarct size on admission. This is a cross-sectional study of 80 neuroimaging-confirmed acute ischaemic patients who presented within seven days of symptom onset and 80 control subjects. The ischaemic stroke cases had stroke severity and infarct volume determined on admission by the National Institute of Health Stroke Scale (NIHSS) and neuroimaging (brain CT/MRI). A baseline serum copeptin level was measured in the study subjects. Spearman correlation and Kruskal Wallis test were used to determine the relationship between serum copeptin level with admission NIHSS and infarct size respectively. The receiver operating characteristic (ROC) curve was calculated to determine the sensitivity and specificity of copeptin to predict severity and outcome. The mean age of the study group was 61.3 ± 12.7 years with 55.0% males and 45.0% females. The serum level of copeptin was significantly higher in the stroke cases with a median of 28.6 pmol/L (interquartile range (IQR)- 15.4-31.6 pmol/L) versus 8.8 pmol/L (IQR- 3.2- 10.7 pmol/L) among the stroke-free controls (p= 0.001) at a statistically significant level. There was a weak correlation between copeptin and NIHSS calculated at admission to measure stroke severity (r- 0.02, p= 0.873). Patients with infarct sizes in the fourth quartile (infarct sizes greater than 18.78 cm3) had higher copeptin levels, though this was not statistically significant (H= 2.88; p= 0.410). Admission serum copeptin did not show a statistically significant prognostic value in predicting stroke severity and mortality in stroke patients who presented within seven days of symptomonset with an area under curve (AUC) of 0.51 (95% CI: 0.36-0.65; p= 0.982). In this study, copeptin was higher among the stroke cases compared with the stroke-free controls which suggests a significant prognostic value in risk stratification in the acute phase of stroke; however, this did not significantly correlate with stroke severity and thus warrants further study in this field to elucidate it's fascinating potential as a prognostic biomarker (especially in the acute period) as this may enable allocation of a better-focused therapy for stroke patients.

The feasibility, repeatability, validity and responsiveness of the EQ-5D-3L in Krio for patients with stroke in Sierra Leone

ObjectivesTo assess the feasibility, repeatability, validity and responsiveness of the EQ-5D-3L in Krio for patients with stroke in Sierra Leone, the first psychometric assessment of the EQ-5D-3L to be conducted in patients with stroke in Sub Saharan Africa.MethodsA prospective stroke register at two tertiary government hospitals recruited all patients with the WHO definition of stroke and followed patients up at seven days, 90 days and one year post stroke. The newly translated EQ-5D-3L, Barthel Index (BI), modified Rankin Scale (mRS) and National Institute of Health Stroke Scale (NIHSS), a measure of stroke severity, were collected by trained researchers, face to face during admission and via phone at follow up. Feasibility was assessed by completion rate and proportion of floor/ceiling effects. Internal consistency was assessed by inter item correlations (IIC) and Cronbach’s alpha. Repeatability of the EQ-5D-3L was examined using test–retest, EQ-5D-3L utility scores at 90 days were compared to EQ-5D-3L utility scores at one year in the same individuals, whose Barthel Index had remained within the minimally clinical important difference. Known group validity was assessed by stroke severity. Convergent validity was assessed against the BI, using Spearman’s rho. Responsiveness was assessed in patients whose BI improved or deteriorated from seven to 90 days. Sensitivity analyses were conducted using the UK and Zimbabwe value sets, to evaluate the effect of value set, in a subgroup of patients with no formal education to evaluate the influence of patient educational attainment, and using the mRS instead of the BI to evaluate the influence of utilising an alternative functional scale.ResultsThe EQ-5D-3L was completed in 373/460 (81.1%), 360/367 (98.1%) and 299/308 (97.1%) eligible patients at seven days, 90 days and one year post stroke. Missing item data was low overall, but was highest in the anxiety/depression dimension 1.3% (5/373). Alpha was 0.81, 0.88 and 0.86 at seven days, 90 days and one year post stroke and IIC were within pre-specified ranges. Repeatability of the EQ-5D-3L was moderate to poor, weighted Kappa 0.23–0.49. EQ-5D-3L utility was significantly associated with stroke severity at all timepoints. Convergent validity with BI was strong overall and for shared subscales. EQ-5D-3L was moderately responsive to both improvement Cohen’s D 0.55 (95% CI:0.15—0.94) and deterioration 0.92 (95% CI:0.29—1.55). Completion rates were similar in patients with no formal education 148/185 (80.0%) vs those with any formal education 225/275 (81.8%), and known group validity for stroke severity in patients with no formal education was strong. Using the Zimbabwe value set instead of the UK value set, and using the mRS instead of the BI did not change the direction or significance of results.ConclusionsThe EQ-5D-3L for stroke in Sierra Leone was feasible, and responsive including in patients with no formal education. However, repeatability was moderate to poor, which may be due to the study design, but should add a degree of caution in the analysis of repeated measures of EQ-5D-3L over time in this population. Known group validity and convergent validity with BI and mRS were strong. Further research should assess the EQ-5D in the general population, examine test–retest reliability over a shorter time period and assess the acceptability and validity of the anxiety/depression dimension against other validated mental health instruments. Development of an EQ-5D value set for West Africa should be a research priority.

A Systematic Review and Meta-Analysis on the Identification of Predictors Associated With Insomnia or Sleep Disturbance in Post-stroke Patients.

The aim of this study was to identify the factors associated with sleep disturbances in individuals after a stroke.To systematically identify relevant studies, an extensive search strategy was devised. We conducted comprehensive searches in major electronic databases including PubMed, Embase, PsycINFO, and Cochrane Library.The search was limited to articles published in English between January 1, 2011, and February 10, 2024.Pooled effect estimates, such as odds ratio (OR) or mean difference (MD) along with their confidence interval (CIs), were calculated using random-effects models for categorical variables and continuous variables, respectively. A total of nine studies were included in this meta-analysis.The pooled prevalence of insomnia across the included studies was determined to be 40% (95% CI = 30%-49%), with individual study prevalence ranging from 22% to 72%. A pooled analysis showed that gender demonstrated a statistically significant association with sleep disturbance, with females exhibiting a higher likelihood (OR = 1.49, 95% CI = 1.16-1.91, p = 0.002) compared to males. The National Institutes of Health Stroke Scale (NIHSS) score, a measure of stroke severity, was associated with sleep disturbance (MD = 0.86, 95% CI = 0.56-1.17, p = 0.001), indicating that patients withsevere strokes may be more prone to sleep disturbances.These findings underscore the importance of comprehensive evaluation and targeted interventions to address sleep-related issues in stroke patients, particularly those with severe neurological impairment.

The relationship between hemoglobin-to-red cell distribution width (RDW) ratio (HRR) and mortality in stroke patients.

In recent years, many studies have shown that hemoglobin to red cell distribution width ratio (HRR), which is the ratio of hemoglobin (Hb) to red cell distribution width (RDW), is associated with inflammation. Inflammation is linked to both the development of stroke and the severe effects that follow. Therefore, the relationship between the HRR and mortality in patients with stroke was investigated in our study. 127 stroke patients who visited the emergency department between March 1, 2023, and June 1, 2023, were retrospectively evaluated. The National Institutes of Health Stroke Scale (NIHSS) was used to measure stroke severity. All stroke patients were divided into four groups: patients with atrial fibrillation (AF), those without AF, and those with low and high HRR. HRR levels were compared between patients with and without AF. The relationship between HRR and mortality was also analyzed. HRR levels were found to be significantly lower in patients with AF compared to those without AF (p<0.05 for all). NIHSS, requirement for mechanical ventilation, and mortality rate were significantly higher in the low HRR (HRR≤0.795) group compared to the high HRR group (HRR>0.795) (p<0.05 for all). HRR outperformed Hb and RDW alone in predicting mortality (AUC; 0.975, 0.952, 0.911, respectively). Additionally, a significant positive correlation was found between HRR levels and NIHSS (p<0.001). Low HRR measured on admission is a useful marker for predicting mortality and determining the severity of stroke.

Association Between Stroke Severity and Serum Troponin in Acute Stroke.

Serum troponin is often elevated in patients with acute stroke and its mechanism is unknown. In a retrospective single-center cohort study, we evaluated the association between stroke severity and serum troponin in 187 patients with acute stroke using multivariable modified Poisson models. A one-point increase in the National Institutes of Health Stroke Scale (measure of stroke severity) was associated with a marginally higher serum troponin level in adjusted models (aIRR 1.03; 1.01-1.05, P = 0.001). The modest, yet potentially independent, association between stroke severity and serum troponins could suggest a neurogenic basis for a cardiac injury in patients with acute stroke.

Change in Hospital Risk-standardized Stroke Mortality Performance With and Without the Passive Surveillance Stroke Severity Score

Background: Adjustment for baseline stroke severity is necessary for accurate assessment of hospital performance. We evaluated whether adjusting for the Passive Surveillance Stroke SeVerity (PaSSV) score, a measure of stroke severity derived using administrative data, changed hospital-specific estimated 30-day risk-standardized mortality rate (RSMR) after stroke. Methods: We used linked administrative data to identify adults who were hospitalized with ischemic stroke or intracerebral hemorrhage across 157 hospitals in Ontario, Canada between 2014 and 2019. We fitted a random effects logistic regression model using Markov Chain Monte Carlo methods to estimate hospital-specific 30-day RSMR and 95% credible intervals with adjustment for age, sex, Charlson comorbidity index, and stroke type. In a separate model, we additionally adjusted for stroke severity using PaSSV. Hospitals were defined as low-performing, average-performing, or high-performing depending on whether the RSMR and 95% credible interval were above, overlapping, or below the cohort’s crude mortality rate. Results: We identified 65,082 patients [48.0% were female, the median age (25th,75th percentiles) was 76 years (65,84), and 86.4% had an ischemic stroke]. The crude 30-day all-cause mortality rate was 14.1%. The inclusion of PaSSV in the model reclassified 18.5% (n=29) of the hospitals. Of the 143 hospitals initially classified as average-performing, after adjustment for PaSSV, 20 were reclassified as high-performing and 8 were reclassified as low-performing. Of the 4 hospitals initially classified as low-performing, 1 was reclassified as high-performing. All 10 hospitals initially classified as high-performing remained unchanged. Conclusion: PaSSV may be useful for risk-adjusting mortality when comparing hospital performance. External validation of our findings in other jurisdictions is needed.

Acute stress symptoms 1-2 weeks after stroke predict the subsequent development of post-traumatic stress symptoms: A prospective cohort study.

To date no research has examined the potential influence of acute stress symptoms (ASD) on subsequent development of post-traumatic stress disorder (PTSD) symptoms in stroke survivors. Our objective was to examine whether acute stress symptoms measured 1-2 weeks post-stroke predicted the presence of post-traumatic stress symptoms measured 6-12 weeks later. Prospective within-groups study. Fifty four participants who completed a measure of acute stress disorder at 1-2 weeks following stroke (time 1) and 31 of these participants completed a measure of posttraumatic stress disorder 6-12 weeks later (time 2). Participants also completed measures of stroke severity, functional impairment, cognitive impairment, depression, anxiety, pre-morbid intelligence and pain across both time points. Some 22% met the criteria for ASD at baseline and of those, 62.5% went on to meet the criteria for PTSD at follow-up. Meanwhile two of the seven participants (28.6%) who met the criteria for PTSD at Time 2, did not meet the ASD criteria at Time 1 (so that PTSD developed subsequently). A hierarchical multiple regression analysis indicated that the presence of acute stress symptoms at baseline was predictive of post-traumatic stress symptoms at follow-up (R2 = .26, p < .01). Less severe stroke was correlated with higher levels of post-traumatic stress symptoms at Time 2 (rho = .42, p < .01). The results highlight the importance of early assessment and identification of acute stress symptoms in stroke survivors as a risk factor for subsequent PTSD. Both ASD and PTSD were prevalent and the presence of both disorders should be assessed.

326 Pre-morbid sleep disturbance and its association with stroke severity: results from the international INTERSTROKE study

Abstract Background We have previously shown that disturbances in sleep to be associated with acute stroke, but their association with stroke severity is less certain. In the INTERSTROKE study, we evaluated the association of pre-morbid sleep disturbance with stroke severity and functional outcome in acute stroke patients. Methods INTERSTROKE was an international case–control study of first acute stroke. This analysis comprised cases who completed a standardised questionnaire concerning nine symptoms of sleep disturbance (sleep onset latency, duration and quality, nocturnal awakening, napping, snoring, snorting and breathing cessation) in the prior month (n = 2,361). Two indices were derived representing sleep disturbance (range 0–9) and Obstructive Sleep Apnoea (OSA; range 0–3) symptoms. The modified-Rankin score (m-RS) was used to measure stroke severity at initial assessment and functional outcome at 1-month follow-up. Severe stroke was defined as an m-RS of &amp;gt;3, and functional deterioration was defined as an increase in m-RS at 1-month. Logistic regression was used to estimate the magnitude of association between symptoms and stroke severity. Results The mean age of participants was 62.9 years, with 42% female, 80% diagnosed with ischaemic stroke and 17% reporting &amp;gt;5 sleep symptoms. On multivariable analysis, there was a graded association between increasing number of sleep disturbance symptoms and initially severe stroke (2–3: Odds Ratio [OR]:1.44; 95% CI [Confidence Interval]:1.07–1.94, 4–5: OR:1.66; CI:1.23–2.25, &amp;gt;5: OR:2.58; CI:1.83–3.66). Having &amp;gt;5 sleep disturbance symptoms was associated with a significant increased odds of functional deterioration at 1-month (OR:1.54; CI:1.01–2.34). A higher OSA score (2–3 vs 0–1) was also associated with a significant increased odds of initially severe stroke (OR:1.48; CI:1.20–1.83) but not functional deterioration at 1-month (OR:1.19; CI:0.93–1.52). Conclusion Symptoms of sleep disturbance were common and associated with an increased odds of severe stroke and functional deterioration at 1-month. Interventions to modify sleep disturbance may help prevent disabling stroke/improve functional outcome after stroke, and should be the subject of future research.

Novel inflammatory biomarkers associated with stroke severity: results from a cross-sectional stroke cohort study

BackgroundStroke is a leading cause of mortality and disability worldwide and its occurrence is expected to increase in the future. Blood biomarkers have proven their usefulness in identification and monitoring of the disease. Stroke severity is a major factor for estimation of prognosis and risk of recurrent events, but knowledge on respective blood biomarkers is still scarce. Stroke pathophysiology comprises a multitude of ischemia-induced inflammatory and immune mediated responses. Therefore, the assessment of an immune-related panel in correlation with stroke severity seems promising.MethodsIn the present cross-sectional evaluation, a set of 92 blood biomarkers of a standardized immune panel were gathered (median 4.6 days after admission) and related to stroke severity measures, assessed at hospital admission of acute stroke patients. Multivariable logistic regression models were used to determine associations between biomarkers and modified Rankin Scale (mRS), linear regression models were used for associations with National Institute of Health Stroke Scale.Results415 patients (mean age 69 years; 41% female) were included for biomarker analysis. C-type lectin domain family 4 member G (CLEC4G; OR = 2.89, 95% CI [1.49; 5.59], padj = 0.026, Cytoskeleton-associated protein 4 (CKAP4; OR = 2.38, 95% CI [1.43; 3.98], padj = 0.019), and Interleukin-6 (IL-6) (IL6; OR = 1.97, 95% CI [1.49; 2.62], padj < 0.001) were positively associated with stroke severity measured by mRS, while Lymphocyte antigen 75 (LY75; OR = 0.37, 95% CI [0.19; 0.73], padj = 0.049) and Integrin alpha-11 (ITGA11 OR = 0.24, 95% CI [0.14, 0.40] padj < 0.001) were inversely associated. When investigating the relationships with the NIHSS, IL-6 (β = 0.23, 95% CI [0.12, 0.33] padj = 0.001) and ITGA11 (β = − 0.60, 95% CI [− 0.83, − 0.37] padj < 0.001) were significantly associated.ConclusionsHigher relative concentrations of plasma CLEC4G, CKAP4, and IL-6 were associated with higher stroke severity, whereas LY75 and ITGA11 showed an inverse association. Future research might show a possible use as therapeutic targets and application in individual risk assessments.

Variation in Carotid Artery Stenosis Measurements Among Facilities Seeking Carotid Stenting Facility Accreditation.

Based on the inclusion criteria of clinical trials, the degree of cervical carotid artery stenosis is often used as an indication for stent placement in the setting of extracranial carotid atherosclerotic disease. However, the rigor and consistency with which stenosis is measured outside of clinical trials are unclear. In an agreement study using a cross-sectional sample, we compared the percent stenosis as measured by real-world physician operators to that measured by independent expert reviewers. As part of the carotid stenting facility accreditation review, images were obtained from 68 cases of patients who underwent carotid stent placement. Data collected included demographics, stroke severity measures, and the documented degree of stenosis, termed operator-reported stenosis (ORS), by 34 operators from 14 clinical sites. The ORS was compared with reviewer-measured stenosis (RMS) as assessed by 5 clinicians experienced in treating carotid artery disease. The median ORS was 90.0% (interquartile range, 80.0%-90.0%) versus a median RMS of 61.1% (interquartile range, 49.8%-73.6%), with a median difference of 21.8% (interquartile range, 13.7%-34.4%), P<0.001. The median difference in ORS and RMS for asymptomatic versus symptomatic patients was not statistically different (24.6% versus 19.6%; P=0.406). The median difference between ORS and RMS for facilities granted initial accreditation was smaller compared with facilities whose accreditation was delayed (17.9% versus 25.5%, P=0.035). The intraclass correlation between ORS and RMS was 0.16, indicating poor agreement. If RMS measurements were used, 72% of symptomatic patients and 10% of asymptomatic patients in the population examined would meet the Centers for Medicare and Medicaid Services criteria for stent placement. Real-world operators tend to overestimate carotid artery stenosis compared with external expert reviewers. Measurements from facilities granted initial accreditation were closer to expert measurements than those from facilities whose accreditation was delayed. Since decisions regarding carotid revascularization are often based on percent stenosis, such measuring discrepancies likely lead to increased procedural utilization.

Identifying optimal cut points of National Institutes of Health Stroke Scale to Predict Mortality: A Population-based Assessment (P11-5.016)

Identifying optimal cut points of National Institutes of Health Stroke Scale to Predict Mortality: A Population-based Assessment (P11-5.016)

Abstract WP184: Identifying Optimal Cut Points Of National Institutes Of Health Stroke Scale To Predict Mortality: A Population-based Assessment

Background: Ischemic stroke is the 5 th leading cause of death in the US. As a measure of stroke severity, initial NIHSS has been used to predict clinical outcome. We sought to identify the optimal cut-points of NIHSS at initial presentation that are associated with higher 30-day mortality. Methods: In 2005, 2010, and 2015 all hospitalized, first acute ischemic stroke events occurring within the Greater Cincinnati area were ascertained. Potential ischemic stroke cases underwent chart abstraction and physician adjudication, including retrospective NIHSS score (range 0 - 42) based on clinical findings at initial presentation. Descriptive statistics for NIHSS were estimated by study year, demographics, and medical history. Data regarding mortality was obtained from the National Death Index. The Contal and O’Quigley method based on a modified log-rank test statistic was used to determine cut-points of the NIHSS score associated with 30-day mortality, and hazard ratios were obtained from Cox models with adjustment for sex, race, and age. Results: In 2005, 2010, and 2015 there were 1704, 1818 and 1852 ischemic stroke events with 30-day mortality rates of 10.5%, 9.6% and 9.0%, respectively. Optimal cut-points of NIHSS &lt;9, 9-16 and &gt;16 were identified. Across all 3 periods, 3431 (84.5%) cases had NIHSS 0-8, 352 (8.7%) had NIHSS 9-16 and 274 (6.8%) &gt;16. Kaplan Meier Survival Curves for the 3 NIHSS groups are shown in the Figure. Strokes with NIHSS &gt;16 at initial presentation were associated with a 15-fold (HR with 95% CI: 13, 19) increase in the risk of death at 30-days compared to those with NIHSS &lt;9. Discussion: NIH Stroke Scale scores are a reliable predictor of mortality, with higher NIHSS scores having higher risk of death. The cut points reported identify subgroups of stroke patients with dramatically different prognoses. Future studies should assess if this excess mortality risk among severe strokes persists after the more widespread implementation of thrombectomy beyond 2015.

Stroke Severity and Level of Dependence Against Risk of Falls in Stroke Patients

A stroke is a neurological disease caused by the blockage or rupture of blood vessels in the brain. Functional dysfunction due to stroke causes stroke patients to be very susceptible to falls. This research aimed to identify the association between the severity of stroke with the level of patient dependence on the risk of falls. This research was a quantitative observational design with a cross-sectional approach. The sample of this study was 66 hospitalized stroke patients who were recruited by quota sampling method. The National Institute of Health Stroke Scale (NIHSS) and Barthel Index are used to measure stroke severity and level of dependence. We assessed the risk of falls using the operational procedure from the hospital. Based on the Spearman rho test, it is found that there is a significant relationship between stroke severity and the level of risk of falls (p=0.000394). Similarly, a significant correlation was found between the level of patient dependence and the level of risk of falls (0.000016). Nurses need to set the nursing care plan for stroke patients who are at risk of falls to prevent further injuries and complications. Continuity of care and family support will help the patient's dependency, reduce the risk of falls, and promote quality of life.

Automated quantification of atrophy and acute ischemic volume for outcome prediction in endovascular thrombectomy.

Short- and long-term outcomes from endovascular thrombectomy (EVT) for large vessel occlusion stroke remain variable. Numerous relevant predictors have been identified, including severity of neurological deficits, age, and imaging features. The latter is typically defined as acute changes (most commonly Alberta Stroke Programme Early CT Score, ASPECTS, at presentation), but there is little information on the impact of imaging assessment of premorbid brain health as a determinant of outcome. To examine the impact of automated measures of stroke severity and underlying brain frailty on short- and long-term outcomes in acute stroke treated with EVT. In 215 patients with anterior circulation stroke, who subsequently underwent EVT, automated analysis of presenting non-contrast CT scans was used to determine acute ischemic volume (AIV) and e-ASPECTS as markers of stroke severity, and cerebral atrophy as a marker of brain frailty. Univariate and multivariate logistic regression were used to identify significant predictors of NIHSS improvement, modified Rankin scale (mRS) at 90 and 30 days, mortality at 90 days and symptomatic intracranial hemorrhage (sICH) following successful EVT. For long-term outcome, atrophy and presenting NIHSS were significant predictors of mRS 0-2 and death at 90 days, whereas age did not reach significance in multivariate analysis. Conversely, for short-term NIHSS improvement, AIV and age were significant predictors, unlike presenting NIHSS. The interaction between age and NIHSS was similar to the interaction of AIV and atrophy for mRS 0-2 at 90 days. Combinations of automated software-based imaging analysis and clinical data can be useful for predicting short-term neurological outcome and may improve long-term prognostication in EVT. These results provide a basis for future development of predictive tools built into decision-aiding software in stroke.

Methods for stroke severity assessment by chart review in the Atherosclerosis Risk in Communities study

Stroke severity is the most important predictor of post-stroke outcome. Most longitudinal cohort studies do not include direct and validated measures of stroke severity, yet these indicators may provide valuable information about post-stroke outcomes, as well as risk factor associations. In the Atherosclerosis Risk in Communities (ARIC) study, stroke severity data were retrospectively collected, and this paper outlines the procedures used and shares them as a model for assessment of stroke severity in other large epidemiologic studies. Trained physician abstractors, who were blinded to other clinical events, reviewed hospital charts of all definite/probable stroke events occurring in ARIC. In this analysis we included 1,198 ischemic stroke events occurring from ARIC baseline (1987–1989) through December 31, 2009. Stroke severity was categorized according to the National Institutes of Health Stroke Scale (NIHSS) score and classified into 5 levels: NIHSS ≤ 5 (minor), NIHSS 6–10 (mild), NIHSS 11–15 (moderate), NIHSS 16–20 (severe), and NIHSS > 20 (very severe). We assessed interrater reliability in a subgroup of 180 stroke events, reviewed independently by the lead abstraction physician and one of the four secondary physician abstractors. Interrater correlation coefficients for continuous NIHSS score as well as percentage of absolute agreement and Cohen Kappa Statistic for NIHSS categories were presented. Determination of stroke severity by the NIHSS, based on data abstracted from hospital charts, was possible for 97% of all ischemic stroke events. Median (25%-75%) NIHSS score was 5 (2–8). The distribution of NIHSS category was NIHSS ≤ 5 = 58.3%, NIHSS 6–10 = 24.5%, NIHSS 11–15 = 8.9%, NIHSS 16–20 = 4.7%, NIHSS > 20 = 3.6%. Overall agreement in the classification of severity by NIHSS category was present in 145/180 events (80.56%). Cohen’s simple Kappa statistic (95% CI) was 0.64 (0.55–0.74) and weighted Kappa was 0.79 (0.72–0.86). Mean (SD) NIHSS score was 5.84 (5.88), with a median score of 4 and range 0–31 for the lead reviewer (rater 1) and mean (SD) 6.16 (6.10), median 4.5 and range 0–36 in the second independent assessment (rater 2). There was a very high correlation between the scores reported in both assessments (Pearson r = 0.90). Based on our findings, we conclude that hospital chart-based retrospective assessment of stroke severity using the NIHSS is feasible and reliable.

Diabetes: Chronic Metformin Treatment and Outcome Following Acute Stroke.

AimTo evaluate if in patients with known diabetes, pretreatment metformin will lead to less severe stroke, better outcome, and lower mortality following acute stroke.MethodsThe Qatar stroke database was interrogated for stroke severity and outcome in patients with ischemic stroke. Outcome was compared in nondiabetic vs. diabetic patients and in diabetic patients on metformin vs. other hypoglycemic agents. The National Institute of Health Stroke Scale was used to measure stroke severity and 90-day modified Rankin scale (mRS) score to determine outcome following acute stroke.ResultsIn total, 4,897 acute stroke patients [nondiabetic: 2,740 (56%) and diabetic: 2,157 (44%)] were evaluated. There were no significant differences in age, risk factors, stroke severity and type, or thrombolysis between the two groups. At 90 days, mRS (shift analysis) showed significantly poor outcome in diabetic patients (p < 0.001) but no differences in mortality. In the diabetic group, 1,132 patients were on metformin and 1,025 on other hypoglycemic agents. mRS shift analysis showed a significantly better outcome in metformin-treated patients (p < 0.001) and lower mortality (8.1 vs. 4.6% p < 0.001). Multivariate negative binomial analyses showed that the presence of diabetes negatively affected the outcome (90-day mRS) by factor 0.17 (incidence risk ratio, IRR, 1.17; CI [1.08–1.26]; p < 0.001) when all independent variables were held constant. In diabetic patients, pre-stroke treatment with metformin improved the outcome (90-day mRS) by factor 0.14 (IRR 0.86 [CI 0.75–0.97] p = 0.006).ConclusionSimilar to previous reports, our study shows that diabetes adversely affects stroke outcome. The use of prior metformin is associated with better outcome in patients with ischemic stroke and results in lower mortality. The positive effects of metformin require further research to better understand its mechanism.

Demographic, clinical and neuroimaging markers of post-stroke emotionalism: A preliminary investigation

IntroductionPost stroke emotionalism (PSE) is a common but poorly understood condition. The value of altered brain structure as a putative risk factor for PSE alongside routinely available demographic and clinical variables has yet to be elucidated. Methods85 patients were recruited from acute inpatient settings within 2 weeks of stroke. PSE was diagnosed using a validated semi-structured interview and standardised measures of stroke severity, functional ability, cognition, mood and quality of life were obtained. Neuroimaging variables (intracranial volume and volumes of cortical grey matter, subcortical grey matter, normal appearing white matter, cerebrum, cerebrospinal fluid and stroke; white matter hyperintensities; and mean cortical thickness) were derived using standardised methods from Magnetic Resonance Imaging (MRI) studies. The relationships between PSE diagnosis, brain structure, demographic and clinical variables were investigated using machine learning algorithms to determine how well different sets of predictors could classify PSE. ResultsThe model with the best performance was derived from neuroradiological variables alone (sensitivity = 0.75; specificity = 0.8235), successfully classifying 9/12 individuals with PSE and 28/34 non-PSE cases. ConclusionsNeuroimaging measures appear to be important in PSE. Future work is needed to determine which specific variables are key. Imaging may complement standard behavioural measures and aid clinicians and researchers.

Quantitative EEG Correlates with NIHSS and MoCA for Assessing the Initial Stroke Severity in Acute Ischemic Stroke Patients

BACKGROUND: National Institutes of Health Stroke Scale (NIHSS) and Montreal Cognitive Assessment (MoCA) measure stroke severity by assessing the functional and cognitive outcome, respectively. However, they cannot be used to measure subtle evolution in clinical symptoms during the early phase. Quantitative EEG (qEEG) can detect any subtle changes in CBF and brain metabolism thus may also benefit for assessing the severity. AIM: This study aims to identify the correlation between qEEG with NIHSS and MoCA for assessing the initial stroke severity in acute ischemic stroke patients. METHODS: This was a cross-sectional study. We recruited 30 patients with first-ever acute ischemic stroke hospitalized in Dr. Sardjito General Hospital, Yogyakarta, Indonesia. We measured the NIHSS, MoCA score, and qEEG parameter during the acute phase of stroke. Correlation and regression analysis was completed to investigate the relationship between qEEG parameter with NIHSS and MoCA. RESULTS: Four acute qEEG parameter demonstrated moderate-to-high correlations with NIHSS and MoCA. DTABR had positive correlation with NIHSS (r = 0.379, p = 0.04). Meanwhile, delta-absolute power, DTABR, and DAR were negatively correlated with MoCA score (r = −0.654, p = 0.01; r = −0.397, p = 0.03; and r = −0.371, p = 0.04, respectively). After adjusted with the confounding variables, delta-absolute power was independently associated with MoCA score, but not with NIHSS (B = −2.887, 95% CI (−4.304–−1.470), p &lt; 0.001). CONCLUSIONS: Several qEEG parameters had significant correlations with NIHSS and MoCA in acute ischemic stroke patients. The use of qEEG in acute clinical setting may provide a reliable and efficient prediction of initial stroke severity. Further cohort study with larger sample size and wide range of stroke severity is still needed.