A predictive risk model for outcomes of ischemic stroke

Early neurological deterioration in patients with minor stroke: A single-center study conducted in Vietnam

A minor ischemic stroke is associated with a higher likelihood of poor clinical outcomes at 90 days when there is early neurological deterioration (END). The objective of this case-control study conducted in a comprehensive stroke facility in Vietnam is to examine the frequency, forecast, and outcomes of patients with END in minor strokes. The study employs a descriptive observational design, longitudinally tracking patients with minor strokes admitted to Bach Mai Hospital's Stroke Center between December 1, 2023, and August 31, 2024. Hospitalized within 24 hours of symptom onset, minor stroke patients with National Institutes of Health Stroke Scale (NIHSS) scores ≤ 5 and items 1a, 1b, and 1c on the NIHSS scale, each equal to 0, were included in the study. The primary measure of interest is the END rate, defined as a rise of 2 or more points in the NIHSS score during the first 72 hours after admission. We conduct a logistic regression analysis to identify forecasting factors for END. Out of 839 patients, 88 (10.5%) had END. In the END group, we found that most patients had complications within the first 24 hours of stroke, accounting for 43.2%; the 24 - 48-hour window accounted for 35.2%, and the 48 - 72-hour window accounted for 21.6%. END was associated with a higher likelihood of poor outcomes (mRS 2 - 6) at discharge (OR = 22.76; 95% CI 11.22 - 46.20; p < 0.01), 30 days post-stroke(OR = 24.38; 95% CI 14.40 - 41.29; p < 0.01), and 90 days post-stroke (OR = 21.74; 95% CI 12.63 - 37.43; p < 0.01). Some of the prognostic factors for END were admission NIHSS score (OR = 1.24; 95% CI 1.03 - 1.49; p = 0.02), admission systolic blood pressure greater than 150mmHg (OR = 1.70; 95% CI 1.03 - 2.81; p = 0.04), admission blood glucose (OR = 1.07; 95% CI 1.01 - 1.14; p = 0.02), reperfusion therapy (OR = 3.35; 95% CI 1.50 - 7.49; p < 0.01), use of antiplatelet monotherapy (OR = 3.69; 95% CI 2.24 - 6.08; p < 0.01), internal capsule infarction (OR = 2.54; 95% CI 1.37 - 4.71; p < 0.01), hemorrhagic transformation (OR = 5.72; 95% CI 1.07 - 30.45; p = 0.04), corresponding extracranial carotid artery occlusion (OR = 4.84; 95% CI 1.26 - 18.65; p = 0.02), and middle cerebral artery occlusion OR = 3.06; 95% CI 1.29 - 7.30; p = 0.01). END in minor stroke patients accounts for 10.5% and is a risk factor for poor neurological outcomes. Admission NIHSS score, higher systolic blood pressure, admission blood glucose, reperfusion therapy, use of antiplatelet monotherapy, internal capsule infarction, hemorrhagic transformation, corresponding extracranial carotid artery occlusion, and middle cerebral artery occlusion were some of the prognostic factors for END in our observational study.

A pilot study comparing the rehabilitation functional outcomes of post-COVID-19 stroke and non-COVID stroke patients: An occupational therapy perspective

Background and purpose: Recent studies have highlighted the clinical characteristics and incidence of post-COVID-19 stroke conditions. Comparing the function and overall prognosis of stroke patients and post-COVID-19 stroke patients is an intriguing idea. Therefore, the aim of this study was to examine and compare the functional outcomes between the two groups from an occupational therapy perspective. Methods: Forty patients admitted to a rehabilitation facility were included, 20 of whom were diagnosed with post-COVID-19 stroke and 20 with non-COVID-19 stroke (ischemic and hemorrhagic). The study was a mixed design consisting of both prospective and retrospective data collection. Existing data from electronic medical records were used for the retrospective dataset. The retrospective dataset only consisted of data from post-COVID-19 stroke patients. The prospective dataset consisted of data from non-COVID-19 stroke patients. Data were collected at the time of admission and at discharge. Outcome measures included the functional independence measure (FIM), the Action Research Arm Test (ARAT), the post-COVID-19 functional status (PCFS) scale, the Borg rating of perceived exertion, and the mini-mental state examination (MMSE). Results: Both the post-COVID-19 stroke and non-COVID stroke groups showed significant differences before and after rehabilitation (NIHSS (National Institutes of Health Stroke Scale): p = 0.014, 0.000, FIM: p = 0.000, 0.000, MMSE: p = 0.015, 0.000, ARAT: p = 0.000, 0.000, respectively). However, the mean difference in the non-COVID-19 stroke group was higher than that in the post-COVID-19 stroke group, particularly in MMSE, FIM, and NIHSS scores (NIHSS: 2.8 ± 0.4, 0.9 ± 0.04, FIM: 34.8 ± 5.03, 32.95 ± 0.81, MMSE: 5.05 ± 3.5, 0.7 ± 1.17, ARAT: 1 ± 0.062, 1.2 ± 0.47, respectively). It was also found that in the post-COVID-19 stroke group, age had a positive influence on NIHSS (p = 0.022) and FIM (p = 0.047), and impaired side affected the NIHSS scores (p = 0.007). In the non-COVID-19 stroke group, significant correlations were found between the NIHSS and FIM scores (r = -0.445, p = 0.050) and the NIHSS and ARAT scores (r = -0.529, p = 0.017). Conclusion: Higher mean differences in the non-COVID-19 stroke group than in the post-COVID-19 group could be due to additional COVID-19 complications in the stroke condition itself. Overall functional gain was observed in both groups due to the effective rehabilitation. Therefore, rehabilitation is critical for functional optimization in such vulnerable populations. There is an urgent need to consider post-pandemic rehabilitation aspects.

Early screening of sleep disordered breathing in hospitalized stroke patients high-resolution pulse oximetry as prognostic and early intervention tools in patients with acute stroke and sleep apnea (HOPES TRIAL)

INTRODUCTION

Sleep Disordered Breathing (SDB) has been shown to increase the risk of stroke and despite recommendations, routine evaluation for SDB in acute stroke is not consistent across institutions. The necessary logistics and expertise required to conduct sleep studies in hospitalized patients remain a significant barrier. This study aims to evaluate the feasibility of high-resolution pulse-oximetry (HRPO) for the screening of SDB in acute stroke. Secondarily, considering impact of SDB on acute stroke, we investigated whether SDB at acute stroke predicts functional outcome at discharge and at 3 months post-stroke.

METHODS

Patients with acute mild to moderate ischemic stroke underwent an overnight HRPO within 48 h of admission. Patients were divided into SDB and no-SDB groups based on oxygen desaturations index(ODI > 10/h). Stepwise multivariate logistic regression analysis was applied to identify the relevant predictors of functional outcome (favorable [mRS 1-2 points] versus unfavorable [mrS > = 3 points]).

RESULTS

Of the 142 consecutively screened patients, 96 were included in the analysis. Of these, 33/96 (34%) were identified as having SDB and were more likely to have unfavorable mRS scores as compared to those without SDB (odds ratio = 2.70, p-value = 0.032).

CONCLUSION

HRPO may be a low-cost and easily administered screening method to detect SDB among patients hospitalized for acute ischemic stroke. Patients with SDB (as defined by ODI) have a higher burden of neurological deficits as compared to those without SDB during hospitalization.

Neuroimaging biomarkers for predicting stroke outcomes: A systematic review

Background and Aims

Stroke is a prominent cause of long-term adult impairment globally and a significant global health issue. Only 14% of stroke survivors achieve full recovery, while 25% to 50% require varying degrees of support, and over half become dependent. The aftermath of a stroke brings profound changes to an individual's life, with early choices significantly impacting their quality of life. This review aims to establish the efficacy of neuroimaging data in predicting long-term outcomes and recovery rates following a stroke.

Methods

A scientific literature search was conducted using the Centre of Reviews and Dissemination (CRD) criteria and PRISMA guidelines for a combined meta-narrative and systematic quantitative review. The methodology involved a structured search in databases like PubMed and The Cochrane Library, following inclusion and exclusion criteria to identify relevant studies on neuroimaging biomarkers for stroke outcome prediction. Data collection utilized the Microsoft Edge Zotero plugin, with quality appraisal conducted via the CASP checklist. Studies published from 2010 to 2024, including observational, randomized control trials, case reports, and clinical trials. Non-English and incomplete studies were excluded, resulting in the identification of 11 pertinent articles. Data extraction emphasized study methodologies, stroke conditions, clinical parameters, and biomarkers, aiming to provide a thorough literature overview and evaluate the significance of neuroimaging biomarkers in predicting stroke recovery outcomes.

Results

The results of this systematic review indicate that integrating advanced neuroimaging methods with highly successful reperfusion therapies following a stroke facilitates the diagnosis of the condition and assists in improving neurological impairments resulting from stroke. These measures reduce the possibility of death and improve the treatment provided to stroke patients.

Conclusion

These findings highlight the crucial role of neuroimaging in advancing our understanding of post-stroke outcomes and improving patient care.

Development and internal validation of machine learning-based models and external validation of existing risk scores for outcome prediction in patients with ischaemic stroke

Aims

We developed new machine learning (ML) models and externally validated existing statistical models [ischaemic stroke predictive risk score (iScore) and totalled health risks in vascular events (THRIVE) scores] for predicting the composite of recurrent stroke or all-cause mortality at 90 days and at 3 years after hospitalization for first acute ischaemic stroke (AIS).

Methods and results

In adults hospitalized with AIS from January 2005 to November 2016, with follow-up until November 2019, we developed three ML models [random forest (RF), support vector machine (SVM), and extreme gradient boosting (XGBOOST)] and externally validated the iScore and THRIVE scores for predicting the composite outcomes after AIS hospitalization, using data from 721 patients and 90 potential predictor variables. At 90 days and 3 years, 11 and 34% of patients, respectively, reached the composite outcome. For the 90-day prediction, the area under the receiver operating characteristic curve (AUC) was 0.779 for RF, 0.771 for SVM, 0.772 for XGBOOST, 0.720 for iScore, and 0.664 for THRIVE. For 3-year prediction, the AUC was 0.743 for RF, 0.777 for SVM, 0.773 for XGBOOST, 0.710 for iScore, and 0.675 for THRIVE.

Conclusion

The study provided three ML-based predictive models that achieved good discrimination and clinical usefulness in outcome prediction after AIS and broadened the application of the iScore and THRIVE scoring system for long-term outcome prediction. Our findings warrant comparative analyses of ML and existing statistical method-based risk prediction tools for outcome prediction after AIS in new data sets.

Pre-stroke activities of daily living do not predict functional decline after stroke in a cohort of community dwelling older subjects at risk for vascular disease

BACKGROUND & PURPOSE

Pre-stroke impairment of activities of daily living (ADL) is considered a major determinant for functional outcome after stroke. However, findings are based on studies in stroke patients in which pre-stroke information is gathered retrospectively, with inherent risks of selection and recall bias. The objective of this study was to verify the predictive value of pre-stroke ADL with respect to ADL decline in a large prospective cohort of community dwelling older subjects with known vascular risk factors or vascular disease, thereby minimizing selection and recall bias.

METHODS

Within the four-year study follow-up of a cohort including 5,804 community dwelling older subjects from three countries at risk for vascular disease, incident stroke survivors were identified. Incident myocardial infarction (MI) survivors and the remaining study survivors without incident vascular events served as comparison groups. Multivariate logistic regression analyses for each of the aforementioned groups were performed to assess associations between pre-stroke ADL by the Barthel Index (BI) and Instrumental Activities of Daily Living (IADL) scale and risk for ADL decline.

RESULTS

In stroke survivors, neither pre-event BI (n = 230, OR 1.00 (95% CI 0.83-1.23)) nor IADL (OR 1.07 (95% CI 0.94 - 1.20)) predicted risk of post-stroke ADL decline in contrast to ADL decline after MI (n = 443, OR 0.83 (95% CI 0.70-0.98) and 0.87 (95% CI 0.78-0.97) respectively) and the group without vascular events (n = 4336, OR 0.85 (95% CI 0.78-0.92) and 0.87 (95% CI 0.83-0.92) respectively).

CONCLUSIONS

In the present prospective cohort of community dwelling older subjects with known vascular risk factors, pre-stroke ADL measured by BI and IADL scale did not predict post-stroke ADL decline.

An interpretable machine learning approach for predicting 30-day readmission after stroke

BACKGROUND

Stroke is the second leading cause of death worldwide and has a significantly high recurrence rate. We aimed to identify risk factors for stroke recurrence and develop an interpretable machine learning model to predict 30-day readmissions after stroke.

METHODS

Stroke patients deposited in electronic health records (EHRs) in Xuzhou Medical University Hospital between February 1, 2021, and November 30, 2021, were included in the study, and deceased patients were excluded. We extracted 74 features from EHRs, and the top 20 features (chi-2 value) were used to build machine learning models. 80% of the patients were used for pre-training. Subsequently, a 20% holdout dataset was used for verification. The Shapley Additive exPlanations (SHAP) method was used to explore the interpretability of the model.

RESULTS

The cohort included 6,558 patients, of whom the mean (SD) age was 65 (11) years, 3,926 were males (59.86 %), and 132 (2.01 %) were readmitted within 30 days. The area under the receiver operating characteristic curve (AUROC) for the optimized model was 0.80 (95 % CI 0.68-0.80). We used the SHAP method to identify the top 10 risk factors (i.e., severe carotid artery stenosis, weak, homocysteine, glycosylated hemoglobin, sex, lymphocyte percentage, neutrophilic granulocyte percentage, urine glucose, fresh cerebral infarction, and red blood cell count). The AUROC of a model with the 10 features was 0.80 (95 % CI 0.69-0.80) and was not significantly different from that of the model with 20 risk factors.

CONCLUSIONS

Our methods not only showed good performance in predicting 30-day readmissions after stroke but also revealed risk factors that provided valuable insights for treatments.

C-REGS 2 - Design and methodology of a high-quality comparative effectiveness observational trial

The main aim of this study is to systematically record Cerebrolysin treatment modalities and concomitant medication, according to local standards, in patients with moderate to severe neurological deficits after acute ischemic stroke and to assess the impact of these parameters on therapy outcome during early rehabilitation (day 21) and on day 90. An open observational treatment design based on the principles of high-quality comparative effectiveness research (HQCER) has been chosen to capture the therapies as applied in real-world clinical practice. HQCER opens a new horizon for strengthening the validity of the results from observational trials, thereby enhancing the associated level of evidence. Rigorous pre-specification of analytical procedures and tight risk-based centralized monitoring were additional measures to improve the impact of the observational approach. The value for real-world studies has become obvious, and such studies based on comparative effectiveness designs supplement the classical study designs by enabling the inclusion of larger proband numbers and more statistical reliability for practical use.

Ordinal Prediction Model of 90-Day Modified Rankin Scale in Ischemic Stroke

Background and Purpose: Prediction models for functional outcomes after ischemic stroke are useful for statistical analyses in clinical trials and guiding patient expectations. While there are models predicting dichotomous functional outcomes after ischemic stroke, there are no models that predict ordinal mRS outcomes. We aimed to create a model that predicts, at the time of hospital discharge, a patient's modified Rankin Scale (mRS) score on day 90 after ischemic stroke.

Methods: We used data from three multi-center prospective studies: CRISP, DEFUSE 2, and DEFUSE 3 to derive and validate an ordinal logistic regression model that predicts the 90-day mRS score based on variables available during the stroke hospitalization. Forward selection was used to retain independent significant variables in the multivariable model.

Results: The prediction model was derived using data on 297 stroke patients from the CRISP and DEFUSE 2 studies. National Institutes of Health Stroke Scale (NIHSS) at discharge and age were retained as significant (p < 0.001) independent predictors of the 90-day mRS score. When applied to the external validation set (DEFUSE 3, n = 160), the model accurately predicted the 90-day mRS score within one point for 78% of the patients in the validation cohort.

Conclusions: A simple model using age and NIHSS score at time of discharge can predict 90-day mRS scores in patients with ischemic stroke. This model can be useful for prognostication in routine clinical care and to impute missing data in clinical trials.

Factors associated with early improvement after intravenous thrombolytic treatment in acute ischemic stroke

OBJECTIVE

: The aim of this study was to determine the factors associated with early neurological improvement (ENI) in patients who experienced acute ischemic stroke and were treated with intravenous recombinant tissue plasminogen activator (IV rt-PA), and determine the relationship with the outcome at the first control.

METHOD

: This study included 377 patients who were treated with IV rt-PA in Izmir Dokuz Eylül University Hospital between January 2010 and October 2018. ENI was defined as a 4 or more improvement in the National Institutes of Health Stroke Scale (NIHSS) score in the first hour, the twenty-fourth hour and the seventh day when compared to the pretreatment phase. The modified Rankin Scale (mRS) 0-1 score was defined as 'very good outcome'.

RESULTS

: The basal NIHSS (p=0.003, p=0.003, p=0.022) was high in the first hour, twenty-fourth hour, and seventh day ENI groups. Blood urea nitrogen (BUN) level was low in the first- and twenty-fourth-hour ENI groups (p=0.007, p=0.020). Furthermore, admission glucose was low at the twenty-fourth hour and on the seventh day ENI groups (p=0.005, p=0.048). A high infarct volume was observed on magnetic resonance imaging (MRI) at the twenty-fourth hour and on the seventh day non-ENI groups (p= <0.001, p= <0.001).

CONCLUSION

: Management of factors associated with ENI and determination of treatment strategies accordingly are important for obtaining a better clinical outcome. It can help quickly select patients, who, even though they will not respond to rt-PA, may be appropriate candidates for bridging therapy.

Implementation Evaluation of a Complex Intervention to Improve Timeliness of Care for Veterans with Transient Ischemic Attack

BACKGROUND

The Protocol-guided Rapid Evaluation of Veterans Experiencing New Transient Neurologic Symptoms (PREVENT) program was designed to address systemic barriers to providing timely guideline-concordant care for patients with transient ischemic attack (TIA).

OBJECTIVE

We evaluated an implementation bundle used to promote local adaptation and adoption of a multi-component, complex quality improvement (QI) intervention to improve the quality of TIA care Bravata et al. (BMC Neurology 19:294, 2019).

DESIGN

A stepped-wedge implementation trial with six geographically diverse sites.

PARTICIPANTS

The six facility QI teams were multi-disciplinary, clinical staff.

INTERVENTIONS

PREVENT employed a bundle of key implementation strategies: team activation; external facilitation; and a community of practice. This strategy bundle had direct ties to four constructs from the Consolidated Framework for Implementation Research (CFIR): Champions, Reflecting & Evaluating, Planning, and Goals & Feedback.

MAIN MEASURES

Using a mixed-methods approach guided by the CFIR and data matrix analyses, we evaluated the degree to which implementation success and clinical improvement were associated with implementation strategies. The primary outcomes were the number of completed implementation activities, the level of team organization and > 15 points improvement in the Without Fail Rate (WFR) over 1 year.

KEY RESULTS

Facility QI teams actively engaged in the implementation strategies with high utilization. Facilities with the greatest implementation success were those with central champions whose teams engaged in planning and goal setting, and regularly reflected upon their quality data and evaluated their progress against their QI plan. The strong presence of effective champions acted as a pre-condition for the strong presence of Reflecting & Evaluating, Goals & Feedback, and Planning (rather than the other way around), helping to explain how champions at the +2 level influenced ongoing implementation.

CONCLUSIONS

The CFIR-guided bundle of implementation strategies facilitated the local implementation of the PREVENT QI program and was associated with clinical improvement in the national VA healthcare system.

TRIAL REGISTRATION

clinicaltrials.gov: NCT02769338.

Predicting Clinical Outcomes in Acute Ischemic Stroke Patients Undergoing Endovascular Thrombectomy with Machine Learning : A Systematic Review and Meta-analysis

PURPOSE

Conventional predictive models are based on a combination of clinical and neuroimaging parameters using traditional statistical approaches. Emerging studies have shown that the machine learning (ML) prediction models with multiple pretreatment clinical variables have the potential to accurately prognosticate the outcomes in acute ischemic stroke (AIS) patients undergoing thrombectomy, and hence identify patients suitable for thrombectomy. This article summarizes the published studies on ML models in large vessel occlusion AIS patients undergoing thrombectomy.

METHODS

We searched electronic databases including PubMed from 1 January 2000 up to 14 October 2019 for studies that evaluated ML algorithms for the prediction of outcomes in stroke patients undergoing thrombectomy. We then used random-effects bivariate meta-analysis models to summarize the studies.

RESULTS

We retained a total of five studies that evaluated ML (4 support vector machine, 1 decision tree model) with a combined cohort of 802 patients. The prevalence of good functional outcome defined by 90-day mRS of 0-2 when available. Random effects model demonstrated that the AUC was 0.846 (95% confidence interval, CI 0.686-0.902). A pooled diagnostic odds ratio of 12.6 was computed. The pooled sensitivity and specificity were 0.795 (95% CI 0.651-0.889) and 0.780 (95% CI 0.634-0.879), respectively.

CONCLUSION

ML may be useful as an adjunct to clinical assessment to predict functional outcomes in AIS patients undergoing thrombectomy, and hence identify suitable patients for treatment. Further studies validating ML models in large multicenter cohorts are necessary to explore this further.

Comparison of knowledge on stroke for stroke patients and the general population in Burkina Faso: a cross-sectional study

Background

In many parts of Africa, there is limited information on awareness of symptoms of stroke, risk factors for stroke and willingness for stroke prevention, both in the general population and in people with stroke. Knowledge and preventive efforts for stroke in patients with a history of the illness are rarely investigated. This study aims to investigate awareness of stroke symptoms in stroke patients who were admitted to hospitals within 72 hours of a confirmed stroke event in Burkina Faso. This study also aims to investigate preventive behavior for stroke for the general population.

Methods

Face-to-face interviews were conducted with the participants. The sample included 110 first-time stroke patients who had been admitted to one of three tertiary teaching hospitals in Burkina Faso within 72 hours and 750 participants from the general population, who were recruited through clustered sampling. Knowledge of stroke warning signs and current and future efforts on stroke prevention were also assessed.

Results

Only 30.9% of the stroke patients believed that they were at risk before the stroke episode. Obvious warning signs were unfamiliar to both groups. Only 1.3% of the respondents from the general population group knew sudden weakness face arm or leg as a sign of stroke. For all future efforts in stroke prevention, stroke patients demonstrated significantly lower willingness to undertake behavioral changes than the general population. Sixty-six percent and 85% of the stroke patients and the general population, respectively, were willing to take steps to reduce blood pressure.

Conclusion

Public education on stroke warning signs and strategies to increase willingness to engage in preventive behaviors are urgent in African countries. Strategies to improve public awareness for developing countries such as Burkina Faso should be designed differently from that of developed countries to incorporate local beliefs.

Empowering Implementation Teams with a Learning Health System Approach: Leveraging Data to Improve Quality of Care for Transient Ischemic Attack

BACKGROUND

Questions persist about how learning healthcare systems should integrate audit and feedback (A&F) into quality improvement (QI) projects to support clinical teams' use of performance data to improve care quality.

OBJECTIVE

To identify how a virtual "Hub" dashboard that provided performance data for patients with transient ischemic attack (TIA), a resource library, and a forum for sharing QI plans and tools supported QI activities among newly formed multidisciplinary clinical teams at six Department of Veterans Affairs (VA) medical centers.

DESIGN

An observational, qualitative evaluation of how team members used a web-based Hub.

PARTICIPANTS

External facilitators and multidisciplinary team members at VA facilities engaged in QI to improve the quality of TIA care.

APPROACH

Qualitative implementation process and summative evaluation of observational Hub data (interviews with Hub users, structured field notes) to identify emergent, contextual themes and patterns of Hub usage.

KEY RESULTS

The Hub supported newly formed multidisciplinary teams in implementing QI plans in three main ways: as an information interface for integrated monitoring of TIA performance; as a repository used by local teams and facility champions; and as a tool for team activation. The Hub enabled access to data that were previously inaccessible and unavailable and integrated that data with benchmark and scientific evidence to serve as a common data infrastructure. Led by champions, each implementation team used the Hub differently: local adoption of the staff and patient education materials; benchmarking facility performance against national rates and peer facilities; and positive reinforcement for QI plan development and monitoring. External facilitators used the Hub to help teams leverage data to target areas of improvement and disseminate local adaptations to promote resource sharing across teams.

CONCLUSIONS

As a dynamic platform for A&F operating within learning health systems, hubs represent a promising strategy to support local implementation of QI programs by newly formed, multidisciplinary teams.

Disruptions of Anaerobic Gut Bacteria Are Associated with Stroke and Post-stroke Infection: a Prospective Case-Control Study

In recent years, preclinical studies have illustrated the potential role of intestinal bacterial composition in the risk of stroke and post-stroke infections. The results of these studies suggest that bacteria capable of producing volatile metabolites, including trimethylamine-N-oxide (TMAO) and butyrate, play opposing, yet important roles in the cascade of events leading to stroke. However, no large-scale studies have been undertaken to determine the abundance of these bacterial communities in stroke patients and to assess the impact of disrupted compositions of the intestinal microbiota on patient outcomes. In this prospective case-control study, rectal swabs from 349 ischemic and hemorrhagic stroke patients (median age, 71 years; IQR: 67-75) were collected within 24 h of hospital admission. Samples were subjected to 16S rRNA amplicon sequencing and subsequently compared with samples obtained from 51 outpatient age- and sex-matched controls (median age, 72 years; IQR, 62-80) with similar cardiovascular risk profiles but without active signs of stroke. Plasma protein biomarkers were analyzed using a combination of nuclear magnetic resonance (NMR) spectroscopy and liquid chromatography-mass spectrometry (LC-MS). Alpha and beta diversity analyses revealed higher disruption of intestinal communities during ischemic and hemorrhagic stroke compared with non-stroke matched control subjects. Additionally, we observed an enrichment of bacteria implicated in TMAO production and a loss of butyrate-producing bacteria. Stroke patients displayed two-fold lower plasma levels of TMAO than controls (median 1.97 vs 4.03 μM, Wilcoxon p < 0.0001). Finally, lower abundance of butyrate-producing bacteria within 24 h of hospital admission was an independent predictor of enhanced risk of post-stroke infection (odds ratio 0.77, p = 0.005), but not of mortality or functional patient outcome. In conclusion, aberrations in trimethylamine- and butyrate-producing gut bacteria are associated with stroke and stroke-associated infections.

Validity of National Institutes of Health Stroke Scale for Severity of Stroke to Predict Mortality Among Patients Presenting With Symptoms of Stroke

Introduction

Cerebrovascular accident (CVA), also termed as stroke, is the third leading cause of mortality and the most common cause of disability globally. The National Institutes of Health Stroke Scale (NIHSS) is a valid assessment tool utilized to determine the severity of the stroke and can be used to prioritize patients to design treatment plans, rehabilitation, and better clinical outcomes. The primary objective of this study was to determine the validity of the NIHSS to predict mortality among patients presenting with symptoms of a stroke.

Material and methods

This was a descriptive case-series conducted over a period of six months between September 2019 and February 2020 at a tertiary care hospital in Nawabshah, Pakistan. The sample population included 141 patients admitted within 24 hours of the onset of symptoms of a stroke. A neurological examination of the patients was performed. On admission, stroke severity was evaluated with the NIHSS. After an initial clinical evaluation, patients underwent a non-enhanced computed tomography (CT) scan of the brain. The score of NIHSS and mortality at 72 hours were recorded on the pre-defined proforma by the investigators. All statistical analysis was performed using Statistical Package for Social Sciences (SPSS) version 23.0 (Armonk, NY: IBM Corp).

Results

The mean age of the participants was 52.37±8.61 years. 68.1% of patients were hypertensive, 29.1% were diabetic, and 36.9% of patients were found with hyperlipidemia. The mortality rate was 41.1%. The mean NIHSS score was 16.68±6.72 points. The findings of this study demonstrated that the score of 14.9% cases was good (0-6 points), the score of 29.1% cases was moderate (7-15 points), and the score of 56% cases was poor (≥16 points). There was a significant association of NIHSS score with mortality (p<0.001).

Conclusions

Baseline NIHSS score has a profound association with mortality after acute stroke. It can help clinicians decide whether to provide thrombolytic treatment, rehabilitation or a combination of both in these patients and decrease the mortality rate. However, more studies are needed to potentiate these conclusions.

Assessment of the Protocol-Guided Rapid Evaluation of Veterans Experiencing New Transient Neurological Symptoms (PREVENT) Program for Improving Quality of Care for Transient Ischemic Attack: A Nonrandomized Cluster Trial

IMPORTANCE

Patients with transient ischemic attack (TIA) are at high risk of recurrent vascular events. Timely management can reduce that risk by 70%; however, gaps in TIA quality of care exist.

OBJECTIVE

To assess the performance of the Protocol-Guided Rapid Evaluation of Veterans Experiencing New Transient Neurological Symptoms (PREVENT) intervention to improve TIA quality of care.

DESIGN, SETTING, AND PARTICIPANTS

This nonrandomized cluster trial with matched controls evaluated a multicomponent intervention to improve TIA quality of care at 6 diverse medical centers in 6 geographically diverse states in the US and assessed change over time in quality of care among 36 matched control sites (6 control sites matched to each PREVENT site on TIA patient volume, facility complexity, and quality of care). The study period (defined as the data period) started on August 21, 2015, and extended to May 12, 2019, including 1-year baseline and active implementation periods for each site. The intervention targeted clinical teams caring for patients with TIA.

INTERVENTION

The quality improvement (QI) intervention included the following 5 components: clinical programs, data feedback, professional education, electronic health record tools, and QI support.

MAIN OUTCOMES AND MEASURES

The primary outcome was the without-fail rate, which was calculated as the proportion of veterans with TIA at a specific facility who received all 7 guideline-recommended processes of care for which they were eligible (ie, anticoagulation for atrial fibrillation, antithrombotic use, brain imaging, carotid artery imaging, high- or moderate-potency statin therapy, hypertension control, and neurological consultation). Generalized mixed-effects models with multilevel hierarchical random effects were constructed to evaluate the intervention associations with the change in the mean without-fail rate from the 1-year baseline period to the 1-year intervention period.

RESULTS

Six facilities implemented the PREVENT QI intervention, and 36 facilities were identified as matched control sites. The mean (SD) age of patients at baseline was 69.85 (11.19) years at PREVENT sites and 71.66 (11.29) years at matched control sites. Most patients were male (95.1% [154 of 162] at PREVENT sites and 94.6% [920 of 973] at matched control sites at baseline). Among the PREVENT sites, the mean without-fail rate improved substantially from 36.7% (58 of 158 patients) at baseline to 54.0% (95 of 176 patients) during a 1-year implementation period (adjusted odds ratio, 2.10; 95% CI, 1.27-3.48; P = .004). Comparing the change in quality at the PREVENT sites with the matched control sites, the improvement in the mean without-fail rate was greater at the PREVENT sites than at the matched control sites (36.7% [58 of 158 patients] to 54.0% [95 of 176 patients] [17.3% absolute improvement] vs 38.6% [345 of 893 patients] to 41.8% [363 of 869 patients] [3.2% absolute improvement], respectively; absolute difference, 14%; P = .008).

CONCLUSIONS AND RELEVANCE

The implementation of this multifaceted program was associated with improved TIA quality of care across the participating sites. The PREVENT QI program is an example of a health care system using QI strategies to improve performance, and may serve as a model for other health systems seeking to provide better care.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT02769338.

Functional Performance and Discharge Setting Predict Outcomes 3 Months After Rehabilitation Hospitalization for Stroke

BACKGROUND

Some clinical features of patients after stroke may be modifiable and used to predict outcomes. Identifying these features may allow for refining plans of care and informing estimates of posthospital service needs. The purpose of this study was to identify key factors that predict functional independence and living setting 3 months after rehabilitation hospital discharge by using a large comprehensive national data set of patients with stroke.

METHODS

The Uniform Data System for Medical Rehabilitation was queried for the records of patients with a diagnosis of stroke who were hospitalized for inpatient rehabilitation from 2005 through 2007. The system includes demographic, administrative, and clinical variables collected at rehabilitation admission, discharge, and 3-month follow-up. Primary outcome measures were the Functional Independence Measure score and living setting 3 months after rehabilitation hospital discharge.

RESULTS

The sample included 16,346 patients (80% white; 50% women; mean [SD] age, 70.3 [13.1] years; 97% ischemic stroke). The strongest predictors of Functional Independence Measure score and living setting at 3 months were those same factors at rehabilitation discharge, despite considering multiple other predictor variables including age, lesion laterality, initial neurologic impairment, and stroke-related comorbid conditions.

CONCLUSIONS

These data can inform clinicians, patients with stroke, and their families about what to expect in the months after hospital discharge. The predictive power of these factors, however, was modest, indicating that other factors may influence postacute outcomes. Future predictive modeling may benefit from the inclusion of educational status, socioeconomic factors, and brain imaging to improve predictive power.

Evaluation of inflammatory markers and mean platelet volume as short-term outcome indicators in young adults with ischemic stroke

Background

Studying outcome predictors in patients with onset of cerebral infarction in early adult life may enhance our knowledge of disease pathophysiology and prognosis.

Aim

The aim is to identify independent predictors of short-term outcome of first-ever ischemic stroke in young adults with special emphasis on inflammatory and thrombogenic markers.

Methods

We enrolled 33 patients aged 19–44 years with first-ever ischemic stroke admitted to Kasr Alainy Stroke Unit and 33 matched controls. Clinical, radiological, and laboratory (adhesion molecules, C-reactive protein, prolactin, and mean platelet volume) evaluations were carried out. Functional outcome at 7 days after stroke onset was assessed using the modified Rankin scale, and independent predictors were identified.

Results

The most frequently identified risk factor was cardiac abnormality. Patients exhibited significantly higher levels of baseline inflammatory and thrombogenic markers compared with controls. These markers were significantly correlated with the stroke severity. Logistic regression model showed that high National Institutes of Health Stroke Scale (NIHSS) score (odds ratios [OR] = 0.13; 95% confidence interval [CI], 0.04–0.24; P = 0.01) and large infarction size (OR = 0.11; 95% CI, 0.09–0.17; P = 0.04) but not the laboratory markers were independent predictors of unfavorable outcome.

Conclusion

Our data suggested that higher NIHSS scores and large infarction size served as independent predictors of short-term unfavorable outcome, while inflammatory and thrombogenic markers did not.

The protocol-guided rapid evaluation of veterans experiencing new transient neurological symptoms (PREVENT) quality improvement program: rationale and methods

BACKGROUND

Transient ischemic attack (TIA) patients are at high risk of recurrent vascular events; timely management can reduce that risk by 70%. The Protocol-guided Rapid Evaluation of Veterans Experiencing New Transient Neurological Symptoms (PREVENT) developed, implemented, and evaluated a TIA quality improvement (QI) intervention aligned with Learning Healthcare System principles.

METHODS

This stepped-wedge trial developed, implemented and evaluated a provider-facing, multi-component intervention to improve TIA care at six facilities. The unit of analysis was the medical center. The intervention was developed based on benchmarking data, staff interviews, literature, and electronic quality measures and included: performance data, clinical protocols, professional education, electronic health record tools, and QI support. The effectiveness outcome was the without-fail rate: the proportion of patients who receive all processes of care for which they are eligible among seven processes. The implementation outcomes were the number of implementation activities completed and final team organization level. The intervention effects on the without-fail rate were analyzed using generalized mixed-effects models with multilevel hierarchical random effects. Mixed methods were used to assess implementation, user satisfaction, and sustainability.

DISCUSSION

PREVENT advanced three aspects of a Learning Healthcare System. Learning from Data: teams examined and interacted with their performance data to explore hypotheses, plan QI activities, and evaluate change over time. Learning from Each Other: Teams participated in monthly virtual collaborative calls. Sharing Best Practices: Teams shared tools and best practices. The approach used to design and implement PREVENT may be generalizable to other clinical conditions where time-sensitive care spans clinical settings and medical disciplines.

TRIAL REGISTRATION

clinicaltrials.gov: NCT02769338 [May 11, 2016].

Predicting functional outcomes after stroke: an observational study of acute single-channel EEG

Background: Early and objective prediction of functional outcome after stroke is an important issue in rehabilitation. Electroencephalography (EEG) has long been utilized to describe and monitor brain function following neuro-trauma, and technological advances have improved usability in the acute setting. However, skepticism persists whether EEG can provide the same prognostic value as neurological examination.Objective: The current cohort study examined the relationship between acute single-channel EEG and functional outcomes after stroke.Methods: Resting-state EEG recorded at a single left pre-frontal EEG channel (FP1) was obtained from 16 adults within 72 h of first stroke. At 30 and 90 days, measures of disability (modified Rankin Scale; mRS) and involvement in daily activities (modified Barthel Index; mBI) were obtained. Acute EEG measures were correlated with functional outcomes and compared to an early neurological examination of stroke severity using the National Institute of Health Stroke Scale (NIHSS). Classification of good outcomes (mRS ≤1 or mBI ≥95) was also examined using Receiver Operator Curve analyses.Results: One-third to one-half of participants experienced incomplete post-stroke recovery, depending on the time point and measure. Functional outcomes correlated with acute theta values (r_s 0.45-0.60), with the strength of associations equivalent to previously reported values obtained from conventional multi-channel systems. Acute theta values ≥0.25 were associated with good outcomes, with positive (67-83%) and negative predictive values (70-90%) comparable to those obtained using the NIHSS.Conclusions: Acute, single-channel EEG can provide unique, non-overlapping clinical information, which may facilitate objective prediction of functional outcome after stroke.

Quality of Care for Veterans With Transient Ischemic Attack and Minor Stroke

Importance

The timely delivery of guideline-concordant care may reduce the risk of recurrent vascular events for patients with transient ischemic attack (TIA) and minor stroke. Although many health care organizations measure stroke care quality, few evaluate performance for patients with TIA or minor stroke, and most include only a limited subset of guideline-recommended processes.

Objective

To assess the quality of guideline-recommended TIA and minor stroke care across the Veterans Health Administration (VHA) system nationwide.

Design, Setting, and Participants

This cohort study included 8201 patients with TIA or minor stroke cared for in any VHA emergency department (ED) or inpatient setting during federal fiscal year 2014 (October 1, 2013, through September 31, 2014). Patients with length of stay longer than 6 days, ventilator use, feeding tube use, coma, intensive care unit stay, inpatient rehabilitation stay before discharge, or receipt of thrombolysis were excluded. Outlier facilities for each process of care were identified by constructing 95% CIs around the facility pass rate and national pass rate sites when the 95% CIs did not overlap. Data analysis occurred from January 16, 2016, through June 30, 2017.

Main Outcomes and Measures

Ten elements of care were assessed using validated electronic quality measures.

Results

In the 8201 patients included in the study (mean [SD] age, 68.8 [11.4] years; 7877 [96.0%] male; 4856 [59.2%] white), performance varied across elements of care: brain imaging by day 2 (6720/7563 [88.9%]; 95% CI, 88.2%-89.6%), antithrombotic use by day 2 (6265/7477 [83.8%]; 95% CI, 83.0%-84.6%), hemoglobin A1c measurement by discharge or within the preceding 120 days (2859/3464 [82.5%]; 95% CI, 81.2%-83.8%), anticoagulation for atrial fibrillation by day 7 after discharge (1003/1222 [82.1%]; 95% CI, 80.0%-84.2%), deep vein thrombosis prophylaxis by day 2 (3253/4346 [74.9%]; 95% CI, 73.6%-76.2%), hypertension control by day 90 after discharge (4292/5979 [71.8%]; 95% CI, 70.7%-72.9%), neurology consultation by day 1 (5521/7823 [70.6%]; 95% CI, 69.6%-71.6%), electrocardiography by day 2 or within 1 day prior (5073/7570 [67.0%]; 95% CI, 65.9%-68.1%), carotid artery imaging by day 2 or within 6 months prior (4923/7685 [64.1%]; 95% CI, 63.0%-65.2%), and moderate- to high-potency statin prescription by day 7 after discharge (3329/7054 [47.2%]; 95% CI, 46.0%-48.4%). Performance varied substantially across facilities (eg, neurology consultation had a facility outlier rate of 53.0%). Performance was higher for admitted patients than for patients cared for only in EDs with the greatest disparity for carotid artery imaging (4478/5927 [75.6%] vs 445/1758 [25.3%]; P < .001).

Conclusions and Relevance

This national study of VHA system quality of care for patients with TIA or minor stroke identified opportunities to improve care quality, particularly for patients who were discharged from the ED. Health care systems should engage in ongoing TIA care performance assessment to complement existing stroke performance measurement.

Processes of Care Associated With Risk of Mortality and Recurrent Stroke Among Patients With Transient Ischemic Attack and Nonsevere Ischemic Stroke

IMPORTANCE

Early evaluation and management of patients with transient ischemic attack (TIA) and nonsevere ischemic stroke improves outcomes.

OBJECTIVE

To identify processes of care associated with reduced risk of death or recurrent stroke among patients with TIA or nonsevere ischemic stroke.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study included all patients with TIA or nonsevere ischemic stroke at Department of Veterans Affairs emergency department or inpatient settings from October 2010 to September 2011. Multivariable logistic regression was used to model associations of processes of care and without-fail care, defined as receiving all guideline-concordant processes of care for which patients are eligible, with risk of death and recurrent stroke. Data were analyzed from March 2018 to April 2019.

MAIN OUTCOMES AND MEASURES

Risk of all-cause mortality and recurrent ischemic stroke at 90 days and 1 year was calculated. Overall, 28 processes of care were examined. Without-fail care was assessed for 6 processes: brain imaging, carotid artery imaging, hypertension medication intensification, high- or moderate-potency statin therapy, antithrombotics, and anticoagulation for atrial fibrillation.

RESULTS

Among 8076 patients, the mean (SD) age was 67.8 (11.6) years, 7752 patients (96.0%) were men, 5929 (73.4%) were white, 474 (6.1%) had a recurrent ischemic stroke within 90 days, 793 (10.7%) had a recurrent ischemic stroke within 1 year, 320 (4.0%) died within 90 days, and 814 (10.1%) died within 1 year. Overall, 9 processes were independently associated with lower odds of both 90-day and 1-year mortality after adjustment for multiple comparisons: carotid artery imaging (90-day adjusted odds ratio [aOR], 0.49; 95% CI, 0.38-0.63; 1-year aOR, 0.61; 95% CI, 0.52-0.72), antihypertensive medication class (90-day aOR, 0.58; 95% CI, 0.45-0.74; 1-year aOR, 0.70; 95% CI, 0.60-0.83), lipid measurement (90-day aOR, 0.68; 95% CI, 0.51-0.90; 1-year aOR, 0.64; 95% CI, 0.53-0.78), lipid management (90-day aOR, 0.46; 95% CI, 0.33-0.65; 1-year aOR, 0.67; 95% CI, 0.53-0.85), discharged receiving statin medication (90-day aOR, 0.51; 95% CI, 0.36-0.73; 1-year aOR, 0.70; 95% CI, 0.55-0.88), cholesterol-lowering medication intensification (90-day aOR, 0.47; 95% CI, 0.26-0.83; 1-year aOR, 0.56; 95% CI, 0.41-0.77), antithrombotics by day 2 (90-day aOR, 0.56; 95% CI, 0.40-0.79; 1-year aOR, 0.69; 95% CI, 0.55-0.87) or at discharge (90-day aOR, 0.59; 95% CI, 0.41-0.86; 1-year aOR, 0.69; 95% CI, 0.54-0.88), and neurology consultation (90-day aOR, 0.67; 95% CI, 0.52-0.87; 1-year aOR, 0.74; 95% CI, 0.63-0.87). Anticoagulation for atrial fibrillation was associated with lower odds of 1-year mortality only (aOR, 0.59; 95% CI, 0.40-0.85). No processes were associated with reduced risk of recurrent stroke after adjustment for multiple comparisons. The rate of without-fail care was 15.3%; 1216 patients received all guideline-concordant processes of care for which they were eligible. Without-fail care was associated with a 31.2% lower odds of 1-year mortality (aOR, 0.69; 95% CI, 0.55-0.87) but was not independently associated with stroke risk.

CONCLUSIONS AND RELEVANCE

Patients who received 6 readily available processes of care had lower adjusted mortality 1 year after TIA or nonsevere ischemic stroke. Clinicians caring for patients with TIA and nonsevere ischemic stroke should seek to ensure that patients receive all guideline-concordant processes of care for which they are eligible.

Clinical characteristics and risk score for poor clinical outcome of acute ischemic stroke patients treated with intravenous thrombolysis therapy

BACKGROUND

Tissue plasminogen activator (t-PA) is an effective therapy for acute ischemic stroke, but some patients still have poor clinical outcome. In this study, we investigated clinical characteristics of stroke patients and determined predictors for poor clinical outcome in response to t-PA treatment.

METHODS

Clinical data from 247 patients were retrospectively reviewed. Clinical parameters that were associated with survival of patients were analyzed. Areas under receiver operating characteristic curves (ROC) were used to determine the feasibility of using various combinations of the clinical parameters to predict poor clinical response. The clinical outcome was defined according to the changes in Modified Rankin Scale.

RESULTS

Overall, 145 patients had improved/complete recovery, 73 had no change, and 29 had worsening conditions or died during the in-clinic period. A univariate analysis showed that baseline characteristics including age, CRP, blood glucose level, systolic blood pressure, and admission NIHSS were significantly different (p < 0.05) among patients with different clinical outcome. A further multivariate analysis was then performed. Variables associated with poor clinical outcome (worsening/death) (p < 0.1) were included in the logistic regression model. Four parameters were retained in the model: Age, CRP, Blood glucose level, and Systolic blood pressure (ACBS). To allow a convenient usage of the ACBS classifier, the parameters were put into a scoring system, and the score at 7.7 was chosen as a cut-off. The ROC curve of this ACBS classifier has an area under the curve (AUC) of 0.7788, higher than other individual parameters. The ACBS classifier provided enhanced sensitivity of 69.2% and specificity of 74.3%.

CONCLUSION

The ACBS classifier provided a satisfactory power in estimating the patients' clinical outcome. After further validating, the classifier may provide important information to clinicians for making clinical decisions.

Predictive Value of Head-Neck CTA Combined with ABCD2 Scale Score for Patients with Cerebral Infarction of Vertebrobasilar Transient Ischemic Attack (TIA)

Background

The present study was designed to evaluate the predictive value of head-neck computed tomography angiography (CTA) combined with ABCD2 score scale for patients with cerebral infarction of vertebrobasilar transient ischemic attack (TIA).

Material/Methods

A total of 92 patients with TIA who were admitted to our hospital from January 2014 to June 2015 were enrolled in this study. ABCD2 score and CTA combined with ABCD2 score were assessed.

Results

The incidence of cerebral infarction was highest in the high-risk group, followed by the middle-risk group and low-risk group. The incidence of cerebral infarction was related to the degree of stenosis in head-neck CTA, which was highest in the severe stenosis group, followed by the moderate stenosis group and mild stenosis/normal group, with significant differences. The incidence of cerebral infarction in patients with cerebral artery stenosis was correlated with the incidence of cerebral infarction in the head and neck CTA, which was severe > medium > normal/low (P<0.05).

Conclusions

The ABCD2 score can accurately predict the early development from TIA to cerebral infarction. If it is used in combination with head-neck CTA; CTA combined ABCD2 score can further improve the accuracy of prediction, which makes it feasible for use in prediction of the development of vertebrobasilar TIA to cerebral infarction.

The efficacy of intravenous thrombolysis in acute ischemic stroke patients with white matter hyperintensity

OBJECTIVES

We aimed to investigate effects of deep white matter hyperintensity (DWMH) and periventricular hyperintensity (PVH) on the efficacy of intravenous thrombolysis (IVT) in patients with acute ischemic stroke (AIS).

METHODS

A total of 113 AIS patients with WMH were categorized into the PVH group and the DWMH group according to the lesion location, with the division of two subgroups based on whether or not they received IVT treatment: the thrombolysis group and the control group. Kaplan-Meier analysis was used for proportional hazards of recurrent stroke. Further, multivariate Cox regression analysis was employed.

RESULTS

Of total patients, there were 62 PVH patients and 51 DWMH patients: 27 of PVH patients and 22 of DWMH patients received IVT, and the remaining patients only received routine treatment. DWMH patients had a higher risk of END (36.4% vs. 11.1%; p = 0.034) and HT (22.7% vs. 3.7%; p = 0.038) than PVH patients in the thrombolysis group. Moreover, DWMH patients undergoing IVT also had a higher risk of END (36.4% vs. 10.3%; x²  = 5.050; p = 0.025) and HT (22.7% vs. 3.4%; x²  = 4.664; p = 0.031) than DWMH patients without IVT. Again, PVH patients had a higher rate of recurrent stroke (20.0% vs. 3.4%; p = 0.034) than DWMH patients in the control group after 90-day follow-up. Kaplan-Meier analysis showed a significant difference in cumulative probability of no major endpoint events (p = 0.039). Further, multivariate Cox regression revealed that PVH is an independent risk factor for stroke recurrence in AIS patients after adjusting confounding factors.

CONCLUSIONS

The location of WMH is closely associated with the efficacy of IVT in AIS patients.

Factors Associated with Early Recovery after Intravenous Thrombolytic Therapy in Acute Ischemic Stroke

Introduction

In this study, we aimed to identify the factors associated with early neurological improvement (ENI) in acute stroke patients treated with intravenous recombinant tissue plasminogen activator (IV rt-PA), and to determine the association between ENI and outcomes at 3 months after stroke.

Methods

Patients with acute ischemic stroke who were treated with IV rt-PA within 4.5 hours of symptom onset from February 2009 to December 2016 were included in the study at the stroke center of Eskişehir Osmangazi University Medical Faculty. ENI was defined as an improvement in National Institutes of Health Stroke Scale (NIHSS) score of ≥8 points compared to the pretreatment score or an NIHSS score of 0 or 1 at 24 hours after stroke. We assessed the outcomes at 3 months after treatment using the modified Rankin Scale (mRS) score, and mRS scores of 0-1 were defined as 'very good' outcomes.

Results

ENI was observed in 43.9% of 355 patients included in the study. Very good outcome at the 3rd month was detected in 80.1% of the patients with ENI, and in 15.6% of the patients without ENI (p<0.001). Patients with ENI were younger (p=0.025), and had lower NIHSS scores (p=0.027) and higher ASPECT scores (p=0.008) than those without. The ENI group had lower serum glucose levels at the time of admission (p< 0.001). Additionally, the presence of diabetes mellitus, hypertension, and hyperdense artery sign were more frequent in the ENI group (p=0.001, p=0.024, and p<0.001, respectively). Finally, multiple regression analysis showed a significant relationship between serum glucose level, hyperdense artery sign, and ENI.

Conclusion

There is a significant relationship between ENI and very good outcome at 3 months in acute stroke patients who received IV rt-PA. Therefore, the management of factors such as serum glucose level, NIHSS score, ASPECT score and presence of hyperdense artery sign which are related to ENI, and the determination of treatment strategies according to them are important issues for achieving a better outcome in acute ischemic stroke.

An Evolutionary Computation Approach for Optimizing Multilevel Data to Predict Patient Outcomes

Widespread adoption of electronic health records (EHR) and objectives for meaningful use have increased opportunities for data-driven predictive applications in healthcare. These decision support applications are often fueled by large-scale, heterogeneous, and multilevel (i.e., defined at hierarchical levels of specificity) patient data that challenge the development of predictive models. Our objective is to develop and evaluate an approach for optimally specifying multilevel patient data for prediction problems. We present a general evolutionary computational framework to optimally specify multilevel data to predict individual patient outcomes. We evaluate this method for both flattening (single level) and retaining the hierarchical predictor structure (multiple levels) using data collected to predict critical outcomes for emergency department patients across five populations. We find that the performance of both the flattened and hierarchical predictor structures in predicting critical outcomes for emergency department patients improve upon the baseline models for which only a single level of predictor—either more general or more specific—is used (p < 0.001). Our framework for optimizing the specificity of multilevel data improves upon more traditional single-level predictor structures and can readily be adapted to similar problems in healthcare and other domains.

Prognostic models for complete recovery in ischemic stroke: a systematic review and meta-analysis

Background

Prognostic models have been increasingly developed to predict complete recovery in ischemic stroke. However, questions arise about the performance characteristics of these models. The aim of this study was to systematically review and synthesize performance of existing prognostic models for complete recovery in ischemic stroke.

Methods

We searched journal publications indexed in PUBMED, SCOPUS, CENTRAL, ISI Web of Science and OVID MEDLINE from inception until 4 December, 2017, for studies designed to develop and/or validate prognostic models for predicting complete recovery in ischemic stroke patients. Two reviewers independently examined titles and abstracts, and assessed whether each study met the pre-defined inclusion criteria and also independently extracted information about model development and performance. We evaluated validation of the models by medians of the area under the receiver operating characteristic curve (AUC) or c-statistic and calibration performance. We used a random-effects meta-analysis to pool AUC values.

Results

We included 10 studies with 23 models developed from elderly patients with a moderately severe ischemic stroke, mainly in three high income countries. Sample sizes for each study ranged from 75 to 4441. Logistic regression was the only analytical strategy used to develop the models. The number of various predictors varied from one to 11. Internal validation was performed in 12 models with a median AUC of 0.80 (95% CI 0.73 to 0.84). One model reported good calibration. Nine models reported external validation with a median AUC of 0.80 (95% CI 0.76 to 0.82). Four models showed good discrimination and calibration on external validation. The pooled AUC of the two validation models of the same developed model was 0.78 (95% CI 0.71 to 0.85).

Conclusions

The performance of the 23 models found in the systematic review varied from fair to good in terms of internal and external validation. Further models should be developed with internal and external validation in low and middle income countries.

Electronic supplementary material

The online version of this article (10.1186/s12883-018-1032-5) contains supplementary material, which is available to authorized users.

Increased blood pressure variability after endovascular thrombectomy for acute stroke is associated with worse clinical outcome

BACKGROUND AND PURPOSE

Blood pressure variability has been found to contribute to worse outcomes after intravenous tissue plasminogen activator, but the association has not been established after intra-arterial therapies.

METHODS

We retrospectively reviewed patients with an ischemic stroke treated with intra-arterial therapies from 2005 to 2015. Blood pressure variability was measured as standard deviation (SD), coefficient of variation (CV), and successive variation (SV). Ordinal logistic regression models were fitted to the outcome of the modified Rankin Scale (mRS) with univariable predictors of systolic blood pressure variability. Multivariable ordinal logistic regression models were fitted to the outcome of mRS with covariates that showed independent predictive ability (P<0.1).

RESULTS

There were 182 patients of mean age 63.2 years and 51.7% were female. The median admission National Institutes of Health Stroke Scalescore was 16 and 47.3% were treated with intravenous tissue plasminogen activator. In a univariable ordinal logistic regression analysis, systolic SD, CV, and SV were all significantly associated with a 1-point increase in the follow-up mRS (OR 2.30-4.38, all P<0.002). After adjusting for potential confounders, systolic SV was the best predictor of a 1-point increase in mRS at follow-up (OR 2.63-3.23, all P<0.007).

CONCLUSIONS

Increased blood pressure variability as measured by the SD, CV, and SV consistently predict worse neurologic outcomes as measured by follow-up mRS in patients with ischemic stroke treated with intra-arterial therapies. The SV is the strongest and most consistent predictor of worse outcomes at all time intervals.

Early Rehabilitation After Stroke: a Narrative Review

PURPOSE OF REVIEW

Despite current rehabilitative strategies, stroke remains a leading cause of disability in the USA. There is a window of enhanced neuroplasticity early after stroke, during which the brain's dynamic response to injury is heightened and rehabilitation might be particularly effective. This review summarizes the evidence of the existence of this plastic window, and the evidence regarding safety and efficacy of early rehabilitative strategies for several stroke domain-specific deficits.

RECENT FINDINGS

Overall, trials of rehabilitation in the first 2 weeks after stroke are scarce. In the realm of very early mobilization, one large and one small trial found potential harm from mobilizing patients within the first 24 h after stroke, and only one small trial found benefit in doing so. For the upper extremity, constraint-induced movement therapy appears to have benefit when started within 2 weeks of stroke. Evidence for non-invasive brain stimulation in the acute period remains scant and inconclusive. For aphasia, the evidence is mixed, but intensive early therapy might be of benefit for patients with severe aphasia. Mirror therapy begun early after stroke shows promise for the alleviation of neglect. Novel approaches to treating dysphagia early after stroke appear promising, but the high rate of spontaneous improvement makes their benefit difficult to gauge. The optimal time to begin rehabilitation after a stroke remains unsettled, though the evidence is mounting that for at least some deficits, initiation of rehabilitative strategies within the first 2 weeks of stroke is beneficial. Commencing intensive therapy in the first 24 h may be harmful.

Contribution of Neuro-Imaging for Prediction of Functional Recovery after Ischemic Stroke

Prediction measures of recovery and outcome after stroke perform with only modest levels of accuracy if based only on clinical data. Prediction scores can be improved by including morphologic imaging data, where size, location, and development of the ischemic lesion is best documented by magnetic resonance imaging. In addition to the primary lesion, the involvement of fiber tracts contributes to prognosis, and consequently the use of diffusion tensor imaging (DTI) to assess primary and secondary pathways improves the prediction of outcome and of therapeutic effects. The recovery of ischemic tissue and the progression of damage are dependent on the quality of blood supply. Therefore, the status of the supplying arteries and of the collateral flow is not only crucial for determining eligibility for acute interventions, but also has an impact on the potential to integrate areas surrounding the lesion that are not typically part of a functional network into the recovery process. The changes in these functional networks after a localized lesion are assessed by functional imaging methods, which additionally show altered pathways and activated secondary centers related to residual functions and demonstrate changes in activation patterns within these networks with improved performance. These strategies in some instances record activation in secondary centers of a network, for example, also in homolog contralateral areas, which might be inhibitory to the recovery of primary centers. Such findings might have therapeutic consequences, for example, image-guided inhibitory stimulation of these areas. In the future, a combination of morphological imaging including DTI of fiber tracts and activation studies during specific tasks might yield the best information on residual function, reserve capacity, and prospects for recovery after ischemic stroke.

Glucocorticoid-associated blood glucose response and MS relapse recovery

OBJECTIVE

To determine the relationship between MS relapse recovery and blood glucose (BG) response to IV methylprednisolone (IVMP) treatment.

METHODS

We retrospectively identified 36 patients with MS admitted for IVMP treatment of acute relapse who had adequate data to characterize BG response, relapse severity, and recovery. The relationship between glucocorticoid-associated nonfasting BG (NFBG) and relapse recovery was assessed.

RESULTS

Highest recorded nonfasting BG (maximum NFBG [maxNFBG]) values were significantly higher in patients with MS without relapse recovery compared with those with recovery (271 ± 68 vs 209 ± 48 mg/dL, respectively; p = 0.0045). After adjusting for relapse severity, MS patients with maxNFBG below the group median were 6 times (OR = 6.01; 95% CI, 1.08-33.40; p = 0.040) more likely to experience relapse recovery than those with maxNFBG above the group median. In a multiple regression model adjusting for age, sex, and relapse severity, a 1-mg/dL increase in the maxNFBG was associated with 4.5% decrease in the probability of recovery (OR = 0.955; 95% CI, 0.928-0.983; p = 0.002).

CONCLUSIONS

These findings suggest that higher glucocorticoid-associated NFBG values in acutely relapsing patients with MS are associated with diminished probability of recovery. This relationship could reflect steroid-associated hyperglycemia and/or insulin resistance, defects in non-steroid-associated (e.g., prerelapse) glucose metabolism, or both. This study included only those admitted for an MS relapse, and it is this subset of patients for whom these findings may be most relevant. A prospective study to evaluate glucose regulation and MS relapse recovery in a broader outpatient MS population is under way.

Early transition to comfort measures only in acute stroke patients: Analysis from the Get With The Guidelines-Stroke registry

BACKGROUND

Death after acute stroke often occurs after forgoing life-sustaining interventions. We sought to determine the patient and hospital characteristics associated with an early decision to transition to comfort measures only (CMO) after ischemic stroke (IS), intracerebral hemorrhage (ICH), and subarachnoid hemorrhage (SAH) in the Get With The Guidelines-Stroke registry.

METHODS

We identified patients with IS, ICH, or SAH between November 2009 and September 2013 who met study criteria. Early CMO was defined as the withdrawal of life-sustaining treatments and interventions by hospital day 0 or 1. Using multivariable logistic regression, we identified patient and hospital factors associated with an early (by hospital day 0 or 1) CMO order.

RESULTS

Among 963,525 patients from 1,675 hospitals, 54,794 (5.6%) had an early CMO order (IS: 3.0%; ICH: 19.4%; SAH: 13.1%). Early CMO use varied widely by hospital (range 0.6%-37.6% overall) and declined over time (from 6.1% in 2009 to 5.4% in 2013; p < 0.001). In multivariable analysis, older age, female sex, white race, Medicaid and self-pay/no insurance, arrival by ambulance, arrival off-hours, baseline nonambulatory status, and stroke type were independently associated with early CMO use (vs no early CMO). The correlation between hospital-level risk-adjusted mortality and the use of early CMO was stronger for SAH (r = 0.52) and ICH (r = 0.50) than AIS (r = 0.15) patients.

CONCLUSIONS

Early CMO was utilized in about 5% of stroke patients, being more common in ICH and SAH than IS. Early CMO use varies widely between hospitals and is influenced by patient and hospital characteristics.

Factors Associated With Ischemic Stroke Survival and Recovery in Older Adults

BACKGROUND AND PURPOSE

Little is known about factors that predispose older adults to poor recovery after a stroke. In this study, we sought to evaluate prestroke measures of frailty and related factors as markers of vulnerability to poor outcomes after ischemic stroke.

METHODS

In participants aged 65 to 99 years with incident ischemic strokes from the Cardiovascular Health Study, we evaluated the association of several risk factors (frailty, frailty components, C-reactive protein, interleukin-6, and cystatin C) assessed before stroke with stroke outcomes of survival, cognitive decline (≥5 points on Modified Mini-Mental State Examination), and activities of daily living decline (increase in limitations).

RESULTS

Among 717 participants with incident ischemic stroke with survival data, slow walking speed, low grip strength, and cystatin C were independently associated with shorter survival. Among participants <80 years of age, frailty and interleukin-6 were also associated with shorter survival. Among 509 participants with recovery data, slow walking speed, and low grip strength were associated with both cognitive and activities of daily living decline poststroke. C-reactive protein and interleukin-6 were associated with poststroke cognitive decline among men only. Frailty status was associated with activities of daily living decline among women only.

CONCLUSIONS

Markers of physical function-walking speed and grip strength-were consistently associated with survival and recovery after ischemic stroke. Inflammation, kidney function, and frailty also seemed to be determinants of survival and recovery after an ischemic stroke. These markers of vulnerability may identify targets for differing pre and poststroke medical management and rehabilitation among older adults at risk of poor stroke outcomes.

A statistical model for stroke outcome prediction and treatment planning

Stroke is a major cause of mortality and long-term disability in the world. Predictive outcome models in stroke are valuable for personalized treatment, rehabilitation planning and in controlled clinical trials. We design a new multi-class classification model to predict outcome in the short-term, the putative therapeutic window for several treatments. Our model addresses the challenges of class imbalance, where the training data is dominated by samples of a single class, and highly correlated predictor and outcome variables, which makes learning the effects of treatments on the outcome difficult. Empirically our model outperforms the best-known previous predictive models and can infer the most effective treatments in improving outcome that have been independently validated in clinical studies.

CHA2DS2-VASc risk factors as predictors of stroke after acute coronary syndrome: A systematic review and meta-analysis

Background:

Stroke is a rare but serious complication of acute coronary syndrome. At present, no specific score exists to identify patients at higher risk. The aim of the present study is to test whether each clinical variable included in the CHA2DS2-VASc score retains its predictive value in patients with recent acute coronary syndrome, irrespective of atrial fibrillation.

Methods:

The meta-analysis was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines. All clinical trials and observational studies presenting data on the association between stroke/transient ischemic attack incidence and at least one CHA2DS2-VASc item in patients with a recent acute coronary syndrome were considered in the analysis. Atrial fibrillation diagnosis was also considered.

Results:

The whole cohort included 558,193 patients of which 7108 (1.3%) had an acute stroke and/or transient ischemic attack during follow-up (median nine months; 1st–3rd quartile 1–12 months). Age and previous stroke had the highest odds ratios (odds ratio 2.60; 95% confidence interval 2.21–3.06 and odds ratio 2.74; 95% confidence interval 2.19–3.42 respectively), in accordance with the two-point value given in the CHA2DS2-VASc score. All other factors were positively associated with stroke, although with lower odds ratios. Atrial fibrillation, while present in only 11.2% of the population, confirmed its association with an increased risk of stroke and/or transient ischemic attack (odds ratio 2.04; 95% confidence interval 1.71–2.44).

Conclusions:

All risk factors included in the CHA2DS2-VASc score are associated with stroke/ transient ischemic attack in patients with recent acute coronary syndrome, and retain similar odds ratios to what already seen in atrial fibrillation. The utility of CHA2DS2-VASc score for risk stratification of stroke in patients with acute coronary syndrome remains to be determined.

Depression, Type 2 Diabetes, and Poststroke Cognitive Impairment

Background. Ten percent of stroke survivors develop dementia, which increases to more than a third after recurrent stroke. Other survivors develop less severe vascular cognitive impairment. In the general population, depression, and diabetes interact in predicting dementia risk, and they are both prevalent in stroke. Objective. To assess the cumulative association of comorbid depressive symptoms and type 2 diabetes with cognitive outcomes among stroke survivors. Methods. Multicenter observational cohort study of people within 6 months of stroke. Depression and cognitive status were screened using the Center for Epidemiological Studies Depression (CES-D) scale and the Montreal Cognitive Assessment (MoCA), respectively. Processing speed, executive function and memory were assessed using the Trail Making Test parts A and B, and the 5 Word Delayed Free Recall task. Results. Among 342 participants (age 67.0 ± 13.5 years, 43.3% female, 46 ± 35 days poststroke), the prevalence of type 2 diabetes was 32.2% and depressive symptoms (CES-D ≥16) were found in 40.6%. Diabetes and depressive symptoms increased the risk of severe cognitive impairment (MoCA <20) with adjusted odds ratio (OR) 2.12 (95% confidence interval [CI] 1.20-3.74, P = .010) for 1 comorbidity and OR 3.18 (95% CI 1.26-8.02, P = .014) for both comorbidities. Associated cognitive deficits included executive function ( F1, 168 = 3.43, P = .035) but not processing speed ( F1, 168 = 1.86, P = .16) or memory ( F1, 168 = 0.82, P = .44). Conclusions. Diabetes and depressive symptoms were associated cumulatively with poorer cognitive screening outcomes poststroke, particularly deficits in executive function. Having 1 comorbidity doubled the odds of screening for severe cognitive impairment, having both tripled the odds.

TURN Score Predicts 90-day Outcome in Acute Ischemic Stroke Patients After IV Thrombolysis

BACKGROUND AND PURPOSE

We developed the TURN score for predicting symptomatic intracerebral hemorrhage (sICH) after IV thrombolysis. Our purpose was to evaluate its ability to predict 90-day outcome.

METHODS

We retrospectively analyzed data from 303 patients who received IV rt-PA during the NINDS rt-PA trial. Severe outcome was defined as 90-day modified Rankin scale (mRS) scores ≥5, 90-day Barthel index (BI) scores <60 and 90-day Glasgow Outcome Scale (GOS) scores >2. Excellent outcome was defined as 90-day mRS scores ≤1, 90-day BI scores ≥95 and 90-day GOS scores = 1. Agreement between TURN and 90-day outcome was assessed by univariate logistic regression reporting odds ratios (OR) and by areas under the receiver operating characteristic curves (AUROC). TURN was also compared with 6 other scores for predicting sICH or severe outcome.

RESULTS

TURN predicted 90-day mRS ≥5 with OR 5.73, 95% confidence interval (3.60, 9.10), P < 0.001 and AUROC 0.83, 95% confidence interval (0.77, 0.89). TURN also predicted 90-day mRS ≤1 with OR 5.24, 95% confidence interval (3.43, 7.99), P < 0.001 and AUROC 0.80, 95% confidence interval (0.74, 0.85). TURN predicted 90-day mRS ≥5 with OR significantly higher than DRAGON (2.30, P = 0.01), ASTRAL (1.18, P < 0.001), HAT (2.89, P = 0.05) and SEDAN (2.16, P = 0.01), and with AUROC significantly higher than SPAN-100 (0.64, P < 0.001) and SEDAN (0.71, P = 0.01). Likewise, TURN predicted 90-day mRS ≤1 with OR significantly higher than Stroke-TPI (2.89, P = 0.05), DRAGON (2.29, P = 0.01), ASTRAL (1.15, P < 0.001), HAT (2.71, P = 0.04) and SEDAN (2.15, P = 0.01), and with AUROC significantly higher than SPAN-100 (0.58, P < 0.001) and SEDAN (0.70, P = 0.01). Similar results were obtained using 90-day BI and 90-day GOS scores.

CONCLUSIONS

TURN predicted 90-day outcome with comparable or better accuracy compared to several existing clinical scores.

Ischemic stroke outcome: A review of the influence of post-stroke complications within the different scenarios of stroke care

Stroke remains one of the main causes of death and disability worldwide. The challenge of predicting stroke outcome has been traditionally assessed from a general point of view, where baseline non-modifiable factors such as age or stroke severity are considered the most relevant factors. However, after stroke occurrence, some specific complications such as hemorrhagic transformations or post stroke infections, which lead to a poor outcome, could be developed. An early prediction or identification of these circumstances, based on predictive models including clinical information, could be useful for physicians to individualize and improve stroke care. Furthermore, the addition of biological information such as blood biomarkers or genetic polymorphisms over these predictive models could improve their prognostic value. In this review, we focus on describing the different post-stroke complications that have an impact in short and long-term outcome across different time points in its natural history and on the clinical-biological information that might be useful in their prediction.

Imaging screening of catastrophic neurological events using a software tool: preliminary results

BACKGROUND

In Portugal, as in most countries, the most frequent organ donors are brain-dead donors. To answer the increasing need for transplants, donation programs have been implemented. The goal is to recognize virtually all the possible and potential brain-dead donors admitted to hospitals. The aim of this work was to describe preliminary results of a software application designed to identify devastating neurological injury victims who may progress to brain death and can be possible organ donors.

METHODS

This was an observational, longitudinal study with retrospective data collection. The software application is an automatic algorithm based on natural language processing for selected keywords/expressions present in the cranio-encephalic computerized tomography (CE CT) scan reports to identify catastrophic neurological situations, with e-mail notification to the Transplant Coordinator (TC). The first 7 months of this application were analyzed and compared with the standard clinical evaluation methodology.

RESULTS

The imaging identification tool showed a sensitivity of 77% and a specificity of 66%; predictive positive value (PPV) was 0.8 and predictive negative value (PNV) was 0.7 for the identification of catastrophic neurological events.

CONCLUSION

The methodology proposed in this work seems promising in improving the screening efficiency of critical neurological events.

Synthesis of clinical prediction models under different sets of covariates with one individual patient data

Background

Recently, increased development of clinical prediction models has been reported in the medical literature. However, evidence synthesis methodologies for these prediction models have not been sufficiently studied, especially for practical situations such as a meta-analyses where only aggregated summaries of important predictors are available. Also, in general, the covariate sets involved in the prediction models are not common across studies. As in ordinary model misspecification problems, dropping relevant covariates would raise potentially serious biases to the prediction models, and consequently to the synthesized results.

Methods

We developed synthesizing methods for logistic clinical prediction models with possibly different sets of covariates. In order to aggregate the regression coefficient estimates from different prediction models, we adopted a generalized least squares approach with non-linear terms (a sort of generalization of multivariate meta-analysis). Firstly, we evaluated omitted variable biases in this approach. Then, under an assumption of homogeneity of studies, we developed bias-corrected estimating procedures for regression coefficients of the synthesized prediction models.

Results

Numerical evaluations with simulations showed that our approach resulted in smaller biases and more precise estimates compared with conventional methods, which use only studies with common covariates or which utilize a mean imputation method for omitted coefficients. These methods were also applied to a series of Japanese epidemiologic studies on the incidence of a stroke.

Conclusions

Our proposed methods adequately correct the biases due to different sets of covariates between studies, and would provide precise estimates compared with the conventional approach. If the assumption of homogeneity within studies is plausible, this methodology would be useful for incorporating prior published information into the construction of new prediction models.

Neurologic symptom severity after a recent noncardioembolic stroke and recurrent vascular risk

BACKGROUND

There is a well-established relation of symptom severity with functional status and mortality after an index stroke. However, little is known about the impact of symptom severity of a recent index stroke on risk of recurrent vascular events.

METHODS

We reviewed the data set of a multicenter trial involving 3680 recent noncardioembolic stroke patients aged 35 years or older and followed for 2 years. Independent associations of stroke severity (as measured by National Institutes of Health Stroke Scale [NIHSS] score) with recurrent stroke (primary outcome) and stroke/coronary heart disease (CHD)/vascular death (secondary outcome) were analyzed. NIHSS score was analyzed as a dichotomous (<4 versus ≥4) and a continuous variable.

RESULTS

Among study subjects, 550 (15%) had NIHSS scores of 4 or more (overall scores ranged from 0 to 18, median score was 1 [25th-75th percentile 0-2]). NIHSS was measured at a median of 35 days after the index stroke. After adjusting for multiple covariates, NIHSS of 4 or more was independently linked to a higher risk of recurrent stroke (hazard ratio [HR], 1.37; 95% confidence interval [CI], 1.01-1.84) and risk of stroke/CHD/vascular death (HR, 1.32; 95% CI, 1.07-1.64). Analysis of NIHSS score as a continuous variable also showed a higher risk of recurrent stroke (HR, 1.06; 95% CI, 1.00-1.12) and stroke/CHD/vascular death (HR, 1.05; 95% CI, 1.01-1.09) with increasing index stroke symptom severity.

CONCLUSIONS

Greater residual symptom severity after a recent stroke is associated with higher risk of recurrent vascular events. Future studies are needed to confirm this relationship and to clarify its underlying mechanisms.

Cerebral arterial calcification is an imaging prognostic marker for revascularization treatment of acute middle cerebral arterial occlusion

BACKGROUND AND PURPOSE

To study the significance of intracranial artery calcification as a prognostic marker for acute ischemic stroke patients undergoing revascularization treatment after middle cerebral artery (MCA) trunk occlusion.

METHODS

Patients with acute MCA trunk occlusion, who underwent intravenous and/or intra-arterial revascularization treatment, were enrolled. Intracranial artery calcification scores were calculated by counting calcified intracranial arteries among major seven arteries on computed tomographic angiography. Patients were divided into high (HCB; score ≥3) or low calcification burden (LCB; score <3) groups. Demographic, imaging, and outcome data were compared, and whether HCB is a prognostic factor was evaluated. Grave prognosis was defined as modified Rankin Scale 5-6 for this study.

RESULTS

Of 80 enrolled patients, the HCB group comprised 15 patients, who were older, and more commonly had diabetes than patients in the LCB group. Initial National Institutes of Health Stroke Scale (NIHSS) scores did not differ (HCB 13.3±2.7 vs. LCB 14.6±3.8) between groups. The final good reperfusion after revascularization treatment (thrombolysis in cerebral infarction score 2b-3, HCB 66.7% vs. LCB 69.2%) was similarly achieved in both groups. However, the HCB group had significantly higher NIHSS scores at discharge (16.0±12.3 vs. 7.9±8.3), and more frequent grave outcome at 3 months (57.1% vs. 22.0%) than the LCB group. HCB was proven as an independent predictor for grave outcome at 3 months when several confounding factors were adjusted (odds ratio 4.135, 95% confidence interval, 1.045-16.359, P=0.043).

CONCLUSIONS

Intracranial HCB was associated with grave prognosis in patients who have undergone revascularization for acute MCA trunk occlusion.

Predicting Final Disposition after using the Orpington Prognostic Scor

Background:

Prediction of outcome after stroke is important for triage decisions, prognostic estimates for family and for appropriate resource utilization. Prognostication must be timely and simply applied. Several scales have shown good prognostic value. In Calgary, the Orpington Prognostic Score (OPS) has been used to predict outcome as an aid to rehabilitation triage. However, the OPS has not been assessed at one week for predictive capability.

Methods:

Among patients admitted to a sub-acute stroke unit, OPS from the first week were examined to determine if any correlation existed between final disposition after rehabilitation and first week score. The predictive validity of the OPS at one week was compared to National Institute of Health Stroke Scale (NIHSS) score at 24 hours using logistic regression and receiver operator characteristics analysis. The primary outcome was final disposition after discharge from the stroke unit if the patient went directly home, or died, or from the inpatient rehabilitation unit.

Results:

The first week OPS was highly predictive of final disposition. However, no major advantage in using the first week OPS was observed when compared to 24h NIHSS score. Both scales were equally predictive of final disposition of stroke patients, post rehabilitation.

Conclusion:

The first week OPS can be used to predict final outcome. The NIHSS at 24h provides the same prognostic information.