Predicting functional outcome in acute stroke: comparison of a simple six variable model with other predictive systems and informal clinical prediction

Sex differences in stroke reperfusion therapy in Aotearoa (New Zealand)

BACKGROUND AND AIMS

Stroke is a leading cause of death in Aotearoa (New Zealand), and stroke reperfusion therapy is a key intervention. Sex differences in stroke care have previously been asserted internationally. This study assessed potential differences in stroke reperfusion rates and quality metrics by sex in Aotearoa (New Zealand).

METHODS

This study used data from three overlapping sources. The National Stroke Reperfusion Register provided 4-year reperfusion data from 2018 to 2021 on all patients treated with reperfusion therapy (intravenous thrombolysis and thrombectomy), including time delays, treatment rates, mortality and complications. Linkage to Ministry of Health administrative and REGIONS Care study data provided an opportunity to control for confounders and explore potential mechanisms. T-test and Wilcoxon rank-sum analyses were used for continuous variables, while the chi-squared test and logistic regression were used for comparing dichotomous variables.

RESULTS

Fewer women presented with ischaemic stroke (12 186 vs 13 120) and were 4.2 years older than men (median (interquartile range (IQR)) 79 (68-86) vs 73 (63-82) years). Women were overall less likely to receive reperfusion therapy (13.9% (1704) vs 15.8% (2084), P < 0.001) with an adjusted odds ratio of 0.83 (0.77-0.90), P < 0.001. The adjusted odds ratio for thrombolysis was lower for women (0.82 (0.76-0.89), P < 0.001), but lower rates of thrombectomy fell just short of statistical significance ((0.89 (0.79-1.00), P = 0.05). There were no significant differences in complications, delays or documented reasons for non-thrombolysis.

CONCLUSIONS

Women were less likely to receive thrombolysis, even after adjusting for age and stroke severity. We found no definitive explanation for this disparity.

Exploring the Utility of Autonomic Nervous System Evaluation for Stroke Prognosis

Stroke is a major cause of functional disability and is increasing in frequency. Therefore, stroke prognosis must be both accurate and timely. Among other biomarkers, heart rate variability (HRV) is investigated in terms of prognostic accuracy within stroke patients. The literature research of two databases (MEDLINE and Scopus) is performed to trace all relevant studies published within the last decade addressing the potential utility of HRV for stroke prognosis. Only the full-text articles published in English are included. In total, forty-five articles have been traced and are included in the present review. The prognostic value of biomarkers of autonomic dysfunction (AD) in terms of mortality, neurological deterioration, and functional outcome appears to be within the range of known clinical variables, highlighting their utility as prognostic tools. Moreover, they may provide additional information regarding poststroke infections, depression, and cardiac adverse events. AD biomarkers have demonstrated their utility not only in the setting of acute ischemic stroke but also in transient ischemic attack, intracerebral hemorrhage, and traumatic brain injury, thus representing a promising prognostic tool whose clinical application may greatly facilitate individualized stroke care.

Comparison of Stroke Care Costs in Urban and Nonurban Hospitals and Its Association With Outcomes in New Zealand: A Nationwide Economic Evaluation

BACKGROUND

Although geographical differences in treatment and outcomes after stroke have been described, we lack evidence on differences in the costs of treatment between urban and nonurban regions. Additionally, it is unclear whether greater costs in one setting are justified given the outcomes achieved. We aimed to compare costs and quality-adjusted life years in people with stroke admitted to urban and nonurban hospitals in New Zealand.

METHODS

Observational study of patients with stroke admitted to the 28 New Zealand acute stroke hospitals (10 in urban areas) recruited between May and October 2018. Data were collected up to 12 months poststroke including treatments in hospital, inpatient rehabilitation, other health service utilization, aged residential care, productivity, and health-related quality of life. Costs in New Zealand dollars were estimated from a societal perspective and assigned to the initial hospital that patients presented to. Unit prices for 2018 were obtained from government and hospital sources. Multivariable regression analyses were conducted when assessing differences between groups.

RESULTS

Of 1510 patients (median age 78 years, 48% female), 607 presented to nonurban and 903 to urban hospitals. Mean hospital costs were greater in urban than nonurban hospitals ($13 191 versus $11 635, P=0.002), as were total costs to 12 months ($22 381 versus $17 217, P<0.001) and quality-adjusted life years to 12 months (0.54 versus 0.46, P<0.001). Differences in costs and quality-adjusted life years remained between groups after adjustment. Depending on the covariates included, costs per additional quality-adjusted life year in the urban hospitals compared to the nonurban hospitals ranged from $65 038 (unadjusted) to $136 125 (covariates: age, sex, prestroke disability, stroke type, severity, and ethnicity).

CONCLUSIONS

Better outcomes following initial presentation to urban hospitals were associated with greater costs compared to nonurban hospitals. These findings may inform greater targeted expenditure in some nonurban hospitals to improve access to treatment and optimize outcomes.

Copeptin Implementation on Stroke Prognosis

Predicting functional outcome following stroke is considered to be of key importance in an attempt to optimize overall stroke care. Although clinical prognostic tools have been widely implemented, optimal blood biomarkers might be able to yield additional information regarding each stroke survivor's propensity for recovery. Copeptin seems to have interesting prognostic potential poststroke. The present review aims to explore the prognostic significance of copeptin in stroke patients. Literature research of two databases (MEDLINE and Scopus) was conducted to trace all relevant studies published between 16 February 2012 and 16 February 2022 that focused on the utility of copeptin as a prognostic marker in acute stroke setting. 25 studies have been identified and included in the present review. The predictive ability of copeptin regarding both functional outcome and mortality appears to be in the range of established clinical variables, thus highlighting the added value of copeptin evaluation in stroke management. Apart from acute ischemic stroke, the discriminatory accuracy of the biomarker was also demonstrated among patients with transient ischemic attack, intracerebral hemorrhage, and subarachnoid hemorrhage. Overall, copeptin represents a powerful prognostic tool, the clinical implementation of which is expected to significantly facilitate the individualized management of stroke patients.

Post-stroke outcomes predicted from multivariate lesion-behaviour and lesion network mapping

Clinicians and scientists alike have long sought to predict the course and severity of chronic post-stroke cognitive and motor outcomes, as the ability to do so would inform treatment and rehabilitation strategies. However, it remains difficult to make accurate predictions about chronic post-stroke outcomes due, in large part, to high inter-individual variability in recovery and a reliance on clinical heuristics rather than empirical methods. The neuroanatomical location of a stroke is a key variable associated with long-term outcomes, and because lesion location can be derived from routinely collected clinical neuroimaging data there is an opportunity to use this information to make empirically based predictions about post-stroke deficits. For example, lesion location can be compared to statistically weighted multivariate lesion-behaviour maps of neuroanatomical regions that, when damaged, are associated with specific deficits based on aggregated outcome data from large cohorts. Here, our goal was to evaluate whether we can leverage lesion-behaviour maps based on data from two large cohorts of individuals with focal brain lesions to make predictions of 12-month cognitive and motor outcomes in an independent sample of stroke patients. Further, we evaluated whether we could augment these predictions by estimating the structural and functional networks disrupted in association with each lesion-behaviour map through the use of structural and functional lesion network mapping, which use normative structural and functional connectivity data from neurologically healthy individuals to elucidate lesion-associated networks. We derived these brain network maps using the anatomical regions with the strongest association with impairment for each cognitive and motor outcome based on lesion-behaviour map results. These peak regional findings became the 'seeds' to generate networks, an approach that offers potentially greater precision compared to previously used single-lesion approaches. Next, in an independent sample, we quantified the overlap of each lesion location with the lesion-behaviour maps and structural and functional lesion network mapping and evaluated how much variance each could explain in 12-month behavioural outcomes using a latent growth curve statistical model. We found that each lesion-deficit mapping modality was able to predict a statistically significant amount of variance in cognitive and motor outcomes. Both structural and functional lesion network maps were able to predict variance in 12-month outcomes beyond lesion-behaviour mapping. Functional lesion network mapping performed best for the prediction of language deficits, and structural lesion network mapping performed best for the prediction of motor deficits. Altogether, these results support the notion that lesion location and lesion network mapping can be combined to improve the prediction of post-stroke deficits at 12-months.

Stroke Core Volume Weighs More Than Recanalization Time for Predicting Outcome in Large Vessel Occlusion Recanalized Within 6 h of Symptoms Onset

Introduction

Current guidelines suggest that perfusion imaging should only be performed > 6 h after symptom onset. Pathophysiologically, brain perfusion should matter whatever the elapsed time. We aimed to compare relative contribution of recanalization time and stroke core volume in predicting functional outcome in patients treated by endovascular thrombectomy within 6-h of stroke-onset.

Methods

Consecutive patients presenting between January 2015 and June 2021 with (i) an acute ischaemic stroke due to an anterior proximal occlusion, (ii) a successful thrombectomy (TICI >2a) within 6-h of symptom-onset and (iii) CT perfusion imaging were included. Core stroke volume was automatically computed using RAPID software. Two linear regression models were built that included in the null hypothesis the pre-treatment NIHSS score and the hypoperfusion volume (Tmax > 6 s) as confounding variables and 24 h post-recanalization NIHSS and 90 days mRS as outcome variables. Time to recanalization was used as covariate in one model and stroke core volume as covariate in the other.

Results

From a total of 377 thrombectomies, 94 matched selection criteria. The Model null hypothesis explained 37% of the variability for 24 h post-recanalization NIHSS and 42% of the variability for 90 days MRS. The core volume as covariate increased outcome variability prediction to 57 and 56%, respectively. Time to recanalization as covariate marginally increased outcome variability prediction from 37 and 34% to 40 and 42.6%, respectively.

Conclusion

Core stroke volume better explains outcome variability in comparison to the time to recanalization in anterior large vessel occlusion stroke with successful thrombectomy done within 6 h of symptoms onset. Still, a large part of outcome variability prediction fails to be explained by the usual predictors.

Predictors of stroke favorable functional outcome in Guinea, results from the Conakry stroke registry

Low- to middle-income countries (LMICs) now bear most of the stroke burden. In LMICs, stroke epidemiology and health care systems are different from HICs. Therefore, a high-income country (HIC)-based predictive model may not correspond to the LMIC stroke context. Identify the impact of modifiable variables in acute stroke management in Conakry, Guinea as potential predictors of favorable stroke outcome. Data were extracted from the Conakry stroke registry that includes 1018 patients. A logistic regression model was built to predict favorable stroke outcomes, defined as mRS 0–2. Age, admission NIHSS score, mean arterial blood pressure and capillary glycemia were chosen as covariates. Delay to brain CT imaging under 24 h from symptom onset, fever, presence of sores and abnormal lung auscultation were included as factors. NIHSS score on admission, age and ischemic stroke were included in the null model as nuisance parameters to determine the contribution of modifiable variables to predict stroke favorable outcome. Lower admission NIHSS, brain CT imaging within 24 h of symptoms onset and lower mean arterial blood pressure emerged as a significant positive predictors of favorable stroke outcome with respective odd ratios (OR) of 1.35 [1.28–1.43], 2.1 [1.16–3.8] and 1.01 [1.01–1.04]. The presence of fever or sores impacted negatively stroke favorable outcomes with OR of 0.3 [0.1–0.85] and 0.25 [0.14–0.45]. The area under receiver operating characteristic curves (AUC) of the model was 0.86. This model explained 44.5% of the variability of the favorable stroke outcome with 10.2% of the variability explained by the modifiable variables when admission NIHSS, and ischemic stroke were included in the null model as nuisance parameter. In the Conakry stroke registry, using a logistic regression to predict stroke favorable outcome, five variables that led to an AUC of 0.86: admission NIHSS, early brain CT imaging, fever, sores and mean blood pressure. This paves the way for future public health interventions to test whether modulating amendable variables leads to increased favorable stroke outcomes in LMICs.

Prognostic factors of functional outcome in post-acute stroke in the rehabilitation unit

BACKGROUND/PURPOSE

This retrospective study aimed to determine which factors, such as cognition, motor recovery, swallowing function, and bladder and bowel functions, significantly predicted independence in the activities of daily living (ADL) at hospital discharge in a domestic population of patients experiencing post-acute stroke who received in-hospital rehabilitation.

METHODS

We reviewed medical records that were retrieved from the Integrated Medical Database, National Taiwan University Hospital (NTUH-iMD) of 3000 patients who suffered from stroke and were admitted to NTUH from 2014 to 2017. The main outcome measure was independence in the basic ADL (modified Barthel index [mBI]) at discharge. Regression analyses were used to identify prognostic factors for the basic ADL (mBI).

RESULTS

The total mBI improved from 40.7 ± 33.0 to 63.1 ± 34.1 in eligible 2538 patients during their hospital stay. The baseline daily activity function (R² change = 0.042) was the most important prognostic factor associated with independence at discharge, followed by dependence in sitting up (R² change = 0.014), impaired sitting balance (R² change = 0.010), the Brunnstrom stage of hemiplegic lower limb (R² change = 0.006), and the presence of bladder incontinence (R² change = 0.006) assessed by physician upon rehabilitation admission (R² = 0.53, p < 0.05). Dependency in sitting up, impaired sitting balance, and the presence of urinary incontinence were negative prognostic factors of ADL independence at discharge (p < 0.05). By contrast, the Brunnstrom stage of hemiplegic lower limb and baseline mBI scores at rehabilitation admission were positive prognostic factors of ADL independence at discharge (p < 0.05).

CONCLUSION

Baseline ADL function was the most important prognostic factor of functional independence in post-acute stroke. Moreover, the activity limitation of dependency on sitting up and motor function impairment of hemiplegic lower limb prognosticated functional independence.

International stroke genetics consortium recommendations for studies of genetics of stroke outcome and recovery

Numerous biological mechanisms contribute to outcome after stroke, including brain injury, inflammation, and repair mechanisms. Clinical genetic studies have the potential to discover biological mechanisms affecting stroke recovery in humans and identify intervention targets. Large sample sizes are needed to detect commonly occurring genetic variations related to stroke brain injury and recovery. However, this usually requires combining data from multiple studies where consistent terminology, methodology, and data collection timelines are essential. Our group of expert stroke and rehabilitation clinicians and researchers with knowledge in genetics of stroke recovery here present recommendations for harmonizing phenotype data with focus on measures suitable for multicenter genetic studies of ischemic stroke brain injury and recovery. Our recommendations have been endorsed by the International Stroke Genetics Consortium.

Age-Related Disparities in the Quality of Stroke Care and Outcomes in Rehabilitation Hospitals: The Australian National Audit

INTRODUCTION

Stroke affects all ages. Despite increased incidence in those <65 years, little is known about age-based differences in inpatient rehabilitation management and outcomes.

OBJECTIVES

To investigate management and outcomes, comparing younger (<65 years) and older (≥65 years) patients with stroke, who received inpatient rehabilitation.

METHODS

Multicentre, cross-sectional study using data from Australian hospitals who participated in the Stroke Foundation national stroke rehabilitation audit (2016-2018). Chi-square tests compared characteristics and care by age. Multivariable regression models were used to compare outcomes by age (e.g. length of stay). Models were adjusted for sex, stroke type and severity factors.

RESULTS

7,165 audited cases from 127 hospitals; 23% <65 years (66% male; 72% ischaemic stroke). When compared to older patients, younger patients were more likely male (66% vs 52%); identify as Aboriginal or Torres Strait Islander (6% vs 1%); be less disabled on admission; receive psychology (46% vs 34%) input, and community reintegration support, including return to work (OR 1.47, 95% CI 1.03, 2.11), sexuality (OR 1.60, 95% CI 1.39, 1.84) and self-management (OR 1.39, 95% CI 1.23, 1.57) advice. Following adjustment, younger patients had longer lengths of stay (coeff 3.54, 95% CI 2.27, 4.81); were more likely to be independent on discharge (aOR 1.96, 95% CI 1.68, 2.28); be discharged to previous residences (aOR 1.64, 95% CI 1.41, 1.91) and receive community rehabilitation (aOR: 2.27, 95% CI 1.91, 2.70).

CONCLUSIONS

Age-related differences exist in characteristics, management and outcomes for inpatients with stroke accessing rehabilitation in Australia.

Reducing Ethnic and Geographic Inequities to Optimise New Zealand Stroke Care (REGIONS Care): Protocol for a Nationwide Observational Study

BACKGROUND

Stroke systems of care differ between larger urban and smaller rural settings and it is unclear to what extent this may impact on patient outcomes. Ethnicity influences stroke risk factors and care delivery as well as patient outcomes in nonstroke settings. Little is known about the impact of ethnicity on poststroke care, especially in Māori and Pacific populations.

OBJECTIVE

Our goal is to describe the protocol for the Reducing Ethnic and Geographic Inequities to Optimise New Zealand Stroke Care (REGIONS Care) study.

METHODS

This large, nationwide observational study assesses the impact of rurality and ethnicity on best practice stroke care access and outcomes involving all 28 New Zealand hospitals caring for stroke patients, by capturing every stroke patient admitted to hospital during the 2017-2018 study period. In addition, it explores current access barriers through consumer focus groups and consumer, carer, clinician, manager, and policy-maker surveys. It also assesses the economic impact of care provided at different types of hospitals and to patients of different ethnicities and explores the cost-efficacy of individual interventions and care bundles. Finally, it compares manual data collection to routine health administrative data and explores the feasibility of developing outcome models using only administrative data and the cost-efficacy of using additional manually collected registry data. Regarding sample size estimates, in Part 1, Study A, 2400 participants are needed to identify a 10% difference between up to four geographic subgroups at 90% power with an α value of .05 and 10% to 20% loss to follow-up. In Part 1, Study B, a sample of 7645 participants was expected to include an estimated 850 Māori and 419 Pacific patients and to provide over 90% and over 80% power, respectively. Regarding Part 2, 50% of the patient or carer surveys, 40 provider surveys, and 10 focus groups were needed to achieve saturation of themes. The main outcome is the modified Rankin Scale (mRS) score at 3 months. Secondary outcomes include mRS scores; EQ-5D-3L (5-dimension, 3-level EuroQol questionnaire) scores; stroke recurrence; vascular events; death; readmission at 3, 6, and 12 months; cost of care; and themes around access barriers.

RESULTS

The study is underway, with national and institutional ethics approvals in place. A total of 2379 patients have been recruited for Part 1, Study A; 6837 patients have been recruited for Part 1, Study B; 10 focus groups have been conducted and 70 surveys have been completed in Part 2. Data collection has essentially been completed, including follow-up assessment; however, primary and secondary analyses, data linkage, data validation, and health economics analysis are still underway.

CONCLUSIONS

The methods of this study may provide the basis for future epidemiological studies that will guide care improvements in other countries and populations.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/25374.

Predicting specific abilities after disabling stroke: Development and validation of prognostic models

Background

Predicting specific abilities (e.g. walk and talk) to provide a functional profile six months after disabling stroke could help patients/families prepare for the consequences of stroke and facilitate involvement in treatment decision-making.

Aim

To develop new statistical models to predict specific abilities six months after stroke and test their performance in an independent cohort of patients with disabling stroke.

Methods

We developed models to predict six specific abilities (to be independent, walk, talk, eat normally, live without major anxiety/depression, and to live at home) using data from seven large multicenter stroke trials with multivariable logistic regression. We included 13,117 participants recruited within three days of hospital admission. We assessed model discrimination and derived optimal cut-off values using four statistical methods. We validated the models in an independent single-center cohort of patients (n = 403) with disabling stroke. We assessed model discrimination and calibration and reported the performance of our models at the statistically derived cut-off values.

Results

All six models had good discrimination in external validation (AUC 0.78–0.84). Four models (predicting to walk, eat normally, live without major anxiety/depression, live at home) calibrated well. Models had sensitivities between 45.0 and 97.9% and specificities between 21.6 and 96.5%.

Conclusions

We have developed statistical models to predict specific abilities and demonstrated that these models perform reasonably well in an independent cohort of disabling stroke patients. To aid decision-making regarding treatments, further evaluation of our models is required.

Effects of Age on Long-Term Functional Recovery in Patients with Stroke

Background and objectives: Age might be a determinant that limits functional recovery in patients with stroke. Here, we investigated the effect of age on functional recovery within 30 months after stroke onset. Materials and Methods: This retrospective longitudinal study enrolled 111 patients with first-ever stroke. Functional recovery was assessed at 2 weeks and at 1, 6, and 30 months after stroke onset using the modified Barthel Index (MBI), modified Rankin Score (mRS), functional ambulation category (FAC), muscle strength, and Mini-Mental State Examination (MMSE). A generalized estimating equation analysis was performed. Results: With the MBI, function improved until 6 months after stroke onset in patients aged <70 years and until 1 month after stroke onset in patients ≥70 years. At 30 months after stroke, there was no significant change of MBI in patients aged <70 years, whereas there was a significant decline in older patients. With the mRS and FAC, function improved until 30 months after stroke onset in patients aged <70 years and until 1 month after stroke onset in older patients. Motor deficit, assessed using the Medical Research Council (MRC), improved significantly until 6 months after stroke onset in patients aged <70 years. There was a significant improvement in cognition (assessed using the MMSE) until 6 months after stroke onset in patients aged <70 years and until 1 month after stroke onset in older patients. Conclusions: Long-term functional recovery occurred for up to 30 months after stroke. Patients aged ≥70 years showed functional decline between 6 and 30 months after onset. These findings could be useful when measuring functional recovery after stroke.

Premorbid physical activity is modestly associated with gait independence after a stroke: an exploratory study

Background

Regaining physical function after a stroke is important for independence and for performing activities of daily living. Particularly, cerebrovascular disease, which includes stroke, is not entirely avoidable. In the present study, we aimed to observe the association between premorbid physical activities and gait independence after a stroke.

Methods

Consecutive cerebrovascular stroke patients were asked to fill a questionnaire regarding their premorbid physical activities. The association between gait independence at the completion of in-hospital rehabilitation and premorbid physical activities, as well as age, stroke type, lesion size, and comorbidities, was investigated statistically.

Results

Of 130 consecutive patients with stroke who answered the questionnaire regarding their premorbid physical activities, 97 regained gait independence. Ambulation and occupational or household activities were most frequently performed by all the participants before stroke onset. Participants who acquired gait independence tended to indicate various premorbid activities compared to participants who did not recover gait independence. Estimating premorbid physical activities in metabolic equivalents suggested that moderate to vigorous activities were associated with an increased probability of post-stroke independent gait but this tendency was dismissed after multivariate analysis including age and history of stroke.

Conclusions

Premorbid physical activity is associated with gait independence after a stroke, but this association is not as strong as those of age or history of stroke.

Electronic supplementary material

The online version of this article (10.1186/s11556-018-0208-8) contains supplementary material, which is available to authorized users.

Rehabilitation in oldest-old stroke patients: a comparison within over 65 population

BACKGROUND

Considering the demographic trend, characterized by a marked aging due to the increase in life expectancy and the improvement in medical care, in the next future elderly patients will represent the majority of stroke victims with a strong impact on rehabilitative services.

AIM

To investigate and characterize differences in functional outcome in elderly patients after stroke.

DESIGN

Observational study.

SETTING

Post-acute inpatient rehabilitation.

POPULATION

Subjects aged ≥65 years with acute (i.e. within 30 days from onset) ischemic or hemorrhagic stroke.

METHODS

At admission, all patients underwent neurological and clinical examination, functional evaluation and laboratory assessment. Comorbidities and clinical complications during hospital stay were recorded. Functional status was evaluated by means of the Functional Independence Measure (FIM) administered at admission and discharge. All patients underwent neuromotor rehabilitation, and speech therapy in case of aphasia, once a day, six days per week.

RESULTS

The study enrolled 402 patients, who were stratified in three groups according to age: 145 patients in Group 1, the young-old (65-74.9 years, G1), 206 in Group 2, the middle-old (75-84.9 years, G2) and 51 in Group 3, the oldest-old (≥85 years, G3). At discharge, FIM total scores increased significantly for all the groups (P<0.001); however FIM gains, as well as the efficiency parameters derived from FIM were significantly lower in G3 when compared with G1 and G2. G3 showed a significantly higher rate of comorbidities and a higher presence of pressure sores; infections occurred mainly in G2 and G3. Hospitalization was significantly longer for G1 and G2 with respect to G3, while mortality rates were significantly higher in G2 and G3 with respect to G1. The variables that predicted functional outcome were age, previous stroke, stroke severity and functional status at admission.

CONCLUSIONS

Despite advancing age seems to be associated with a reduced effectiveness of the rehabilitation process and a greater number of complications, intensive rehabilitation can produce significant functional gains for all stroke survivors, regardless of age.

CLINICAL REHABILITATION IMPACT

Understanding the specificity of this population will offer older subjects targeted interventions and, for health systems, better allocation of resources and the development of more effective approaches.

Prediction of Outcome in Patients With Acute Ischemic Stroke Based on Initial Severity and Improvement in the First 24 h

Introduction

Stroke severity measured by the baseline National Institutes of Health Stroke Scale (NIHSS) is a strong predictor of stroke outcome. Early change of baseline severity may be a better predictor of outcome. Here, we hypothesized that the change in NIHSS in the first 24 h after stroke improved stroke outcome prediction.

Materials and methods

Patients from the Leuven Stroke Genetics Study were included when the baseline NIHSS (B-NIHSS) was determined on admission in the hospital and NIHSS after 24 h could be obtained from patient files. The delta NIHSS, relative reduction NIHSS, and major neurological improvement (NIHSS of 0–1 or ≥8-point improvement at 24 h) were calculated. Good functional outcome (GFO) at 90 days was defined as a modified Rankin Scale of 0–2. Independent predictors of outcome were identified by multivariate logistic regression. We performed a secondary analysis after excluding patients presenting with a minor stroke (NIHSS 0–5) since the assessment of change in NIHSS might be more reliable in patients presenting with a moderate to severe deficit.

Results

We analyzed the outcome in 369 patients. B-NIHSS was associated with GFO (odds ratio: 0.82; 95% CI 0.77–0.86). In a multivariate model with B-NIHSS and age as predictors, the accuracy [area under the curve (AUC): 0.82] improved by including the delta NIHSS (AUC: 0.86; p < 0.01). In 131 patients with moderate to severe stroke, the predictive multivariate model was more accurate when including the RR NIHSS (AUC: 0.83) to the model which included B-NIHSS, age and ischemic heart disease (AUC: 0.77; p = 0.03).

Conclusion

B-NIHSS is a predictor of stroke outcome. In this cohort, the prediction of GFO was improved by adding change in stroke severity after 24 h to the model.

Development and validation of the Dutch Stroke Score for predicting disability and functional outcome after ischemic stroke: A tool to support efficient discharge planning

Introduction

We aimed to develop and validate a prognostic score for disability at discharge and functional outcome at three months in patients with acute ischemic stroke based on clinical information available on admission.

Patients and methods

The Dutch Stroke Score (DSS) was developed in 1227 patients with ischemic stroke included in the Paracetamol (Acetaminophen) In Stroke study. Predictors for Barthel Index (BI) at discharge (‘DSS-discharge’) and modified Rankin Scale (mRS) at three months (‘DSS-3 months’) were identified in multivariable ordinal regression. The models were internally validated with bootstrapping techniques. The DSS-3 months was externally validated in the PRomoting ACute Thrombolysis in Ischemic StrokE study (1589 patients) and the Preventive Antibiotics in Stroke Study (2107 patients). Model performance was assessed in terms of discrimination, expressed by the area under the receiver operating characteristic curve (AUC), and calibration.

Results

At model development, the strongest predictors of Barthel Index at discharge were age per decade over 60 (odds ratio = 1.55, 95% confidence interval (CI) 1.41–1.68), National Institutes of Health Stroke Scale (odds ratio = 1.24 per point, 95% CI 1.22–1.26) and diabetes (odds ratio = 1.62, 95% CI 1.32–1.91). The internally validated AUC was 0.76 (95% CI 0.75–0.79). The DSS-3 months, additionally consisting of previous stroke and atrial fibrillation, performed similarly at internal (AUC 0.75, 95% CI 0.74–0.77) and external validation (AUC 0.74 in PRomoting ACute Thrombolysis in Ischemic StrokE (95% CI 0.72–0.76) and 0.69 in Preventive Antibiotics in Stroke Study (95% CI 0.69–0.72)). Observed outcome was slightly better than predicted.

Discussion: The DSS had satisfactory performance in predicting BI at discharge and mRS at three months in ischemic stroke patients.

Conclusion

If further validated, the DSS may contribute to efficient stroke unit discharge planning alongside patients' contextual factors and therapeutic needs.

Simple prediction scores predict good and devastating outcomes after stroke more accurately than physicians

Introduction

physicians are often asked to prognosticate soon after a patient presents with stroke. This study aimed to compare two outcome prediction scores (Five Simple Variables [FSV] score and the PLAN [Preadmission comorbidities, Level of consciousness, Age, and focal Neurologic deficit]) with informal prediction by physicians.

Methods

demographic and clinical variables were prospectively collected from consecutive patients hospitalised with acute ischaemic or haemorrhagic stroke (2012-13). In-person or telephone follow-up at 6 months established vital and functional status (modified Rankin score [mRS]). Area under the receiver operating curves (AUC) was used to establish prediction score performance.

Results

five hundred and seventy-five patients were included; 46% female, median age 76 years, 88% ischaemic stroke. Six months after stroke, 47% of patients had a good outcome (alive and independent, mRS 0-2) and 26% a devastating outcome (dead or severely dependent, mRS 5-6). The FSV and PLAN scores were superior to physician prediction (AUCs of 0.823-0.863 versus 0.773-0.805, P < 0.0001) for good and devastating outcomes. The FSV score was superior to the PLAN score for predicting good outcomes and vice versa for devastating outcomes (P < 0.001). Outcome prediction was more accurate for those with later presentations (>24 hours from onset).

Conclusion

the FSV and PLAN scores are validated in this population for outcome prediction after both ischaemic and haemorrhagic stroke. The FSV score is the least complex of all developed scores and can assist outcome prediction by physicians.

Patient-specific prediction of functional recovery after stroke

Background and aims

Clinical predictive models for stroke recovery could offer the opportunity of targeted early intervention and more specific information for patients and carers. In this study, we developed and validated a patient-specific prognostic model for monitoring recovery after stroke and assessed its clinical utility.

Methods

Four hundred and ninety-five patients from the population-based South London Stroke Register were included in a substudy between 2002 and 2004. Activities of daily living were assessed using Barthel Index) at one, two, three, four, six, eight, 12, 26, and 52 weeks after stroke. Penalized linear mixed models were developed to predict patients’ functional recovery trajectories. An external validation cohort included 1049 newly registered stroke patients between 2005 and 2011. Prediction errors on discrimination and calibration were assessed. The potential clinical utility was evaluated using prognostic accuracy measurements and decision curve analysis.

Results

Predictive recovery curves showed good accuracy, with root mean squared deviation of 3 Barthel Index points and a R2 of 83% up to one year after stroke in the external cohort. The negative predictive values of the risk of poor recovery (Barthel Index <8) at three and 12 months were also excellent, 96% (95% CI [93.6–97.4]) and 93% [90.8–95.3], respectively, with a potential clinical utility measured by likelihood ratios (LR+:17 [10.8–26.8] at three months and LR+:11 [6.5–17.2] at 12 months). Decision curve analysis showed an increased clinical benefit, particularly at threshold probabilities of above 5% for predictive risk of poor outcomes.

Conclusions

A recovery curves tool seems to accurately predict progression of functional recovery in poststroke patients.

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.

Do studies of the weekend effect really allow for differences in illness severity? An analysis of 14 years of stroke admissions

Background

An increased mortality rate among patients admitted to hospital at weekends has been found in many studies, and this ‘weekend effect’ has been used to justify major health service reorganisation. Most studies have used routine administrative data to adjust for potential confounding factors, and are unable to measure differences in illness severity due to the tendency of patients with milder symptoms to stay home at weekends. We set out to estimate the importance of such unmeasured ‘confounding by severity’, using data from a hospital stroke register.

Methods

All suspected acute stroke admissions in Gateshead were prospectively registered over a period of 14.3 years, including information on premorbid factors, measures of stroke severity and survival to hospital discharge. We examined whether each factor differed between weekday and weekend admissions, then used logistic regression to estimate the main contributors to variation in mortality rates.

Results

Stroke severity, measured by the Scandinavian Stroke Scale (SSS), was significantly greater among weekend admissions and strongly associated with mortality, and after adjustment for SSS score in logistic regression, the weekend effect completely disappeared. By contrast, most indicators of pre-stroke function, comorbidity or stroke type did not differ between weekday and weekend admissions, although some of them had prognostic significance.

Conclusions

The sorts of factors measurable in administrative databases only account for a small part of the prognostically important differences in case-mix between weekday and weekend stroke admissions. While increasing weekend staffing might improve adherence to care standards, evidence that it could save lives is unreliable.

Is health-related quality of life between 90 and 180 days following stroke associated with long-term unmet needs?

PURPOSE

Understanding the relationship between health-related quality of life (HRQoL) and long-term unmet needs is important for guiding services to optimise life following stroke. We investigated whether HRQoL between 90 and 180 days following stroke was associated with long-term unmet needs.

METHODS

Data from Australian Stroke Clinical Registry (AuSCR) registrants who participated in the Australian Stroke Survivor Needs Survey were used. Outcome data, including the EQ-5D, are routinely collected in AuSCR between 90 and 180 days post-stroke. Unmet needs were assessed at a median of 2 years and categorised into: health; everyday living; work/leisure; and support domains. Multivariable regression was used to determine associations between the EQ-5D dimensions and the likelihood of experiencing unmet needs and the visual analogue scale (VAS) (rating 0-100) and number of reported unmet needs.

RESULTS

In total, 173 AuSCR registrants completed the Needs Survey (median age 69 years, 67 % male; 77 % ischaemic stroke). VAS scores were negatively associated with the number of reported long-term unmet needs [irr 0.98, (95 % CI 0.97, 0 99) p < 0.001]. Having EQ-5D activity limitations was associated with unmet living needs (aOR 4.5, 95 % CI 1.1, 18.8). Requiring living supports at 90-180 days was associated with unmet health needs (aOR 4.9, 95 % CI 1.5, 16.1). Those with pain at 90-180 days were less likely to report unmet health (aOR 0.09, 95 % CI 0.02, 0.4) and support needs (aOR 0.2, 95 % CI 0.06, 0.6).

CONCLUSION

Routinely collected HRQoL data can identify survivors at risk of experiencing long-term unmet needs. This information is important for targeting service delivery to optimise outcomes following stroke.

Stroke patients admitted within normal working hours are more likely to achieve process standards and to have better outcomes

BACKGROUND

The presence of a 'weekend' effect has been shown across a range of medical conditions, but has not been consistently observed for patients with stroke.

AIMS

We investigated the impact of admission time on a range of process and outcome measures after stroke.

METHODS

Using routine data from National Scottish data sets (2005-2013), time of admission was categorised into weekday, weeknight and weekend/public holidays. The main process measures were swallow screen on day of admission (day 0), brain scan (day 0 or 1), aspirin (day 0 or 1), admission to stroke unit (day 0 or 1), and thrombolysis administration. After case-mix adjustment, multivariable logistic regression was used to estimate the OR for mortality and discharge to home/usual place of residence.

RESULTS

There were 52,276 index stroke events. Compared to weekday, the adjusted OR (95%CI) for early stroke unit admission was 0.81 (0.77 to 0.85) for weeknight admissions and 0.64 (0.61 to 0.67) for weekend/holiday admissions; early brain scan 1.30 (0.87 to 1.94) and 1.43 (0.95 to 2.18); same day swallow screen 0.86 (0.81 to 0.91) and 0.85 (0.81 to 0.90); thrombolysis 0.85 (0.75 to 0.97) and 0.85 (0.75 to 0.97), respectively. Seven-day mortality, 30-day mortality and 30-day discharge for weekend admission compared to weekday was 1.17 (1.05 to 1.30); 1.08 (1.00 to 1.17); and 0.90 (0.85 to 0.95), respectively.

CONCLUSIONS

Patients with stroke admitted out of hours and at weekends or public holidays are less likely to be managed according to current guidelines. They experience poorer short-term outcomes than those admitted during normal working hours, after correcting for known independent predictors of outcome and early mortality.

The impact of stroke unit care on outcome in a Scottish stroke population, taking into account case mix and selection bias

BACKGROUND AND AIM

Randomised trials indicate that stroke unit care reduces morbidity and mortality after stroke. Similar results have been seen in observational studies but many have not corrected for selection bias or independent predictors of outcome. We evaluated the effect of stroke unit compared with general ward care on outcomes after stroke in Scotland, adjusting for case mix by incorporating the six simple variables (SSV) model, also taking into account selection bias and stroke subtype.

METHODS

We used routine data from National Scottish datasets for acute stroke patients admitted between 2005 and 2011. Patients who died within 3 days of admission were excluded from analysis. The main outcome measures were survival and discharge home. Multivariable logistic regression was used to estimate the OR for survival, and adjustment was made for the effect of the SSV model and for early mortality. Cox proportional hazards model was used to estimate the hazard of death within 365 days.

RESULTS

There were 41 692 index stroke events; 79% were admitted to a stroke unit at some point during their hospital stay and 21% were cared for in a general ward. Using the SSV model, we obtained a receiver operated curve of 0.82 (SE 0.002) for mortality at 6 months. The adjusted OR for survival at 7 days was 3.11 (95% CI 2.71 to 3.56) and at 1 year 1.43 (95% CI 1.34 to 1.54) while the adjusted OR for being discharged home was 1.19 (95% CI 1.11 to 1.28) for stroke unit care.

CONCLUSIONS

In routine practice, stroke unit admission is associated with a greater likelihood of discharge home and with lower mortality up to 1 year, after correcting for known independent predictors of outcome, and excluding early non-modifiable mortality.

Differences in Wake-up and Unknown Onset Stroke Examined in a Stroke Registry

Introduction

Debate exists as to whether wake-up stroke (WUS) (i.e. symptoms first noted on waking) differs from stroke developing while awake [awake onset stroke (AOS)]. Unknown onset stroke (UOS) with unclear symptom onset time is infrequently studied.

Aims

This study aimed to examine differences in stroke characteristics and outcomes in these three groups.

Methods

The stroke registry database from Halifax Infirmary, Canada, was interrogated for hospitalised stroke patients between 1999–2011. Information was available on demographics, stroke characteristics, and functional status at discharge and six months (modified Rankin score [mRS]).

Results

Of 3890 patients, 65% had AOS, 21% WUS and 14% UOS. UOS patients were significantly older, more commonly female and living alone than AOS patients, with no difference between AOS and WUS. UOS rates increased from 10 to 16% of patients during the study period ( P < 0·0001). UOS but not WUS had a higher stroke severity than AOS. Intracerebral hemorrhage was less common (9 vs. 13%) and lacunar stroke more common (23 vs. 19%) in WUS compared to AOS. In UOS left hemisphere location was more likely, and lacunar stroke less common. Excellent outcomes were slightly lower for WUS. UOS had significantly higher rates of in-hospital mortality (23 vs. 16%, P < 0·0001) and poorer functional outcome six months after stroke (mRS < 3 in 26% of UOS and 46% of AOS, P = 0·02).

Conclusion

WUS has lower rates of ICH but similar stroke severity and outcomes to AOS. UOS prevalence appears to be increasing, with higher stroke severity and worse prognosis.

Comparison of statistical and clinical predictions of functional outcome after ischemic stroke

Background

To determine whether the predictions of functional outcome after ischemic stroke made at the bedside using a doctor’s clinical experience were more or less accurate than the predictions made by clinical prediction models (CPMs).

Methods and Findings

A prospective cohort study of nine hundred and thirty one ischemic stroke patients recruited consecutively at the outpatient, inpatient and emergency departments of the Western General Hospital, Edinburgh between 2002 and 2005. Doctors made informal predictions of six month functional outcome on the Oxford Handicap Scale (OHS). Patients were followed up at six months with a validated postal questionnaire. For each patient we calculated the absolute predicted risk of death or dependence (OHS≥3) using five previously described CPMs. The specificity of a doctor’s informal predictions of OHS≥3 at six months was good 0.96 (95% CI: 0.94 to 0.97) and similar to CPMs (range 0.94 to 0.96); however the sensitivity of both informal clinical predictions 0.44 (95% CI: 0.39 to 0.49) and clinical prediction models (range 0.38 to 0.45) was poor. The prediction of the level of disability after stroke was similar for informal clinical predictions (ordinal c-statistic 0.74 with 95% CI 0.72 to 0.76) and CPMs (range 0.69 to 0.75). No patient or clinician characteristic affected the accuracy of informal predictions, though predictions were more accurate in outpatients.

Conclusions

CPMs are at least as good as informal clinical predictions in discriminating between good and bad functional outcome after ischemic stroke. The place of these models in clinical practice has yet to be determined.

The association of CHA2DS2-VASc score and blood biomarkers with ischemic stroke outcomes: the Belgrade stroke study

BACKGROUND

Many blood biomarkers have a positive association with stroke outcome, but adding blood biomarkers to the National Institutes of Health Stroke Scale (NIHSS) did not significantly improve its discriminatory ability. We investigated the association of the CHA2DS2-VASc score with unfavourable functional outcome (defined as a 30-day modified Rankin Scale [mRS] ≥ 3) in patients presenting with acute ischemic stroke (AIS), and examined whether the addition of blood biomarkers (troponin I [TnI], fibrinogen, C-reactive protein [CRP]) affects the model discriminatory ability.

METHODS

We conducted an observational single-centre study of consecutive patients with AIS. All patients were admitted to hospital within 24 hours from the neurological symptoms onset.

RESULTS

Of 240 patients (mean age 70.0 ± 8.9 years), unfavourable 30-day outcome occurred in 92 (38.3%). Patients with mRS ≥ 3 were older and more likely to have atrial fibrillation or other comorbidities (all p<0.001). They had higher levels of CRP, fibrinogen, TnI and higher CHA2DS2-VASc and CHADS2 scores (all p<0.05). The adjusted CHA2DS2-VASc score had excellent predictive ability for poor stroke outcome (c-statistic 0.982;95%CI,0.964-1.000, p<0.001). Whilst CRP had the highest sensitivity (83.7%), cardiac TnI was the most specific (97.3%) for prediction of poor stroke outcome (cut-off: >0.09 µg/L). Compared with each of these biomarkers, CHA2DS2-VASc score had significantly better predictive ability for poor stroke outcome (c-statistic for CRP, Fibrinogen and TnI was 0.853;95%CI,0.802-0.895, 0.848;95%CI,0.796-0.891, and 0.792;95%CI,0.736-0.842, all p<0.001, respectively, versus 0.932;95%CI,0.892-0.960, p<0.001 for the CHA2DS2-VASc, all p for the comparisons<0.01). There was no significant difference in the predictive ability of the CHA2DS2-VASc score vs. combinations of the CHA2DS2-VASc and TnI or TnI, fibrinogen and CRP (z statistic 0.369, p = 0.7119; integrated discrimination index 0.00801 and 0.00172, respectively, both p>0.05).

CONCLUSIONS

The CHA2DS2-VASc score alone reliably predicts 30-day unfavourable outcome of stroke. Adding blood biomarkers to the CHA2DS2-VASc score did not significantly increase the predictive ability of the model.

Formal and informal prediction of recurrent stroke and myocardial infarction after stroke: a systematic review and evaluation of clinical prediction models in a new cohort

BACKGROUND

The objective of this study was to: (1) systematically review the reporting and methods used in the development of clinical prediction models for recurrent stroke or myocardial infarction (MI) after ischemic stroke; (2) to meta-analyze their external performance; and (3) to compare clinical prediction models to informal clinicians' prediction in the Edinburgh Stroke Study (ESS).

METHODS

We searched Medline, EMBASE, reference lists and forward citations of relevant articles from 1980 to 19 April 2013. We included articles which developed multivariable clinical prediction models for the prediction of recurrent stroke and/or MI following ischemic stroke. We extracted information to assess aspects of model development as well as metrics of performance to determine predictive ability. Model quality was assessed against a pre-defined set of criteria. We used random-effects meta-analysis to pool performance metrics.

RESULTS

We identified twelve model development studies and eleven evaluation studies. Investigators often did not report effective sample size, regression coefficients, handling of missing data; typically categorized continuous predictors; and used data dependent methods to build models. A meta-analysis of the area under the receiver operating characteristic curve (AUROCC) was possible for the Essen Stroke Risk Score (ESRS) and for the Stroke Prognosis Instrument II (SPI-II); the pooled AUROCCs were 0.60 (95% CI 0.59 to 0.62) and 0.62 (95% CI 0.60 to 0.64), respectively. An evaluation among minor stroke patients in the ESS demonstrated that clinicians discriminated poorly between those with and those without recurrent events and that this was similar to clinical prediction models.

CONCLUSIONS

The available models for recurrent stroke discriminate poorly between patients with and without a recurrent stroke or MI after stroke. Models had a similar discrimination to informal clinicians' predictions. Formal prediction may be improved by addressing commonly encountered methodological problems.

Interleukin-6, a reliable prognostic factor for ischemic stroke

BACKGROUND

Interleukin-6 (IL-6) is one of the inflammatory mediators characterized by elevated levels in ischemic stroke (IS) patients. The present study set out to assess the role of IL-6, as a marker for inflammation, in the severity and prognosis of acute IS.

METHODS

In a cross-sectional descriptive study, 45 patients with acute IS were selected. Patients with their first day of stroke were included in the study. National Institutes of Health Stroke Scale (NIHSS) and the modified Rankin Scale (mRS) for stroke severity were evaluated on Days 1, 5, 90, and 365. Serum IL-6 level was measured by enzyme-linked immunosorbent assay (ELISA) on days 1 and 5.

RESULTS

In the present study, 45 patients with a mean age of 77.6 ± 4.9 including 32 (71%) men and 13 (28.9%) women were studied. Death occurred in 2 (4.4%) patients before discharge from the hospital; the others, be that as it may, followed the study until Day 365 with a mortality rate of 6 (13.3%). A positive significant correlation was found between IL-6, and NIHSS and mRS of the patients from the time of admission to the end of the follow-up period (P < 0.001, r = 0.6). Moreover, there was a significant correlation between IL-6 and infarction size in brain magnetic resonance imaging (MRI) scan (P < 0.001, r = 0.7).

CONCLUSION

The evidence from the present study suggests that IL-6 contributes to determination of severity of ischemic stroke. In addition, IL-6 concentrations affect clinical outcomes in ischemic stroke.

Predicting outcomes after transient ischemic attack and stroke

PURPOSE OF REVIEW

Predicting functional outcome and mortality after stroke, with or without thrombolysis, is a critical role of neurologists. This article reviews the predictors of outcome after ischemic stroke.

RECENT FINDINGS

Several scores were recently designed to predict (1) mortality and poor functional outcome after ischemic stroke, (2) the functional outcome and risk of symptomatic intracranial hemorrhage (sICH) after thrombolysis, and (3) the risk of stroke following TIA. Validation of these prediction instruments is ongoing, and studies will be critical to determine the general applicability of these scores.

SUMMARY

Although several scores were developed to predict mortality and outcome after stroke, it may be premature to employ these prediction scores to determine individual patient outcome. Similarly, prediction scores should not be used to deny patients tissue plasminogen activator (tPA), even if the scores predict that the patient has a high likelihood of sICH or poor outcome after thrombolysis.

The relevance of living supports on antiplatelet adherence and trial participation: the SPS3 trial

BACKGROUND

While living with others has been associated with improved functional outcome after acute stroke, it is unclear if this affects adherence to stroke prevention measures.

AIMS

We examined the relationship between living arrangements and adherence to antiplatelet therapy assignment and participation status in an international randomized trial for secondary stroke prevention.

METHOD

Antiplatelet therapy adherence, trial retention outcomes, and baseline characteristics for participants enrolled in the Secondary Prevention of Small Subcortical Strokes study were compared between those who lived alone vs. with others (n = 2374). Participant status at end-of-trial was categorized into (1) on assigned antiplatelet, (2) off assigned antiplatelet by participant request, or (3) participant withdrew consent/lost to follow-up. Multivariable multivariate logistic regression was used to identify patient features at entry predictive of participant status at trial end.

RESULTS

Living arrangement, alone vs. with other(s), was not significantly associated with participant status. Participants enrolled in the United States/Canada (odds ratio 3.1, confidence intervals 2.0-5.0, vs. Latin America), taking more (7+) prescription medications (odds ratio 1.7, confidence intervals 1.1-2.7, vs. 0-2 medications), and scoring lower on the Stroke Specific Quality of Life scale (odds ratio 1.3, confidence intervals 1.1-1.5, per 10 points) were more likely to withdraw or become lost to follow-up in the study vs. completing the study on assigned antiplatelet therapy. Participants enrolled in the United States/Canada (odds ratio 5.0, confidence intervals 2.4-10.0, vs. Latin America) and taking fewer (0-2) medications (odds ratio 1.9, confidence intervals 1.2-3.1 vs. 3-6 medications) were more likely to request discontinuation of assigned antiplatelet medication vs. completing the study.

CONCLUSION

Living with others was not independently predictive of protocol adherence in this cohort. Number of medications and Stroke Specific Quality of Life scale score may be more indicative of likelihood of trial participation and acceptance of long-term antiplatelet regimen.

Predictors of early mortality in patients with ischemic stroke

Accurate predictors of early outcome in stroke patients have a number of important applications, such as introducing secondary prevention strategies, supporting treatment decisions or designing randomized clinical trials. Surprisingly, a generally accepted, reliable and well-validated mortality-prediction model is still unavailable. This review outlines the most important predictors of in-hospital mortality that could be assessed at admission to hospital emergency room within 24 h of ischemic stroke onset. A number of factors are discussed such as nonmodifiable factors (e.g., age, gender and genetic factors); type of stroke and its severity - measured by different clinical score scales; predictive models; laboratory markers; special neuroradiological and neurophysiological tests; and comorbid conditions at admission and quality of hospital care.

Simple variables predict miserable outcome after intravenous thrombolysis

BACKGROUND AND PURPOSE

To test the predictability of miserable outcome amongst ischaemic stroke patients receiving intravenous thrombolysis (IVT) based on a simple variables model (SVM) and to compare the model's predictive performance with that of an existing score which includes imaging and laboratory parameters (DRAGON).

METHODS

The SVM consists of the parameters age, independence before stroke, normal Glasgow coma verbal score, able to lift arms and able to walk. In a derivation cohort (n = 1346) and a validation cohort (n = 638) of consecutive IVT-treated stroke patients, the probability estimated by SVM and the observed occurrence of miserable 3-month outcome (modified Rankin score 5-6) were compared. The performances of SVM and the DRAGON score were compared. The area under the receiver operating curve (AUC) (95% confidence interval, CI) and the bootstrapping approach were used to compare the predictive performance.

RESULTS

The AUCs to predict miserable outcome in the derivation cohort were 0.807 (95% CI 0.774-0.838) using the SVM and 0.822 (0.790-0.850) using the DRAGON score (P = 0.3). For the validation cohort, AUCs were 0.786 (0.742-0.829) for the SVM and 0.809 (0.774-0.845) for the DRAGON score (P = 0.23). Only one patient with an SVM probability of >70% for miserable outcome in either cohort had a good outcome whilst 83% had a miserable outcome. An online SVM calculator to estimate the probability of miserable outcome for individual patients is available under http://www.unispital-basel.ch/SVM-Tool.

CONCLUSION

The SVM was similar in accuracy to the DRAGON score for predicting miserable outcome after IVT. As these simple variables are available already at the pre-hospital stage, the SVM may facilitate and accelerate pre-hospital triage of patients at high risk for miserable outcome after IVT towards endovascular treatment.

Predictive value of circulating interleukin-6 and heart-type fatty acid binding protein for three months clinical outcome in acute cerebral infarction: multiple blood markers profiling study

Introduction

There is no single blood marker for predicting the prognosis in ischemic stroke. A combination of multiple blood markers may enhance the ability to predict long-term outcome following ischemic stroke.

Methods

Blood concentrations of neuronal markers (neuron-specific enolase, visinin-like protein 1, heart type fatty acid binding protein (hFABP) and neuroglobin), astroglial markers (S100B and glial fibrillary acidic protein), inflammatory markers (IL-6, TNF-α, and C-reactive protein), blood-brain barrier marker (matrix metalloproteinase 9), and haemostatic markers (D-dimer and PAI-1) were measured within 24 hours after stroke onset. The discrimination and reclassification for favorable and poor outcome were compared after adding individual or a combination of blood markers to the clinical model of stroke outcome.

Results

In multivariate analysis, natural log-transformed (_log) IL-6 (odds ratio (OR): 1.75, 95% CI: 1.25 to 2.25, P = 0.001) and _loghFABP (OR: 3.23, 95% CI: 1.44 to 7.27, P = 0.005) were independently associated with poor outcome. The addition of a single blood marker to the clinical model did not improve the discriminating ability of the clinical model of stroke outcome. However, the addition of the combination of _logIL-6 and _loghFABP to the clinical model showed improved discrimination (area under receiver operating characteristic (AUROC) curve: 0.939 versus 0.910, P = 0.03) and reclassification performance (net reclassification improvement index: 0.18, P = 0.005).

Conclusions

A combination of circulating IL-6 and hFABP level has an additive clinical value for the prediction of stroke outcome.

Blood Biomarkers in Stroke: Research and Clinical Practice

Blood biomarkers may have applications in stroke diagnosis, outcome prediction, or treatment. In this article, we provide a focused review on some of the methodological challenges and potential developments of biomarkers in stroke. We review the approaches to the development of a diagnostic blood marker: a candidate marker approach, marker panels, and –omics. Then we examined the role of blood markers to predict recurrent stroke and treatment response in stroke.

The Use of Blood Biomarkers to Predict Poor Outcome After Acute Transient Ischemic Attack or Ischemic Stroke

Background and Purpose—

The prediction of death or disability (“poor outcome”) after stroke by validated clinical models might be improved by the addition of blood biomarker measurements. We investigated whether such measurements improved the classification of patients into 4 categories of predicted risk of poor outcome: very high, intermediate high, intermediate low, and very low.

Methods—

We prospectively recruited symptomatic patients within 24 hours of ischemic cerebrovascular events. We measured clinical prognostic variables in each patient. We drew blood soon after admission and measured markers of inflammation, thrombosis, cardiac strain, and cerebral damage. We assessed poor outcome at 3 months with the modified Rankin Scale and recovery of symptoms at 24 hours. We measured the association between blood marker levels and poor outcome after adjustment for stroke severity and age with multivariate logistic regression. Where these associations were statistically significant, we calculated the net reclassification index.

Results—

We recruited 270 patients with acute ischemic cerebrovascular events. At 3 months, 112 patients had a poor outcome. After adjustment for stroke severity and age, only interleukin-6 and N-terminal pro-brain natriuretic peptide were significantly associated with poor outcome. The addition of either interleukin-6 or N-terminal pro-brain natriuretic peptide to National Institutes of Health Stroke Scale and age did not improve the prediction of a poor outcome.

Conclusions—

Neither interleukin-6 nor N-terminal pro-brain natriuretic peptide had sufficient predictive power to be of clinical use to predict poor outcome after stroke. The search for better markers to improve the classification of patients across clinically relevant boundaries of predicted probabilities of outcome events needs to continue.

Factors associated with functional recovery and home discharge in stroke patients admitted to a convalescent rehabilitation ward

AIMS

This study aimed to determine the predictive factors for functional recovery and home discharge in stroke patients receiving in-hospital rehabilitation.

METHODS

This study included a consecutive series of 174 stroke patients (average age 73.0 ± 10.8) admitted to the convalescent rehabilitation ward at Azumino Red Cross Hospital in Japan after acute rehabilitation. The main outcome measures were functional recovery (functional independence measure [FIM] at discharge and Montebello rehabilitation factor score [MRFS]) and home discharge.

RESULTS

Total FIM improved from 72.6 ± 27.6 to 87.7 ± 29.9 during the hospital stay (P < 0.001). The average MRFS was 0.30 ± 0.28. Of the 174 patients, 151 were discharged home (87%). Age, stroke type, premorbid independence, motor FIM, and cognitive FIM at admission showed a significant association with FIM at discharge, while age, premorbid independence, motor FIM at admission, and cognitive FIM at admission were statistically significant predictors of MRFS. Female sex, not living with family, premorbid independence, and neglect were negatively associated with home discharge.

CONCLUSIONS

Premorbid disability and cognitive dysfunction at admission were both negatively associated with functional recovery and home discharge in patients undergoing inpatient stroke rehabilitation.

Predicting acute ischaemic stroke outcome using clinical and temporal thresholds

Background. Few studies have analysed the natural course of cerebral ischaemia for predicting outcome. We aimed to determine the early clinical findings and the thresholds for deficit severity and symptom duration that make it possible to stratify outcome. Methods. We included 154 patients with transient ischaemic attack or ischaemic stroke. Stroke profiles and neurological status were assessed from onset to 24 hrs, on admission, at 48 hrs, and at discharge. Outcomes were evaluated using the modified Rankin Scale. Positive and negative predictive values were calculated for the different thresholds. The model was subsequently evaluated on a new prospective cohort of 157 patients. Results. Initial National Institute of Health Stroke Scale (NIHSS) score <5 and symptoms regressing within 135 min were predictive of good outcome. Initial NIHSS score >22 and symptom stability after 1,230 min were predictive of physical dependency or death. Conclusions. Low and high NIHSS cut-off points are effective positive predictive values for good and poor outcomes. Thresholds for symptom duration are less conclusive.

Association of circulating inflammatory markers with recurrent vascular events after stroke: a prospective cohort study

BACKGROUND AND PURPOSE

inflammatory markers may be associated with recurrent vascular events after stroke. We aimed to determine the association between IL-6, C-reactive protein, fibrinogen and white cell count, with recurrent vascular events after stroke, and to compare the association between circulating inflammatory markers with the risk of death from vascular vs nonvascular causes.

METHODS

we prospectively recruited patients with acute stroke (n=817) and followed them for up to 4 years for the occurrence of fatal or nonfatal recurrent stroke, myocardial infarction or fatal vascular events, and death from any cause (n=159).

RESULTS

the delay to assessment was a median of 10 days. The adjusted incidence of the outcome cluster recurrent stroke, myocardial infarction or vascular death after stroke was significantly higher with higher levels of IL-6 (75(th) to 25(th) percentile hazard ratio, 1.56; 95% CI, 1.37-1.77), C-reactive protein (75(th) to 25(th) percentile hazard ratio, 1.08; 95% CI, 1.04-1.11), and fibrinogen (75(th) to 25(th) percentile hazard ratio, 1.45; 95% CI, 1.24-1.72). The associations between inflammatory markers and death were stronger than with recurrent vascular events. The associations of inflammatory markers with vascular and nonvascular deaths were similar.

CONCLUSIONS

although inflammatory markers were associated with an increased risk of recurrent vascular events and vascular death after stroke, they were also associated with nonvascular causes of death, suggesting that inflammatory markers do not play a causal role specifically in the generation of recurrent vascular events after stroke. Future studies of the prediction of recurrent vascular events after stroke should concentrate on clinical variables or different blood markers.

Selecting patients for rehabilitation after acute stroke: are there variations in practice?

OBJECTIVE

To investigate whether there were variations in practice in selection for rehabilitation after stroke, after adjustment for case mix.

DESIGN

Prospective multicenter audit.

SETTING

Seven acute stroke units in metropolitan and regional Victoria, Australia.

PARTICIPANTS

Consecutive acute stroke admissions (N=616).

INTERVENTIONS

None.

MAIN OUTCOME MEASURES

Mobility Scale for Acute Stroke Score and Modified Barthel Index (MBI) scores for continence at day 3 poststroke, discharge destination from the acute hospital.

RESULTS

Data were analyzed for 616 stroke survivors. Considerable variability in the percentage of cases accessing inpatient rehabilitation was observed in severe stroke (27%-67%) and mild stroke (27%-73%). To assess adjustment for case mix, a multinomial logistic regression was conducted with the outcome variable being discharge destination (home, rehabilitation, or nursing home), and the predictors being Mobility Scale for Acute Stroke Score, MBI continence scores, age, and social situation. The overall amount of variability explained in discharge destination by the predictors was 63% (Nagelkerke pseudo R(2)). The regression analysis was repeated, adding unit code as a predictor. Unit code was a significant contributor to the model (P<.01).

CONCLUSION

The results of the study indicate that, after adjusting for case mix, there may be variations in practice in selection for rehabilitation leading to inequities of access.

Predicting functional outcome after stroke by modelling baseline clinical and CT variables

BACKGROUND

we aimed to assess whether the performance of stroke outcome models comprising simple clinical variables could be improved by the addition of more complex clinical variables and information from the first computed tomography (CT) scan.

METHODS

538 consecutive acute ischaemic and haemorrhagic stroke patients were enrolled in a Stroke Outcome Study between 2001 and 2002. Independent survival (modified Rankin scale <or=2) was assessed at 6 months. Models based on clinical and radiological variables from the first assessment were developed using multivariate logistic regression analysis.

RESULTS

three models were developed (I-III). Model I included age, pre-stroke independence, arm power and a stroke severity score (area under a receiver operating characteristic curve, AUC = 0.882) but performed no better than Model II, which comprised age, pre-stroke independence, normal verbal component of the Glasgow coma score, arm power and being able to walk without assistance (AUC 0.876). Model III, including two radiological variables and clinical variables, was not statistically superior to model II (AUC 0.901, P = 0.12). Model II was externally validated in two independent datasets (AUCs of 0.773 and 0.787).

CONCLUSION

this study demonstrates an externally validated stroke outcome prediction model using simple clinical variables. Outcome prediction was not significantly improved with CT-derived radiological variables or more complex clinical variables.

Clinical application of blood biomarkers in cerebrovascular disease

Identifying a biomarker or panel of biomarkers of cerebral ischemia would have a major impact on the care of stroke patients by facilitating early management decisions and individualization of care. Biochemical surrogates of cerebral ischemia might also play an important role by identifying relevant pathways for novel therapeutic strategies and by facilitating early clinical trials in cerebrovascular disease. Serum biomarkers related to pathways of hemostasis, oxidation and inflammation, or alterations in glial and neuronal proteins, have been identified but none have been recommended for routine clinical use. This review describes the most promising biomarkers of cerebrovascular disease and the context and limitations in which they have been studied.