Derivation and validation of a simple risk score for predicting 1-year mortality in stroke

Age-Specific Association of Co-Morbidity With Home-Time After Acute Stroke

OBJECTIVE

To examine the association of co-morbidity with home-time after acute stroke and whether the association is influenced by age.

METHODS

We conducted a province-wide study using linked administrative databases to identify all admissions for first acute ischemic stroke or intracerebral hemorrhage between 2007 and 2018 in Alberta, Canada. We used ischemic stroke-weighted Charlson Co-morbidity Index of 3 or more to identify those with severe co-morbidity. We used zero-inflated negative binomial models to determine the association of severe co-morbidity with 90-day and 1-year home-time, and logistic models for achieving ≥ 80 out of 90 days of home-time, assessing for effect modification by age and adjusting for sex, stroke type, comprehensive stroke center care, hypertension, atrial fibrillation, year of study, and separately adjusting for estimated stroke severity. We also evaluated individual co-morbidities.

RESULTS

Among 28,672 patients in our final cohort, severe co-morbidity was present in 27.7% and was associated with lower home-time, with a greater number of days lost at younger age (-13 days at age < 60 compared to -7 days at age 80+ years for 90-day home-time; -69 days at age < 60 compared to -51 days at age 80+ years for 1-year home-time). The reduction in probability of achieving ≥ 80 days of home-time was also greater at younger age (-22.7% at age < 60 years compared to -9.0% at age 80+ years). Results were attenuated but remained significant after adjusting for estimated stroke severity and excluding those who died. Myocardial infarction, diabetes, and cancer/metastases had a greater association with lower home-time at younger age, and those with dementia had the greatest reduction in home time.

CONCLUSION

Severe co-morbidity in acute stroke is associated with lower home-time, more strongly at younger age.

Association of co-morbidity with acute stroke mortality by age and time since stroke: A population-based study

OBJECTIVE

To examine whether the association of co-morbidity with mortality after acute stroke is influenced by stroke type, age, sex, or time since stroke.

MATERIALS AND METHODS

We conducted a province-wide population-based study using linked administrative databases to identify all admissions for acute stroke between 2007-2018 in Alberta, Canada. We used Cox proportional hazard models to determine the association of severe co-morbidity based on the Charlson Co-morbidity Index with 1-year mortality after stroke, assessing for effect modification by stroke type, age, and sex, and with adjustment for estimated stroke severity, comprehensive stroke centre care, hypertension, atrial fibrillation, and year of study. We used a piecewise model to analyze the impact of co-morbidity across four time periods.

RESULTS

We had 28,672 patients in our final cohort (87.8% ischemic stroke). The hazard of mortality with severe co-morbidity was higher for individuals with ischemic stroke (adjusted hazard ratio [aHR] 2.20, 95% CI 2.07-2.32) compared to those with intracerebral hemorrhage (aHR 1.70, 95% CI 1.51-1.92; pint<0.001), and higher in individuals under age 75 (aHR 3.20, 95% CI 2.90-3.53) compared to age ≥75 (aHR 1.93, 95% CI 1.82-2.05, pint<0.001). There was no interaction by sex. The hazard ratio increased in a graded fashion at younger ages and was higher after the first 30 days of acute stroke.

CONCLUSION

There was a stronger association between co-morbidity and mortality at younger age and in the subacute phase of stroke. Further research is needed to determine the reason for these findings and identify ways to improve outcomes among those with stroke and co-morbid conditions at young age.

Mortality after large artery occlusion acute ischemic stroke

Despite randomized trials showing a functional outcome benefit in favor of endovascular therapy (EVT), large artery occlusion acute ischemic stroke is associated with high mortality. We performed a retrospective analysis from a prospectively collected code stroke registry and included patients presenting between November 2016 and April 2019 with internal carotid artery and/or proximal middle cerebral artery occlusions. Ninety-day mortality status from registry follow-up was corroborated with the Social Security Death Index. A multivariable logistic regression model was fitted to determine demographic and clinical characteristics associated with 90-day mortality. Among 764 patients, mortality rate was 26%. Increasing age (per 10 years, OR 1.48, 95% CI 1.25–1.76; p < 0.0001), higher presenting NIHSS (per 1 point, OR 1.05, 95% CI 1.01–1.09, p = 0.01), and higher discharge modified Rankin Score (per 1 point, OR 4.27, 95% CI 3.25–5.59, p < 0.0001) were independently associated with higher odds of mortality. Good revascularization therapy, compared to no EVT, was independently associated with a survival benefit (OR 0.61, 95% CI 0.35–1.00, p = 0.048). We identified factors independently associated with mortality in a highly lethal form of stroke which can be used in clinical decision-making, prognostication, and in planning future studies.

A Dynamic Model for Predicting Survival up to 1 Year After Ischemic Stroke

BACKGROUND

This study developed and validated a dynamic prediction model for survival after ischaemic stroke up to 1 year.

METHODS

Patients with stroke (n = 425) who participated in a sub-study (2002-2004) from the South London Stroke Register (SLSR) were selected for model derivation. The model was developed using the extended Cox model with time-dependent covariates. The two temporal validation cohorts from SLSR included 1735 (1995-2002) and 2155 patients (2004-2016). The discrimination, calibration and clinical utility of the model were assessed.

RESULTS

Six strong predictors were used in the model, namely, age, sex, stroke subtype, stroke severity and pre-stroke and post-stroke disabilities. The c-statistics was 0.822 at 1 year in the derivation cohort. The model had a fair performance with prognostic accuracies of 77%-83% in the validation 1 cohort and 70%-75% in the validation 2 cohort. A good calibration was observed in the derivation cohort.

CONCLUSION

The proposed model can accurately predict survival up to 1 year after ischaemic stroke.

Predicting Early Mortality of Acute Ischemic Stroke

Background and Purpose—

Several risk factors are known to increase mid- and long-term mortality of ischemic stroke patients. Information on predictors of early stroke mortality is scarce but often requested in clinical practice. We therefore aimed to develop a rapidly applicable tool for predicting early mortality at the stroke unit.

Methods—

We used data from the nationwide Austrian Stroke Unit Registry and multivariate regularized logistic regression analysis to identify demographic and clinical variables associated with early (≤7 days poststroke) mortality of patients admitted with ischemic stroke. These variables were then used to develop the Predicting Early Mortality of Ischemic Stroke score that was validated both by bootstrapping and temporal validation.

Results—

In total, 77 653 ischemic stroke patients were included in the analysis (median age: 74 years, 47% women). The mortality rate at the stroke unit was 2% and median stay of deceased patients was 3 days. Age, stroke severity measured by the National Institutes of Health Stroke Scale, prestroke functional disability (modified Rankin Scale >0), preexisting heart disease, diabetes mellitus, posterior circulation stroke syndrome, and nonlacunar stroke cause were associated with mortality and served to build the Predicting Early Mortality of Ischemic Stroke score ranging from 0 to 12 points. The area under the curve of the score was 0.879 (95% CI, 0.871–0.886) in the derivation cohort and 0.884 (95% CI, 0.863–0.905) in the validation sample. Patients with a score ≥10 had a 35% (95% CI, 28%–43%) risk to die within the first days at the stroke unit.

Conclusions—

We developed a simple score to estimate early mortality of ischemic stroke patients treated at a stroke unit. This score could help clinicians in short-term prognostication for management decisions and counseling.

Visual field defect after ischemic stroke-impact on mortality

OBJECTIVES

We aimed to investigate the impact of visual field defects (VFD) on mortality in ischemic stroke patients.

MATERIALS AND METHODS

All patients with acute infarction and a clinically detected VFD from February 2006 to December 2013 in the NORSTROKE Registry (n = 506) were included and compared with ischemic stroke patients with normal visual fields (n = 2041). A record of patients who had died per ultimo April 2015 was obtained from the central registry at Haukeland University Hospital.

RESULTS

Patients with VFD were significantly older (75.0 vs 69.8, P < .001) than patients with normal visual fields. The majority of patients with VFD was male, had higher cardiovascular morbidity prestroke, and were more likely to have shorter median time from symptom onset to admission (1.7 hours vs 2.7 hours, P < .001). Baseline National Institute of Health Stroke Scale (NIHSS) score was higher (12.7 vs 3.5, P < .001) as was modified Rankin Scale (mRS) score (3.5 vs 1.9, P < .001) and Barthel Index was lower (51.9 vs 84.8, P < .001) day 7. VFD was associated with increased mortality on Kaplan-Meier plots. Hazard ratio was significantly higher for patients with VFD after adjusting for age, sex, employment prior to infarction, married prior to infarction, institutionalization prior to infarction, prior myocardial infarction, atrial fibrillation, smoking, Barthel Index score and i.v. thrombolysis with Cox regression (hazard ratios [HR] 1.30, CI 1.07-1.56, P = .007).

CONCLUSIONS

Having a visual field defect after ischemic stroke is independently associated with increased mortality. This should be addressed when selecting candidates for thrombolysis and in the rehabilitation process.

Multimorbidities Are Associated to Lower Survival in Ischaemic Stroke: Results from a Brazilian Stroke Cohort (EMMA Study)

BACKGROUND

Stroke prognosis is related to the multimorbidity profile. Moreover, performing an individual evaluation of most common cerebrovascular risk factors (CVRF) not always identifies patients with poor prognosis. Thus, we decided to evaluate multimorbidity profile, focusing on the Charlson Comorbidity Index (CCI) validated by Goldstein for ischaemic stroke (IS) patients, a score that measures a burden of comorbidities and its related mortality in the long-term survival of the EMMA Study (Study of Stroke Mortality and Morbidity).

METHODS

Nine hundred fifty-nine individuals (median age 70 years) had validated data on the diagnosis of IS, main CVRF and clinical comorbidities pre index event such as atrial fibrillation (AF), stroke recurrence, diabetes, hypertension, heart failure and cancer. CCI modified by Goldstein was calculated, which includes 17 clinical conditions with scores ranging from 1 to 6 (0-31 points). Survival analyses were performed by Kaplan-Meier curves and Cox logistic regression models (cumulative hazard ratio [HR] with [95% CI]) for all-cause mortality at 180 days, and every 3 years up to 9-year follow-up. Mortality analyzes were performed by CCI categorized according to weight added to comorbidities (Reference group: zero, moderate: 1, severe: 2 and very severe: ≥3 points). We also tested the modification effect of AF and stroke recurrence including these conditions in the CCI.

RESULTS

The overall survival rate was 47% (508 deaths/959). The worst survival (577, 95% CI 381-773 days) and the highest risk of death after stroke were observed in the very severe CCI group (HR 3.18; 95% CI 2.16-4.69) up to 9 years. The inclusion of previous AF and stroke in the CCI slightly increased the risk of death for very severe CCI (HR 3.27; 95% CI 2.07-5.18).

CONCLUSIONS

A high burden of comorbidities represented an independent predictor of poor prognosis increasing the risk of dying by 2 to 3 times among IS up to 9 years in the EMMA study. The inclusion of other CVRF such as AF and stroke recurrence slightly modified all-cause mortality risk.

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.

Medical complications experienced by first-time ischemic stroke patients during inpatient, tertiary level stroke rehabilitation

[Purpose] The aim of this study was to assess the medical complications in first-time ischemic stroke patients, to identify the factors related to occurrence of complications. [Subjects and Methods] First-time ischemic stroke patients (n=81) admitted to a tertiary level inpatient rehabilitation center during a 5 year period were included in the study. The attending physiatrist noted the presence of specific medical complications and complications that required transfer to the acute care facility from patient records. The Oxfordshire Community Stroke Project classification was used to define the clinical subtypes of the ischemic stroke patients. The Charlson comorbidity index was used to evaluate co-morbid conditions. Functional disability was assessed using the Functional Independence Measure at admission and discharge. [Results] We found that 88.9% of the patients had at least one complication. The five most common complications were urinary tract infection (48.1%), shoulder pain (37.0%), insomnia (37.0%), depression (32.1%), and musculoskeletal pain other than shoulder pain (32.1%) and 11.1% of patients were transferred to acute care facility during rehabilitation period. Functional Independence Measure scores both at admission and discharge were significantly lower in patients with at least one complication than in patients with no complications. [Conclusion] Medical complications are common among patients undergoing stroke rehabilitation. Close interdisciplinary collaboration between physiatrists and other medical specialities is necessary for optimal management.

Web-based tool for dynamic functional outcome after acute ischemic stroke and comparison with existing models

BACKGROUND

Acute ischemic stroke (AIS) is one of the leading causes of death and adult disability worldwide. In the present study, we aimed to develop a web-based risk model for predicting dynamic functional status at discharge, 3-month, 6-month, and 1-year after acute ischemic stroke (Dynamic Functional Status after Acute Ischemic Stroke, DFS-AIS).

METHODS

The DFS-AIS was developed based on the China National Stroke Registry (CNSR), in which eligible patients were randomly divided into derivation (60%) and validation (40%) cohorts. Good functional outcome was defined as modified Rankin Scale (mRS) score ≤ 2 at discharge, 3-month, 6-month, and 1-year after AIS, respectively. Independent predictors of each outcome measure were obtained using multivariable logistic regression. The area under the receiver operating characteristic curve (AUROC) and plot of observed and predicted risk were used to assess model discrimination and calibration.

RESULTS

A total of 12,026 patients were included and the median age was 67 (interquartile range: 57-75). The proportion of patients with good functional outcome at discharge, 3-month, 6-month, and 1-year after AIS was 67.9%, 66.5%, 66.9% and 66.9%, respectively. Age, gender, medical history of diabetes mellitus, stroke or transient ischemic attack, current smoking and atrial fibrillation, pre-stroke dependence, pre-stroke statins using, admission National Institutes of Health Stroke Scale score, admission blood glucose were identified as independent predictors of functional outcome at different time points after AIS. The DFS-AIS was developed from sets of predictors of mRS ≤ 2 at different time points following AIS. The DFS-AIS demonstrated good discrimination in the derivation and validation cohorts (AUROC range: 0.837-0.845). Plots of observed versus predicted likelihood showed excellent calibration in the derivation and validation cohorts (all r = 0.99, P < 0.001). When compared to 8 existing models, the DFS-AIS showed significantly better discrimination for good functional outcome and mortality at discharge, 3-month, 6-month, and 1-year after AIS (all P < 0.0001).

CONCLUSION

The DFS-AIS is a valid risk model to predict functional outcome at discharge, 3-month, 6-month, and 1-year after AIS.

Derivation and External Validation of a Case Mix Model for the Standardized Reporting of 30-Day Stroke Mortality Rates

Background and Purpose—

Case mix adjustment is required to allow valid comparison of outcomes across care providers. However, there is a lack of externally validated models suitable for use in unselected stroke admissions. We therefore aimed to develop and externally validate prediction models to enable comparison of 30-day post-stroke mortality outcomes using routine clinical data.

Methods—

Models were derived (n=9000 patients) and internally validated (n=18 169 patients) using data from the Sentinel Stroke National Audit Program, the national register of acute stroke in England and Wales. External validation (n=1470 patients) was performed in the South London Stroke Register, a population-based longitudinal study. Models were fitted using general estimating equations. Discrimination and calibration were assessed using receiver operating characteristic curve analysis and correlation plots.

Results—

Two final models were derived. Model A included age (<60, 60–69, 70–79, 80–89, and ≥90 years), National Institutes of Health Stroke Severity Score (NIHSS) on admission, presence of atrial fibrillation on admission, and stroke type (ischemic versus primary intracerebral hemorrhage). Model B was similar but included only the consciousness component of the NIHSS in place of the full NIHSS. Both models showed excellent discrimination and calibration in internal and external validation. The c-statistics in external validation were 0.87 (95% confidence interval, 0.84–0.89) and 0.86 (95% confidence interval, 0.83–0.89) for models A and B, respectively.

Conclusions—

We have derived and externally validated 2 models to predict mortality in unselected patients with acute stroke using commonly collected clinical variables. In settings where the ability to record the full NIHSS on admission is limited, the level of consciousness component of the NIHSS provides a good approximation of the full NIHSS for mortality prediction.

Predicting Clinical Outcomes After Thrombolysis Using the iScore

Background and Purpose—

The ischemic stroke risk score (iScore) is a validated tool developed to estimate the risk of death and functional outcomes early after an acute ischemic stroke. Our goal was to determine the ability of the iScore to estimate clinical outcomes after intravenous thrombolysis tissue-type plasminogen activator (tPA) in the Virtual International Stroke Trials Archive (VISTA).

Methods—

We applied the iScore ( www.sorcan.ca/iscore ) to patients with an acute ischemic stroke within the VISTA collaboration to examine the effect of tPA. We explored the association between the iScore (<200 and ≥200) and the primary outcome of favorable outcome at 3 months defined as a modified Rankin scale score of 0 to 2. Secondary outcomes included death at 3 months, catastrophic outcomes (modified Rankin scale, 4–6), and Barthel index >90 at 3 months.

Results—

Among 7140 patients with an acute ischemic stroke, 2732 (38.5%) received tPA and 711 (10%) had an iScore ≥200. Overall, tPA treatment was associated with a significant improvement in the primary outcome among patients with an iScore <200 (38.9% non-tPA versus 47.5% tPA; P <0.001) but was not associated with a favorable outcome among patients with an iScore ≥200 (5.5% non-tPA versus 7.6% tPA; P =0.45). In the multivariable analysis after adjusting for age, baseline National Institutes of Health Stroke Scale, and onset-to-treatment time, there was a significant interaction between tPA administration and iScore; tPA administration was associated with 47% higher odds of a favorable outcome at 3 months among patients with an iScore <200 (odds ratio, 1.47; 95% confidence interval, 1.30–1.67), whereas the association between tPA and favorable outcome among those with an iScore ≥200 remained nonsignificant (odds ratio, 0.80; 95% confidence interval, 0.45–1.42). A similar pattern of benefit with tPA among patients with an iScore <200, but not ≥200, was observed for secondary outcomes including death.

Conclusions—

The iScore is a useful and validated tool that helps clinicians estimate stroke outcomes. In stroke patients participating in VISTA, an iScore <200 was associated with better outcomes at 3 months after tPA.

Evaluation of IScore validity in a Greek cohort of patients with type 2 diabetes

Background

Diabetes constitutes a risk factor for stroke that also aggravates stroke prognosis. Several prognostic models have been developed for the evaluation of neurologic status, severity, short-term functional outcome and mortality of stroke patients. IScore is a novel tool recently developed in order to predict mortality rates within 30 days and 1 year after ischemic stroke and diabetes is not included in the scoring scale of IScore. The aim of the present study was to evaluate and compare IScore validity in ischemic stroke patients with and without diabetes.

Methods

This prospective study included 312 consecutive Caucasian patients with type 2 diabetes and 222 Caucasian patients without diabetes admitted for ischemic stroke in a tertiary Greek hospital. Thirty-day and 1-year IScores were individually calculated for each patient and actual mortality was monitored at the same time intervals. IScore’s predictive ability and calibration was evaluated and compared for ischemic stroke patients with and without diabetes. The performance of IScore for predicting 30 and 1-year mortality between patients with and without diabetes was assessed by determining the calibration and discrimination of the score. The area under the receiver operating characteristic curve was used to evaluate the discriminative ability of IScore for patients with and without diabetes, whereas the calibration of IScore was assessed by the Hosmer–Lemeshow goodness-of fit statistic.

Results

Baseline population characteristics and mortality rates did not differ significantly for both cohorts. IScore values were significantly higher for patients with diabetes at 30 days and 1 year after ischemic stroke and patients with diabetes presented more frequently with lacunar strokes. Based on ROC curves analysis IScore’s predictive ability for 30 day mortality was excellent, without statistically significant difference, for both cohorts. Predictive ability for 1 year mortality was also excellent for both groups with significantly better ability for patients with diabetes especially at high score values. Calibration of the model was good for both groups of patients.

Conclusions

IScore accurately predicts mortality in acute ischemic stroke Caucasian patients with and without diabetes with higher efficacy in predicting 1 year mortality in patients with diabetes especially with high scores.

Predicting clinical outcomes and response to thrombolysis in acute stroke patients with diabetes

OBJECTIVE

Few tools are available to evaluate clinical outcomes and response to thrombolysis (tPA) in stroke patients with diabetes. We explored how the iScore (www.sorcan.ca/iscore), a validated risk score, predicts clinical outcomes in stroke patients with and without diabetes.

RESEARCH DESIGN AND METHODS

We applied the iScore to stroke patients presenting to stroke centers participating in the Registry of the Canadian Stroke Network. Main outcomes included favorable outcome, defined as a modified Rankin scale (mRS) 0-2 at discharge, and intracerebral hemorrhage (ICH) after tPA.

RESULTS

Among 12,686 patients with an acute ischemic stroke, 3,228 (25.5%) had diabetes. Among patients receiving tPA (n = 1,689), those with diabetes had a lower rate of a favorable outcome compared with their counterparts (24.3 vs. 31.1%; RR 0.90 [95% CI 0.82-0.98]). The risk of ICH was not significantly different in patients with or without diabetes (for any type 12.6 vs. 12.5%, RR 1.01 [0.72-1.40]; for symptomatic ICH 7.5 vs. 6.8%, RR 1.11 [0.70-1.72]). The regression analysis revealed a decline in the probability of a favorable outcome after tPA with increments in the iScore (P value for iScore × tPA interaction <0.001). There was no difference in the response to tPA predicted by the iScore between stroke patients with and without diabetes (P value = 0.07).

CONCLUSIONS

Stroke patients with diabetes have poorer outcomes compared with patients without diabetes, which is not explained by ICH. The iScore similarly predicts response to tPA between stroke patients with and without diabetes.

JURaSSiC: accuracy of clinician vs risk score prediction of ischemic stroke outcomes

OBJECTIVE

We compared the accuracy of clinicians and a risk score (iScore) to predict observed outcomes following an acute ischemic stroke.

METHODS

The JURaSSiC (Clinician JUdgment vs Risk Score to predict Stroke outComes) study assigned 111 clinicians with expertise in acute stroke care to predict the probability of outcomes of 5 ischemic stroke case scenarios. Cases (n = 1,415) were selected as being representative of the 10 most common clinical presentations from a pool of more than 12,000 stroke patients admitted to 12 stroke centers. The primary outcome was prediction of death or disability (modified Rankin Scale [mRS] ≥3) at discharge within the 95% confidence interval (CI) of observed outcomes. Secondary outcomes included 30-day mortality and death or institutionalization at discharge.

RESULTS

Clinicians made 1,661 predictions with overall accuracy of 16.9% for death or disability at discharge, 46.9% for 30-day mortality, and 33.1% for death or institutionalization at discharge. In contrast, 90% of the iScore-based estimates were within the 95% CI of observed outcomes. Nearly half (n = 53 of 111; 48%) of participants were unable to accurately predict the probability of the primary outcome in any of the 5 rated cases. Less than 1% (n = 1) provided accurate predictions in 4 of the 5 cases and none accurately predicted all 5 case outcomes. In multivariable analyses, the presence of patient characteristics associated with poor outcomes (mRS ≥3 or death) in previous studies (older age, high NIH Stroke Scale score, and nonlacunar subtype) were associated with more accurate clinician predictions of death at 30 days (odds ratio [OR] 2.40, 95% CI 1.57-3.67) and with a trend for more accurate predictions of death or disability at discharge (OR 1.85, 95% CI 0.99-3.46).

CONCLUSIONS

Clinicians with expertise in stroke performed poorly compared to a validated tool in predicting the outcomes of patients with an acute ischemic stroke. Use of the risk stroke outcome tool may be superior for decision-making following an acute ischemic stroke.

External validation of the iScore for predicting ischemic stroke mortality in patients in China

BACKGROUND AND PURPOSE

The iScore is a prediction tool developed to estimate the risk of death in patients after hospitalization for an acute ischemic stroke. Our aim was to determine the accuracy of the iScore in patients with ischemic stroke in China.

METHODS

The iScore was used to predict 30-day mortality rate in 11 656 patients and 1-year mortality rate in 11 051 patients with acute ischemic stroke. These patients were identified from the China National Stroke Registry (CNSR) data set. Model discrimination was quantified by calculating the C statistic. The calibration was assessed using Pearson correlation coefficient.

RESULTS

The 30-day and 1-year mortality rates were 5.4% and 14.3%, respectively. The C statistics were 0.825 (95% confidence interval, 0.807-0.843) for 30-day mortality and 0.822 (95% confidence interval, 0.810-0.833) for 1-year mortality. The plots of observed versus predicted mortality rates showed excellent model calibration in the external validation samples from the CNSR (Pearson correlation coefficient, 0.925 for 30-day and 0.998 for 1-year mortality; both P<0.0001).

CONCLUSIONS

The iScore reliably predicts 30-day and 1-year mortality in Chinese patients with ischemic stroke.

The iScore predicts efficacy and risk of bleeding in the National Institute of Neurological disorders and Stroke Tissue Plasminogen Activator Stroke Trial

The iScore is a validated tool to estimate outcomes after an acute ischemic stroke. A previous study showed the iScore can predict clinical response and risk of intracerebral hemorrhage (ICH) after administration of tissue plasminogen activator (tPA). We applied the iScore (www.sorcan.ca/iscore) to participants in the National Institute of Neurological Disorders and Stroke tPA stroke trials to evaluate its ability to estimate clinical response and risk of ICH after thrombolysis. Based on results from our previous study, patients were stratified a priori into iScore <200 and iScore ≥ 200. The main outcome measure was ICH. Secondary outcomes included favorable composite outcome (defined as a modified Rankin Scale score of 0 or 1, National Institutes of Health Stroke Scale score ≤ 1, Barthel Index ≥ 95, or Glasgow Outcome Scale <1 at 3 months) and functional outcomes. The iScore was calculated in all 624 patients enrolled in the trial. The cohort comprised 507 patients (81%) with an iScore <200 and 117 (19%) with an iScore ≥ 200. An iScore ≥ 200 was associated with greater risk of symptomatic ICH in the tPA group compared with the placebo group (15.4% v 3.9%; P = .04). Similar findings were found for ICH of any type (30.8% v 11.5%; P = .014), with higher ICH mortality (69.2% v 23.8%; P < .001). Despite the higher favorable composite outcome of tPA therapy in patients with an iScore <200 (58.7% v 41.9%; P < .001), this therapy had no benefit in patients with an iScore ≥ 200 (15.4% v 13.4%; P = .77). In patients receiving tPA in the National Institute of Neurological Disorders and Stroke trial, the iScore estimated the clinical response and risk of hemorrhagic complications. Further prospective studies are needed before a change in practice can be recommended.

The iScore predicts effectiveness of thrombolytic therapy for acute ischemic stroke

BACKGROUND AND PURPOSE

Tools to predict the clinical response after intravenous thrombolytic therapy (tPA) are scarce. The iScore is an existing validated tool to estimate outcomes after an acute ischemic stroke. The purpose of this study was to determine the ability of the iScore to predict clinical response and risk of hemorrhagic transformation after tPA.

METHODS

We applied the iScore (www.sorcan.ca/iscore) to patients presenting with an acute ischemic stroke at 11 stroke centers in Ontario, Canada, between 2003 and 2009 identified from the Registry of the Canadian Stroke Network. A cohort of patients with stroke treated at 154 centers in Ontario was used for external validation. We compared outcomes between patients receiving and not receiving tPA after adjusting for differences in baseline characteristics using propensity-score matching. Patients were stratified into 3 a priori defined groups according to stroke severity using the iScore.

RESULTS

Among 12 686 patients with an acute ischemic stroke, 1696 (13.4%) received intravenous thrombolysis. Higher iScores were associated with poor outcomes in both the tPA and non-tPA groups (P<0.001). Among those at low and medium risk based on their iScores, tPA use was associated with a benefit in the primary outcome (relative risk, 0.74 for those with low-risk iScores; 95% CI, 0.67-0.84; relative risk, 0.88 for those with medium risk iScores; 95% CI, 0.84-0.93). There was no difference in clinical outcomes between matched patients receiving and not receiving tPA in the highest iScore group (relative risk, 0.97; 95% CI, 0.94-1.01). Similar results were observed for disability at discharge and length of stay. The incident risk of neurological deterioration and hemorrhagic transformation (any or symptomatic) with tPA increased with the iScore risk. Results were similar in the validation cohort for risk of poor outcome with tPA by iScore level.

CONCLUSIONS

The iScore may be used to predict clinical response and risk of hemorrhagic complications after tPA for an acute ischemic stroke. Patients with high iScores may not have a clinically meaningful benefit from intravenous tPA at the time of carrying a higher risk of hemorrhagic complications.

The iScore Predicts Poor Functional Outcomes Early After Hospitalization for an Acute Ischemic Stroke

Background and Purpose—

The iScore is a prediction tool originally developed to estimate the risk of death after hospitalization for an acute ischemic stroke. Our objective was to determine whether the iScore could also predict poor functional outcomes.

Methods—

We applied the iScore to patients presenting with an acute ischemic stroke at multiple hospitals in Ontario, Canada, between 2003 and 2008, who had been identified from the Registry of the Canadian Stroke Network regional stroke center database (n=3818) and from an external data set, the Registry of the Canadian Stroke Network Ontario Stroke Audit (n=4635). Patients were excluded if they were included in the sample used to develop and validate the initial iScore. Poor functional outcomes were defined as: (1) death at 30 days or disability at discharge, in which disability was defined as having a modified Rankin Scale 3 to 5; and (2) death at 30 days or institutionalization at discharge.

Results—

The prevalence of poor functional outcomes in the Registry of the Canadian Stroke Network and the Ontario Stroke Audit, respectively, were 55.7% and 44.1% for death at 30 days or disability at discharge and 16.9% and 16.2%, respectively, for death at 30 days or institutionalization at discharge. The iScore stratified the risk of poor outcomes in low- and high-risk individuals. Observed versus predicted outcomes showed high correlations: 0.988 and 0.940 for mortality or disability and 0.985 and 0.993 for mortality or institutionalization in the Registry of the Canadian Stroke Network and Ontario Stroke Audit cohorts.

Conclusions—

The iScore can be used to estimate the risk of death or a poor functional outcome after an acute ischemic stroke.

IScore

Background—

A predictive model of stroke mortality may be useful for clinicians to improve communication with and care of hospitalized patients. Our aim was to identify predictors of mortality and to develop and validate a risk score model using information available at hospital presentation.

Methods and Results—

This retrospective study included 12 262 community-based patients presenting with an acute ischemic stroke at multiple hospitals in Ontario, Canada, between 2003 and 2008 who had been identified from the Registry of the Canadian Stroke Network (8223 patients in the derivation cohort, 4039 in the internal validation cohort) and the Ontario Stroke Audit (3720 for the external validation cohort). The mortality rates for the derivation and internal validation cohorts were 12.2% and 12.6%, respectively, at 30 days and 22.5% and 22.9% at 1 year. Multivariable predictors of 30-day and 1-year mortality included older age, male sex, severe stroke, nonlacunar stroke subtype, glucose ≥7.5 mmol/L (135 mg/dL), history of atrial fibrillation, coronary artery disease, congestive heart failure, cancer, dementia, kidney disease on dialysis, and dependency before the stroke. A risk score index stratified the risk of death and identified low- and high- risk individuals. The c statistic was 0.850 for 30-day mortality and 0.823 for 1-year mortality for the derivation cohort, 0.851 for the 30-day model and 0.840 for the 1-year mortality model in the internal validation set, and 0.790 for the 30-day model and 0.782 for the 1-year model in the external validation set.

Conclusion—

Among patients with ischemic stroke, factors identifiable within hours of hospital presentation predicted mortality risk at 30 days and 1 year. The predictive score may assist clinicians in estimating stroke mortality risk and policymakers in providing a quantitative tool to compare facilities.

Determinants of length of stay in stroke patients: a geriatric rehabilitation unit experience

The objective was to identify the predictors of length of stay--the impact of age, comorbidity, and stroke subtype- on the outcome of geriatric stroke patients. One hundred and seventy stroke patients (129 first-ever ischemic, 25 hemorrhagic, and 16 ischemic second strokes) were included in the study. The Oxfordshire Community Stroke Project classification for clinical subtypes of ischemic stroke patients and the Charlson comorbidity index were used to evaluate comorbidity. The Functional Independence Measure (FIM) scores were noted on admission and at discharge. Comparison of the patients below and over 65 years revealed that elderly patients had higher comorbidity scores, were more likely to be prematurely discharged, and were less likely to be successfully rehabilitated despite similar FIM scores on admission. Excluding premature discharges, FIM scores on admission emerged as the only predictor of length of stay. Age, stroke type, lesion characteristics, and comorbidities are not significant associates of prolonged length of stay. Results and limitations inherent to our study and similar stroke studies are discussed within the context of rehabilitation differences among rehabilitation centers and countries.