A prognostic index for 30-day mortality after stroke

European Stroke Organisation and European Society for Swallowing Disorders guideline for the diagnosis and treatment of post-stroke dysphagia

Post-stroke dysphagia (PSD) is present in more than 50% of acute stroke patients, increases the risk of complications, in particular aspiration pneumonia, malnutrition and dehydration, and is linked to poor outcome and mortality. The aim of this guideline is to assist all members of the multidisciplinary team in their management of patients with PSD. These guidelines were developed based on the European Stroke Organisation (ESO) standard operating procedure and followed the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach. An interdisciplinary working group identified 20 relevant questions, performed systematic reviews and meta-analyses of the literature, assessed the quality of the available evidence and wrote evidence-based recommendations. Expert opinion was provided if not enough evidence was available to provide recommendations based on the GRADE approach. We found moderate quality of evidence to recommend dysphagia screening in all stroke patients to prevent post-stroke pneumonia and to early mortality and low quality of evidence to suggest dysphagia assessment in stroke patients having been identified at being at risk of PSD. We found low to moderate quality of evidence for a variety of treatment options to improve swallowing physiology and swallowing safety. These options include dietary interventions, behavioural swallowing treatment including acupuncture, nutritional interventions, oral health care, different pharmacological agents and different types of neurostimulation treatment. Some of the studied interventions also had an impact on other clinical endpoints such as feedings status or pneumonia. Overall, further randomized trials are needed to improve the quality of evidence for the treatment of PSD.

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.

Stroke ICU Patient Mortality Day Prediction

This article presents a study on development of methods for analysis of data reflecting the process of treatment of stroke inpatients to predict clinical outcomes at the emergency care unit. The aim of this work is to develop models for the creation of validated risk scales for early intravenous stroke with minimum number of parameters with maximum prognostic accuracy and possibility to calculate the time of “expected intravenous stroke mortality”. The study of experience in the development and use of medical information systems allows us to state the insufficient ability of existing models for adequate data analysis, weak formalization and lack of system approach in the collection of diagnostic data, insufficient personalization of diagnostic data on the factors determining early intravenous stroke mortality.

In our study we divided patients into 3 subgroups according to the time of death - up to 1 day, 1 to 3 days, and 4 to 10 days. Early mortality in each subgroup was associated with a number of demographic, clinical, and instrumental-laboratory characteristics based on the interpretation of the results of calculating the significance of predictors of binary classification models by machine learning methods from the Scikit-Learn library. The target classes in training were “mortality rate of 1 day”, “mortality rate of 1–3 days”, “mortality rate from 4 days”. AUC ROC of trained models reached 91% for the method of random forest. The results of interpretation of decision trees and calculation of significance of predictors of built-in methods of random forest coincide that can prove to correctness of calculations.

mSOAR: an effective bedside stroke prognosis tool

The modified-SOAR (mSOAR) score is composed of the stroke subtype, Oxfordshire Community Stroke Project classification, age, pre-stroke modified Rankin score (mRS) and the National Institutes of Health Stroke Scale score. It has previously been shown to be a reliable predictor of mortality and length of -hospital stay. This study sought to identify whether the mSOAR can also be used to predict patient disability on discharge. A post-hoc calculation of mSOAR using Sentinel Stroke National Audit Programme (SSNAP) data and electronic discharge -summaries was performed on all stroke admissions to Bridgend Hospital over an 11-month period. This study included 230 patients, of which 88% had suffered infarcts and 23% had experienced a previous cerebrovascular episode or transient ischaemic attack; 52% were female. The mortality rate was 13% and 57% had slight disability or less (mRS≤2) on discharge. Each increase in mSOAR score was associated with significantly worse discharge disability (p<0.05). We conclude that the mSOAR score is an excellent tool for predicting both discharge disability and mortality. As such, it's useful for admission prognosis discussions with patients, their relatives and the multidisciplinary team and for early supported discharge decision making.

Risk prediction models for mortality in patients with cardiovascular disease: The BioBank Japan project

Background

Cardiovascular disease (CVD) is a leading cause of death in Japan. The present study aimed to develop new risk prediction models for long-term risks of all-cause and cardiovascular death in patients with chronic phase CVD.

Methods

Among the subjects registered in the BioBank Japan database, 15,058 patients aged ≥40 years with chronic ischemic CVD (ischemic stroke or myocardial infarction) were divided randomly into a derivation cohort (n = 10,039) and validation cohort (n = 5019). These subjects were followed up for 8.55 years in median. Risk prediction models for all-cause and cardiovascular death were developed using the derivation cohort by Cox proportional hazards regression. Their prediction performances for 5-year risk of mortality were evaluated in the validation cohort.

Results

During the follow-up, all-cause and cardiovascular death events were observed in 2962 and 962 patients from the derivation cohort and 1536 and 481 from the validation cohort, respectively. Risk prediction models for all-cause and cardiovascular death were developed from the derivation cohort using ten traditional cardiovascular risk factors, namely, age, sex, CVD subtype, hypertension, diabetes, total cholesterol, body mass index, current smoking, current drinking, and physical activity. These models demonstrated modest discrimination (c-statistics, 0.703 for all-cause death; 0.685 for cardiovascular death) and good calibration (Hosmer-Lemeshow χ²-test, P = 0.17 and 0.15, respectively) in the validation cohort.

Conclusions

We developed and validated risk prediction models of all-cause and cardiovascular death for patients with chronic ischemic CVD. These models would be useful for estimating the long-term risk of mortality in chronic phase CVD.

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We developed risk prediction models for death after cardiovascular disease (CVD).

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Performances of these models were validated in an independent cohort.

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Our models may be used to estimate mortality risk in chronic CVD patients.

External Validation of a Case-Mix Adjustment Model for the Standardized Reporting of 30-Day Stroke Mortality Rates in China

BACKGROUND AND PURPOSE

A case-mix adjustment model has been developed and externally validated, demonstrating promise. However, the model has not been thoroughly tested among populations in China. In our study, we evaluated the performance of the model in Chinese patients with acute stroke.

METHODS

The case-mix adjustment model A includes items on age, presence of atrial fibrillation on admission, National Institutes of Health Stroke Severity Scale (NIHSS) score on admission, and stroke type. Model B is similar to Model A but includes only the consciousness component of the NIHSS score. Both model A and B were evaluated to predict 30-day mortality rates in 13,948 patients with acute stroke from the China National Stroke Registry. The discrimination of the models was quantified by c-statistic. Calibration was assessed using Pearson's correlation coefficient.

RESULTS

The c-statistic of model A in our external validation cohort was 0.80 (95% confidence interval, 0.79-0.82), and the c-statistic of model B was 0.82 (95% confidence interval, 0.81-0.84). Excellent calibration was reported in the two models with Pearson's correlation coefficient (0.892 for model A, p<0.001; 0.927 for model B, p = 0.008).

CONCLUSIONS

The case-mix adjustment model could be used to effectively predict 30-day mortality rates in Chinese patients with acute stroke.

Brain Edema After Ischaemic Stroke

Objectives:

To determine the incidence of brain edema after ischaemic stroke and its impact on the outcome of patients in the acute phase of ischaemic stroke.

Patients and Methods:

We retrospectively analyzed 114 patients. Ischaemic stroke and brain edema are verified by computed tomography. The severity of stroke was determined by National Institutes of Health Stroke Scale. Laboratory findings were made during the first four days of hospitalization, and complications were verified by clinical examination and additional tests.

Results:

In 9 (7.9%) patients developed brain edema. Pneumonia was the most common complication (12.3%). Brain edema had a higher incidence in women, patients with hypertension and elevated serum creatinine values, and patients who are suffering from diabetes. There was no significant correlation between brain edema and survival in patients after acute ischaemic stroke. Patients with brain edema had a significantly higher degree of neurological deficit as at admission, and at discharge (p = 0.04, p = 0.004).

Conclusion:

The cerebral edema is common after acute ischaemic stroke and no effect on survival in the acute phase. The existence of brain edema in acute ischaemic stroke significantly influence the degree of neurological deficit.

Urinary incontinence as a predictor of death after new-onset stroke: a meta-analysis

BACKGROUND AND PURPOSE

Urinary incontinence (UI) could be an indicator of increased mortality after new-onset stroke. The aim of the present meta-analysis was to characterize this association.

METHODS

A systematic search retrieved all studies exploring the post-stroke period and comparing death among patients suffering from UI with those without UI. Hazard ratios (HRs) were extracted or estimated from the published proportion of deaths. Various meta-analyses pooled unadjusted HRs, HRs adjusted for confounders and HRs stratified by subgroups of strokes (ischaemic or haemorrhagic), using models with random effects. Heterogeneity was explored through stratification of studies and meta-regression of predefined parameters.

RESULTS

The meta-analysis included 24 studies. UI increased the mortality among the general stroke patients in pooled unadjusted (HR, 5.1; 95% CI, 3.9-6.7) and adjusted (HR, 2.2; 95% CI, 1.8-2.7) analyses. This association was also found among ischaemic (HR, 8.5; 95% CI, 4.6-15.7) and haemorrhagic (HR, 3.9; 95% CI, 1.4-11.3) subgroups of strokes. Studies including indwelling catheters, published more than 10 years ago or with the highest quality on the selection criteria of the Newcastle-Ottawa Quality Assessment scale were associated with a greater effect of UI on mortality. Funnel plots showed a clear asymmetry for adjusted associations. After correcting for this potential publication bias, the pooled HRs still demonstrated a positive association between UI and mortality.

CONCLUSIONS

Urinary incontinence indicates high risk of death after a new-onset stroke. Validity of the analyses on adjusted models is limited by an obvious publication bias.

Predicting those who will walk after rehabilitation in a specialist stroke unit

Objective: To establish whether the ability to use a wheelchair shortly after a stroke or continence are related to the likelihood of walking by time of discharge.

Design and subjects: An observational study in patients admitted to a stroke rehabilitation unit for under-65s over a three-year period.

Methods: Functional Independence Measure (FIM) subscores for walking were examined on all patients at time of admission and discharge. Walking was defined by an FIM ≤ 5 in that section. Comparisons were then made between those who could self-propel a wheelchair within a week of admission with those who could not. Continence (defined by an FIM subscore of ≥ 6 in that category) was also correlated to walking at discharge.

Main outcome measure: Walking at time of discharge defined by an FIM ≥ 5 in that section.

Results: From 393 admissions, 135 were excluded because they could already walk (FIM subscore ≥ 5 in that particular section) and three died during their admission. Out of the remaining 255 patients, 108 could self-propel on admission and 147 could not. While 105 (97%) of the self-propellors could walk by time of discharge, only 91 (62%) of the non-propellors could do so (χ2=42.237, df=1, P < 0.001, odds ratio (OR) 21.54 (6.52-71.51)). Although continence also predicted improved likelihood of walking, this was at a lower level of significance and correspondingly lower odds ratio (χ2=5.894, df=1, P=0.015, OR 1.94 (1.13-3.32)).

Conclusions: The ability to self-propel a wheelchair shortly after a stroke is a significant predictor of eventually being able to walk. Our data suggest that it is even more significant than continence, which is the most consistent predictor previously found.

Derivation and Validation of a Novel Prognostic Scale (Modified–Stroke Subtype, Oxfordshire Community Stroke Project Classification, Age, and Prestroke Modified Rankin) to Predict Early Mortality in Acute Stroke

Background and Purpose—

The stroke subtype, Oxfordshire Community Stroke Project classification, age, and prestroke modified Rankin (SOAR) score is a prognostic scale proposed for early mortality prediction after acute stroke. We aimed to evaluate whether including a measure of initial stroke severity (National Institutes of Health Stroke Scale and modified-SOAR [mSOAR] scores) would improve the prognostic accuracy.

Methods—

Using Anglia Stroke and Heart Clinical Network data, 2008 to 2011, we assessed the performance of SOAR and mSOAR against in-hospital mortality using area under the receiver operating curve statistics. We externally validated the prognostic utility of SOAR and mSOAR using an independent cohort data set from Glasgow. We described calibration using Hosmer–Lemeshow goodness-of-fit test.

Results—

A total of 1002 patients were included in the derivation cohort, and 105 (10.5%) died as inpatients. The area under the receiver operating curves for outcome of early mortality derived from the SOAR and mSOAR scores were 0.79 (95% confidence interval, 0.75–0.84) and 0.83 (95% confidence interval, 0.79–0.86), respectively ( P =0.001). The external validation data set contained 1012 patients with stroke; of which, 121 (12.0%) patients died within 90 days. The mSOAR scores identified the risk of early mortality ranging from 3% to 42%. External validation of mSOAR score yielded an area under the receiver operating curve of 0.84 (95% confidence interval, 0.82–0.88) for outcome of early mortality. Calibration was good ( P =0.70 for the Hosmer–Lemeshow test).

Conclusions—

Adding National Institutes of Health Stroke Scale data to create a modified-SOAR score improved prognostic utility in both derivation and validation data sets. The mSOAR may have clinical utility by using easily available data to predict mortality.

The SOAR (Stroke subtype, Oxford Community Stroke Project classification, Age, prestroke modified Rankin) score strongly predicts early outcomes in acute stroke

BACKGROUND

Previous prognostic scoring systems in predicting stroke mortality are complex, require multiple measures that vary with time and failed to produce a simple scoring system.

AIMS/HYPOTHESIS

The study aims to derive and internally validate a stroke prognostic scoring system to predict early mortality and hospital length of stay.

METHODS

Data from a U.K. multicenter stroke register were examined (1997-2010). Using a prior hypothesis based on our and others observations, we selected five patient-related factors (age, gender, stroke subtype, clinical classification, and prestroke disability) as candidate prognostic indicators. An 8-point score was derived based on multiple logistic regression model using four out of five variables. Performance of the model was assessed by plotting the estimated probability of in-hospital death against the actual probability by testing for overfitting (calibration) and area under the curve methods (discrimination).

RESULTS

The total sample consisted of 12,355 acute stroke patients (ischemic stroke 91.0%). The score predicted both in-patient and seven-day mortality. The crude in-patient mortality were 1.57%, 4.02%, 10.65%, 21.41%, 46.60%, 62.72%, and 75.81% for those who scored 0, 1, 2, 3, 4, 5, and 6, respectively. The calibration of the model revealed no evidence of overfitting (estimated overfitting 0.001). The area under the curve values for both in-hospital and seven-day mortality were 0.79. The score predicted length of stay with a higher score was associated with longer median length of stay in those discharged alive and shorter median length of stay in those who died (P for both <0.001).

CONCLUSIONS

A simple 8-point clinical score is highly predictive of acute stroke mortality and length of hospital stay. It could be used as prognostic tool in service planning and also to risk-stratify patients to use these outcomes as markers of stroke care quality across institutions.

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.

A risk score for in-hospital death in patients admitted with ischemic or hemorrhagic stroke

BACKGROUND

We aimed to derive and validate a single risk score for predicting death from ischemic stroke (IS), intracerebral hemorrhage (ICH), and subarachnoid hemorrhage (SAH).

METHODS AND RESULTS

Data from 333 865 stroke patients (IS, 82.4%; ICH, 11.2%; SAH, 2.6%; uncertain type, 3.8%) in the Get With The Guidelines-Stroke database were used. In-hospital mortality varied greatly according to stroke type (IS, 5.5%; ICH, 27.2%; SAH, 25.1%; unknown type, 6.0%; P<0.001). The patients were randomly divided into derivation (60%) and validation (40%) samples. Logistic regression was used to determine the independent predictors of mortality and to assign point scores for a prediction model in the overall population and in the subset with the National Institutes of Health Stroke Scale (NIHSS) recorded (37.1%). The c statistic, a measure of how well the models discriminate the risk of death, was 0.78 in the overall validation sample and 0.86 in the model including NIHSS. The model with NIHSS performed nearly as well in each stroke type as in the overall model including all types (c statistics for IS alone, 0.85; for ICH alone, 0.83; for SAH alone, 0.83; uncertain type alone, 0.86). The calibration of the model was excellent, as demonstrated by plots of observed versus predicted mortality.

CONCLUSIONS

A single prediction score for all stroke types can be used to predict risk of in-hospital death following stroke admission. Incorporation of NIHSS information substantially improves this predictive accuracy.

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.

Risk Score for In-Hospital Ischemic Stroke Mortality Derived and Validated Within the Get With The Guidelines–Stroke Program

Background—

There are few validated models for prediction of in-hospital mortality after ischemic stroke. We used Get With the Guidelines–Stroke Program data to derive and validate prediction models for a patient's risk of in-hospital ischemic stroke mortality.

Methods and Results—

Between October 2001 and December 2007, there were 1036 hospitals that contributed 274 988 ischemic stroke patients to this study. The sample was randomly divided into a derivation (60%) and validation (40%) sample. Logistic regression was used to determine the independent predictors of mortality and to assign point scores for a prediction model. We also separately derived and validated a model in the 109 187 patients (39.7%) with a National Institutes of Health Stroke Scale (NIHSS) score recorded. Model discrimination was quantified by calculating the C statistic from the validation sample. In-hospital mortality was 5.5% overall and 5.2% in the subset in which NIHSS score was recorded. Characteristics associated with in-hospital mortality were age, arrival mode (eg, via ambulance versus other mode), history of atrial fibrillation, previous stroke, previous myocardial infarction, carotid stenosis, diabetes mellitus, peripheral vascular disease, hypertension, history of dyslipidemia, current smoking, and weekend or night admission. The C statistic was 0.72 in the overall validation sample and 0.85 in the model that included NIHSS score. A model with NIHSS score alone provided nearly as good discrimination (C statistic 0.83). Plots of observed versus predicted mortality showed excellent model calibration in the validation sample.

Conclusions—

The Get With the Guidelines–Stroke risk model provides clinicians with a well-validated, practical bedside tool for mortality risk stratification. The NIHSS score provides substantial incremental information on a patient's short-term mortality risk and is the strongest predictor of mortality.

Mortality and institutionalization in early survivors of stroke: the effects of cognition, vascular mild cognitive impairment, and vascular dementia

We explored th effects of vascular mild cognitive impairment (VaMCI), vascular dementia (VaD), and other predictors on mortality and institutionalization in early survivors of ischemic stroke without previous dementia who had been admitted to a stroke unit. A total of 202 consecutive consenting eligible ischemic stroke survivors and a matched sample of 97 community controls were followed for up to 10 years. Data for 167 patients who underwent detailed assessment 3-6 months after stroke were analyzed to determine predictors of outcomes. Cumulative mortality rates for patients (and controls) were 27% (4%) for the first 5 years and rose to 83% (10%) by 10 years. Predictors of mortality were older age, any cognitive impairment, less independent function, and less education. Nursing home admission rates were 24% at 5 years and 32% at 10 years for patients and 0 for controls over 8.9 years. Predictors of institutionalization were less independent function and older age. Patients with ischemic stroke who survive the first week have moderate, lower-than-expected mortality rates in the first 5 years that increase thereafter. VaMCI, VaD, and functional decline are predictors of mortality, while functional decline and older age predict institutionalization.

Can the aspiration detected by videofluoroscopic swallowing studies predict long-term survival in stroke patients with dysphagia?

PURPOSE

This study aimed to evaluate whether the aspiration detected by videofluoroscopic swallowing study (VSS) could predict the long-term survival in stroke patients with dysphagia in the post-acute phase of stroke.

METHODS

A cohort of 182 consecutive patients with stroke-related dysphagia referred for VSS from July 1994 to April 1999 was retrospectively constructed. VSS findings and clinical features in the post-acute phase of stroke were recorded. The records thus obtained were then linked to the National Death Register to track the occurrence of patient deaths until December 31, 2000.

RESULTS

Of the 182 patients, 91 (50%) showed aspiration during VSS performed for a median duration of 8.4 weeks after stroke, and 76 (42%) had silent aspiration. In the post-acute phase of stroke (14.7 +/- 8.7 weeks after stroke, mean + standard deviation), 56 (31%) were tube-fed, and 88 (48%) were wheelchair-confined. A total of 65 patients died in a median follow-up duration of 30.8 months after VSS. Patients were classified into three groups based on the findings of VSS-detected aspiration or penetration, but no difference was noted in their survival curves. In the Cox stepwise regression analysis, only advanced age, recurrent stroke (hazard ratio 1.74, 95% CI 1.06-2.85), the need of tube-feeding (hazard ratio 2.07, 95% CI 1.19-3.59), and being wheelchair-confined (hazard ratio 2.83, 95% CI 1.54-5.19) during follow-up were independent predictors of long-term survival.

CONCLUSIONS

VSS-detected aspiration during the post-acute phase of stroke was not predictive for the long-term survival in stroke patients with dysphagia.

Variables Associated With 7-Day, 30-Day, and 1-Year Fatality After Ischemic Stroke

Background and Purpose— Seven-day, 30-day, and 1-year case-fatality indicators have been used to compare stroke care among hospitals, provinces, and countries and to implement quality improvement strategies. However, limited information is available concerning variables associated with stroke case fatality at these different points in time. We sought to identify and compare variables associated with 7-day, 30-day, and 1-year stroke fatality.

Methods— This was a cohort study of consecutive patients with acute ischemic stroke admitted to 11 stroke centers in Ontario, Canada, between July 2003 and March 2005 and captured in the Registry of the Canadian Stroke Network (RCSN). The RCSN database was linked to administrative databases to capture all deaths occurring within 7, 30, and 365 days of hospital admission for ischemic stroke. Logistic regression was used to determine variables associated with stroke fatality at each time point. Outcome measures were all-location mortality within 7 days, 30 days, and 1 year of hospital admission.

Results— Our cohort included 3631 patients admitted with ischemic stroke. Seven-day case fatality was 6.9% (249/3631), 30-day case fatality was 12.6% (457/3631), and 1-year case fatality was 23.6% (856/3631). In the multivariable analyses, stroke severity, neurologic deterioration during hospitalization, nonuse of antithrombotics during hospital admission, and lack of assessment by a stroke team were the most consistent predictors of case fatality at 7 days, 30 days, and 1 year after stroke. Physician experience in stroke management was inversely associated with 7-day and 30-day mortality, whereas age, comorbid illness, and pneumonia during hospital admission were associated with 30-day and 1-year mortality.

Conclusions— Stroke severity and certain processes of care were associated with case fatality at 7days, 30 days, and 1 year after stroke. This information may be useful for comparing risk-adjusted case-fatality rates among hospitals and for implementing strategies to improve the processes and quality of care in the acute phase of stroke.

Stroke and atherothrombosis: An Update on the Role of Antiplatelet Therapy

Atherothrombosis is responsible for most acute ischemic manifestations of atherosclerotic disease, including stroke. Individuals with evidence of atherothrombotic disease in one vascular bed have a significant risk of recurrence and show increased vulnerability over time for other manifestations elsewhere in the vasculature. Ischemic event rates for asymptomatic patients with multiple atherothrombotic risk factors appear to be similar to those in patients with documented cardiovascular disease. For example, diabetes mellitus and obesity are found at alarmingly high rates in patients with prior cardiovascular events, including stroke or transient ischemic attacks. Antiplatelet therapy is a key component of atherothrombotic event prevention. The results of the Clopidogrel for High Atherothrombotic Risk and Ischemic Stabilization, Management and Avoidance (CHARISMA) study showed that while dual antiplatelet therapy with aspirin and clopidogrel may not play a role in primary prevention, post hoc analysis alluded to the possibility of benefit for dual antiplatelet therapy in certain populations of stroke patients. We examined current recommendations for the prevention of atherothrombotic events, focusing on the role of oral antiplatelet agents in patients with ischemic stroke.

Acute physiologic predictors of mortality and functional and cognitive recovery in hemorrhagic stroke: 1-, 3-, and 6-month assessments

This study was conducted to evaluate the prognostic values of acute physiologic parameters of mortality and functional and cognitive recovery. We studied 108 patients with hemorrhagic stroke admitted within 24 hours after stroke onset to a neurologic intensive care department. Details concerning potential physiologic predictors were collected (i.e., systolic and diastolic blood pressure, pulse rate, respiration rate, body temperature, hematocrit, Pao(2), Paco(2) and serum osmolality, pH, cholesterol, and glucose levels) at admission. As outcome variables, mortality and functional and cognitive recovery at 1, 3, and 6 months were measured. Results showed that blood pressure, serum pH, and Pao(2) on admission are significant predictors of mortality; that respiratory rate and hematocrit on admission are significant predictors of functional recovery; and that respiratory rate, Pao(2), and heart rate on admission predict cognitive recovery. It appears that the physiologic predictors of hemorrhagic stroke are remarkably dependent on outcome definitions (i.e., mortality, functional disability, or cognitive ability), but not with recovery times.

The effect of admission physiological variables on 30 day outcome after stroke

INTRODUCTION

Potentially modifiable physiological variables may influence stroke prognosis but their independence from modifiable factors remains unclear.

METHODS

Admission physiological measures (blood pressure, heart rate, temperature and blood glucose) and other unmodifiable factors were recorded from patients presenting within 48 hours of stroke. These variables were compared with the outcomes of death and death or dependency at 30 days in multivariate statistical models.

RESULTS

In the 186 patients included in the study, age, atrial fibrillation and the National Institutes of Health Stroke Score were identified as unmodifiable factors independently associated with death and death or dependency. After adjusting for these factors, none of the physiological variables were independently associated with death, while only diastolic blood pressure (DBP) > or = 90 mmHg was associated with death or dependency at 30 days (p = 0.02).

CONCLUSIONS

Except for elevated DBP, we found no independent associations between admission physiology and outcome at 30 days in an unselected stroke cohort. Future studies should look for associations in subgroups, or by analysing serial changes in physiology during the early post-stroke period.

Substantial effective sample sizes were required for external validation studies of predictive logistic regression models

BACKGROUND AND OBJECTIVES

The performance of a prediction model is usually worse in external validation data compared to the development data. We aimed to determine at which effective sample sizes (i.e., number of events) relevant differences in model performance can be detected with adequate power.

METHODS

We used a logistic regression model to predict the probability that residual masses of patients treated for metastatic testicular cancer contained only benign tissue. We performed standard power calculations and Monte Carlo simulations to estimate the numbers of events that are required to detect several types of model invalidity with 80% power at the 5% significance level.

RESULTS

A validation sample with 111 events was required to detect that a model predicted too high probabilities, when predictions were on average 1.5 times too high on the odds scale. A decrease in discriminative ability of the model, indicated by a decrease in the c-statistic from 0.83 to 0.73, required 81 to 106 events, depending on the specific scenario.

CONCLUSION

We suggest a minimum of 100 events and 100 nonevents for external validation samples. Specific hypotheses may, however, require substantially higher effective sample sizes to obtain adequate power.

Predictors of Hyperacute Clinical Worsening in Ischemic Stroke Patients Receiving Thrombolytic Therapy

BACKGROUND AND PURPOSE

Although long-term outcome determinants in acute ischemic stroke (AIS) patients have been defined, less is known about those predicting hyperacute worsening after thrombolytic therapy (TT). We investigated predictors of short-term clinical worsening (National Institutes of Health Stroke Scale [NIHSS] change > or =4 within 24 hours of admission).

METHODS

We studied 201 AIS patients who received TT within 6 hours of symptom onset. We determined baseline demographics, comorbidities, NIHSS at baseline and at 24 hours after TT, head computed tomography scan before and within 24 hours after TT, and angiographic recanalization in patients treated with intra-arterial (IA) thrombolysis. Significance of relationships was evaluated by t test or Wilcoxon signed rank sum test. Logistic regression model (LRM) was fitted to determine independence of significant variables.

RESULTS

Of 201 patients, 13% worsened, 39% improved, and 48% remained unchanged 24 hours after TT. Most patients (72%) received IA thrombolysis. Patients who deteriorated, compared with those who improved, were more likely to have complicating intracranial hemorrhage (ICH; P<0.001), absent recanalization (P=0.026), and higher blood glucose (BG; P=0.049). Hyperglycemia (>150 mg/dL) was greater in patients who worsened even in presence of recanalization (P=0.004, odds ratio [OR] 6.47). LRM showed that adjusted OR for increased risk of bad outcome and mortality for an increase of BG by 50 mg/dL is 1.56 and 1.38, respectively.

CONCLUSIONS

Hyperglycemia and ICH are independent predictors of hyperacute worsening in AIS patients receiving TT. Although recanalization is the purpose of IA thrombolysis, its impact on clinical improvement may not be apparent without strict BG control.

Pneumonia in acute stroke patients fed by nasogastric tube

BACKGROUND

Aspiration pneumonia is the most important acute complication of stroke related dysphagia. Tube feeding is usually recommended as an effective and safe way to supply nutrition in dysphagic stroke patients.

OBJECTIVE

To estimate the frequency of pneumonia in acute stroke patients fed by nasogastric tube, to determine risk factors for this complication, and to examine whether the occurrence of pneumonia is related to outcome.

METHODS

Over an 18 month period a prospective study was done on 100 consecutive patients with acute stroke who were given tube feeding because of dysphagia. Intermediate outcomes were pneumonia and artificial ventilation. Functional outcome was assessed at three months. Logistic regression and multivariate regression analyses were used, respectively, to identify variables significantly associated with the occurrence of pneumonia and those related to a poor outcome.

RESULTS

Pneumonia was diagnosed in 44% of the tube fed patients. Most patients acquired pneumonia on the second or third day after stroke onset. Patients with pneumonia more often required endotracheal intubation and mechanical ventilation than those without pneumonia. Independent predictors for the occurrence of pneumonia were a decreased level of consciousness and severe facial palsy. The NIH stroke scale score on admission was the only independent predictor of a poor outcome.

CONCLUSIONS

Nasogastric tubes offer only limited protection against aspiration pneumonia in patients with dysphagia from acute stroke. Pneumonia occurs mainly in the first days of the illness and patients with decreased consciousness and a severe facial palsy are especially endangered.

A prediction model of 1-year mortality for acute ischemic stroke patients

OBJECTIVE

To develop a prediction model for 1-year mortality in patients with acute ischemic stroke, with the model to be at least as useful and accurate as other previously developed prediction models.

DESIGN

Retrospective cohort study.

SETTING

Neurology department at an Australian tertiary teaching hospital.

PARTICIPANTS

Four hundred forty consecutive patients diagnosed with acute ischemic stroke between July 1, 1995, and June 30, 1997.

INTERVENTIONS

Two hundred twenty-three (51%) patients were randomly assigned to the derivation sample to develop a prediction model using the Cox proportional hazards model. The model was then validated in a validation sample of 217 (49%) patients.

MAIN OUTCOME MEASURE

One-year mortality.

RESULTS

Eight clinical predictors were included in the final model: unconsciousness (3 points), dysphagia (7 points), urinary incontinence (9 points), both sides affected (4 points), hyperthermia (4 points), ischemic heart disease (3 points), peripheral vascular disease (3 points), and diabetes mellitus (2 points). Patients with scores of 10 or higher were allocated to the high-risk group, which had a 1-year mortality rate of 76%, compared with a 1-year mortality rate of 8% in the low-risk group. There was no statistically significant difference in terms of sensitivity, specificity, and positive predictive value in the validation sample.

CONCLUSION

We developed a predictive model for 1-year mortality in acute ischemic stroke patients. The model is easy to use and is comparable in its accuracy with other predictive models.

Hyperglycaemia in patients with acute ischaemic stroke: how often do we screen for undiagnosed diabetes?

BACKGROUND

Hyperglycaemia is common among patients with acute ischaemic stroke, and may be due to the physiological stress of the acute stroke event or reflect underlying diabetes mellitus. The under-diagnosis of diabetes in the general population, combined with the association of diabetes and stroke, suggests a rationale for screening for diabetes among hyperglycaemic stroke patients.

AIM

To determine how often clinicians screen for diabetes among hyperglycaemic stroke patients without a prior diagnosis of diabetes.

DESIGN

Retrospective medical record review.

METHODS

We reviewed the records of acute ischaemic stroke patients admitted at any of ten Connecticut hospitals from May 1996 through December 1998.

RESULTS

We identified 90 acute stroke patients with no prior history of diabetes. The prevalence of hyperglycaemia varied from 31% down to 6%, depending on the maximum glucose cut-off used to define hyperglycaemia: from > or = 140 mg/dl (7.8 mmol/l) to > or = 200 mg/dl (11.1 mmol/l). Only one of the hyperglycaemic patients (1/90, 1%) had any evidence that a clinician screened or planned to screen for undiagnosed diabetes: one patient had a haemoglobin A1c measured during the hospitalization, none received oral glucose tolerance testing while hospitalized, and no discharge summary included a plan to screen for diabetes as an out-patient.

DISCUSSION

Hyperglycaemic stroke patients without a previous diagnosis of diabetes are not routinely screened for diabetes. This situation represents an opportunity, currently unused, to identify an important and modifiable condition.

Acute hyperglycemia adversely affects stroke outcome: a magnetic resonance imaging and spectroscopy study

Controversy exists whether acute hyperglycemia is causally associated with worse stroke outcome or simply reflects a more severe stroke. In reversible ischemia models, hyperglycemia is associated with lactic acidosis and conversion of penumbral tissue to infarction. However, the relationship between hyperglycemia, lactic acidosis, and stroke outcome has not been explored in humans. Sixty-three acute stroke patients were prospectively evaluated with serial diffusion-weighted and perfusion-weighted magnetic resonance imaging and acute blood glucose measurements. Patients with hypoperfused at-risk tissue were identified by acute perfusion-diffusion lesion mismatch. As a substudy, acute and subacute magnetic resonance spectroscopy was performed in the 33 most recent patients to assess the relationship between acute blood glucose and lactate production in the ischemic region. In 40 of 63 patients with acute perfusion-diffusion mismatch, acute hyperglycemia was correlated with reduced salvage of mismatch tissue from infarction, greater final infarct size, and worse functional outcome. These correlations were independent of baseline stroke severity, lesion size, and diabetic status. Furthermore, higher acute blood glucose in patients with perfusion-diffusion mismatch was associated with greater acute-subacute lactate production, which, in turn, was independently associated with reduced salvage of mismatch tissue. In contrast, acute blood glucose levels in nonmismatch patients did not independently correlate with outcome measures, nor was there any acute-subacute increase in lactate in this group. Acute hyperglycemia increases brain lactate production and facilitates conversion of hypoperfused at-risk tissue into infarction, which may adversely affect stroke outcome. These findings support the need for randomized controlled trials of aggressive glycemic control in acute stroke.