Evaluation of the ESRS and SPI-II scales for short-term prognosis of minor stroke and transient ischemic attack

Consensus clustering of gene expression profiles in peripheral blood of acute ischemic stroke patients

Acute ischemic stroke (AIS) is a primary cause of mortality and morbidity worldwide. Currently, no clinically approved immune intervention is available for AIS treatment, partly due to the lack of relevant patient classification based on the peripheral immunity status of patients with AIS. In this study, we adopted the consensus clustering approach to classify patients with AIS into molecular subgroups based on the transcriptomic profiles of peripheral blood, and we identified three distinct AIS molecular subgroups and 8 modules in each subgroup by the weighted gene co-expression network analysis. Remarkably, the pre-ranked gene set enrichment analysis revealed that the co-expression modules with subgroup I-specific signature genes significantly overlapped with the differentially expressed genes in AIS patients with hemorrhagic transformation (HT). With respect to subgroup II, exclusively male patients with decreased proteasome activity were identified. Intriguingly, the majority of subgroup III was composed of female patients who showed a comparatively lower level of AIS-induced immunosuppression (AIIS). In addition, we discovered a non-linear relationship between female age and subgroup-specific gene expression, suggesting a gender- and age-dependent alteration of peripheral immunity. Taken together, our novel AIS classification approach could facilitate immunomodulatory therapies, including the administration of gender-specific therapeutics, and attenuation of the risk of HT and AIIS after ischemic stroke.

Comparisons of Stroke Knowledge and Health Behaviors in Patients With Hypertensive Stroke at Different Recurrence Risk Strata: The Comprehensive Reminder System Based on the Health Belief Model Study

BACKGROUND

Risk factor management via behavioral change contributes substantially to secondary stroke prevention. The health belief model identified self-perceived risk as a significant factor in behavior change. In previous studies, people have tended to incorrectly estimate their risk of stroke. Little is known about the differences in stroke knowledge and health behaviors in patients who have had a stroke with different risks of stroke recurrence in China.

OBJECTIVE

The aims of this study were to determine the accuracy of self-perceived risk of stroke recurrence and to compare stroke knowledge and health behaviors in patients with hypertensive stroke at different recurrence risk strata.

METHODS

Baseline data from 174 patients in the Comprehensive Reminder System based on the Health Belief Model (CRS-HBM) study were used. Self-perceived risk was assessed via the susceptibility subcategory of the Short-Form Health Belief Model Scale, and actual risk was stratified using the Essen Stroke Risk Score.

RESULTS

Only 27.0% of the patients estimated their risks of stroke recurrence accurately. Patients who perceived themselves to be at higher risk had better knowledge of warning signs. Compared with patients who underestimated their risk of stroke recurrence, those who accurately estimated or overestimated their risk less likely to smoke.

CONCLUSIONS

Most patients incorrectly estimated their risk of stroke recurrence. Communicating with patients about their future risk of recurrent stroke may help improve their stroke knowledge and health behaviors. Implementation of the Comprehensive Reminder System based on the Health Belief Model focusing on risk education aimed at prevention of stroke recurrence is warranted in China.

Serum β2-Microglobulin Is Closely Associated With the Recurrence Risk and 3-Month Outcome of Acute Ischemic Stroke

Background and Purpose: Inflammation plays a significant role in the pathogenesis of acute ischemic stroke (AIS). The role of β2-microglobulin (β2M) as a potential initiator of the inflammatory response in AIS is unclear. The purpose of this study was to analyze the relationship of serum β2M with the recurrence risk and 3-month outcome of AIS.

Methods: A total of 205 patients with AIS were recruited, and their clinical and biochemical characteristics were collected. All patients were followed up for 3 months after stroke onset, and the occurrence of death or major disability at 3 months after onset was the outcome of interest in this study. We evaluated the association of serum β2M levels with the National Institute of Health Stroke Scale (NIHSS) scores, modified Rankin Scale (mRS) scores, and Essen Stroke Risk Score (ESRS) values in patients with AIS. Then, we used receiver operating curve analysis to calculate the optimal cutoff value for discriminating outcomes in patients with AIS and a binary logistic regression model to evaluate the risk factors for a poor outcome after AIS.

Results: Our results showed that serum β2M levels were significantly and positively correlated with ESRS values (r = 0.176, P < 0.001) and mRS scores (r = 0.402, P < 0.001), but the levels of β2M were not correlated with NIHSS scores (r = 0.080, P = 0.255) or with infarct volume (r = 0.013, P = 0.859). In a further study, we found that 121 patients (59.02%) had poor outcomes. The optimal β2M cutoff to predict the 3-month outcome of AIS in this study was 1.865 mg/l, and β2M was independently associated with a poor outcome at 3 months (OR = 3.325, 95% confidence interval: 1.089~10.148).

Conclusions: In conclusion, we inferred that serum β2M was positively associated with the recurrence risk and 3-month outcome of AIS, but it did not appear to be directly related to the severity of AIS or the size of the infarct at admission.

Clinical Risk Score for Predicting Recurrence Following a Cerebral Ischemic Event

Introduction: Recurrent stroke has a higher rate of death and disability. A number of risk scores have been developed to predict short-term and long-term risk of stroke following an initial episode of stroke or transient ischemic attack (TIA) with limited clinical utilities. In this paper, we review different risk score models and discuss their validity and clinical utilities.

Methods: The PubMed bibliographic database was searched for original research articles on the various risk scores for risk of stroke following an initial episode of stroke or TIA. The validation of the models was evaluated by examining the internal and external validation process as well as statistical methodology, the study power, as well as the accuracy and metrics such as sensitivity and specificity.

Results: Different risk score models have been derived from different study populations. Validation studies for these risk scores have produced conflicting results. Currently, ABCD² score with diffusion weighted imaging (DWI) and Recurrence Risk Estimator at 90 days (RRE-90) are the two acceptable models for short-term risk prediction whereas Essen Stroke Risk Score (ESRS) and Stroke Prognosis Instrument-II (SPI-II) can be useful for prediction of long-term risk.

Conclusion: The clinical risk scores that currently exist for predicting short-term and long-term risk of recurrent cerebral ischemia are limited in their performance and clinical utilities. There is a need for a better predictive tool which can overcome the limitations of current predictive models. Application of machine learning methods in combination with electronic health records may provide platform for development of new-generation predictive tools.

Serum beta2-microglobulin levels are highly associated with the risk of acute ischemic stroke

Inflammation is considered an important mechanism of cell death or survival after ischemic stroke. As an important marker of inflammation, the role of β2-microglobulin (β2M) in acute ischemic stroke is unclear. We investigated the relationship between serum β2M and the risk of acute ischemic stroke (AIS). Patients with AIS (202 cases), intracerebral hemorrhage (ICH, 41 cases), and healthy controls (253 cases) were recruited. Clinical and biochemical characteristics were collected. We used three binary logistic regression models to evaluate the correlation of β2M with the risk of AIS. Furthermore, we investigated the relationship between serum β2M and the National Institute of Health Stroke Scale (NIHSS) score, the Trial of ORG 10172 in Acute Stroke Treatment (TOAST) subtypes, and the Essen Stroke Risk Score (ESRS) in patients with AIS. Our results showed that serum β2M levels in patients with AIS were much higher than those in patients with ICH and in the control subjects. Individuals with higher levels of β2M had higher odds of AIS. Moreover, serum β2M levels were significantly and positively correlated with ESRS. In addition, the levels of β2M were varied with different subgroups of AIS (TOAST classification). Serum β2M is highly associated with the risk of AIS.

Thinking About the Future: A Review of Prognostic Scales Used in Acute Stroke

Background: There are many prognostic scales that aim to predict functional outcome following acute stroke. Despite considerable research interest, these scales have had limited impact in routine clinical practice. This may be due to perceived problems with internal validity (quality of research), as well as external validity (generalizability of results). We set out to collate information on exemplar stroke prognosis scales, giving particular attention to the scale content, derivation, and validation.

Methods: We performed a focused literature search, designed to return high profile scales that use baseline clinical data to predict mortality or disability. We described prognostic utility and collated information on the content, development and validation of the tools. We critically appraised chosen scales based on the CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modeling Studies (CHARMS).

Results: We chose 10 primary scales that met our inclusion criteria, six of which had revised/modified versions. Most primary scales used 5 input variables (range: 4–13), with substantial overlap in the variables included. All scales included age, eight included a measure of stroke severity, while five scales incorporated pre-stroke level of function (often using modified Rankin Scale), comorbidities and classification of stroke type. Through our critical appraisal, we found issues relating to excluding patients with missing data from derivation studies, and basing the selection of model variable on significance in univariable analysis (in both cases noted for six studies). We identified separate external validation studies for all primary scales but one, with a total of 60 validation studies.

Conclusions: Most acute stroke prognosis scales use similar variables to predict long-term outcomes and most have reasonable prognostic accuracy. While not all published scales followed best practice in development, most have been subsequently validated. Lack of clinical uptake may relate more to practical application of scales rather than validity. Impact studies are now necessary to investigate clinical usefulness of existing scales.

Validation of the Essen Stroke Risk Score in different subtypes of ischemic stroke

OBJECTIVE

Predictive scores are important tools for stratifying patients based on their risk of future vascular events and for selecting preventive therapies. The aim of this study is to validate the Essen Stroke Risk Score (ESRS) for stratifying stroke recurrence in different subtypes of non-atrial fibrillation ischemic stroke in a large Chinese cohort.

METHODS

Data were derived from the Blood pressure and clinical Outcome in Stroke Survivors registry, which includes a cohort of 2204 stroke patients. All patients were further classified according to the TOAST (Trial of Org 10 172 in Acute Stroke Treatment) criteria. We stratified one-year cumulative rates for stroke and composite vascular events using the ESRS. The predictive power of the ESRS was assessed using the area under the receiver-operator curves (AUC).

RESULTS

Among 1699 patients included in the study, the AUC of ESRS was 0.58 (95% CI: 0.52-0.64) for recurrent stroke, whereas 0.59 (95% CI: 0.53-0.64) for composite vascular events at 1 year. In patients with large-artery atherosclerosis (LAA) subtype of stroke, the AUC of ESRS was both 0.61 (95% CI: 0.54-0.68) for recurrent stroke and composite vascular events. However, no significant AUC was observed in patients with small-artery occlusion subtype of stroke.

CONCLUSIONS

In patients with LAA subtype of non-atrial fibrillation stroke, the ESRS has moderate accuracy in stratifying the risk of both recurrent strokes and major vascular events within the first year. However, the ESRS couldn't accurately stratify the risk of recurrent strokes in patients with small-artery atherosclerosis subtype of non-atrial fibrillation stroke.