Predicting Early Mortality of Acute Ischemic Stroke

Machine learning-based prognostication of mortality in stroke patients

Objectives

Predicting stroke mortality is crucial for personalized care. This study aims to design and evaluate a machine learning model to predict one-year mortality after a stroke.

Materials and methods

Data from the National Multiethnic Stroke Registry was utilized. Eight machine learning (ML) models were trained and evaluated using various metrics. SHapley Additive exPlanations (SHAP) analysis was used to identify the influential predictors.

Results

The final analysis included 9840 patients diagnosed with stroke were included in the study. The XGBoost algorithm exhibited optimal performance with high accuracy (94.5%) and AUC (87.3%). Core predictors encompassed National Institutes of Health Stroke Scale (NIHSS) at admission, age, hospital length of stay, mode of arrival, heart rate, and blood pressure. Increased NIHSS, age, and longer stay correlated with higher mortality. Ambulance arrival and lower diastolic blood pressure and lower body mass index predicted poorer outcomes.

Conclusions

This model's predictive capacity emphasizes the significance of NIHSS, age, hospital stay, arrival mode, heart rate, blood pressure, and BMI in stroke mortality prediction. Specific findings suggest avenues for data quality enhancement, registry expansion, and real-world validation. The study underscores machine learning's potential for early mortality prediction, improving risk assessment, and personalized care. The potential transformation of care delivery through robust ML predictive tools for Stroke outcomes could revolutionize patient care, allowing for personalized plans and improved preventive strategies for stroke patients. However, it is imperative to conduct prospective validation to evaluate its practical clinical effectiveness and ensure its successful adoption across various healthcare environments.

Technical Risk Stratification Nomogram Model for 90-Day Mortality Prediction in Patients With Acute Basilar Artery Occlusion Undergoing Endovascular Thrombectomy: A Multicenter Cohort Study

BACKGROUND

This study aimed to establish and validate a nomogram model for predicting 90-day mortality in patients with acute basilar artery occlusion receiving endovascular thrombectomy.

METHODS AND RESULTS

A total of 242 patients with basilar artery occlusion undergoing endovascular thrombectomy were enrolled in our study, in which 172 patients from 3 stroke centers were assigned to the training cohort, and 70 patients from another center were assigned to the validation cohort. Univariate and multivariate logistic regression analyses were adopted to screen prognostic predictors, and those with significance were subjected to establish a nomogram model in the training cohort. The discriminative accuracy, calibration, and clinical usefulness of the nomogram model was verified in the internal and external cohorts. Six variables, including age, baseline National Institutes of Health Stroke Scale score, Posterior Circulation-Alberta Stroke Program Early CT (Computed Tomography) score, Basilar Artery on Computed Tomography Angiography score, recanalization failure, and symptomatic intracranial hemorrhage, were identified as independent predictors of 90-day mortality of patients with basilar artery occlusion and were subjected to develop a nomogram model. The nomogram model exhibited good discrimination, calibration, and clinical usefulness in both the internal and the external cohorts. Additionally, patients were divided into low-, moderate-, and high-risk groups based on the risk-stratified nomogram model.

CONCLUSIONS

Our study proposed a novel nomogram model that could effectively predict 90-day mortality of patients with basilar artery occlusion after endovascular thrombectomy and stratify patients with high, moderate, or low risk, which has a potential to facilitate prognostic judgment and clinical management of stroke.

Stroke disease-specific quality of life trajectories and their associations with caregivers' anxiety, depression, and burden in stroke population: a longitudinal, multicentre study

AIMS

The aims of this study were to: (i) test if there are clusters of stroke survivors who experience distinct trajectories of quality of life (QOL) from hospital rehabilitation discharge to 12-month follow-up; (ii) test if any sociodemographic or clinical variables predict this class membership; and (iii) examine the associations between the clusters of stroke survivors' and their caregivers' trajectories of anxiety, depression, and burden over time.

METHODS AND RESULTS

A total of 415 stroke survivors and their caregivers were recruited in Italy for this 1-year, longitudinal, multicentre prospective study, filling out a survey at five time points. We found two distinct trajectories of change in stroke survivors' psychological QOL (i.e. Memory, Communication, Emotion, and Participation). The first trajectory (86% of the survivors) included those who started with greater levels of QOL and improved slightly to markedly in all psychological domains, while the second trajectory (14% of the survivors) comprised those who started with lower overall levels of psychological QOL and experienced a worsening or no changes at all in these dimensions up to 12-month follow-up. Very few clinical and sociodemographic variables at baseline predicted class membership. Finally, caregivers of those patients who experienced no change or a worsening in psychological QOL reported greater distress and burden over time.

CONCLUSION

Our results highlight the need for more tailored interventions to improve patients' psychological QOL and consequently their caregivers' well-being. This requires a shift from a stroke survivor-centred approach to a stroke survivor- and caregiver-centred one.

Patterns and predictors of ten-year mortality after discharge from community-based post-acute care for acquired brain injury: A retrospective cohort study (ABI-RESTaRT), Western Australia, 1991-2017

BACKGROUND

Survivors of acquired brain injury (ABI) are left with long-term disability and an increased risk of mortality years post-injury.

OBJECTIVE

To examine 10-year mortality in adults with ABI after discharge from post-acute care and identify modifiable risk factors to reduce long-term mortality risk.

METHODS

Retrospective cohort study of 586 adults with traumatic (TBI) or non-traumatic brain injury (NTBI), or neurologic condition, consecutively discharged from a post-acute rehabilitation service in Western Australia from 1-Mar-1991 to 31-Dec-2017. Data sources included rehabilitation records, and linked mortality, hospital, and emergency department data. Survival status at 10 years post-discharge was determined. All-cause and cause-specific age- and sex-adjusted standardised mortality ratios (SMR) by ABI diagnosis were calculated using Australian population reference data. Risk factors were examined using multilevel cox proportional hazards regression.

RESULTS

Compared with the Australian population, 10-year all-cause mortality was significantly elevated for all diagnosis cohorts, with the first 12 months the highest risk period. Accidents or intentional self-harm deaths were elevated in TBI (13.2, 95%CI 5.4; 12.1). Neurodegenerative disease deaths were elevated in Neurologic (21.9, 95%CI 13.0; 30.9) and Stroke (19.8; 95%CI 2.4; 27.2) cohorts. Stroke (20.8; 95%CI 7.9; 33.8) and circulatory disease deaths (6.2; 95%CI 2.3; 9.9) were also elevated in Stroke. Psychiatric comorbidity was the strongest risk factor followed by older age, geographical remoteness, and cardiac, vascular, genitourinary and renal comorbidity. Clinically significant improvement in functional independence and psychosocial functioning significantly reduced mortality risk.

CONCLUSIONS

Individuals with ABI have an elevated risk of mortality years post-injury. Comorbidity management, continuity of care, and rehabilitation are important to reduce long-term mortality risk.

Nomogram to predict 6-month mortality in acute ischemic stroke patients treated with endovascular treatment

Background

Acute Ischemic Stroke (AIS) presents significant challenges in evaluating the effectiveness of Endovascular Treatment (EVT). This study develops a novel prognostic model to predict 6-month mortality post-EVT, aiding in identifying patients likely to benefit less from this intervention, thus enhancing therapeutic decision-making.

Methods

We employed a cohort of AIS patients from Shenyang First People's Hospital, serving as the Validation set, to develop our model. LASSO regression was used for feature selection, followed by logistic regression to create a prognostic nomogram for predicting 6-month mortality post-EVT. The model's performance was validated using a dataset from PLA Northern Theater Command General Hospital, assessing discriminative ability (C-index), calibration (calibration plot), and clinical utility (decision curve analysis). Statistical significance was set at p < 0.05.

Results

The development cohort consisted of 219 patients. Six key predictors of 6-month mortality were identified: "Lack of Exercise" (OR, 4.792; 95% CI, 1.731-13.269), "Initial TICI Score 1" (OR, 1.334; 95% CI, 0.628-2.836), "MRS Score 5" (OR, 1.688; 95% CI, 0.754-3.78), "Neutrophil Percentage" (OR, 1.08; 95% CI, 1.042-1.121), "Onset Blood Sugar" (OR, 1.119; 95% CI, 1.007-1.245), and "Onset NIHSS Score" (OR, 1.074; 95% CI, 1.029-1.121). The nomogram demonstrated a high predictive capability with a C-index of 0.872 (95% CI, 0.830-0.911) in the development set and 0.830 (95% CI, 0.726-0.920) in the validation set.

Conclusion

Our nomogram, incorporating factors such as Lack of Exercise, Initial TICI Score 1, MRS Score 5, Neutrophil Percentage, Onset Blood Sugar, and Onset NIHSS Score, provides a valuable tool for predicting 6-month mortality in AIS patients post-EVT. It offers potential to refine early clinical decision-making and optimize patient outcomes, reflecting a shift toward more individualized patient care.

Development and validation of machine learning-based model for mortality prediction in patients with acute basilar artery occlusion receiving endovascular treatment: multicentric cohort analysis

BACKGROUND

Predicting mortality in stroke patients using information available before endovascular treatment (EVT) is an essential component for supporting clinical decision-making. Although the mortality rate of acute basilar artery occlusion (ABAO) after EVT has reached 40%, few studies have focused on predicting mortality in these individuals. Thus, we aimed to develop and validate a machine learning-based mortality prediction tool based on preoperative information for ABAO patients receiving EVT.

METHODS

The derivation cohort comprised patients from southern provinces of China in the BASILAR registry. The model (POSITIVE: Predicting mOrtality of baSilar artery occlusion patIents Treated wIth EVT) was trained and optimized using a fivefold cross-validation method in which hyperparameters were selected and fine-tuned. This model was retrospectively tested in patients from the northern provinces of China from the BASILAR registry. A prospective test of POSITIVE was performed on consecutive patients from two hospitals between January 2020 and June 2022.

RESULTS

Extreme gradient boosting was employed to construct the POSITIVE model, which achieved the best predictive performance among the eight machine learning algorithms and showed excellent discrimination (area under the curve (AUC) 0.83, 95% confidence interval (95% CI) 0.80 to 0.87) and calibration (Hosmer-Lemeshow test, P>0.05) in the development cohort. AUC yielded by the POSITIVE model for the retrospective test was 0.79 (95% CI 0.71 to 0.85), higher than that obtained by traditional models. Prospective comparisons showed that the POSITIVE model achieved the highest AUC (0.82, 95% CI 0.74 to 0.90) among all prediction models.

CONCLUSION

We developed a machine learning algorithm and retrospective and prospective testing with multicentric cohorts, which exhibited a solid predictive performance and may act as a convenient reference to guide decision-making for ABAO patients. The POSITIVE model is presented online for user-friendly access.

External Validation and Recalibration of a Mortality Prediction Model for Patients with Ischaemic Stroke

BACKGROUND

Stroke is a highly prevalent disease that can provoke severe disability. We evaluate a predictive model based on the Minimum Basic Data Set (MBDS) compiled by the Spain Health Ministry, obtained for the period 2008-2012 for patients with ischaemic stroke in Spain, to establish the model's validity and to optimise its calibration. The MBDS is the main clinical-administrative database for hospitalisations recorded in Spain, and to our knowledge, no predictive models for stroke mortality have previously been developed using this resource. The main study aim is to perform an external validation and recalibration of the coefficients of this predictive model with respect to a chronologically later cohort.

MATERIAL AND METHODS

External validation (testing the model on a different cohort to assess its performance) and recalibration (validation with optimisation of model coefficients) were performed using the MBDS for patients admitted for ischaemic stroke in the period 2016-2018. A cohort study was designed, in which a recalibrated model was obtained by applying the variables of the original model without their coefficients. The variables from the original model were then applied to the subsequent cohort, together with the coefficients from the initial model. The areas under the curve (AUC) of the recalibration and the external validation procedure were compared.

RESULTS

The recalibrated model produced an AUC of 0.743 and was composed of the following variables: age (odds ratio, OR:1.073), female sex (OR:1.143), ischaemic heart disease (OR:1.192), hypertension (OR:0.719), atrial fibrillation (OR:1.414), hyperlipidaemia (OR:0.652), heart failure (OR:2.133) and posterior circulation stroke (OR: 0.755). External validation produced an AUC of 0.726.

CONCLUSIONS

The recalibrated clinical model thus obtained presented moderate-high discriminant ability and was generalisable to predict death for patients with ischaemic stroke. Rigorous external validation slightly decreased the AUC but confirmed the validity of the baseline model for the chronologically later cohort.

[Inclisiran in patients with acute ischemic stroke: first data]

AIM

To evaluate the effect of inclisiran therapy on parameters of lipid metabolism in hospitalized patients with acute ischemic stroke.

MATERIAL AND METHODS

A prospective, observational, non-randomized study was performed. The study included 12 patients with acute ischemic stroke prescribed with a combination lipid-lowering therapy with inclisiran (284 mg as a single dose). At 15 days after the start of therapy, changes in blood lipid composition were assessed. For quantitative variables, median, maximum and minimum values were determined. The significance of differences between related samples in quantitative variables was assessed using the Mann-Whitney test.

RESULTS

Before the start of combination lipid-lowering therapy, total cholesterol (TC) was 7.33 mmol/l and low-density lipoprotein C (LDL-C) was 5.23 mmol/l. At 15 days after the start of inclisiran therapy, TC significantly decreased by 52.1 % and LDL-C decreased by 71.1 %. The proportion of patients who reached the LDL-C goal was 66.7 %. There were no adverse events considered by the investigators to be related with the therapy.

CONCLUSION

The strategy of early administration of inclisiran (or its combination with a statin) in patients with ischemic stroke allows safe achievement of a significant reduction in LDL-C already in 15 days after the start of therapy.

An interpretable ensemble learning model facilitates early risk stratification of ischemic stroke in intensive care unit: Development and external validation of ICU-ISPM

Ischemic stroke (IS) is a common and severe condition that requires intensive care unit (ICU) admission, with high mortality and variable prognosis. Accurate and reliable predictive tools that enable early risk stratification can facilitate interventions to improve patient outcomes; however, such tools are currently lacking. In this study, we developed and validated novel ensemble learning models based on soft voting and stacking methods to predict in-hospital mortality from IS in the ICU using two public databases: MIMIC-IV and eICU-CRD. Additionally, we identified the key predictors of mortality and developed a user-friendly online prediction tool for clinical use. The soft voting ensemble model, named ICU-ISPM, achieved an AUROC of 0.861 (95% CI: 0.829-0.892) and 0.844 (95% CI: 0.819-0.869) in the internal and external test cohorts, respectively. It significantly outperformed the APACHE scoring system and was more robust than individual models. ICU-ISPM obtained the highest performance compared to other models in similar studies. Using the SHAP method, the model was interpretable, revealing that GCS score, age, and intubation were the most important predictors of mortality. This model also provided a risk stratification system that can effectively distinguish between low-, medium-, and high-risk patients. Therefore, the ICU-ISPM is an accurate, reliable, interpretable, and clinically applicable tool, which is expected to assist clinicians in stratifying IS patients by the risk of mortality and rationally allocating medical resources. Based on ICU-ISPM, an online risk prediction tool was further developed, which was freely available at: http://ispm.idrblab.cn/.

One-Year Survival of Ischemic Stroke Patients Requiring Mechanical Ventilation

BACKGROUND

The outcome of patients with acute ischemic stroke who require mechanical ventilation has been poor. Intubation due to a reversible condition could be associated with better 1-year survival.

METHODS

All adult patients treated in Helsinki University Hospital in 2016-2020 who were admitted because of an ischemic stroke (either stroke or thrombosis seen on imaging) and needed mechanical ventilation were included in this retrospective cohort study. Data on demographics, medical history, index stroke, and indication for intubation were collected. The primary outcome was 1-year mortality. Secondary outcomes were modified Rankin Scale (mRS) score at 3 months and living arrangements at 1 year.

RESULTS

The mean age of the cohort (N = 121) was 66 ± 11 (mean ± SD) years, and the mean admission National Institutes of Health Stroke Scale score was 17 ± 10. Forty-four (36%) patients were male. The most common indication for intubation was unconsciousness (51%), followed by respiratory failure or airway compromise (28%). One-year mortality was 55%. Three-month mRS scores were available for 114 (94%) patients, with the following distribution: 0-2, 18%; 3-5, 28%; and 6 (dead), 54%. Of the 1-year survivors, 72% were living at home. In the multivariate analysis, only age over 75 years and intubation due to unconsciousness, respiratory failure, or cardiac arrest remained significantly associated with mortality.

CONCLUSIONS

The indication for intubation seems to significantly affect outcome. Functional outcome at 3 months is often poor, but a great majority of 1-year survivors are able to live at home.

Significant Mortality Associated With COVID-19 and Comorbid Cerebrovascular Disease: A Quantitative Systematic Review

We report the first quantitative systematic review of cerebrovascular disease in coronavirus disease 2019 (COVID-19) to provide occurrence rates and associated mortality. Through a comprehensive search of PubMed we identified 8 cohort studies, 5 case series, and 2 case reports of acute cerebrovascular disease in patients with confirmed COVID-19 diagnosis. Our first meta-analysis utilizing the identified publications focused on comorbid cerebrovascular disease in recovered and deceased patients with COVID-19. We performed 3 additional meta-analyses of proportions to produce point estimates of the mortality and incidence of acute cerebrovascular disease in COVID-19 patients. Patient's with COVID-19 who died were 12.6 times more likely to have a history of cerebrovascular disease. We estimated an occurrence rate of 2.6% (95% confidence interval, 1.2-5.4%) for acute cerebrovascular disease among consecutively admitted patients with COVID-19. While for those with severe COVID-19' we estimated an occurrence rate of 6.5% (95% confidence interval, 4.4-9.6%). Our analysis estimated a rate of 35.5% for in-hospital mortality among COVID-19 patients with concomitant acute cerebrovascular disease. This was consistent with a mortality rate of 34.0% which we obtained through an individual patient analysis of 47 patients derived from all available case reports and case series. COVID-19 patients with either acute or chronic cerebrovascular disease have a high mortality rate with higher occurrence of cerebrovascular disease in patients with severe COVID-19.

Neuroinflammation and anti-inflammatory therapy for ischemic stroke

Stroke remains one of the most devastating and challenging neurological diseases worldwide. Inflammation, as well as oxidative stress is one of the main contributors to post-stroke injuries, and oxidative stress can further induce inflammation. Moreover, the inflammatory response is closely related to immune modulation in ischemic stroke progression. Hence, major ischemic stroke treatment strategies include targeting inflammatory responses, immune modulation (especially immune cells), and inflammatory response to suppress stroke progression. To date, several drugs have demonstrated clinical efficacy, such as Etanercept and Fingolimod. However, only edaravone dexborneol has successfully passed the phase III clinical trial and been approved by the National Medical Products Administration (NMPA) to treat ischemic stroke in China, which can restore redox balance and regulate inflammatory immune responses, thus providing neuroprotection in ischemic stroke. In this review, we will comprehensively summarize the current advances in the application of inflammatory biomarkers, neuroinflammation and neuro-immunotherapeutic scenarios for ischemic stroke, thus aiming to provide a theoretical basis and new prospects and frontiers for clinical applications.

Predictors of Short-Term Mortality in Patients with Ischemic Stroke

Background and Objectives: The purpose of this study is to investigate the predictive factors for intrahospital mortality in ischemic stroke patients. We will examine the association between a range of clinical and demographic factors and intrahospital mortality, including age, sex, comorbidities, laboratory values, and medication use. Materials and Methods: This retrospective, longitudinal, analytic, observational cohort study included 243 patients over 18 years old with a new ischemic stroke diagnosis who were hospitalized in Cluj-Napoca Emergency County Hospital. Data collected included the patient demographics, baseline characteristics at hospital admission, medication use, carotid artery Doppler ultrasound, as well as cardiology exam, and intrahospital death. Results: Multivariate logistic regression was used to determine which variables were independently associated with intrahospital death. An NIHSS score > 9 (OR-17.4; p < 0.001) and a lesion volume > 22.3 mL (OR-5.8; p = 0.003) were found to be associated with the highest risk of death. In contrast antiplatelet treatment (OR-0.349; p = 0.04) was associated with lower mortality rates. Conclusions: Our study identified a high NIHSS score and large lesion volume as independent risk factors for intrahospital mortality in ischemic stroke patients. Antiplatelet therapy was associated with lower mortality rates. Further studies are needed to explore the potential mechanisms underlying these associations and to develop targeted interventions to improve patient outcomes.

Effect of the Frequency of Rehabilitation Treatments on the Long-Term Mortality of Stroke Survivors with Mild-to-Moderate Disabilities under the Korean National Health Insurance Service System

Given the increase in stroke-related social costs, studies on survival and functional prognosis after stroke are urgently needed. Therefore, we investigated the relationship between the frequency of rehabilitation treatments in the acute and subacute phases of stroke and the long-term mortality of stroke survivors with mild-to-moderate disabilities. We performed a retrospective cohort study using data from the Korean National Health Insurance Service database. Our final cohort included 733 patients with national disability registration grades 4-6. The number of special rehabilitation treatment claim codes was used as a proxy for the frequency of rehabilitation treatments. Furthermore, we categorized the rehabilitation frequencies within 24 months of stroke onset as 1-50, 51-200, 201-400, and >400. The dependent variable was all-cause mortality, and it was evaluated from 24 to 84 months after stroke onset. Severe disability was associated with a lower long-term mortality rate in the chronic phase (p < 0.001). In the Cox regression analysis, severe disability, older age, male sex, and chronic kidney disease were independent risk factors for long-term mortality in patients with stroke and mild-to-moderate disabilities. However, the frequency of acute/subacute rehabilitation treatments did not significantly improve long-term mortality. Our results suggest that the association between rehabilitation frequency and lower long-term mortality for patients with mild-to-moderate stroke was inconclusive. Therefore, further study is needed to determine a better-customized rehabilitation treatment system for these patients.

Development and internal validation of a clinical risk score for in-hospital mortality after stroke: a single-centre retrospective cohort study in Northwest Ethiopia

OBJECTIVE

To develop and validate a clinical risk score for in-hospital stroke mortality.

DESIGN

The study used a retrospective cohort study design.

SETTING

The study was carried out in a tertiary hospital in the Northwest Ethiopian region.

PARTICIPANTS

The study included 912 patients who had a stroke admitted to a tertiary hospital between 11 September 2018 and 7 March 2021.

MAIN OUTCOME MEASURES

Clinical risk score for in-hospital stroke mortality.

METHODS

We used EpiData V.3.1 and R V.4.0.4 for data entry and analysis, respectively. Predictors of mortality were identified by multivariable logistic regression. A bootstrapping technique was performed to internally validate the model. Simplified risk scores were established from the beta coefficients of predictors of the final reduced model. Model performance was evaluated using the area under the receiver operating characteristic curve and calibration plot.

RESULTS

From the total stroke cases, 132 (14.5%) patients died during the hospital stay. We developed a risk prediction model from eight prognostic determinants (age, sex, type of stroke, diabetes mellitus, temperature, Glasgow Coma Scale, pneumonia and creatinine). The area under the curve (AUC) of the model was 0.895 (95% CI: 0.859-0.932) for the original model and was the same for the bootstrapped model. The AUC of the simplified risk score model was 0.893 (95% CI: 0.856-0.929) with a calibration test p value of 0.225.

CONCLUSIONS

The prediction model was developed from eight easy-to-collect predictors. The model has excellent discrimination and calibration performance, similar to that of the risk score model. It is simple, easily remembered, and helps clinicians identify the risk of patients and manage it properly. Prospective studies in different healthcare settings are required to externally validate our risk score.

The value of clinical routine blood biomarkers in predicting long-term mortality after stroke

Background:

Several blood biomarkers have been identified as predictors for poor outcome after ischemic stroke. However, recent studies mainly focused on single or experimental biomarkers and considered rather short follow-up intervals limiting their value for daily clinical practice. We, therefore, aimed to compare various clinical routine blood biomarkers for their predictive value on post-stroke mortality over a 5-year follow-up period.

Patients and methods:

This data analysis of a prospective single-center study included all consecutive ischemic stroke patients admitted to the stroke unit of our university hospital over a 1-year period. Various blood biomarkers of inflammation, heart failure, metabolic disorders, and coagulation were analyzed from standardized routine blood samples collected within 24 h of hospital admission. All patients underwent a thorough diagnostic workup and were followed for 5 years post-stroke.

Results:

Of 405 patients (mean age: 70.3 years), 72 deceased (17.8%) during the follow-up period. While various routine blood biomarkers were associated with post-stroke mortality in univariable analyses, only NT-proBNP remained an independent predictor (adjusted odds ratio 5.1; 95% CI 2.0–13.1; p < 0.001) for death after stroke. NT-proBNP levels ⩾794 pg/mL ( n = 169, 42%) had a sensitivity of 90% for post-stroke mortality with a negative predictive value of 97% and was additionally associated with cardioembolic stroke and heart failure (each p ⩽ 0.05).

Conclusion:

NT-proBNP represents the most relevant routine blood-based biomarker for the prediction of long-term mortality after ischemic stroke. Increased NT-proBNP levels indicate a vulnerable subgroup of stroke patients in which early and thorough cardiovascular assessment and consistent follow-ups could improve outcome after stroke.

Derivation and Validation of a New Visceral Adiposity Index for Predicting Short-Term Mortality of Patients with Acute Ischemic Stroke in a Chinese Population

The visceral adiposity index (VAI) is related to the occurrence of various cardiometabolic diseases, atherosclerosis, and stroke. However, few studies have analyzed the impact on the short-term prognosis of stroke. We assessed the effect of VAI on short-term prognoses in patients with acute ischemic stroke through a retrospective cohort study of 225 patients with acute stroke who were admitted to the neurological intensive care unit of our hospital. We collected metabolic indicators (blood pressure, fasting glucose, lipids), National Institutes of Health Stroke Scale (NIHSS) scores, symptomatic intracranial hemorrhage, and other disease evaluation indicators on 197 patients who were screened for inclusion. VAI was calculated by using baseline data (sex, height, weight, waist circumference (WC)). We assessed functional recovery according to modified Rankin scale scores after 90 days. The receiver operating characteristic (ROC) curve was used to calculate the VAI cutoff value that affects short-term outcomes. A nomogram that can predict the risk of short-term mortality in patients with acute ischemic stroke was drawn. In total, 28 patients died within 90 days. Those patients had higher VAI (p = 0.000), higher triglyceride (TG) (p = 0.020) and NIHSS scores (p = 0.000), and lower high-density lipoprotein cholesterol (HDL-C) (p = 0.000) than patients who survived. VAI had higher predictive value of short-term mortality than did body mass index (BMI), body fat mass index (BFMI), and WC. VAI and NIHSS scores were independent risk factors for the short-term mortality of patients with stroke. Patients with a VAI > 2.355 had a higher risk of short-term mortality. VAI has a predictive value higher than that of traditional metabolic indicators such as BMI, BFMI, and WC. The nomogram, composed of NIHSS, VAI, HDL-C, and TG, may predict the short-term mortality of cerebral infarction patients.

The many roles of urgent catheter interventions: from myocardial infarction to acute stroke and pulmonary embolism

INTRODUCTION

Cardiovascular diseases (CVDs) are the leading cause of cardiovascular mortality and a major contributor to disability worldwide. The prevalence of CVDs is continuously increasing, and from 1990 to 2019, it has doubled. Global cardiovascular mortality has increased from 12.1 million in 1990 to 18.6 million cases in 2019. The development of therapeutic options for these diseases is at the forefront of interest concerning the extensive socio-economic consequences. Modern endovascular transcatheter therapeutic options contribute to the reduction of cardiovascular morbidity and mortality.

AREAS COVERED

The article concentrates on the triad of the most common causes of acute cardiovascular mortality and morbidity - myocardial infarction, ischemic stroke, and pulmonary embolism. Current evidence-based indications, specific interventional techniques, and remaining unsolved issues are reviewed and compared. A personal perspective on the possible implications for the future is provided.

EXPERT OPINION

Primary angioplasty for ST-segment elevation myocardial infarction is a well-established therapeutic option with proven mortality benefits. We suppose that catheter-based interventions for acute stroke will spread quickly from centers of excellence to routine clinical practice. We believe that ongoing research will provide a basis for the expansion of interventional treatment of pulmonary embolism soon.

Preventive ceftriaxone in patients at high risk of stroke-associated pneumonia. A post-hoc analysis of the PASS trial

BACKGROUND

Infections complicate the acute phase of stroke in one third of patients and especially pneumonia is associated with increased risk of death or dependency. In randomized trials of stroke patients, preventive antibiotics reduced overall infections, but did not reduce pneumonia or improve outcome. This may be explained by broad selection criteria, including many patients with a low risk of pneumonia. To assess the potential of selection of patients at high risk of pneumonia, we performed a post-hoc analysis in the Preventive Antibiotics in Stroke Study (PASS).

METHODS

PASS was a multicentre phase 3 trial in acute stroke patients who were randomized to preventive ceftriaxone for four days within 24 hours or standard care. For this analysis patients were divided based on the ISAN risk score for pneumonia as follows: low (0-6), medium (7-14) and high (15-21). Primary outcomes were pneumonia rate during admission as judged by the treating physician, and by an independent committee; secondary outcomes were overall infections and unfavorable outcome (modified Rankin Scale ≥3). We adjusted with multivariable regression for possible confounders: age, stroke subtype and severity, pre-stroke dependency and diabetes.

RESULTS

Pneumonia occurred more frequently in higher risk groups (25.7% (high), 9.0% (medium) 1.5%, (low)). The absolute difference in pneumonia rate between patients treated with ceftriaxone or standard care increased with the ISAN score (low: 0.5%, medium: 1.2%, high: 10.1%). After adjustment ceftriaxone reduced overall infections in the low and medium groups, not in the high-risk group. There was a trend towards reduction of pneumonia as judged by the committee (3.7% vs 13.6%, aOR = 0.164, p = 0.063) in the high-risk group.

CONCLUSIONS

This post-hoc analysis of PASS confirmed higher rates of pneumonia with higher ISAN scores, and suggests that in acute stroke patients with an ISAN score of ≥15, preventive ceftriaxone for four days may reduce pneumonia rate.

Non-Neurological Complications after Mechanical Thrombectomy for Acute Ischemic Stroke: A Retrospective Single-Center Study

Introduction

The global burden of stroke is high and mechanical thrombectomy is the cornerstone of the treatment. Incidences of acute non-neurological-complications are poorly described. Improve knowledge about these complications may allow to better prevent, detect and/or manage them. The aim is to identify risk markers of death or poor evolution.

Method

We conducted a retrospective single-center study to analyzed the incidence of non-neurologicalcomplications after mechanical thrombectomy in acute ischemic stroke. Patients who had experienced a stroke and undergone thrombectomy were identified using a registry in which we prospectively collected data from each patient admitted to our hospital with a diagnosis of stroke. Quantitative and qualitative variables were analyses. The association between studied variables and hospital death was assessed using simple logistic regression models.

Result

361 patients were reviewed but 16 were excluded due to a lack of medical information. Between 2012 and 2019, 345 patients were included. The median admission NIHSS score was 15. Seven percent of the patients died in the ICU. The following independent risk markers of death in the ICU were identified by logistic regression: respiratory complication, hypotension, infectious complication, and hyperglycemia.

Conclusion

In this large retrospective study of stroke, respiratory complications and pulmonary infections represented the most important non-neurological adverse events encountered in the ICU and associated with a risk of death.

Timing and causes of death after endovascular thrombectomy in patients with acute ischemic stroke

Introduction:

Endovascular thrombectomy (EVT) increases the chance of good functional outcome after ischemic stroke caused by a large vessel occlusion, but the risk of death in the first 90 days is still considerable. We assessed the causes, timing and risk factors of death after EVT to aid future studies aiming to reduce mortality.

Patients and methods:

We used data from the MR CLEAN Registry, a prospective, multicenter, observational cohort study of patients treated with EVT in the Netherlands between March 2014, and November 2017. We assessed causes and timing of death and risk factors for death in the first 90 days after treatment. Causes and timing of death were determined by reviewing serious adverse event forms, discharge letters, or other written clinical information. Risk factors for death were determined with multivariable logistic regression.

Results:

Of 3180 patients treated with EVT, 863 (27.1%) died in the first 90 days. The most common causes of death were pneumonia (215 patients, 26.2%), intracranial hemorrhage (142 patients, 17.3%), withdrawal of life-sustaining treatment because of the initial stroke (110 patients, 13.4%) and space-occupying edema (101 patients, 12.3%). In total, 448 patients (52% of all deaths) died in the first week, with intracranial hemorrhage as most frequent cause. The strongest risk factors for death were hyperglycemia and functional dependency before the stroke and severe neurological deficit at 24–48 h after treatment.

Discussion and conclusion:

When EVT fails to decrease the initial neurological deficit, strategies to prevent complications like pneumonia and intracranial hemorrhage after EVT could improve survival, as these are often the cause of death.

One-year mortality after acute stroke: a prospective cohort study from a comprehensive stroke care centre, Kerala, India

OBJECTIVES

The primary objective was to report the 1-year all-cause mortality among patients with stroke. The secondary objectives were (1) to report the mortality stratified by type of stroke and sex and (2) to report predictors of 1-year mortality among patients with stroke.

DESIGN

A prospective cohort study.

SETTING

Institutional-stroke care unit of a tertiary care hospital PARTICIPANTS: Patients who were treated in the study institution during 2016-2020 for acute stroke and were followed up for a period of 1 year after stroke in the same institution.

MAIN OUTCOME MEASURES

The main outcome measures were the mortality proportion of any stroke and first ever stroke cohorts at select time points, including in-hospital stay, along with 2 weeks, 2 months, 6 months and 1 year after index stroke. The secondary outcomes were (1) mortality proportions stratified by sex and type of stroke and (2) predictors of 1-year mortality for any stroke and first ever stroke.

RESULTS

We recruited a total of 1336 patients. The mean age of participants was 61.6 years (13.5 years). The mortality figures for 2 weeks, 2 months, 6 months and 12 months after discharge were 79 (5.9%), 88 (6.7%), 101 (7.6%) and 114 (8.5%), respectively, in the full cohort. The in-hospital mortality was 45 (3.4%). The adjusted analysis revealed 3 predictors for 1-year mortality after first ever stroke-age, pre-treatment National Institutes of Health Stroke Scale (NIHSS) score and Modified Rankin Scale (mRS) score at baseline. The same for the full cohort had only two predictors-age and pre-treatment NIHSS score.

CONCLUSION

Mortality of stroke at 1-year follow-up in the study population is low in comparison to several studies published earlier. The predictors of 1-year mortality after stroke included age, NIHSS score at baseline and mRS score at baseline.

The Role of Extracellular Vesicles in Ischemic Stroke Severity

The possibility of characterizing the extracellular vesicles (EVs) based on parental cell surface markers and their content makes them a new attractive prognostic biomarker. Thus, our study aims to verify the role of EVs as relevant prognostic factors for acute and mid-term outcomes in ischemic stroke. Forty-seven patients with acute ischemic stroke were evaluated at admission (T0), immediately after recanalization treatment or after 2 h in non-treated patients (T1) and after one week (Tw) using the National Institutes of Health Stroke Scale (NIHSS), and after 3 months using the Modified Rankin Scale (mRS). Total count and characterization of EVs were assessed by Nanosight analysis and flow cytometry. The relationships between stroke outcomes and EV count were assessed through multivariable negative binomial regression models. We found that the amount of platelet-derived EVs at admission was positively associated with the severity of ischemic stroke at the onset as well as with the severity of mid-term outcome. Moreover, our study revealed that T-cell-derived EVs at admission were positively related to both early and mid-term ischemic stroke outcomes. Finally, T-cell-derived EVs at T1 were positively related to mid-term ischemic stroke outcome. The present study suggests that specific EV subtypes are associated with stroke severity and both short- and long-term outcomes. EVs could represent a valid tool to improve risk stratification in patients with ischemic stroke and post-recanalization treatment monitoring.

State of the Science: The Relevance of Symptoms in Cardiovascular Disease and Research: A Scientific Statement From the American Heart Association

Symptoms of cardiovascular disease drive health care use and are a major contributor to quality of life. Symptoms are of fundamental significance not only to the diagnosis of cardiovascular disease and appraisal of response to medical therapy but also directly to patients' daily lives. The primary purpose of this scientific statement is to present the state of the science and relevance of symptoms associated with cardiovascular disease. Symptoms as patient-reported outcomes are reviewed in terms of the genesis, manifestation, and similarities or differences between diagnoses. Specifically, symptoms associated with acute coronary syndrome, heart failure, valvular disorders, stroke, rhythm disorders, and peripheral vascular disease are reviewed. Secondary aims include (1) describing symptom measurement methods in research and application in clinical practice and (2) describing the importance of cardiovascular disease symptoms in terms of clinical events and other patient-reported outcomes as applicable.

Association between rehabilitation after reperfusion treatment and in-hospital mortality: Results from a national registry study

Background

There is no effective regimen to reduce the mortality of patients treated with intravenous thrombolysis or endovascular therapy (EVT). Therefore, we aimed to examine whether sequential therapy by rehabilitation could effectively reduce the in-hospital mortality of patients treated with reperfusion therapy.

Methods

This prospective registry study included patients with ischemic stroke who were treated by intravenous thrombolysis or endovascular therapy at Stroke Center Work Plan in China between 1 October 2018 and 31 July 2020. The patients were divided into 2 groups: those with (IRT+) or without (IRT–) inpatient rehabilitation therapy (IRT). The primary outcome was all-cause in-hospital mortality. We used Cox proportional hazards models and conducted a propensity score matching analysis to calculate hazard ratios (HRs) for mortality in the thrombolysis-only and EVT groups.

Results

Of the 189,519 patients in the thrombolysis-only group, 35.7% were women, and the median (interquartile range, IQR) age, onset-to-needle time, and follow-up time were 66 (57–74) years, 165 (119–220) min, and 9 (5–12) days, respectively. Among the 45,211 patients in the EVT group, 35.9% were women, and the median (interquartile range, IQR) age, onset-to-puncture time, and follow-up time were 66 (56–74) years, 297 (205–420) min, and 11 (6–16) days, respectively. In the thrombolysis-only group with a median (IQR) initial National Institutes of Health Stroke Scale (NIHSS) score of 6 (3–11), 105,244 patients (55.5%) treated with IRT had significantly lower all-cause in-hospital mortality [0.6 vs. 2.3%; adjusted HR 0.18 (95% confidence interval (CI) 0.16–0.2)] than those without IRT. In the EVT group with a median (IQR) initial NIHSS score of 15 (10–20), 31,098 patients (68.8%) treated with IRT also had significantly lower all-cause in-hospital mortality [2 vs. 12.1%; adjusted HR, 0.13 (95% CI 0.12–0.15)]. IRT remained significantly associated with reduced in-hospital mortality in sensitivity, subgroup, and propensity score matching analyses among both the thrombolysis-only and EVT groups.

Conclusion

Among the patients with ischemic stroke treated with intravenous thrombolysis or endovascular therapy, sequential therapy by rehabilitation was associated with lower all-cause in-hospital mortality. These findings suggest the necessity of promoting inpatient rehabilitation therapy after reperfusion in patients with ischemic stroke.

Incidence, early case fatality and determinants of stroke in Iran: Golestan Cohort Study

OBJECTIVES

While few studies investigated the incidence of stroke in Iran, no Iranian cohort has estimated the standardized-incidence rate and early fatality of first-ever-stroke subtypes along with associated factors.

METHODS

Golestan Cohort Study is a prospective study launched in northeastern Iran in 2004, including 50,045 individuals aged 40-75 at baseline. Age-standardized incidence rate of first-ever-stroke was calculated per 100,000 person-years, according to World Standard Population. The 28-day case fatality was calculated by dividing the number of fatal first-ever-stroke during the first 28 days by total events. Cox proportional hazard models were conducted to assess incidence and fatality risk factors. We used Population Attributable Fractions to estimate the incidence and early fatality proportions reduced by ideal risk factor control.

RESULTS

1,135 first-ever-strokes were observed during 8.6 (median) years follow-up. First-ever-stroke standardized incidence rate was estimated 185.2 (95% CI: 173.2-197.2) per 100,000 person-years. The 28-day case fatality was 44.1% (95% CI: 40.4-48.2). Hypertension and pre-stroke physical activity were the strongest risk factors associated with first-ever-stroke incidence (Hazard ratio: 2.83; 2.47-3.23) and 28-day case fatality (Hazard ratio: 0.59; 0.44-0.78), respectively. Remarkably, opium consumption was strongly associated with hemorrhagic stroke incidence (Hazard ratio: 1.52; 1.04-2.23) and ischemic stroke fatality (Hazard ratio: 1.44; 1.01-2.09). Overall, modifiable risk factors contributed to 83% and 61% of first-ever-stroke incidence and early fatality, respectively.

CONCLUSION

Efficient risk factor control can considerably reduce stroke occurrence and fatality in our study. Establishing awareness campaigns and 24-hour stroke units seem necessary for improving the stroke management in this area.

Microfluidic Model to Evaluate Astrocyte Activation in Penumbral Region following Ischemic Stroke

Stroke is one of the main causes of death in the US and post-stroke treatment options remain limited. Ischemic stroke is caused by a blood clot that compromises blood supply to the brain, rapidly leading to tissue death at the core of the infarcted area surrounded by a hypoxic and nutrient-starved region known as the penumbra. Recent evidence suggests that astrocytes in the penumbral region play a dual role in stroke response, promoting further neural and tissue damage or improving tissue repair depending on the microenvironment. Thus, astrocyte response in the hypoxic penumbra could promote tissue repair after stroke, salvaging neurons in the affected area and contributing to cognitive recovery. However, the complex microenvironment of ischemic stroke, characterized by gradients of hypoxia and nutrients, poses a unique challenge for traditional in vitro models, which in turn hinders the development of novel therapies. To address this challenge, we have developed a novel, polystyrene-based microfluidic device to model the necrotic and penumbral region induced by an ischemic stroke. We demonstrated that when subjected to hypoxia, and nutrient starvation, astrocytes within the penumbral region generated in the microdevice exhibited long-lasting, significantly altered signaling capacity including calcium signaling impairment.

Risk prediction of 30-day mortality after stroke using machine learning: a nationwide registry-based cohort study

Backgrounds

We aimed to develop and validate machine learning (ML) models for 30-day stroke mortality for mortality risk stratification and as benchmarking models for quality improvement in stroke care.

Methods

Data from the UK Sentinel Stroke National Audit Program between 2013 to 2019 were used. Models were developed using XGBoost, Logistic Regression (LR), LR with elastic net with/without interaction terms using 80% randomly selected admissions from 2013 to 2018, validated on the 20% remaining admissions, and temporally validated on 2019 admissions. The models were developed with 30 variables. A reference model was developed using LR and 4 variables. Performances of all models was evaluated in terms of discrimination, calibration, reclassification, Brier scores and Decision-curves.

Results

In total, 488,497 stroke patients with a 12.3% 30-day mortality rate were included in the analysis. In 2019 temporal validation set, XGBoost model obtained the lowest Brier score (0.069 (95% CI: 0.068–0.071)) and the highest area under the ROC curve (AUC) (0.895 (95% CI: 0.891–0.900)) which outperformed LR reference model by 0.04 AUC (p < 0.001) and LR with elastic net and interaction term model by 0.003 AUC (p < 0.001). All models were perfectly calibrated for low (< 5%) and moderate risk groups (5–15%) and ≈1% underestimation for high-risk groups (> 15%). The XGBoost model reclassified 1648 (8.1%) low-risk cases by the LR reference model as being moderate or high-risk and gained the most net benefit in decision curve analysis.

Conclusions

All models with 30 variables are potentially useful as benchmarking models in stroke-care quality improvement with ML slightly outperforming others.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12883-022-02722-1.

Correlation between red blood cell distribution width, neutrophil to lymphocyte ratio, and neutrophil to platelet ratio with 3-month prognosis of patients with intracerebral hemorrhage: a retrospective study

BACKGROUND

Red cell distribution width (RDW) is a parameter that indsicates the heterogeneity of red blood cell size and could be a prognostic factor in some diseases. Also, intracerebral hemorrhage (ICH) is considered a vascular event with a high mortality rate. We aimed to examine the role of RDW, neutrophil to lymphocyte ratio (NLR), and neutrophil to platelet ratio (NPR) in predicting the prognosis of patients with ICH.

METHODS

This is a retrospective cohort study conducted on 140 patients with ICH admitted to the neurology ward and intensive care unit (ICU) in Imam Reza Hospital, Tabriz, Iran. Demographic data, National Institutes of Health Stroke Scale (NIHSS), and complete blood count test parameters were evaluated within 24 h after hospitalization. These variables were collected and re-evaluated three months later.

RESULTS

The mean age of the study population was 61.14 (± 16) years and 51% were male. The mean NLR (p = 0.05), neutrophil count (p=0.04), platelet count (p = 0.05), and NIHSS (p<0.01)  had a significant difference between the deceased patients and those who partially recovered after three months. The ROC curve showed that NIHSS (area under curve (AUC): 0.902), followed by NPR (AUC: 0.682) variables had the highest AUC.

CONCLUSION

RDW could be a relevant prognostic factor and predictor in determining 3-months survival in ICH. Nevertheless, further large-scale prospective cohorts might be needed to evaluate the associations.

Acute ischaemic stroke associated with SARS-CoV-2 infection in North America

BACKGROUND

To analyse the clinical characteristics of COVID-19 with acute ischaemic stroke (AIS) and identify factors predicting functional outcome.

METHODS

Multicentre retrospective cohort study of COVID-19 patients with AIS who presented to 30 stroke centres in the USA and Canada between 14 March and 30 August 2020. The primary endpoint was poor functional outcome, defined as a modified Rankin Scale (mRS) of 5 or 6 at discharge. Secondary endpoints include favourable outcome (mRS ≤2) and mortality at discharge, ordinal mRS (shift analysis), symptomatic intracranial haemorrhage (sICH) and occurrence of in-hospital complications.

RESULTS

A total of 216 COVID-19 patients with AIS were included. 68.1% (147/216) were older than 60 years, while 31.9% (69/216) were younger. Median [IQR] National Institutes of Health Stroke Scale (NIHSS) at presentation was 12.5 (15.8), and 44.2% (87/197) presented with large vessel occlusion (LVO). Approximately 51.3% (98/191) of the patients had poor outcomes with an observed mortality rate of 39.1% (81/207). Age >60 years (aOR: 5.11, 95% CI 2.08 to 12.56, p<0.001), diabetes mellitus (aOR: 2.66, 95% CI 1.16 to 6.09, p=0.021), higher NIHSS at admission (aOR: 1.08, 95% CI 1.02 to 1.14, p=0.006), LVO (aOR: 2.45, 95% CI 1.04 to 5.78, p=0.042), and higher NLR level (aOR: 1.06, 95% CI 1.01 to 1.11, p=0.028) were significantly associated with poor functional outcome.

CONCLUSION

There is relationship between COVID-19-associated AIS and severe disability or death. We identified several factors which predict worse outcomes, and these outcomes were more frequent compared to global averages. We found that elevated neutrophil-to-lymphocyte ratio, rather than D-Dimer, predicted both morbidity and mortality.

Validation of the Premise Score after Addition of Recurrent Stroke Variable to Predicting Early Mortality in Acute Ischemic Stroke Patients

BACKGROUND: Predicting Early Mortality of Acute Ischemic Stroke (PREMISE) score is a recent scoring derived from the Austrian Stroke Unit Registry. Internal validation assigned by Haji Adam Malik General Hospital Medan in 2020 stated that the performance of its discrimination was not strong enough and leads to a further necessity for an improvement by an addition of another variable. AIM: This study aims to assess the calibration and discrimination performance of the PREMISE score after addition of recurrent stroke variable to predicting early mortality in acute ischemic stroke patients. METHODS: Retrospective cohort study was performed in a population of ischemic stroke patients admitted to Haji Adam Malik General Hospital Medan from January to December 2019. The score’s calibration was calculated by the Hosmer–Lemeshow goodness-of-fit test and its discriminatory power by calculating the area under curve (AUC) after adding the recurrent stroke variable. RESULTS: In total, 223 ischemic stroke patients were included in the analysis, there were 69 patients with recurrent stroke (30.9%). The PREMISE score showed good calibration (Hosmer–Lemeshow p = 0.331) and a strong enough discrimination power with an AUC value of 0.783. The addition of the recurrent stroke variable to the PREMISE score showed an increase score’s calibration with Hosmer–Lemeshow p = 0.575 and discrimination power with an AUC value of 0.806. CONCLUSION: The PREMISE score after the addition of the recurrent stroke variable showed an increase calibration and discrimination performance to predicting early mortality in acute ischemic stroke patients.

Predictive Model and Mortality Risk Score during Admission for Ischaemic Stroke with Conservative Treatment

Background: Stroke is the second cause of mortality worldwide and the first in women. The aim of this study is to develop a predictive model to estimate the risk of mortality in the admission of patients who have not received reperfusion treatment. Methods: A retrospective cohort study was conducted of a clinical–administrative database, reflecting all cases of non-reperfused ischaemic stroke admitted to Spanish hospitals during the period 2008–2012. A predictive model based on logistic regression was developed on a training cohort and later validated by the “hold-out” method. Complementary machine learning techniques were also explored. Results: The resulting model had the following nine variables, all readily obtainable during initial care. Age (OR 1.069), female sex (OR 1.202), readmission (OR 2.008), hypertension (OR 0.726), diabetes (OR 1.105), atrial fibrillation (OR 1.537), dyslipidaemia (0.638), heart failure (OR 1.518) and neurological symptoms suggestive of posterior fossa involvement (OR 2.639). The predictability was moderate (AUC 0.742, 95% CI: 0.737–0.747), with good visual calibration; Pearson’s chi-square test revealed non-significant calibration. An easily consulted risk score was prepared. Conclusions: It is possible to create a predictive model of mortality for patients with ischaemic stroke from which important advances can be made towards optimising the quality and efficiency of care. The model results are available within a few minutes of admission and would provide a valuable complementary resource for the neurologist.

Development and Validation of Prediction Models for Severe Complications After Acute Ischemic Stroke: A Study Based on the Stroke Registry of Northwestern Germany

Background

The treatment of stroke has been undergoing rapid changes. As treatment options progress, prediction of those under risk for complications becomes more important. Available models have, however, frequently been built based on data no longer representative of today’s care, in particular with respect to acute stroke management. Our aim was to build and validate prediction models for 4 clinically important, severe outcomes after stroke.

Methods and Results

We used German registry data from 152 710 patients with acute ischemic stroke obtained in 2016 (development) and 2017 (validation). We took into account potential predictors that were available at admission and focused on in‐hospital mortality, intracranial mass effect, secondary intracerebral hemorrhage, and deep vein thrombosis as outcomes. Validation cohort prediction and calibration performances were assessed using the following 4 statistical approaches: logistic regression with backward selection, l1‐regularized logistic regression, k‐nearest neighbor, and gradient boosting classifier. In‐hospital mortality and intracranial mass effects could be predicted with high accuracy (both areas under the curve, 0.90 [95% CI, 0.90–0.90]), whereas the areas under the curve for intracerebral hemorrhage (0.80 [95% CI, 0.80–0.80]) and deep vein thrombosis (0.73 [95% CI, 0.73–0.73]) were considerably lower. Stroke severity was the overall most important predictor. Models based on gradient boosting achieved better performances than those based on logistic regression for all outcomes. However, area under the curve estimates differed by a maximum of 0.02.

Conclusions

We validated prediction models for 4 severe outcomes after acute ischemic stroke based on routinely collected, recent clinical data. Model performance was superior to previously proposed approaches. These predictions may help to identify patients at risk early after stroke and thus facilitate an individualized level of care.

Predictive value of the videofluoroscopic swallowing study for long-term mortality in patients with subacute stroke

To investigate the usefulness of the videofluoroscopic swallowing study (VFSS) for subacute stroke in predicting long-term all-cause mortality, including not only simple parameters obtained from VFSS results, but also recommended dietary type as an integrated parameter.This was a retrospective study of patients with subacute (<1 month) stroke at a university hospital between February 2014 and September 2019. The independent risk factors were investigated using stepwise Cox regression analysis, which increased the all-cause mortality of patients with stroke among VFSS parameters.A total of 242 patients with subacute stroke were enrolled. The significant mortality-associated factors were age, history of cancer, recommended dietary type (modified dysphagia diet; adjusted hazard ratio [HR], 6.971; P = .014; tube diet, adjusted HR: 10.169; P = .019), and Modified Barthel Index. In the subgroup survival analysis of the modified dysphagia diet group (n = 173), the parameters for fluid penetration (adjusted HR: 1.911; 95% confidence interval, 1.086-3.363; P = .025) and fluid aspiration (adjusted HR: 2.236; 95% confidence interval, 1.274-3.927; P = .005) were significantly associated with mortality.The recommended dietary type determined after VFSS in subacute stroke was a significant risk factor for all-cause mortality as an integrated parameter for dysphagia. Among the VFSS parameters, fluid penetration and aspiration were important risk factors for all-cause mortality in patients with moderate dysphagia after stroke. Therefore, it is important to classify the degree of dysphagia by performing the VFSS test in the subacute period of stroke and to determine the appropriate diet and rehabilitation intervention for mortality-related prognosis.

Increased admission serum total bile acids can be associated with decreased 3-month mortality in patients with acute ischemic stroke

BACKGROUND

Bile acids (BAs) not only play an important role in lipid metabolism and atherosclerosis but also have antiapoptotic and neuroprotective effects. However, few studies have focused on the relationship of the total bile acid (TBA) levels with the severity and prognosis of acute ischemic stroke (AIS).

OBJECTIVES

The aim of this study was to investigate the potential associations of the fasting serum TBA levels on admission with the stroke severity, in-hospital complication incidence and 3 -month all-cause mortality in patients with AIS.

METHODS

A total of 777 consecutive AIS patients were enrolled in this study and were divided into four groups according to the quartiles of the serum TBA levels on admission. Univariate and multivariate logistic regression analyses were used to explore the relationship between the fasting TBA levels and the stroke severity, in-hospital complications, and 3-month mortality in AIS patients.

RESULTS

Patients in group Q3 had the lowest risk of severe AIS (NIHSS > 10) regardless of the adjustments for confounders (P < 0.05). During hospitalization, 115 patients (14.8%) had stroke progression (NIHSS score increased by ≥ 2), and 222 patients (28.6%) developed at least one complication, with no significant difference among the four groups (P > 0.05). There was no significant difference in the incidence of pneumonia, urinary tract infection (UTI), hemorrhagic transformation (HT), gastrointestinal bleeding (GIB), seizures or renal insufficiency (RI) among the four groups (P > 0.05). A total of 114 patients (14.7%) died from various causes (including in-hospital deaths) at the 3-month follow-up, including 42 (21.3%), 26 (13.3%), 19 (9.9%) and 27 (13.9%) patients in groups Q1, Q2, Q3 and Q4 respectively, with significant differences (P = 0.013). After adjusting for confounding factors, the risk of death decreased (P -trend < 0.05) in groups Q2, Q3, and Q4 when compared with group Q1, and the OR values were 0.36 (0.16-0.80), 0.30 (0.13-0.70), and 0.29 (0.13-0.65), respectively.

CONCLUSIONS

TBA levels were inversely associated with the 3-month mortality of AIS patients but were not significantly associated with the severity of stroke or the incidence of complications.

Atrial Fibrillation Is Not an Independent Determinant of Mortality Among Critically Ill Acute Ischemic Stroke Patients: A Propensity Score-Matched Analysis From the MIMIC-IV Database

Background/Objective

This study was conducted to investigate the clinical characteristics and outcomes of patients with acute ischemic stroke and atrial fibrillation (AF) in intensive care units (ICUs).

Methods

In the Medical Information Mart for Intensive Care IV database, 1,662 patients with acute ischemic stroke were identified from 2008 to 2019. Of the 1,662 patients, 653 had AF. The clinical characteristics and outcomes of patients with and without AF were compared using propensity score matching (PSM). Furthermore, univariate and multivariate Cox regression analyzes were performed.

Results

Of the 1,662 patients, 39.2% had AF. The prevalence of AF in these patients increased in a stepwise manner with advanced age. Patients with AF were older and had higher Charlson Comorbidity Index, CHA2DS2-VASc Score, HAS-BLED score, and Acute Physiology Score III than those without AF. After PSM, 1,152 patients remained, comprising 576 matched pairs in both groups. In multivariate analysis, AF was not associated with higher ICU mortality [hazard ratio (HR), 0.95; 95% confidence interval (CI), 0.64–1.42] or in-hospital mortality (HR, 1.08; 95% CI, 0.79–1.47). In Kaplan–Meier analysis, no difference in ICU or in-hospital mortality was observed between patients with and without AF.

Conclusions

AF could be associated with poor clinical characteristics and outcomes; however, it does not remain an independent short-term predictor of ICU and in-hospital mortality among patients with acute ischemic stroke after PSM with multivariate analysis.

Persistent hyperglycemia is a useful glycemic pattern to predict stroke mortality: a systematic review and meta-analysis

BACKGROUND

Glycemic patterns have been reported to be prognostic factors for stroke; however, this remains to be further evaluated. This meta-analysis aimed to evaluate the usefulness of glycemic patterns such as persistent hyperglycemia (PH) including short duration and long duration PH (SPH; LPH), admission hyperglycemia (AH), short-duration hyperglycemia (SH), and persistent normoglycemia (PN) in predicting stroke prognosis using published results.

METHODS

Major scientific databases including but are not limited to PubMed, EMBASE, Web of Science, Ovid, CNKI (Chinese National Knowledge Infrastructure), and Clinicaltrials.gov were searched till 1st March 2021 for clinical trials on the correlation between glycemic patterns and stroke outcomes. The primary outcome was defined as short-term (1- or 3-month) post-stroke mortality, and the secondary outcome was post-stroke hemorrhage at 6 months.

RESULTS

Ten studies involving 3584 individuals were included in the final analysis. In subgroup analyses, PH patients with no history of diabetes had increased post-stroke mortality (odds ratio [OR]: 4.80, 95% CI: 3.06-7.54) than patients with no PH; and patients with glucose levels > 140 mg/dl had greater mortality (OR: 5.12, 95% CI: 3.21-8.18) than those with glucose levels < 140 mg/dl; compared with AH patients, PH patients had increased short-term mortality (OR: 0.31, 95% CI: 0.16-0.60). In the prediction of stroke mortality among patients without diabetes, SPH (OR: 0.28, 95%CI: 0.12-0.69) seemed to be more related to increased mortality than LPH (OR: 0.35, 95% CI: 0.14--0.90).

CONCLUSIONS

PH, especially SPH, could predict increased post-stroke mortality in non-diabetic patients. The rank of individual glycemic patterns in predicting stroke mortality in non-diabetic patients was SPH > LPH > AH > PN.

Involvement of Specialist Palliative Care in a Stroke Unit in Austria-Challenges for Families and Stroke Teams

Purpose: Severe stroke poses vast challenges. Appropriate goals of care according to individual preferences and values have to be developed under time restrictions—often impeded by limited ability to communicate and the need for decisions by surrogates. The aim of our study was to explore the decision-making process and the involvement of specialist palliative care in the acute phase of severe stroke.

Methods: Twenty patients suffering from severe ischemic stroke treated in an Austrian acute inpatient stroke unit were included in a prospective study. Their families were interviewed with a questionnaire (FS-ICU 24), which covered satisfaction with care and decision-making. With a second questionnaire, decision-making processes within the stroke team were investigated.

Results: A palliative approach and early integration of specialist palliative care in severe ischemic stroke results in individualized therapeutic goals, including withholding therapeutic or life-sustaining measures, especially in patients with pre-existing illness.

Conclusions: Family members benefit from understandable and consistent information, emotional support, and a professional team identifying their needs. Stroke unit professionals need skills as well as knowledge and strategies in order to make decisions and provide treatment at the end-of-life, when there may be ethical or legal issues. Close cooperation with specialist palliative care services supports both treatment teams and families with communication and decision-making for patients with severe ischemic stroke.

Predicting short and long-term mortality after acute ischemic stroke using EHR

OBJECTIVE

Despite improvements in treatment, stroke remains a leading cause of mortality and long-term disability. In this study, we leveraged administrative data to build predictive models of short- and long-term post-stroke all-cause-mortality.

METHODS

The study was conducted and reported according to the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) guideline. We used patient-level data from electronic health records, three algorithms, and six prediction windows to develop models for post-stroke mortality.

RESULTS

We included 7144 patients from which 5347 had survived their ischemic stroke after two years. The proportion of mortality was between 8%(605/7144) within 1-month, to 25%(1797/7144) for the 2-years window. The three most common comorbidities were hypertension, dyslipidemia, and diabetes. The best Area Under the ROC curve(AUROC) was reached with the Random Forest model at 0.82 for the 1-month prediction window. The negative predictive value (NPV) was highest for the shorter prediction windows - 0.91 for the 1-month - and the best positive predictive value (PPV) was reached for the 6-months prediction window at 0.92. Age, hemoglobin levels, and body mass index were the top associated factors. Laboratory variables had higher importance when compared to past medical history and comorbidities. Hypercoagulation state, smoking, and end-stage renal disease were more strongly associated with long-term mortality.

CONCLUSION

All the selected algorithms could be trained to predict the short and long-term mortality after stroke. The factors associated with mortality differed depending on the prediction window. Our classifier highlighted the importance of controlling risk factors, as indicated by laboratory measures.

The Impact of Post-contrast Acute Kidney Injury on In-hospital Mortality After Endovascular Thrombectomy in Patients With Acute Ischemic Stroke

Background and Purpose: Clinical outcome and mortality after endovascular thrombectomy (EVT) in patients with ischemic stroke are commonly assessed after 3 months. In patients with acute kidney injury (AKI), unfavorable results for 3-month mortality have been reported. However, data on the in-hospital mortality after EVT in this population are sparse. In the present study, we assessed whether AKI impacts in-hospital and 3-month mortality in patients undergoing EVT.

Materials and Methods: From a prospectively recruiting database, consecutive acute ischemic stroke patients receiving EVT between 2010 and 2018 due to acute large vessel occlusion were included. Post-contrast AKI (PC-AKI) was defined as an increase of baseline creatinine of ≥0.5 mg/dL or >25% within 48 h after the first measurement at admission. Adjusting for potential confounders, associations between PC-AKI and mortality after stroke were tested in univariate and multivariate logistic regression models.

Results: One thousand one hundred sixty-nine patients were included; 166 of them (14.2%) died during the acute hospital stay. Criteria for PC-AKI were met by 29 patients (2.5%). Presence of PC-AKI was associated with a significantly higher risk of in-hospital mortality in multivariate analysis [odds ratio (OR) = 2.87, 95% confidence interval (CI) = 1.16–7.13, p = 0.023]. Furthermore, factors associated with in-hospital mortality encompassed higher age (OR = 1.03, 95% CI = 1.01–1.04, p = 0.002), stroke severity (OR = 1.05, 95% CI = 1.03–1.08, p < 0.001), symptomatic intracerebral hemorrhage (OR = 3.20, 95% CI = 1.69–6.04, p < 0.001), posterior circulation stroke (OR = 2.85, 95% CI = 1.72–4.71, p < 0.001), and failed recanalization (OR = 2.00, 95% CI = 1.35–3.00, p = 0.001).

Conclusion: PC-AKI is rare after EVT but represents an important risk factor for in-hospital mortality and for mortality within 3 months after hospital discharge. Preventing PC-AKI after EVT may represent an important and potentially lifesaving effort in future daily clinical practice.

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.

Predicting mortality in acute ischaemic stroke treated with mechanical thrombectomy: analysis of a multicentre prospective registry

OBJECTIVES

We aimed to determine predictors of mortality within 90 days and develop a simple score for patients with mechanical thrombectomy (MT).

DESIGN

Analysis of a multicentre prospective registry.

SETTING

In six participating centres, patients who had an acute ischaemic stroke (AIS) treated by MT between March 2017 and May 2018 were documented prospectively.

PARTICIPANTS

224 patients with AIS were treated by MT.

RESULTS

Of 224 patients, 49 (21.9%) patients died, and 87 (38.8%) were independent. Variables associated with 90-day mortality were age, previous stroke, admission National Institutes of Health Stroke Scale (NIHSS), fasting blood glucose and occlusion site. Logistic regression identified four variables independently associated with 90-day mortality: age ≥80 years (OR 3.26, 95% CI 1.45 to 7.33), previous stroke (OR 2.33, 95% CI 1.04 to 5.21), admission NIHSS ≥18 (OR 2.37, 95% CI 1.13 to 4.99) and internal carotid artery or basilar artery occlusion (OR 2.92, 95% CI 1.34 to 6.40). Using these data, we developed predicting 90-day mortality of AIS with MT (PRACTICE) score ranging from 0 to 6 points. The receiver operator curve analysis found that PRACTICE score (area under the curve (AUC)=0.744, 95% CI 0.669 to 0.820) was numerically better than iScore (AUC=0.661, 95% CI 0.577 to 0.745) and Predicting Early Mortality of Ischemic Stroke score (AUC=0.638, 95% CI 0.551 to 0.725) for predicting 90-day mortality.

CONCLUSIONS

We developed a simple score to estimate the 90-day mortality of patients who had an AIS treated with MT. But the score needs to be prospectively validated.

TRIAL REGISTRATION NUMBER

Chinese Clinical Trial Registry (ChiCTR-OOC-17013052).

Characteristics and outcomes of COVID-19 associated stroke: a UK multicentre case-control study

OBJECTIVE

We set out to determine which characteristics and outcomes of stroke are associated with COVID-19.

METHODS

This case-control study included patients admitted with stroke to 13 hospitals in England and Scotland between 9 March and 5 July 2020. We collected data on 86 strokes (81 ischaemic strokes and 5 intracerebral haemorrhages) in patients with evidence of COVID-19 at the time of stroke onset (cases). They were compared with 1384 strokes (1193 ischaemic strokes and 191 intracerebral haemorrhages) in patients admitted during the same time period who never had evidence of COVID-19 (controls). In addition, the whole group of stroke admissions, including another 37 patients who appeared to have developed COVID-19 after their stroke, were included in two logistic regression analyses examining which features were independently associated with COVID-19 status and with inpatient mortality.

RESULTS

Cases with ischaemic stroke were more likely than ischaemic controls to occur in Asians (18.8% vs 6.7%, p<0.0002), were more likely to involve multiple large vessel occlusions (17.9% vs 8.1%, p<0.03), were more severe (median National Institutes of Health Stroke Scale score 8 vs 5, p<0.002), were associated with higher D-dimer levels (p<0.01) and were associated with more severe disability on discharge (median modified Rankin Scale score 4 vs 3, p<0.0001) and inpatient death (19.8% vs 6.9%, p<0.0001). Recurrence of stroke during the patient's admission was rare in cases and controls (2.3% vs 1.0%, NS).

CONCLUSIONS

Our data suggest that COVID-19 may be an important modifier of the onset, characteristics and outcome of acute ischaemic stroke.

Persistent inflammation worsens short-term outcomes in massive stroke patients

Background

Persistent inflammation is an important driver of disease progression and affects prognosis. Some indicators of inflammation predict short-term outcomes. The relationship between prognosis, especially mortality, and persistent inflammation in massive stroke has not been studied, and this has been the subject of our research.

Methods

From April 1, 2017 to February 1, 2020, consecutive patients were prospectively enrolled. Clinical data, laboratory data, imaging data and follow-up infections morbidity were compared between 2 groups according to modified Rankin scale (mRS) scores (mRS < 3 and ≥ 3) at 1 month. The binomial logistic analysis was used to determine independent factors of 1-month prognosis. Short-term functional outcome, mortality and infection rates in massive stroke with and without persistent inflammation were compared.

Results

One hundred thirty-nine patients with massive stroke were included from 800 patients. We found that admission blood glucose levels (p = 0.005), proportions of cerebral hemispheric (p = 0.001), posterior circulatory (p = 0.035), and lacunar (p = 0.022) ischemia were higher in poor outcome patients; neutrophil-to-lymphocyte ratio (odd ratio = 1.87, 95%CI 1.14–3.07, p = 0.013) and blood glucose concentrations (odd ratio = 1.34, 95%CI 1.01–1.79, p = 0.043) can independently predict the short-term prognosis in massive stroke patients. We also found that the incidence of pulmonary infection (p = 0.009), one-month mortality (p = 0.003) and adverse outcomes (p = 0.0005) were higher in patients with persistent inflammation.

Conclusions

This study suggested that persistent inflammation is associated with poor prognosis, 1-month mortality and the occurrence of in-hospital pulmonary infection and that higher baseline inflammation level predicts short-term poor outcomes in massive stroke.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12883-021-02097-9.

Predictive Value of the Alberta Stroke Program Early CT Score (ASPECTS) in the Outcome of the Acute Ischemic Stroke and Its Correlation with Stroke Subtypes, NIHSS, and Cognitive Impairment

OBJECTIVES

This study is aimed at correlating ASPECTS with mortality and morbidity in patients with acute middle cerebral artery territory infarction and at determining the cutoff value of ASPECTS that may predict the outcome.

METHODS

150 patients diagnosed with acute middle cerebral artery territory infarction were involved in this study. Risk factors, initial NIHSS, and GCS were determined. An initial or follow-up noncontrast CT brain was done and assessed by ASPECTS. Outcomes were determined by mRS during the follow-up of cases after 3 months. Correlations of ASPECTS and outcome variables were done by Spearman correlation. Logistic regression analysis and ROC curve were done to detect the cutoff value of ASPECTS that predicts unfavorable outcomes.

RESULTS

The most common subtypes of ischemic strokes were lacunar stroke in 66 patients (44%), cardioembolic stroke in 39 patients (26%), and LAA stroke in 30 cases (20%). The cardioembolic stroke had a statistically significant lower ASPECT score than other types of ischemic strokes (P < 0.05). Spearman correlation showed that lower ASPECTS values (worse outcome) were more in older patients and associated with lower initial GCS. ASPECTS values were inversely correlated with initial NIHSS, inpatient stay, inpatient complications, mortality, and mRS. The ASPECTS cutoff value determined for the prediction of unfavorable outcomes was equal to ≤7. The binary logistic regression analysis detected that patients with ASPECTS ≤ 7 were significantly associated with about fourfold increased risk of poor outcomes (OR 3.95, 95% CI 2.09-11.38, and P < 0.01).

CONCLUSIONS

ASPECTS is a valuable and appropriate technique for the evaluation of the prognosis in acute ischemic stroke. Patients with high ASPECTS values are more likely to attain favorable outcomes, and the cutoff value of ASPECTS is a strong predictor for unfavorable outcomes. This trial is registered with ClinicalTrials.gov NCT04235920.

A retrospective study of Yiqi-Huoxue Decoction on blood pressure in patients with acute ischemic stroke

This retrospective study investigated the effect of Yiqi-Huoxue Decoction (YQHXD) on blood pressure (BP) in patients with acute ischemic stroke (AIS).A total of 72 patients with BP following AIS who received routine treatment were included in this retrospective study. Of those, 36 patients received YQHXD and were assigned to a treatment group. The other 36 patients were allocated to a control group. All patients were treated for a total of 4 months. The outcomes were assessed by systolic blood pressure (SBP), diastolic blood pressure (DBP), National Institutes of Health Stroke Scale (NIHSS) score and Barthel index scale (BIS). All outcomes were measured after 4-month treatment.After treatment, all subjects in the treatment group showed greater improvements in SBP (P < .05), DBP (P < .05), NIHSS (P < .05) score, and BIS (P < .05) than those of patients in the control group. In addition, the safety profile is similar in both groups.The findings of this study demonstrated that YQHXD may benefit on BP in patients with AIS. Future studies should focus on warranting the current results.