Initial blood pressure is associated with stroke severity and is predictive of admission cost and one-year outcome in different stroke subtypes: a SRICHS registry study

Communicating Arteries and Leptomeningeal Collaterals: A Synergistic but Independent Effect on Patient Outcomes after Stroke

The collateral system is a compensatory mechanism activated in the acute phase of an ischemic stroke. It increases brain perfusion to the hypoperfused area. Arteries of the Willis' circle supply antegrade blood flow, while pial (leptomeningeal) arteries direct blood via retrograde flow. The aim of our retrospective study was to investigate the relationship between both collateral systems, computed tomography perfusion (CTP) values, and functional outcomes in acute stroke patients. Overall, 158 patients with anterior circulation stroke who underwent mechanical thrombectomy were included in the study. We analyzed the presence of communicating arteries and leptomeningeal arteries on computed tomography angiography. Patients were divided into three groups according to their collateral status. The main outcomes were the rate of functional independence 3 months after stroke (modified Rankin scale score, mRS) and mortality rate. Our study suggests that the collateral status, as indicated by the three groups (unfavorable, intermediate, and favorable), is linked to CT perfusion parameters, potential recuperation ratio, and stroke outcomes. Patients with favorable collateral status exhibited smaller core infarct and penumbra volumes, higher mismatch ratios, better potential for recuperation, and improved functional outcomes compared to patients with unfavorable or intermediate collateral status.

From Admission to Discharge: Predicting National Institutes of Health Stroke Scale Progression in Stroke Patients Using Biomarkers and Explainable Machine Learning

As a result of social progress and improved living conditions, which have contributed to a prolonged life expectancy, the prevalence of strokes has increased and has become a significant phenomenon. Despite the available stroke treatment options, patients frequently suffer from significant disability after a stroke. Initial stroke severity is a significant predictor of functional dependence and mortality following an acute stroke. The current study aims to collect and analyze data from the hyperacute and acute phases of stroke, as well as from the medical history of the patients, in order to develop an explainable machine learning model for predicting stroke-related neurological deficits at discharge, as measured by the National Institutes of Health Stroke Scale (NIHSS). More specifically, we approached the data as a binary task problem: improvement of NIHSS progression vs. worsening of NIHSS progression at discharge, using baseline data within the first 72 h. For feature selection, a genetic algorithm was applied. Using various classifiers, we found that the best scores were achieved from the Random Forest (RF) classifier at the 15 most informative biomarkers and parameters for the binary task of the prediction of NIHSS score progression. RF achieved 91.13% accuracy, 91.13% recall, 90.89% precision, 91.00% f1-score, 8.87% FNrate and 4.59% FPrate. Those biomarkers are: age, gender, NIHSS upon admission, intubation, history of hypertension and smoking, the initial diagnosis of hypertension, diabetes, dyslipidemia and atrial fibrillation, high-density lipoprotein (HDL) levels, stroke localization, systolic blood pressure levels, as well as erythrocyte sedimentation rate (ESR) levels upon admission and the onset of respiratory infection. The SHapley Additive exPlanations (SHAP) model interpreted the impact of the selected features on the model output. Our findings suggest that the aforementioned variables may play a significant role in determining stroke patients' NIHSS progression from the time of admission until their discharge.

Recovery of walking ability in stroke patients through postacute care rehabilitation

BACKGROUND

Walking entails orchestration of the sensory, motor, balance, and coordination systems, and walking disability is a critical concern after stroke. How and to what extent these systems influence walking disability after stroke and recovery have not been comprehensively studied.

METHODS

We retrospectively analyzed patients with stroke in the Post-acute care-Cerebrovascular Diseases (PAC-CVD) program. We compared the characteristics of patient groups stratified by their ability to complete the 5-m walk test across various time points of rehabilitation. We then used stepwise linear regression to examine the degree to which each stroke characteristic and functional ability could predict patient gait performance.

RESULTS

Five hundred seventy-three patients were recruited, and their recovery of walking ability was defined by the timing of recovery in a 5-m walk test. The proportion of patients who could complete the 5-m walk test at admission, at 3 weeks of rehabilitation, at 6 weeks of rehabilitation, between 7 and 12 weeks of rehabilitation, and who could not complete the 5-m walk test after rehabilitation was 52.2%, 21.8%, 8.7%, 8.7%, and 8.6%, respectively. At postacute care discharge, patients who regained walking ability earlier had a higher chance of achieving higher levels of walking activity. Stepwise linear regression showed that Berg Balance Scale (BBS) (β: 0.011, p < .001), age (β: -0.005, p = .001), National Institutes of Health Stroke Scale (NIHSS) (6a + 6b; β: -0.042, p = .018), Mini-Nutritional assessment (MNA) (β: -0.007, p < .027), and Fugl-Meyer upper extremity assessment (FuglUE) (β: 0.002, p = .047) scores predicted patient's gait speed at discharge.

CONCLUSION

Balance, age, leg strength, nutritional status, and upper limb function before postacute care rehabilitation are predictors of walking performance after stroke.

Machine learning predictive model for aspiration screening in hospitalized patients with acute stroke

Dysphagia is a fatal condition after acute stroke. We established machine learning (ML) models for screening aspiration in patients with acute stroke. This retrospective study enrolled patients with acute stroke admitted to a cerebrovascular specialty hospital between January 2016 and June 2022. A videofluoroscopic swallowing study (VFSS) confirmed aspiration. We evaluated the Gugging Swallowing Screen (GUSS), an early assessment tool for dysphagia, in all patients and compared its predictive value with ML models. Following ML algorithms were applied: regularized logistic regressions (ridge, lasso, and elastic net), random forest, extreme gradient boosting, support vector machines, k-nearest neighbors, and naïve Bayes. We finally analyzed data from 3408 patients, and 448 of them had aspiration on VFSS. The GUSS showed an area under the receiver operating characteristics curve (AUROC) of 0.79 (0.77-0.81). The ridge regression model was the best model among all ML models, with an AUROC of 0.81 (0.76-0.86), an F1 measure of 0.45. Regularized logistic regression models exhibited higher sensitivity (0.66-0.72) than the GUSS (0.64). Feature importance analyses revealed that the modified Rankin scale was the most important feature of ML performance. The proposed ML prediction models are valid and practical for screening aspiration in patients with acute stroke.

[Prognostic factors for mortality due to acute arterial stroke in a North African population]

Introduction

cerebrovascular accident (stroke) constitutes a major public health problem due to the number of people affected and to its medical social and economic consequences. This study aims to identify poor vital prognostic factors for survival in patients with acute arterial stroke.

Methods

we conducted a prospective study of patients with symptoms suggestive of stroke at the two University Hospitals of Sfax, Tunisia over a period of 4 months. Patients were followed-up for a period of 1 month.

Results

we collected data from 200 patients. After one month of follow-up, mortality was 19.9%. Poor prognostic factors were: male sex, consumption of tobacco, a history of stroke, low Glasgow score, high NIHSS, headaches, acute symptomatic epileptic seizures, Babinski's sign, mydriasis, aphasia, combined deviation of the head and the eyes, high PAS, PAD and PAM, hyperthermia, hyperglycaemia, leukocytosis, high concentration of CRP, creatinine, urea and troponin T, haemorrhagic stroke, perilesional oedema, a mass effect, commitment, total middle cerebral artery topography of ischemia, early signs of ischemia, meningeal hemorrhage, ventricular flood, hydrocephalus, the recourse to respiratory support, to anti-edematous treatment and to antihypertensive therapy, hemorrhagic transformation, vascular epilepsy, infectious, metabolic complications, complications of bed sores.

Conclusion

the identification of the predictive factors for survival allows for optimisation of therapeutic procedures and better implementation of patient' management. A comparative study will be considered to measure the impact of the corrective measures.

Correlation between pre-admission blood pressure and outcome in a large telestroke cohort

BACKGROUND

Telemedicine rapidly connects patients, with acute ischemic stroke symptoms, with neurovascular specialists for assessment to reduce chemical thrombolysis delivery times. Management of AIS includes maintaining target systolic blood pressures (SBP). In this retrospective study, we assess the efficacy of the telestroke (TS) system at a primary stroke center and the prognostic value of SBP throughout the transportation process.

METHODS

Patients presenting with acute-onset neurological symptoms to the TS hospitals network, over a 5-year period, were assessed. Those with a confirmed diagnosis of AIS were included. We examined demographics, presenting-NIHSS, last SBP before transfer from the network hospital and continuous BP during transport, stroke risk factors, hospital-course, door-to-needle (DTN) time, treatments, and modified Rankin Scale(mRS). Multivariate analysis was conducted to evaluate the prognostic value of SBP on stroke outcome.

RESULTS

Of 2,928 patients identified, 1,353 were diagnosed with AIS. Mean age was 66.6 years (SD = 15.4), 47.6% female. Most cases affected the MCA(44.5%). Mean presenting-NIHSS was 8.67(SD = 8.38) and mean SBP was 148 mmHg(SD = 25.39). 73.2% treated using a standard protocol, 23.7% given IVrt-PA, and 6.8% received mechanical thrombectomy(MT). Mean DTN was 96 min(SD = 46; 27.3% <60 min). Age, presenting-NIHSS and pre-existing hypertension were associated with higher mortality and/or higher mRS. SBP was not associated with higher mortality and morbidity.

CONCLUSIONS

This study displays better clinical outcomes at latest follow-up when compared to current international TS studies. SBP during transportation to the hub hospital did not prove to be a useful prognostic metric. However, future studies should address the limitations of this study to confirm these findings.

Association of High Blood Homocysteine and Risk of Increased Severity of Ischemic Stroke Events

Stroke is the leading cause of death and disability in the world as well as in Indonesia. Initial stroke severity is an important factor that affects short- and long-term stroke outcomes. This cross-sectional study was conducted in Cipto Mangunkusumo Hospital from July 2017 to January 2018 to investigate the factors that affect stroke severity. A total of 77 acute ischemic stroke patients were divided into three groups, which include low blood homocysteine levels (< 9 μmol/L), moderate blood homocysteine levels (9-15 μmol/L), and high blood homocysteine levels (> 15 μmol/L). The acquired data were analyzed using Kruskal-Wallis test and a significant difference of initial National Institute of Health Stroke Scale (NIHSS) and blood homocysteine levels ( H  = 13.328, p  = 0.001) were seen, with a mean rank of 25.86 for low blood homocysteine levels, 33.69 for moderate blood homocysteine levels, and 48.94 for high blood homocysteine levels. The patients were then divided into two groups based on the NIHSS (≤5 and > 5) to calculate the risk correlation of blood homocysteine levels and NIHSS by using regression. We found that patients with high blood homocysteine levels had 14.4 times higher risk of having NIHSS > 5 compared with those with low blood homocysteine levels ( p  = 0.002, 95% confidence interval [CI] [2.714-76.407]), and 3.9 times higher risk compared with those with moderate blood homocysteine levels ( p  = 0.011, 95% CI [1.371-11.246]). We concluded that homocysteine is a risk factor for a higher stroke severity. Future studies to evaluate the usefulness of homocysteine-lowering therapy in stroke patients are recommended.

Registry-based stroke research in Taiwan: past and future

Stroke registries are observational databases focusing on the clinical information and outcomes of stroke patients. They play an important role in the cycle of quality improvement. Registry data are collected from real-world experiences of stroke care and are suitable for measuring quality of care. By exposing inadequacies in performance measures of stroke care, research from stroke registries has changed how we manage stroke patients in Taiwan. With the success of various quality improvement campaigns, mortality from stroke and recurrence of stroke have decreased in the past decade. After the implementation of a nationwide stroke registry, researchers have been creatively expanding how they use and collect registry data for research. Through the use of the nationwide stroke registry as a common data model, researchers from many hospitals have built their own stroke registries with extended data elements to meet the needs of research. In collaboration with information technology professionals, stroke registry systems have changed from web-based, manual submission systems to automated fill-in systems in some hospitals. Furthermore, record linkage between stroke registries and administrative claims databases or other existing databases has widened the utility of registry data in research. Using stroke registry data as the reference standard, researchers have validated several algorithms for ascertaining the diagnosis of stroke and its risk factors from claims data, and have also developed a claims-based index to estimate stroke severity. By making better use of registry data, we believe that we will provide better care to patients with stroke.

Causes of Death in Different Subtypes of Ischemic and Hemorrhagic Stroke

Causes of death in both ischemic stroke (IS) and hemorrhagic stroke (HS) subtypes are not comprehensively studied. Between 2008 and 2011, we enrolled 11 215 first-ever stroke patients from the Stroke Registry of Chang-Gung Healthcare System and linked these data to the national death registry. The main causes of death in each stroke subtype were assessed. Patients with HS had higher overall mortality than IS (32.0% vs 18.1%, P < .001). In IS subtypes, large-artery atherosclerosis plus cardioembolism had the worst mortality (40.7%, P < .001). Stroke was the leading cause of death in both IS and HS within the first year. Stroke remained the major cause of death in HS, but cancer was the leading cause of death in IS after the first year. After excluding the patients with previous cancer history, cancer was still an important cause of death in IS and HS, particularly in the IS subtypes of small vessel occlusion, stroke of undetermined etiology, and transient ischemic attack.