Clinical Differences Between Stroke and Stroke Mimics in Code Stroke Patients

Early identification and characterisation of stroke to support prehospital decision-making using artificial intelligence: a scoping review protocol

INTRODUCTION

Stroke is a time-critical condition and one of the leading causes of mortality and disability worldwide. To decrease mortality and improve patient outcome by improving access to optimal treatment, there is an emerging need to improve the accuracy of the methods used to identify and characterise stroke in prehospital settings and emergency departments (EDs). This might be accomplished by developing computerised decision support systems (CDSSs) that are based on artificial intelligence (AI) and potential new data sources such as vital signs, biomarkers and image and video analysis. This scoping review aims to summarise literature on existing methods for early characterisation of stroke by using AI.

METHODS AND ANALYSIS

The review will be performed with respect to the Arksey and O'Malley's model. Peer-reviewed articles about AI-based CDSSs for the characterisation of stroke or new potential data sources for stroke CDSSs, published between January 1995 and April 2023 and written in English, will be included. Studies reporting methods that depend on mobile CT scanning or with no focus on prehospital or ED care will be excluded. Screening will be done in two steps: title and abstract screening followed by full-text screening. Two reviewers will perform the screening process independently, and a third reviewer will be involved in case of disagreement. Final decision will be made based on majority vote. Results will be reported using a descriptive summary and thematic analysis.

ETHICS AND DISSEMINATION

The methodology used in the protocol is based on information publicly available and does not need ethical approval. The results from the review will be submitted for publication in a peer-reviewed journal. The findings will be shared at relevant national and international conferences and meetings in the field of digital health and neurology.

Visual symptoms in acute stroke - A systematic review of observational studies

OBJECTIVE

Atypical symptoms of stroke, such as non-specific visual symptoms, are a challenging aspect of acute stroke diagnostics. Among patients evaluated for stroke in the Emergency Department, 2-28% present with stroke chameleons, and 30-43% with stroke mimics. We aimed to identify the type of visual symptoms present in typical strokes, stroke mimics, and stroke chameleons.

PATIENTS AND METHODS

By use of Preferred Reporting Items for Systematic Reviews and Meta-Analysis we searched PubMed and Embase for studies with reports of acute visual symptoms in typical strokes vs mimics or chameleons (PROSPERO protocol, ID CRD42022364749). Risk of bias was assessed by The Critical Appraisal Skills Program.

RESULTS

Thirteen papers were included, comprising data from 9248 patients evaluated for stroke. Compared to mimics, visual symptoms in stroke presented more frequently as hemianopia (28.2% vs 4.8%, 7,4% vs 2.3%, 22% vs 0%), visual loss (11.6% vs 1.8%), visual field defect (11.6% vs 4%, 24% vs 2%, 19% vs 1.7%), eye movement disorder (19.4% vs 6.4%), eye deviation (9.6% vs 0.9%), gaze palsy (32.1% vs 8.6%), oculomotor disturbance (37% vs 0%), and visual inattention (17.5% vs 4%). Compared to strokes, mimics more often presented "non-systematized visual trouble" (10% vs 3%) and blurred vision (22% vs 5%), whereas "visual disturbance" was reported more often in stroke chameleons than in typical strokes (10% vs 3%).

CONCLUSION

Detailed reports of visual symptoms were lacking in most studies, however blurred vision and "non-systematized visual trouble" were more frequent in mimics, "visual disturbance" in stroke chameleons, and negative visual symptoms such as visual field defects in typical strokes. A more systematic and detailed approach to visual symptoms may facilitate acute stroke recognition in patients with visual symptoms.

Risk Factors of Recurrent Stroke in Young and Middle-Aged Stroke Patients after Interventional Therapy

Objective

To explore the risk factors of recurrent stroke in young and middle-aged stroke patients after interventional therapy.

Methods

Retrospective analysis was conducted on the data of 300 young and middle-aged stroke patients treated in our hospital (February 2015–February 2017). All patients received interventional therapy. They were followed up continuously after the interventional therapy, with recurrent stroke as the only endpoint event, and those who did not have the endpoint events were followed up for 5 years. Then, the patients were divided into the occurrence group and the nonoccurrence group according to whether there was a stroke. The social demographic data and clinical examination data of all patients were collected to analyze the differences between the groups. Logistic regression analysis was performed on the factors with statistically significant differences to verify the factors affecting recurrent stroke in young and middle-aged stroke patients after interventional therapy.

Results

Among the 300 patients, 69 (23.0%) had recurrent stroke and 231 (77.0%) had no recurrent stroke. The occurrence group (n = 69) had 12 cases (17.4%) of massive cerebral infarction, 18 cases (26.1%) of cerebral watershed infarction, 5 cases (7.2%) of multiple cerebral infarction, 25 cases (36.2%) of lacunar infarction, and 9 cases (13.0%) of TIA. Notable differences were observed in age, drinking history, marital status, body weight, diastolic pressure, systolic pressure, fasting blood glucose, glycosylated hemoglobin, cholesterol, and fibrinogen between the occurrence group and the nonoccurrence group (P < 0.05). The binary logistic regression analysis showed that age, drinking history, diastolic pressure, fasting blood glucose, glycosylated hemoglobin, cholesterol, and fibrinogen were the influencing factors of recurrent stroke in young and middle-aged stroke patients after interventional therapy.

Conclusion

Blood glucose, blood lipid, blood pressure, age, and living habits have an impact on recurrent stroke in young and middle-aged patients after interventional therapy. Therefore, while strictly controlling blood glucose, blood lipid, and blood pressure, patients should improve their living habits and enhance the awareness of prevention after interventional therapy.