4 research outputs found
MAMAF-Net: Motion-Aware and Multi-Attention Fusion Network for Stroke Diagnosis
Stroke is a major cause of mortality and disability worldwide from which one
in four people are in danger of incurring in their lifetime. The pre-hospital
stroke assessment plays a vital role in identifying stroke patients accurately
to accelerate further examination and treatment in hospitals. Accordingly, the
National Institutes of Health Stroke Scale (NIHSS), Cincinnati Pre-hospital
Stroke Scale (CPSS) and Face Arm Speed Time (F.A.S.T.) are globally known tests
for stroke assessment. However, the validity of these tests is skeptical in the
absence of neurologists. Therefore, in this study, we propose a motion-aware
and multi-attention fusion network (MAMAF-Net) that can detect stroke from
multimodal examination videos. Contrary to other studies on stroke detection
from video analysis, our study for the first time proposes an end-to-end
solution from multiple video recordings of each subject with a dataset
encapsulating stroke, transient ischemic attack (TIA), and healthy controls.
The proposed MAMAF-Net consists of motion-aware modules to sense the mobility
of patients, attention modules to fuse the multi-input video data, and 3D
convolutional layers to perform diagnosis from the attention-based extracted
features. Experimental results over the collected StrokeDATA dataset show that
the proposed MAMAF-Net achieves a successful detection of stroke with 93.62%
sensitivity and 95.33% AUC score
Obesity and the Risk of Cryptogenic Ischemic Stroke in Young Adults
Objectives: We examined the association between obesity and early-onset cryptogenic ischemic stroke (CIS) and whether fat distribution or sex altered this association. Materials and Methods: This prospective, multi-center, case-control study included 345 patients, aged 18-49 years, with first-ever, acute CIS. The control group included 345 age-and sex-matched stroke-free individuals. We measured height, weight, waist circumference, and hip circumference. Obesity metrics analyzed included body mass index (BMI), waist-to-hip ratio (WHR), waist-to-stature ratio (WSR), and a body shape index (ABSI). Models were adjusted for age, level of education, vascular risk factors, and migraine with aura. Results: After adjusting for demographics, vascular risk factors, and migraine with aura, the highest tertile of WHR was associated with CIS (OR for highest versus lowest WHR tertile 2.81, 95%CI 1.43-5.51; P=0.003). In sex-specific analyses, WHR tertiles were not associated with CIS. However, using WHO WHR cutoff values (>0.85 for women, >0.90 for men), abdominally obese women were at increased risk of CIS (OR 2.09, 95%CI 1.02-4.27; P=0.045). After adjusting for confounders, WC, BMI, WSR, or ABSI were not associated with CIS. Conclusions: Abdominal obesity measured with WHR was an independent risk factor for CIS in young adults after rigorous adjustment for concomitant risk factors.Peer reviewe
Association between Migraine and Cryptogenic Ischemic Stroke in Young Adults
Objective To assess the association between migraine and cryptogenic ischemic stroke (CIS) in young adults, with subgroup analyses stratified by sex and presence of patent foramen ovale (PFO)
Searching for Explanations for Cryptogenic Stroke in the Young: Revealing the Triggers, Causes, and Outcome (SECRETO): Rationale and design
Background: Worldwide, about 1.3 million annual ischaemic strokes (IS) occur in adults aged <50 years. Of these early-onset strokes, up to 50% can be regarded as cryptogenic or associated with conditions with poorly documented causality like patent foramen ovale and coagulopathies