Percutaneous left atrial appendage closure for cerebrovascular accident prevention: rationale, indications, technical aspects, clinical results and future perspective

Intervention Effect of Rehabilitation Robotic Bed Under Machine Learning Combined With Intensive Motor Training on Stroke Patients With Hemiplegia

It was aimed to discuss the effect of bed-type rehabilitation robots under machine learning combined with intensive motor training on the motor function of lower limbs of stroke patients with hemiplegia. A total of 80 patients with stroke hemiplegia were taken as the subjects, who all had a course of treatment for less than 6 months in the Rehabilitation Medicine Department of Ganzhou Hospital. These patients were divided into the experimental group (40 cases) and the control group (40 cases) by random number method. For patients in the control group, conventional intensive motor training was adopted, whereas the conventional intensive motor training combined with the bed-type rehabilitation robot under machine learning was applied for patients in the experimental group. Fugl-Meyer Assessment of Lower Extremity (FMA-LE), Rivermead Mobility Index (RMI), and Modified Barthel Index (MBI) were used to evaluate the motor function and mobility of patients. The human–machine collaboration experiment system was constructed, and the software and hardware of the control system were designed. Then, the experimental platform for lower limb rehabilitation training robots was built, and the rehabilitation training methods for stroke patients with hemiplegia were determined by completing the contact force experiment. The results showed that the prediction effect of back-propagation neural network (BPNN) was better than that of the radial basis neural network (RBNN). The bed-type rehabilitation robot under machine learning combined with intensive motor training could significantly improve the motor function and mobility of the lower limbs of stroke patients with hemiplegia.

Current Guidelines on Management of Amaurosis Fugax and Transient Ischemic Attacks

ABSTRACT

Transient ischemic attack (TIA) is defined as a transient episode of neurological dysfunction resulting from focal brain, spinal cord, or retinal ischemia, without associated infarction. Consequently, a TIA encompasses amaurosis fugax (AF) that is a term used to denote momentary visual loss from transient retinal ischemia. In this review, we use the word TIA to refer to both cerebral TIAs (occurring in the brain) and AF (occurring in the retina). We summarize the key components of a comprehensive evaluation and management of patients presenting with cerebral and retinal TIA.All TIAs should be treated as medical emergencies, as they may herald permanent disabling visual loss and devastating hemispheric or vertebrobasilar ischemic stroke. Patients with suspected TIA should be expeditiously evaluated in the same manner as those with an acute stroke. This should include a detailed history and examination followed by specific diagnostic studies. Imaging of the brain and extracranial and intracranial blood vessels forms the cornerstone of diagnostic workup of TIA. Cardiac investigations and serum studies to evaluate for etiological risk factors are also recommended.The management of all TIAs, whether cerebral or retinal, is similar and should focus on stroke prevention strategies, which we have categorized into general and specific measures. General measures include the initiation of appropriate antiplatelet therapy, encouraging a healthy lifestyle, and managing traditional risk factors, such as hypertension, dyslipidemia, and diabetes. Specific management measures require the identification of a specific TIA etiology, such as moderate-severe (greater than 50% of stenosis) symptomatic extracranial large vessel or intracranial steno-occlusive atherosclerotic disease, aortic arch atherosclerosis, and atrial fibrillation.