Evaluation of Neurosteer System (Quantitative EEG Features) in Stroke Patients Suffering From Disorders of Consciousness
试验速览
- 阶段
- 不适用
- 状态
- 撤回
- 试验地点
- 1
- 主要终点
- Correlation between consciousness level changes as evaluated by current clinical tools (i.e. GCS) and Brain Activity Features extracted using the Neurosteer technology.
研究概览
简要总结
This is an observational study. Patients who fulfill all inclusion criteria and none of the exclusion criteria will be enrolled in the study, be neurologically evaluated and will go through a series of EEG recordings during their hospitalization. EEG recordings will be analyzed using proprietary computational analyses.
详细描述
The abnormal state of consciousness is difficult to define, measure and characterize. Many of the terms mean different things to different people, and may prove inaccurate when transmitting and recording information regarding the state of consciousness of a patient. Modern clinical assessments of level of consciousness such as the Glasgow Coma Scale (GCS) or the Grady Coma Scale, in addition to being subjective assessments, are incomplete and insufficient as they are based on assessment of responsiveness only.
An objective tool to asses a level of consciousness is therefore needed. Such a tool may be used to determine the level of consciousness independent of personal interpretation and/or variance between clinicians and provide consistency in assessment across patients and between medical facilities.
The Neurosteer system provides objective neurological biomarkers using a wearable easy-to-use affordable system. The system facilitate the capture and interpretation of EEG data with only a single patch of electrodes, attached on the subject's forehead. Neurosteer examination includes completing auditory tasks while measuring brain activity with the device. The data is analyzed using machine learning methods to produce biomarkers, enabling a report of the patient's activity in real time and offline. The examination is easy to preform and can be conducted in every clinic or in patients' homes.
In this study, research clinical staff (RCS) will identify potential subjects after being hospitalized in the department and will examine the eligibility of subject according to inclusion and exclusion criteria.
When a legal guardian is assigned, guardian will sign the Informed Consent Form (ICF). Otherwise, RCS will approach an independent physician who will be informed about the study and its goals. Independent physician will evaluate patient's eligibility for study. RCS will also inform patient's family/accompanying individuals on study's objective and design.
研究设计
- 研究类型
- Observational
- 观察模型
- Case Only
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Men and women over the age of
- •Hospitalized in Soroka University Medical Center (SUMC) Neurology department with a diagnosis of Stroke.
- •NIHSS score ≥6.
排除标准
- •Damage to integrity of scalp and/or skull.
- •Any verbal or non-verbal form of objection from patient.
- •Any verbal or non-verbal form of objection from patient's family member or significant other.
结局指标
主要结局
Correlation between consciousness level changes as evaluated by current clinical tools (i.e. GCS) and Brain Activity Features extracted using the Neurosteer technology.
时间窗: Level of consciousness will be assessed every 4 hours, up to 3 days (72 hours) after joining the study.
Consciousness level changes will be evaluated by: 1. Glasgow Coma Scale (GCS). A commonly used assessment tool that evaluates level of consciousness following a traumatic brain injury. The GCS score can range from 3 (completely unresponsive) to 15 (responsive). Generally, the brain injury is classified as: Severe, \< 8-9, Moderate, 9-12 and Mild, ≥ 13. 2. Neurosteer system (single channel EEG recording during cognitive auditory tasks). Using data analysis (a variant of the wavelet packet analysis and the best basis algorithm), the EEG signal is transformed into brain activity features (e.g. ST4, A0). Pearson correlation will be calculated between the mean activity of the EEG features and individual's GCS scores.
次要结局
未报告次要终点