NCT04928690Unknown不适用
Prediction of Amyloid and Mild Cognitive Impairment in Early Stage Alzheimer's Disease From Remote Speech Phenotyping (EARS)
Novoic Limited0 个研究点目标入组 140 人开始时间: 2021年6月20日最近更新:
适应症
试验速览
- 阶段
- 不适用
- 发起方
- 入组人数
- 140
- 主要终点
- Area under the curve (AUC) of the receiver operating characteristic (ROC) curve of the binary classifier distinguishing between amyloid positive (Arms 1 and 3) and amyloid negative (Arms 2 and 4) Arms using speech recordings as input.
研究概览
简要总结
The S22 study investigates, in a cross-sectional study, the ability of algorithms that analyse acoustic and linguistic patterns of spoken language to predict the presence of amyloid positivity in early stage Alzheimer's disease, specifically in Mild Cognitive Impairment (MCI) and cognitively normal (CN) cohorts; and whether similar algorithms can predict cognitive functioning, in classifying MCI vs CN.
研究设计
- 研究类型
- Observational
- 观察模型
- Case Control
- 时间视角
- Cross Sectional
入排标准
- 年龄范围
- 50 Years 至 85 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Amyloid status must be known, based on an amyloid PET scan or CSF amyloid test, no older than 30 months at the time of consent for Arm 2 and Arm 4 participants (amyloid negative Arms).
- •Amyloid status must be known, based on an amyloid PET scan or CSF amyloid test, no older than 60 months at the time of consent for Arm 1 and Arm 3 (amyloid positive Arms).
- •Subjects must be aged 50-85 (inclusive).
- •Subjects must have MMSE scores of 23-30 (inclusive) based on a test not older than 1 month at the time of the visit.
- •Date of diagnosis (if applicable) maximum of five years prior to consent.
- •Subjects' first language must be English.
- •Willing to participate in a study investigating speech and cognitive impairment.
- •Able to provide valid informed consent.
- •Able to use, or has a caregiver who is able to use a smartphone device.
- •Has access to a smartphone device running an operation system of Android 6 or above; or iOS 10 or above.
- •If taking part in the study through virtual visits, the following inclusion criteria also applies:
- •Able to use, or has a caregiver who is able to use a personal computer, notebook or tablet.
- •Has access to a personal computing device of that is running an operating system of macOS X with macOS 10.9 or later, or Windows 7 or above, or Ubuntu 12.04 or higher; OR has access internet browser software Internet Explorer version 11 or above; or Microsoft Edge version 12 or above, or Firefox version 27 or above, or Google Chrome version 30 or above, or Safari version 7 or above; AND capable of audio and video recording; AND able to connect to the internet.
排除标准
- •Clinically significant unstable psychiatric illness in 6 months.
- •Diagnosis of General Anxiety Disorder.
- •Current, or history within the past 2 years of major depressive disorder diagnosis (according to DSM-5 criteria83); or psychiatric symptoms that, in the opinion of the investigator, could interfere with study procedures.
- •History or presence of stroke within the past 2 years.
- •Documented history of transient ischemic attack or unexplained loss of consciousness within the last 12 months.
- •The participant is using drugs to treat symptoms related to AD, and the doses of these drugs were not stable for at least 8 weeks prior to consent.
- •Participant is, or previously has been enrolled in the Sponsor's NOV-0100 or NOV-0110 studies.
结局指标
主要结局
Area under the curve (AUC) of the receiver operating characteristic (ROC) curve of the binary classifier distinguishing between amyloid positive (Arms 1 and 3) and amyloid negative (Arms 2 and 4) Arms using speech recordings as input.
时间窗: baseline
次要结局
- The Cohen's kappa of the binary classifier distinguishing between amyloid positive (Arms 1 and 3) and amyloid negative (Arms 2 and 4) Arms.(baseline)
- The specificity of the binary classifier distinguishing between the MCI (Arms 1 and 2) and the CN (Arms 3 and 4) Arms.(baseline)
- For each classifier/regressor in outcome 1-16, the correlation between the AUC/CIA and each age group, gender and speech-to-reverberation modulation energy ratio group, as measured by the Kendall rank correlation coefficient.(baseline)
- The sensitivity of the binary classifier distinguishing between amyloid positive (Arms 1 and 3) and amyloid negative (Arms 2 and 4) Arms.(baseline)
- The specificity of the binary classifier distinguishing between amyloid positive (Arms 1 and 3) and amyloid negative (Arms 2 and 4) Arms.(baseline)
- The sensitivity of the binary classifier distinguishing between amyloid positive cognitively normal (CN) (Arm 3) and amyloid negative cognitively normal (CN) (Arm 4) Arms.(baseline)
- The specificity of the binary classifier distinguishing between amyloid positive MCI (Arm 1) and amyloid negative MCI (Arm 2) Arms.(baseline)
- The AUC of the binary classifier distinguishing between amyloid positive MCI (Arm 1) and amyloid negative MCI (Arm 2) Arms.(baseline)
- The Cohen's kappa of the binary classifier distinguishing between the MCI (Arms 1 and 2) and the CN (Arms 3 and 4) Arms.(baseline)
- The specificity of the binary classifier distinguishing between amyloid positive cognitively normal (CN) (Arm 3) and amyloid negative cognitively normal (CN) (Arm 4) Arms.(baseline)
- The Cohen's kappa of the binary classifier distinguishing between amyloid positive cognitively normal (CN) (Arm 3) and amyloid negative cognitively normal (CN) (Arm 4) Arms.(baseline)
- The sensitivity of the binary classifier distinguishing between amyloid positive MCI (Arm 1) and amyloid negative MCI (Arm 2) Arms.(baseline)
- The AUC of the binary classifier distinguishing between the MCI (Arms 1 and 2) and the CN (Arms 3 and 4) Arms.(baseline)
- The AUC of the binary classifier distinguishing between amyloid positive cognitively normal (CN) (Arm 3) and amyloid negative cognitively normal (CN) (Arm 4) Arms.(baseline)
- The Cohen's kappa of the binary classifier distinguishing between amyloid positive MCI (Arm 1) and amyloid negative MCI (Arm 2) Arms.(baseline)
- The sensitivity of the binary classifier distinguishing between the MCI (Arms 1 and 2) and the CN (Arms 3 and 4) Arms.(baseline)
研究者
相似试验
已完成
不适用
Longitudinal Evaluation of Amyloid Risk and Neurodegeneration - the LEARN StudyCognition DisordersNCT02488720University of Southern California538
已完成
不适用
Prediction of MMSE Scores for Cognitive ImpairmentCognitive ImpairmentHealthy ControlNCT06611475Blekinge Institute of Technology693
撤回
不适用
Efficacy of Pulsatile IV Insulin on Cognition and Amyloid Burden in Patients With Alzheimer's DiseaseMild Cognitive ImpairmentAlzheimer's DiseaseNCT01636596Louisiana State University Health Sciences Center Shreveport
已完成
不适用
Cognitive Function and Prevalence of Amyloid Marker in Frail Older AdultsFrail ElderlyNCT03129269University Hospital, Toulouse344
已完成
不适用
The Cohort Study of Cognitive Impairment in Chinese Hemodialysis PatientsCognitive ImpairmentHemodialysis ComplicationOutcomeNeuropsychological TestsNCT03251573Beijing Shijitan Hospital, Capital Medical University613