Application of AI Technology for the Diagnosis and Treatment of Geriatric Diseases
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 入组人数
- 460
- 试验地点
- 1
- 主要终点
- speech
研究概览
简要总结
- Characteristics of handwriting, gait, speech, eye movements, biological samples (blood, urine, stool, saliva, etc.), images, EEG, and other relevant markers in patients with Alzheimer's disease.
(2) Characteristics of handwriting, gait, language, eye movement, biological samples (blood, urine, stool, saliva, etc.), imaging, EEG, and other relevant markers in patients with Parkinson's disease.
(3) Characteristics of handwriting, gait, language, eye movement, biological samples (blood, urine, stool, saliva, etc.), images, EEG, and other relevant markers in patients with other neurological disorders.
(4) Characteristics of handwriting, gait, language, eye movement, biological samples (blood, urine, stool, saliva, etc.), images, EEG and other relevant markers in elderly patients.
详细描述
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Study variables (factors) and measurements
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All enrolled subjects collected data including general clinical information, PD patients completed motor function assessment and non-motor function assessment, AD patients completed cognitive function assessment and mood-sleep assessment, patients with other neurological disorders perfected disease-related clinical information and scale assessment, and healthy elderly and young controls perfected general clinical information and scale screening.
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All selected subjects complete handwriting recording, gait assessment, language entry and eye movement recording, and collect biological samples (blood (3 ml/case), urine (3 ml/case), stool (2 g/case), saliva (3 ml/case) and other clinical test results), imaging, EEG and other relevant markers for the study of diagnostic and treatment plan and correlation analysis of AI technology.
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Motor symptom assessment: UPDRS score
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Non-motor symptom assessment: Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MOCA), Hamilton Anxiety Scale (HAMD), and Hamilton Anxiety Diagnostic Scale (HAD). Hamilton Anxiety Scale (HAMD), Hamilton Depression Scale (HDMD), SF-36.
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Sample size 100 patients with primary Parkinson's disease were included, 100 patients with Alzheimer's disease were included, 100 patients with other neurological disorders were included, 80 healthy elderly controls, and 80 healthy young controls.
3 Data collection and management Data collection was firstly collected by applying the paper version of the case report form, and then entered into the computer by a specialized person.
研究设计
- 研究类型
- Observational
- 观察模型
- Case Control
- 时间视角
- Retrospective
入排标准
- 年龄范围
- 8 Years 至 100 Years（Child, Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- 未提供
排除标准
- 未提供
结局指标
主要结局
speech
时间窗: 2022-2~2026-6
The speech of the patients were collected and analyzed,the specific indicators used should be adjusted according to the results of artificial intelligence calculation, and the unit should be adjusted according to the indicators used.
biological samples (blood, urine, stool, saliva, etc.)
时间窗: 2022-2~2026-6
3-5ml of biological specimens were retained for testing and data analysis
Handwriting
时间窗: 2022-2~2026-6
The patterns and related auxiliary features of patients' handwritten notes were analyzed,the specific indicators used should be adjusted according to the results of artificial intelligence calculation, and the unit should be adjusted according to the indicators used.
eye movements
时间窗: 2022-2~2026-6
The eye movement data of the patients were collected and analyzed,the specific indicators used should be adjusted according to the results of artificial intelligence calculation, and the unit should be adjusted according to the indicators used.
images
时间窗: 2022-2~2026-6
MRI、MRA、SWI、DTI and other imaging data were analyzed,the specific indicators used should be adjusted according to the results of artificial intelligence calculation, and the unit should be adjusted according to the indicators used.
other relevant markers
时间窗: 2022-2~2026-6
Some other markers are waiting to be studied and discovered,the specific indicators used should be adjusted according to the results of artificial intelligence calculation, and the unit should be adjusted according to the indicators used.
gait
时间窗: 2022-2~2026-6
The patients' stride length and gait frequency were analyzed，the specific indicators used should be adjusted according to the results of artificial intelligence calculation, and the unit should be adjusted according to the indicators used.
EEG
时间窗: 2022-2~2026-6
Mean frequency, relative power, absolute power, electrode correlation, coherence, time-frequency analysis，etc
次要结局
未报告次要终点