AI-Enhanced Optimization of Acute Levodopa Challenge Test

Beijing Tiantan Hospital2,000 enrolled

Overview

A quantitative evaluation method was developed for Parkinson's disease and other atypical parkinonism by integrating an innovative motor paradigm with perception technologies and artificial intelligence. Combined with traditional motor paradigms and the acute levodopa challenge test, this study aims to identify diagnostic cut-off values for PD and other atypical parkinonism, explore digital biomarkers for early and differential diagnosis, and establish a corresponding diagnostic model.

Study Type

OBSERVATIONAL

Enrollment

2,000

Conditions

Vascular Parkinsonism Drug-induced Parkinsonism Corticobasal Degeneration (CBD)Parkinson Disease (PD)Dementia With Lewy Body Disease Progressive Supranuclear Palsy(PSP)Multiple System Atrophy (MSA)

Eligibility

Sex: ALLMin age: 50 YearsMax age: 75 Years

Medical Language ↔ Plain English

Inclusion Criteria: 1. Parkinson's disease (PD) group: 1. Patients with confirmed Parkinson's disease diagnosed based on the 2015 International Movement Disorder Society (MDS) Parkinson's Disease Diagnostic Criteria; 2. Patients with early-stage PD meet the Hoehn-Yahr score ≤ 2.5 points, and patients with intermediate and advanced PD meet the Hoehn-Yahr score of 2.5-5 points; 3. Subjects are 50-75 years old (including boundary values), gender is not limited; 4. Agree to undergo study-related examination evaluation and sign informed consent. 2. Multiple system atrophy (MSA) group : 1. Patients with confirmed or probable MSA diagnosed based on the diagnostic criteria for MSA published by the International Movement Disorder Society (MDS) in 2022 ;2. Subjects are 50-75 years old (including boundary values), gender is not limited; 3. Agree to undergo study-related examination evaluation and sign informed consent. 3. Progressive supranuclear palsy (PSP) group: 1. Patients with confirmed or probable PSP diagnosed based on the diagnostic criteria of the 2017 International Movement Disorder Association PSP Collaborative Group; 2. Subjects are 50-75 years old (including boundary values), gender is not limited; 3. Agree to undergo study-related examination evaluation and sign informed consent. 4. Vascular parkinsonism (VP) group: 1. In line with the diagnostic recommendations of vascular parkinsonism in accordance with the 2004 International Association for Movement Disorders and the 2017 Chinese expert consensus; 2. Subjects are 50-75 years old (including boundary values), gender is not limited; 3. Agree to undergo study-related examination evaluation and sign informed consent. 5. Drug-induced parkinsonism (DIP) group: 1. Parkinsonism; 2. Drug history, the appearance of symptoms is related to specific drugs; 3. Symptoms are reversible, and the symptoms are reduced or disappeared when the corresponding drugs are reduced; 4. Rule out other causes; 5. Subjects are 50-75 years old (including boundary values), gender is not limited; 6. Agree to undergo study-related examination evaluation and sign informed consent. 6. Corticobasal degeneration (CBD) group: 1. Diagnosis of probable or probable CBD based on the 2019 Chinese diagnostic criteria for corticobasal degeneration; 2. Subjects are 50-75 years old (including boundary values), gender is not limited; 3. Agree to undergo study-related examination evaluation and sign informed consent. 7. Dementia with Lewy Bodies (DLB) Group: 1. Diagnosed as probable or possible DLB based on the 2017 international DLB diagnostic criteria and the 2021 Chinese DLB diagnostic criteria. 2. Exhibits symptoms of Parkinsonism. 3. Subjects are aged 50-75 years (inclusive), with no gender restriction. 4. Agree to undergo study-related assessments and evaluations and signs the informed consent form. Exclusion Criteria: 1. Cognitive dysfunction, unable to complete the study (MMSE \< 23) 2. Inability to tolerate levodopa shock test 3. Patients with failure of important organs (heart, lung, liver, kidney, etc.), malignant tumors, unstable conditions and other serious internal diseases 4. Those with serious behavioral problems or mental disorders 5. Inability to sign informed consent 6. Other conditions that are considered unsuitable by the investigator to participate in this study.

Outcomes

Primary Outcomes

Accuracy

Using quantitative assessment methods, conduct exploratory research on new methods for early diagnosis.The test correctly identified the total proportion of individuals with and without the disease.

Time frame: baseline

Diagnostic Odds Ratio

Using quantitative assessment methods, conduct exploratory research on new methods for early diagnosis.The ratio of positive likelihood ratio to negative likelihood ratio reflects the diagnostic efficiency of the test.

Time frame: baseline

Specificity

Using quantitative assessment methods, conduct exploratory research on new methods for early diagnosis.The proportion of healthy people without a certain disease correctly identified by a diagnostic test. High specificity means that the test rarely misdiagnoses healthy people as disease patients (i.e., low false positive rate).

Time frame: baseline

Negative Predictive Value

Using quantitative assessment methods, conduct exploratory research on new methods for early diagnosis.Among all individuals who tested negative, the proportion who were truly free of the disease.

Time frame: baseline

Sensitivity

Using quantitative assessment methods, conduct exploratory research on new methods for early diagnosis.The proportion of patients with a disease correctly identified by a diagnostic test. High sensitivity means that the test rarely misses cases of disease (i.e., low false negative rate).

Time frame: baseline

Positive Predictive Value

Using quantitative assessment methods, conduct exploratory research on new methods for early diagnosis.Of all the individuals who tested positive, the proportion who actually had the disease.

Time frame: baseline

Secondary Outcomes

Negative Predictive Value

Conduct differential diagnosis between Parkinson's disease and other Parkinsonian syndromes.Among all individuals who test negative, the proportion who are truly free of the disease.

Time frame: baseline

root mean square error

Quantify the magnitude of the prediction error

Time frame: baseline

Correlation Coefficient

Strength of the linear relationship between reflection and true results

Time frame: baseline

Specificity

Conduct differential diagnosis between Parkinson's disease and other Parkinsonian syndromes.Diagnostic tests correctly identify the proportion of healthy people who do not have a disease.

Time frame: baseline

Sensitivity

Conduct differential diagnosis between Parkinson's disease and other Parkinsonian syndromes.Refers to the proportion of patients with a disease that a diagnostic test correctly identifies.

Time frame: baseline

Positive Predictive Value

Conduct differential diagnosis between Parkinson's disease and other Parkinsonian syndromes.Of all the individuals who tested positive, the proportion who actually had the disease

Time frame: baseline

Coefficient of Determination

The proportion of variation that reflects the interpretation of the results

Time frame: baseline

Diagnostic Odds Ratio

Conduct differential diagnosis between Parkinson's disease and other Parkinsonian syndromes.The ratio of positive likelihood ratio to negative likelihood ratio reflects the diagnostic efficiency of the test.

AI-Enhanced Optimization of Acute Levodopa Challenge Test

Overview

Conditions

Interventions

Eligibility

Locations (1)

Outcomes

Primary Outcomes

Secondary Outcomes

Central Contacts