Clinical Trials Logo

Clinical Trial Details — Status: Recruiting

Administrative data

NCT number NCT05906719
Other study ID # u3
Secondary ID
Status Recruiting
Phase
First received
Last updated
Start date March 1, 2023
Est. completion date April 1, 2024

Study information

Verified date March 2023
Source Ruijin Hospital
Contact Lun Liu, MD,PhD
Phone 021-86-64370045
Email jly0520@hotmail.com
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial Summary

The Movement Disorders Society (MDS) Unified Parkinson's Disease Rating Scale (UPDRS) Part III (MDS-UPDRS III) is the primary assessment method for motor symptoms in Parkinson's disease patients. Currently, movement disorder specialists conduct semi-quantitative scoring, which entails limitations such as subjectivity, weak sensitivity, and a limited number of professional physicians. This study, based on machine vision, establishes gold standard labels according to expert scoring. By using machine learning, we develop a machine rating model and compare the model's performance with gold standard rating and general clinical rating to investigate the accuracy of machine vision-based MDS-UPDRS III machine rating.


Recruitment information / eligibility

Status Recruiting
Enrollment 871
Est. completion date April 1, 2024
Est. primary completion date April 1, 2024
Accepts healthy volunteers No
Gender All
Age group 20 Years to 80 Years
Eligibility Inclusion Criteria: - Meeting the diagnostic criteria for Parkinsonism established by the International Movement Disorder Society: having bradykinesia, and meeting at least one of the two criteria for resting tremor or muscle rigidity - 20 to 80 years old - Good compliance, voluntarily joining the study, and able to sign an informed consent form or have it signed by a legal representative Exclusion Criteria: - Significant cognitive impairment (MMSE = 23) - Unable to sign written informed consent or unable to complete the trial due to other reasons - Other situations in which the researcher deems the participant unsuitable for this study - Participation in other clinical trials

Study Design


Related Conditions & MeSH terms


Intervention

Other:
video recording
Patients' performance of MDS-UPDRS III will be recorded.

Locations

Country Name City State
China Beijing Hospital, Neurology Department Beijing Beijing
China Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University Beijing Beijing
China Department of Neurology, West China Hospital, Sichuan University Chengdu Sichuan
China Department of Neurology, Fujian Medical University Union Hospital Fuzhou Fujian
China Department of Neurology, Guangdong Neuroscience Institute, Guangdong General Hospital, Guangdong Academy of Medical Sciences Guangzhou Guangdong
China Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine Shanghai Shanghai
China Department of Neurology and Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University Suzhou Jiangsu
China Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology Wuhan Hubei

Sponsors (8)

Lead Sponsor Collaborator
Ruijin Hospital Beijing Hospital, Beijing Tiantan Hospital, Fujian Medical University Union Hospital, Guangdong Provincial People's Hospital, Second Affiliated Hospital of Soochow University, West China Hospital, Wuhan Union Hospital, China

Country where clinical trial is conducted

China, 

Outcome

Type Measure Description Time frame Safety issue
Primary ACC0 of machine rating vs gold standard rating The accuracy rate when machine rating equals gold standard rating. 1 day
Primary ACC1 of machine rating vs gold standard rating The accuracy rate when machine rating equals the range of gold standard rating plus or minus one. 1 day
Primary Weighted kappa of machine rating vs gold standard rating The weighted kappa when machine rating equals gold standard rating. 1 day
Primary Lin's CCC of machine rating vs gold standard rating The Lin's Concordance Correlation Coefficient when machine rating equals gold standard rating. 1 day
Secondary Accuracy rate of machine rating vs general clinical rating Comparing the absolute residuals between machine rating and the gold standard rating with the absolute residuals between general clinical raitng and the gold standard rating. 1 day
Secondary Accuracy rate of machine facilitated rating vs general clinical rating Comparing the absolute residuals between machine facilitated rating and the gold standard rating with the absolute residuals between general clinical raitng and the gold standard rating. 1 day
See also
  Status Clinical Trial Phase
Recruiting NCT05040958 - Carotid Atherosclerotic Plaque Load and Neck Circumference
Completed NCT04440553 - A Mobile App to Increase Physical Activity in Students N/A
Completed NCT04828655 - Analysis of Bioparametric Measures for Correlating Daily Habits and Reducing Blood Pressure N/A
Completed NCT04977687 - Machine Learning Predict Renal Replacement Therapy After Cardiac Surgery
Completed NCT04966598 - Machine Learning Predict Acute Kidney Injury in Patients Following Cardiac Surgery
Recruiting NCT06277297 - Prognotic Role of CMR in Takotsubo Syndrome
Recruiting NCT06204133 - Model Study on Cervical Cancer Screening Strategies and Risk Prediction
Completed NCT05085743 - Prediction of Endotracheal Tube Depth by Using Deep Convolutional Neural Networks
Not yet recruiting NCT05809232 - Impact of Machine Learning-based Clinician Decision Support Algorithms in Perioperative Care N/A
Not yet recruiting NCT04399811 - Near-infrared Vision for Microcirculatory Status
Completed NCT06278272 - AI Evaluation of Pancreatic Exocrine Insufficiency in CP Patients
Withdrawn NCT05442762 - Social Media-based Vaccine Confidence and Hesitancy Monitoring
Not yet recruiting NCT06421480 - Using Machine Learning to Detect Risky Behavior in Psychiatric Clinics
Not yet recruiting NCT06423066 - Developing a Machine Learning Model to Predict Pleural Adhesion Preoperatively Using Pleural Ultrasound
Not yet recruiting NCT06428344 - Accuracy of an Artificial Intelligence-assisted Diagnostic System for Caries Diagnosis: a Prospective Multicenter Clinical Study
Not yet recruiting NCT05797064 - Establishment of a Feasibility Model for NOSE Surgery Based on Machine Learning
Recruiting NCT05410171 - Machine Learning-based Early Clinical Warning of High-risk Patients N/A
Active, not recruiting NCT04192175 - Identification of Patients Admitted With COPD Exacerbations and Predicting Readmission Risk Using Machine Learning
Completed NCT05433519 - Diagnostic Accuracy of a Novel Machine Learning Algorithm to Estimate Gestational Age
Recruiting NCT05858892 - Comparison of an Artificial Intelligence-Assisted Rehabilitation Program for Shoulder Musculoskeletal Disorders and the Clinical Decision Making of Therapists