Ignite Creation Date:
2025-12-25 @ 1:20 AM
Ignite Modification Date:
2025-12-25 @ 11:28 PM
Study NCT ID:
NCT04858893
Status:
COMPLETED
Last Update Posted:
2021-05-12
First Post:
2021-04-21
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
Application of Machine Learning Method in Validation of Screening Cognitive Test for Parkinsonisms
Sponsor:
Ospedale Generale Di Zona Moriggia-Pelascini
Organization:
Study Overview
Official Title:
Cognitive Screening in Patients With Parkinsonism: Proposal for a New, Machine Learning Based Diagnostic Tool
Status:
COMPLETED
Status Verified Date:
2021-05
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
CoMDA-ML-P
Brief Summary:
Based on a prospectively collected data analysis, a new tool, namely CoMDA (Cognition in Movement Disorders Assessment) is developed by merging each item of Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA) and Frontal Assessment Battery (FAB). A machine learning, able to classify the cognitive profile and predict patients' at risk of dementia, is created.
Detailed Description:
A prospectively data-base was setting up, collecting CoMDA and in-depht-neuropsychologocal-battery scores, obtained from the evaluation of 500 patients with parkinsonisms. Data were analyzed to compare the classification of patient cognition profile, obtained with CoMDA, MMSE, MoC and FAB, with that obtained from in-depth neuropsychological evaluation. A very high percentage of false negative emerged, for MMSE, MoCA and FAB. Conversely, the CoMDA score significantly reduces the rate of false negative.
This new tool, namely "CoMDA" (Cognition in Movement Disorders Assessment), was composed, by merging each item of Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA) and Frontal Assessment Battery (FAB). Moreover, we created a machine learning, namely "Neural Net 91classification" able to classify the cognitive profile and predict patients' at risk of dementia, providing a prediction of the findings resulting from a in-depht neuropsychological evaluation.
CoMDA and the related Neural Net 91classification represent a reliable, time-sparing screening instrument, which is much more powerful of other common, widely-adopted tools.
This new tool, namely "CoMDA" (Cognition in Movement Disorders Assessment), was composed, by merging each item of Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA) and Frontal Assessment Battery (FAB). Moreover, we created a machine learning, namely "Neural Net 91classification" able to classify the cognitive profile and predict patients' at risk of dementia, providing a prediction of the findings resulting from a in-depht neuropsychological evaluation.
CoMDA and the related Neural Net 91classification represent a reliable, time-sparing screening instrument, which is much more powerful of other common, widely-adopted tools.
Study Oversight
Has Oversight DMC:
False
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?: