A Novel Machine Learning Algorithm to Predict the Lewy Body Dementias

Dementia Clinical Trial

— MLDLB  

Official title:

A Novel Machine Learning Algorithm to Predict the Lewy Body Dementias Using Clinical and Neuropsychological Scores

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT04448340
• Other study ID #: 251ATHENS HOSPITAL
• Status: Recruiting
• Start date: September 1, 2019
• Est. completion date: March 1, 2021

Study information

• Verified date: September 2020
• Source: National and Kapodistrian University of Athens
• Contact: ANASTASIA BOUGEA, DR
• Phone: +306930481046
• Email: annita139[@]yahoo.gr
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

Parkinson's disease dementia (PDD) and Dementia with lewy bodies (DLB) are dementia syndromes that overlap in many clinical features, making their diagnosis difficult in clinical practice, particularly in advanced stages. We propose a machine learning algorithm, based only on non-invasively and easily in-the-clinic collectable predictors, to identify these disorders with a high prognostic performance.

Description:

The algorithm will be develop using dataset from two specialized memory centers, employing a sample of PDD and DLB subjects whose diagnostic follow-up is available for at least 3 years after the baseline assessment. A restricted set of information regarding clinico- demographic characteristics, 6 neuropsychological tests (mini mental, PD Cognitive Rating Scale, Brief Visuospatial Memory test, Symbol digit written, Wechsler adult intelligence scale, trail making A and B) was used as predictors. Two classification algorithms, logistic regression and K-Nearest Neighbors (K-NNs), will be investigated for their ability to predict successfully whether patients suffered from PDD or DLB.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 200
• Est. completion date: March 1, 2021
• Est. primary completion date: October 1, 2020
• Accepts healthy volunteers: No
• Gender: All
• Age group: 50 Years to 90 Years

Eligibility

Inclusion Criteria:

the PDD group comprised of patients fulfilling the Criteria for probable PDD of the Movement Disorders Society (b) the DLB group comprised of patients, according to the recent revised criteria for probable DLB .

Exclusion Criteria:

• major psychiatrics disorders, depression

Related Conditions & MeSH terms

• Dementia
• Lewy Body Disease

Intervention

Diagnostic Test:
• machine learning model
Two classification algorithms, logistic regression and K-Nearest Neighbors (K-NNs), were investigated for their ability to predict successfully whether patients suffered from PDD or DLB.

Locations

Country	Name	City	State
Greece	Anastasia Bougea	Athens	Attiki

Sponsors (1)

Lead Sponsor	Collaborator
National and Kapodistrian University of Athens

Country where clinical trial is conducted

Greece, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	MMSE predictive for dlb or PDD	Two classification algorithms, logistic regression and K-Nearest Neighbors (K-NNs), will combine these tests in order to investigate for their ability to predict successfully whether patients suffered from PDD or DLB.	1 year
Primary	Parkinson's Disease - Cognitive Rating Scale (PD-CRS) predictive for DLB or PDD	Two classification algorithms, logistic regression and K-Nearest Neighbors (K-NNs), will combine these tests in order to investigate for their ability to predict successfully whether patients suffered from PDD or DLB.	1 year
Primary	Brief Visuospatial Memory Test (BVMT-TR) predictive for DLB or PDD	Two classification algorithms, logistic regression and K-Nearest Neighbors (K-NNs), will combine these tests in order to investigate for their ability to predict successfully whether patients suffered from PDD or DLB.	1 year
Primary	Symbol digit written predictive for DLB or PDD	Two classification algorithms, logistic regression and K-Nearest Neighbors (K-NNs), will combine these tests in order to investigate for their ability to predict successfully whether patients suffered from PDD or DLB.	1 year
Primary	Wechsler adult intelligence scale,predictive for DLB or PDD	Two classification algorithms, logistic regression and K-Nearest Neighbors (K-NNs), will combine these tests in order to investigate for their ability to predict successfully whether patients suffered from PDD or DLB.	1 year
Primary	trail making A and B predictive for DLB or PDD	Two classification algorithms, logistic regression and K-Nearest Neighbors (K-NNs), will combine these tests in order to investigate for their ability to predict successfully whether patients suffered from PDD or DLB.	1 year