Cognitive Function Clinical Trial
Official title:
Evaluation of DCTclock™ as a Cognitive Assessment Aid
Verified date | March 2018 |
Source | Digital Cognition Technologies |
Contact | n/a |
Is FDA regulated | No |
Health authority | |
Study type | Interventional |
The overall objective of this study is to demonstrate the safety and effectiveness of DCTclock as an adjunctive tool for use by clinicians to evaluate cognitive function in adults aged 55-95.
Status | Completed |
Enrollment | 450 |
Est. completion date | November 21, 2017 |
Est. primary completion date | November 21, 2017 |
Accepts healthy volunteers | Accepts Healthy Volunteers |
Gender | All |
Age group | 55 Years to 95 Years |
Eligibility |
Inclusion Criteria: - Men and women 55 to 95 years old. Exclusion Criteria: - Ineligible for written informed consent. - Physical impairment of the writing hand. - Impaired manual dexterity. - Impaired vision. - Under the influence of recreational drugs or alcohol at the time of the visit. - Current or recent participation in a clinical trial that includes the use of a drug or intervention to alter cognitive function. - Recent cognitive testing. |
Country | Name | City | State |
---|---|---|---|
United States | Compass Research | Maitland | Florida |
Lead Sponsor | Collaborator |
---|---|
Digital Cognition Technologies |
United States,
Cohen J, Penney DL, Davis R, Libon DJ, Swenson RA, Ajilore O, Kumar A, Lamar M. Digital Clock Drawing: differentiating "thinking" versus "doing" in younger and older adults with depression. J Int Neuropsychol Soc. 2014 Oct;20(9):920-8. doi: 10.1017/S1355617714000757. Epub 2014 Sep 15. — View Citation
Davis R, Libon DJ, Au R, Pitman D, Penney DL. THink: Inferring Cognitive Status from Subtle Behaviors. Proc Conf AAAI Artif Intell. 2014 Jul;2014:2898-2905. — View Citation
Lamar M, Ajilore O, Leow A, Charlton R, Cohen J, GadElkarim J, Yang S, Zhang A, Davis R, Penney D, Libon DJ, Kumar A. Cognitive and connectome properties detectable through individual differences in graphomotor organization. Neuropsychologia. 2016 May;85:301-9. doi: 10.1016/j.neuropsychologia.2016.03.034. Epub 2016 Mar 30. — View Citation
Souillard-Mandar W, Davis R, Rudin C, Au R, Libon DJ, Swenson R, Price CC, Lamar M, Penney DL. Learning Classification Models of Cognitive Conditions from Subtle Behaviors in the Digital Clock Drawing Test. Mach Learn. 2016 Mar;102(3):393-441. Epub 2015 Oct 20. — View Citation
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Other | Construct Validity of DCTclock as Measured by the Comparison of DCTclock Results to the Results of a Battery of Neuropsychological Assessments | The goal of this analysis is to assess the construct validity of DCTclock. Specifically, the goal is to compare scores from the administration of DCTclock to the visit 1 administration of a battery of neuropsychological tests, to characterize the psychometric properties of DCTclock, and to compare those properties to the properties of MMSE. | Visit 1 (day 1) | |
Other | Incidence of Serious Device-related Adverse Events [Safety] | Incidence of serious device-related adverse events. | Visit 1 and visit 2, occuring 1-4 weeks apart | |
Primary | Non-Inferiority of DCTclock Compared to Mini-Mental State Examination (MMSE) | The primary analysis will assess agreement between DCTclock and the Montreal Cognitive Assessment (MoCA) and compare it to the agreement between the MMSE and MoCA at visit 1. | Visit 1 (day 1) | |
Secondary | Quadratic Weighted Kappa on Primary Endpoints | Quadratic weighted Cohen's kappa with 95% CI between DCTclock and MoCA, as well as between MMSE and MoCA. | Visit 1 (day 1) | |
Secondary | Percent Agreement on Primary Endpoints | Positive percent agreement, version A (treating the "Indeterminate" group as "Unimpaired") and version B (removing the "Indeterminate" group from the analysis), and negative percent agreement version A and version B. These were calculated for the DCTclock/MoCA classification table as well as the MMSE/MoCA classification table. 95% CI were also calculated and compared between the two classification tables' calculations. | Visit 1 (day 1) | |
Secondary | Regression Coefficients on Primary Endpoints | Linear and rank-linear regression coefficients (slope, intercept) and 95% CI for DCTclock regressed on MoCA as well as for the MMSE regressed on MoCA. | Visit 1 (day 1) | |
Secondary | Correlation Coefficients on Primary Endpoints | Pearson and Spearman correlation coefficients between DCTclock and MoCA as well as between MMSE and MoCA. | Visit 1 (day 1) | |
Secondary | Quadratic Weighted Kappa on Secondary Endpoints (Test-Retest Reliability) | Quadratic weighted Cohen's Kappa statistics were calculated for both DCTclock and MMSE test-retest data (visit 1 vs visit 2). | Visit 1 and visit 2, occurring 1-4 weeks apart | |
Secondary | Percent Agreement on Secondary Endpoints (Test-retest Reliability) | Positive percent agreement version A (treating the "Indeterminate" group as "Unimpaired") and version B (removing the "Indeterminate" group from the analysis), negative percent agreement version A and version B, indeterminate percent agreement, and unimpaired percent agreement. | Visit 1 and visit 2, occurring 1-4 weeks apart | |
Secondary | Regression Coefficients on Secondary Endpoints (Test-retest Reliability) | Deming, linear, and rank-linear correlation coefficients (intercept, slope) were calculated for visit 1 regressed on visit 2 for both DCTclock and MMSE. | Visit 1 and visit 2, occurring 1-4 weeks apart | |
Secondary | Correlation Coefficients on Secondary Endpoints (Test-retest Reliability) | Pearson and Spearman correlation coefficients were calculated between visit 1 and visit 2 for DCTclock and MMSE, along with 95% CI. | Visit 1 and visit 2, occurring 1-4 weeks apart |
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