Optimizing cCOG, a Web-based tool, to detect dementia with Lewy Bodies

Abstract

Introduction: Distinguishing dementia with Lewy bodies (DLB) from Alzheimer's disease (AD) is challenging due to overlapping presentations. We adapted a Web-based test tool, cCOG, by adding a visuospatial task and a brief clinical survey and assessed its ability to differentiate between DLB and AD. Methods: We included 110 patients (n = 30 DLB, n = 32 AD dementia, and n = 48 controls with subjective cognitive decline (SCD)). Full cCOG comprises six cognitive subtasks and a survey addressing self-reported DLB core and autonomic features. First, we compared cCOG cognitive tasks to traditional neuropsychological tasks for all diagnostic groups and clinical questions to validated assessments of clinical features in DLB only. Then, we studied the performance of cCOG cognitive tasks and clinical questions, separately and combined, in differentiating diagnostic groups. Results: cCOG cognitive tasks and clinical survey had moderate to strong correlations to standard neuropsychological testing (.61≤ rs ≤.77) and to validated assessments of clinical features (.41≤ rs ≤.65), except for fluctuations and REM-sleep behavior disorder (RBD) (rs =.32 and rs =.10). Full cCOG, including both cognitive tasks and brief survey had a diagnostic accuracy (acc) of 0.82 [95% CI 0.73–0.89], with good discrimination of DLB versus AD (acc 0.87 [0.76–0.95]) and DLB versus controls (acc 0.94 [0.86–0.98]). Conclusion: We illustrated that cCOG aids in distinguishing DLB and AD patients by using remote assessment of cognition and clinical features. Our findings pave the way to a funneled, harmonized diagnostic process among memory clinics and, eventually, a more timely and accurate diagnosis of DLB and AD.