Background and Objectives Dementia with Lewy Bodies (DLB) is a heterogeneous disease, with variable signs and symptoms across multiple domains. We aimed to identify associations with rate of change in cognition, everyday functioning (IADL) and quality of life (QoL). Methods We included 121 DLB patients (69 ± 6 yrs, 14%F, MMSE: 25 ± 3) in our prospective cohort (follow‐up 2 ± 1 yrs). We described progression of symptoms and cognitive decline over time. Mixed models were used to investigate whether changes in symptoms were associated to changes in IADL (FAQ), QoL (QoL‐AD) and caregiver burden (ZBI). Last, we investigated whether baseline symptoms and biomarkers predicted decline in cognition (MMSE), IADL (FAQ) and QoL (QoL‐AD). Results Parkinsonism and RBD were most frequently present early in the disease course, while hallucinations were more likely to develop in a later stage. MMSE (annual change β ± SE = −2.06 ± 0.23), QoL‐AD (−1.03 ± 0.20), and FAQ (3.04 ± 0.30) declined over time. Increasing severity of clinical symptoms was associated to increases in FAQ, QoL‐AD and caregiver burden. Baseline clinical symptoms were not predictive for decline in these outcomes. By contrast, AD co‐pathology (CSF pTau/Aβ42 ratio) was associated to steeper decline in MMSE (−1.23 ± 0.54). Medial temporal atrophy (−0.81 ± 0.26) and global cortical atrophy (−0.73 ± 0.36) predisposed for decline in QoL‐AD. Conclusions Our findings imply that underlying disease processes, rather than clinical symptomatology aid in predicting decline. These findings are relevant for treatment strategies and the development of DLB specific outcome measures.
BackgroundDiagnosing dementia with Lewy bodies (DLB) is challenging due to overlapping clinical and cognitive presentation with Alzheimer’s disease (AD). Web‐based cognitive and clinical assessments could aid by providing remote and easily accessible diagnostic tools. In this study, we adapted a web‐based cognitive test tool, cCOG, by adding a visuospatial test and a brief clinical survey and assessed its ability to differentiate between DLB and AD.MethodWe included 110 patients (67±7 years, 44% female, MMSE 26±4; n = 30 DLB, n = 32 AD dementia and n = 48 controls with subjective cognitive decline (SCD)). All completed cCOG, comprising six cognitive subtasks assessing memory functioning, reaction time, executive functioning, a visuospatial task, and a brief survey addressing seven self‐reported DLB core features and suggestive 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.ResultcCOG 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). cCOG cognitive tasks only, resulted in a diagnostic accuracy of 0.70 [95% CI 0.61‐0.78]. Full cCOG, including both cognitive tasks and brief survey had a diagnostic accuracy of 0.82 [95% CI 0.73‐0.89], with good discrimination of DLB versus AD/controls (acc 0.90 [0.83‐0.95]) and DLB versus AD (acc 0.87 [0.76‐0.95]).ConclusionWe 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 to a more timely and accurate diagnosis of DLB and AD.
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