093 How to diagnose lewy body dementia? Prevalence and underlying relationship between clinical and neuropsychological features of DLB

Abstract

IntroductionDespite its importance for management, prognostication and selection of patients for clinical trials, the diagnosis of Dementia with Lewy Bodies (DLB) remains challenging. Complicating this is a recent change in the diagnostic criteria which has arguably shifted the expected phenotype of DLB patients. In this study we aimed to characterize and examine the relationship between cognitive and clinical diagnostic variables in DLB patients to uncover latent symptom clusters that may streamline future diagnostic approaches in the clinic.MethodsThe clinical and neuropsychological profile of 27 prospectively recruited participants diagnosed with probable DLB and 25 age-matched controls was characterized according to the most recent consensus criteria.Symptoms were scored using a novel combination of established clinical and research instruments.ResultsWe demonstrate comparable sensitivity of formal neuropsychological testing and bedside screening tools (MOCA/MMSE) for identifying domain-specific differences between controls and patients(p<0.001). Optimal sensitivity thresholds for diagnosis of Parkinsonism (88.9%) were explored yielding a prevalence range of 50%-90% within our cohort.Factor analysis using all core and supportive features of the diagnostic criteria identified 6 independent factors accounting for 81% of the total variance. Unique relationships identified included between hallucinations and fluctuations and excessive daytime somnolence; between REM sleep behavior disorder and orthostatic hypotension; and Parkinsonism and urinary disturbance. ‘Prodromal’ symptoms including autonomic and early neuropsychiatric features are represented in the remaining factors.ConclusionParsimonious delineation of clinical variables using identified symptom clusters can aid DLB diagnosis.Clusters are also used to highlight latent pathological relationships. Appropriate instruments and thresholds for detecting dementia and core and suggestive features are presented.