This is an international multicentre study aimed at evaluating the combined value of dopaminergic neuroimaging and clinical features in predicting future phenoconversion of idiopathic REM sleep behaviour (iRBD) subjects to overt synucleinopathy. Nine centres sent 123I-FP-CIT-SPECT data of 344 iRBD patients and 256 controls for centralized analysis. 123I-FP-CIT-SPECT images were semiquantified using DaTQUANTTM, obtaining putamen and caudate specific to non-displaceable binding ratios (SBRs). The following clinical variables were also analysed: (i) Movement Disorder Society-sponsored revision of the Unified Parkinson’s Disease Rating Scale, motor section score; (ii) Mini-Mental State Examination score; (iii) constipation; and (iv) hyposmia. Kaplan-Meier survival analysis was performed to estimate conversion risk. Hazard ratios for each variable were calculated with Cox regression. A generalized logistic regression model was applied to identify the best combination of risk factors. Bayesian classifier was used to identify the baseline features predicting phenoconversion to parkinsonism or dementia. After quality check of the data, 263 iRBD patients (67.6 ± 7.3 years, 229 males) and 243 control subjects (67.2 ± 10.1 years, 110 males) were analysed. Fifty-two (20%) patients developed a synucleinopathy after average follow-up of 2 years. The best combination of risk factors was putamen dopaminergic dysfunction of the most affected hemisphere on imaging, defined as the lower value between either putamina (P < 0.000001), constipation, (P < 0.000001) and age over 70 years (P = 0.0002). Combined features obtained from the generalized logistic regression achieved a hazard ratio of 5.71 (95% confidence interval 2.85–11.43). Bayesian classifier suggested that patients with higher Mini-Mental State Examination score and lower caudate SBR asymmetry were more likely to develop parkinsonism, while patients with the opposite pattern were more likely to develop dementia. This study shows that iRBD patients older than 70 with constipation and reduced nigro-putaminal dopaminergic function are at high risk of short-term phenoconversion to an overt synucleinopathy, providing an effective stratification approach for future neuroprotective trials. Moreover, we provide cut-off values for the significant predictors of phenoconversion to be used in single subjects.

Background: Seizures are common in patients with dementia but precise epidemiologic data of epilepsy in neurodegenerative dementia is lacking. Objective: The first aim of the study was to investigate prevalence and clinical characteristics of epilepsy in a large cohort of patients with neurodegenerative dementias. Subsequently, we explored clinical, neuropsychological, and quantitative electroencephalogram (qEEG) data of Alzheimer's disease (AD) patients with epilepsy (AD-EPI) as compared to AD patients without epilepsy (AD-CTR). Methods: We retrospectively evaluated consecutive patients with a diagnosis of a neurodegenerative dementia and a clinically diagnosed epilepsy that required antiepileptic drugs (AED). All patients underwent baseline comprehensive neuropsychological assessment. A follow-up of at least one year was requested to confirm the dementia diagnosis. In AD patients, qEEG power band analysis was performed. AD-CTR and AD-EPI patients were matched for age, Mini-Mental State Examination score, and gender. Results: Thirty-eight out of 2,054 neurodegenerative dementia patients had epilepsy requiring AED. The prevalence of epilepsy was 1.82% for AD, 1.28% for the behavioral variant of frontotemporal dementia (bvFTD), 2.47% for dementia with Lewy bodies (DLB), and 12% for primary progressive aphasia. Epilepsy were more drug-responsive in AD than in non-AD dementias. Finally, no significant differences were found in neuropsychological and qEEG data between AD-EPI and AD-CTR patients. Conclusion: In our cohort, AD, FTD, and DLB dementias have similar prevalence of epilepsy, even if AD patients were more responsive to AED. Moreover, AD-EPI patients did not have significant clinical, neuropsychological qEEG differences compared with AD-CTR patients.

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