To evaluate the mortality, thirteen years after the baseline wave (1994), of participants suffering dementia in the Neurological Disorders in Central Spain (NEDICES) Cohort Study, we conducted a population-based cohort study in the elderly (65 years and more) with 5,278 screened participants at baseline. Mortality has been evaluated by means of the National Death Registry of Spain at 1-5-2007, 13 years after enrolment. Cox's proportional hazards regression models were used to evaluate the hazard of death according to dementia severity and type, adjusting for potential covariates (gender, age, level of education, and co-morbidity). Survival was estimated using Kaplan-Meier method. Of the 5,278 participants screened at baseline, 306 had dementia. Mortality at 13 years was: 275 deaths (89.9%) in dementia subjects; and 2,426 (49.0%) in subjects without dementia. Mortality was higher and statistically significant in dementia subjects. The degree of dementia (DSM-III-R) correlated with the risk of mortality, from mild (HR = 2.23; CI: 1.77-2.82) to moderate (HR =3.10; CI: 2.47-3.89) and severe dementia (HR = 4.98; CI: 3.85-6.44). Survival was similar in Alzheimer's disease and vascular dementia. Factors associated with higher mortality in Cox proportional hazard models were older age, male gender, and comorbidity. Using Population Attributable risk (PAR%), dementia was related to 11.3% of all deaths. Dementia intensity increases the mortality risk at ten years in the NEDICES Study as in other cohort studies. Age, gender, and co-morbidity are associated with higher mortality in dementia patients. Almost one third of deaths in persons over 85 years-old could be attributable to dementia.

Mobile technology is opening a wide range of opportunities for transforming the standard of care for chronic disorders. Using smartphones as tools for longitudinally tracking symptoms could enable personalization of drug regimens and improve patient monitoring. Parkinson's disease (PD) is an ideal candidate for these tools. At present, evaluation of PD signs requires trained experts to quantify motor impairment in the clinic, limiting the frequency and quality of the information available for understanding the status and progression of the disease. Mobile technology can help clinical decision making by completing the information of motor status between hospital visits. This paper presents an algorithm to detect PD by analyzing the typing activity on smartphones independently of the content of the typed text. We propose a set of touchscreen typing features based on a covariance, skewness, and kurtosis analysis of the timing information of the data to capture PD motor signs. We tested these features, both independently and in a multivariate framework, in a population of 21 PD and 23 control subjects, achieving a sensitivity/specificity of 0.81/0.81 for the best performing feature and 0.73/0.84 for the best multivariate method. The results of the alternating finger-tapping, an established motor test, measured in our cohort are 0.75/0.78. This paper contributes to the development of a home-based, high-compliance, and high-frequency PD motor test by analysis of routine typing on touchscreens.

Background Evidences of infectious pathogens in Alzheimer's disease (AD) brains may suggest a deteriorated innate immune system in AD pathophysiology. We previously demonstrated reduced salivary lactoferrin (Lf) levels, one of the major antimicrobial proteins, in AD patients. Methods To assess the clinical utility of salivary Lf for AD diagnosis, we examine the relationship between salivary Lf and cerebral amyloid-β (Aβ) load using amyloid-Positron-Emission Tomography (PET) neuroimaging, in two different cross-sectional cohorts including patients with different neurodegenerative disorders. Findings The diagnostic performance of salivary Lf in the cohort 1 had an area under the curve [AUC] of 0•95 (0•911–0•992) for the differentiation of the prodromal AD/AD group positive for amyloid-PET (PET + ) versus healthy group, and 0•97 (0•924–1) versus the frontotemporal dementia (FTD) group. In the cohort 2, salivary Lf had also an excellent diagnostic performance in the health control group versus prodromal AD comparison: AUC 0•93 (0•876–0•989). Salivary Lf detected prodromal AD and AD dementia distinguishing them from FTD with over 87% sensitivity and 91% specificity. Interpretation Salivary Lf seems to have a very good diagnostic performance to detect AD. Our findings support the possible utility of salivary Lf as a new non-invasive and cost-effective AD biomarker. Funding Instituto de Salud Carlos III (FIS15/00780, FIS18/00118), FEDER, Comunidad de Madrid (S2017/BMD-3700; NEUROMETAB-CM), and CIBERNED (PI2016/01) to E.C.; Spanish Ministry of Economy and Competitiveness (SAF2017-85310-R) to J.L.C., and (PSI2017-85311-P) to M.A.; International Centre on ageing CENIE-POCTEP (0348_CIE_6_E) to M.A.; Instituto de Salud Carlos III (PIE16/00021, PI17/01799), to H.B.