Alzheimer’s disease (AD) is a frequent pathology, with a poor prognosis, for which no curative treatment is available in 2018. AD prevention is an im

There is currently not sufficient evidence to support the effectiveness of face shields for source control. In order to evaluate the comparative barrier performance effect of face masks and face shields, we used an aerosol generator and a particle counter to evaluate the performance of the various devices in comparable situations. We tested different configurations in an experimental setup with manikin heads wearing masks (surgical type I), face shields (22.5 cm high with overhang under the chin of 7 cm and circumference of 35 cm) on an emitter or a receiver manikin head, or both. The manikins were face to face, 25 cm apart, with an intense particle emission (52.5 L/min) for 30 s. The particle counter calculated the total cumulative particles aspirated on a volume of 1.416 L In our experimental conditions, when the receiver alone wore a protection, the face shield was more effective (reduction factor = 54.8%), while reduction was lower with a mask (reduction factor = 21.8%) (p = 0.002). The wearing of a protective device by the emitter alone reduced the level of received particles by 96.8% for both the mask and face shield (p = NS). When both the emitter and receiver manikin heads wore a face shield, the protection allowed for better results in our experimental conditions: 98% reduction for the face shields versus 97.3% for the masks (p = 0.01). Face shields offered an even better barrier effect than the mask against small inhaled particles (<0.3 µm–0.3 to 0.5 µm–0.5 to 1 µm) in all configurations. Therefore, it would be interesting to include face shields as used in our experimental study as part of strategies to reduce transmission within the community setting.

Identifying modifiable risk factors for Alzheimer’s disease (AD) is critical for research. Data mining may be a useful tool for finding new AD associated factors. We included all patients over 49 years of age, hospitalized in France in 2008 (without dementia) and in 2014. Dependent variable was AD or AD dementia diagnosis in 2014. We recoded the diagnoses of hospital stays (in ICD-10) into 137 explanatory variables.To avoid overweighting the "age" variable, we divided the population into 7 sub-populations of 5 years. We analyzed 1,390,307 patients in the PMSI in 2008 and 2014: 55,997 patients had coding for AD or AD dementia in 2014 (4.04%). We associated Alzheimer disease in 2014 with about 20 variables including male sex, stroke, diabetes mellitus, mental retardation, bipolar disorder, intoxication, Parkinson disease, depression, anxiety disorders, alcohol, undernutrition, fall and 3 less explored variables: intracranial hypertension (odd radio [95% confidence interval]: 1.16 [1.12–1.20] in 70–80 years group), psychotic disorder (OR: 1.09 [1.07–1.11] in 70–75 years group) and epilepsy (OR: 1.06 [1.05–1.07] after 70 years). We analyzed 137 variables in the PMSI identified some well-known risk factors for AD, and highlighted a possible association with intracranial hypertension, which merits further investigation. Better knowledge of associations could lead to better targeting (identifying) at-risk patients, and better prevention of AD, in order to reduce its impact.