Factors associated with the onset of Alzheimer’s disease: Data mining in the French nationwide discharge summary database between 2008 and 2014

Abstract

Introduction 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. Methods 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. Results 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). Discussion 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.