Abstract
The evolution of functional autonomy loss leads to institutionalization of people affected by Alzheimer’s disease (AD), to an alteration of their quality of life and that of their caregivers. To predict loss of functional autonomy could optimize prevention strategies, aids and cost of care. The aim of this study was to develop and to cross-validate a model to predict loss of functional autonomy as assessed by Instrumental Activities of Daily Living (IADL) score. Outpatients with probable AD and with 2 or more visits to the Clinical and Research Memory Centre of the University Hospital were included. Four Tree-Augmented Naïve bayesian networks (6, 12, 18 and 24 months of follow-up) were built. Variables included in the model were demographic data, IADL score, MMSE score, comorbidities, drug prescription (psychotropics and AD-specific drugs). A 10-fold cross-validation was conducted to evaluate robustness of models. The study initially included 485 patients in the prospective cohort. The best performance after 10-fold cross-validation was obtained with the model able to predict loss of functional autonomy at 18 months (area under the curve of the receiving operator characteristic curve = 0.741, 27% of patients misclassified, positive predictive value = 77% and negative predictive value = 73%). The 13 variables used explain 41.6% of the evolution of functional autonomy at 18 months. A high-performing predictive model of AD evolution of functional autonomy was obtained. An external validation is needed to use the model in clinical routine so as to optimize the patient care.
Highlights
Introduction and ObjectiveAlzheimer’s disease (AD) is the most common neurodegenerative disease and represents two thirds of dementia cases in the elderly population [1]
Functional autonomy loss represents the main source of handicap in patients with AD
The purpose of this work was to build and validate a Bayesian networks (BN) model to specify the risk of functional autonomy loss of patients with AD
Summary
Introduction and ObjectiveAlzheimer’s disease (AD) is the most common neurodegenerative disease and represents two thirds of dementia cases in the elderly population [1]. This neurodegenerative disease presents with a long asymptomatic period during, which, only characteristic neuropathological lesions, i.e., amyloid deposits and tau pathology, are observed in the brain This phase, which may be associated with amyloid/tau pathology and neurodegenerescence biomarkers, is followed by a subjective cognitive decline phase centered on memory, a mild neurocognitive disorder phase and lastly, the stage of dementia known as major neurocognitive disorder, which induces autonomy loss. This biological, neuroimaging and clinical continuum illustrates a long period of duration of the disease, which should favor multidomain and early interventions involving primary to tertiary prevention programs.
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