Abstract
In this work we aimed to identify neural predictors of the efficacy of multimodal rehabilitative interventions in AD-continuum patients in the attempt to identify ideal candidates to improve the treatment outcome. Subjects in the AD continuum who participated in a multimodal rehabilitative treatment were included in the analysis [n = 82, 38 Males, mean age = 76 ± 5.30, mean education years = 9.09 ± 3.81, Mini Mental State Examination (MMSE) mean score = 23.31 ± 3.81]. All subjects underwent an MRI acquisition (1.5T) at baseline (T0) and a neuropsychological evaluation before (T0) and after intervention (T1). All subjects underwent an intensive multimodal cognitive rehabilitation (8–10 weeks). The MMSE and Neuropsychiatric Inventory (NPI) scores were considered as the main cognitive and behavioral outcome measures, and Delta change scores (T1–T0) were categorized in Improved (ΔMMSE > 0; ΔNPI < 0) and Not Improved (ΔMMSE ≤ 0; ΔNPI ≥ 0). Logistic Regression (LR) and Random Forest classification models were performed including neural markers (Medial Temporal Brain; Posterior Brain (PB); Frontal Brain (FB), Subcortical Brain indexes), neuropsychological (MMSE, NPI, verbal fluencies), and demographical variables (sex, age, education) at baseline. More than 50% of patients showed a positive effect of the treatment (ΔMMSE > 0: 51%, ΔNPI < 0: 52%). LR model on ΔMMSE (Improved vs. Not Improved) indicate a predictive role for MMSE score (p = 0.003) and PB index (p = 0.005), especially the right PB (p = 0.002) at baseline. The Random Forest analysis correctly classified 77% of cognitively improved and not improved AD patients. Concerning the NPI, LR model on ΔNPI (Improved vs. Not Improved) showed a predictive role of sex (p = 0.002), NPI (p = 0.005), PB index (p = 0.006), and FB index (p = 0.039) at baseline. The Random Forest reported a classification accuracy of 86%. Our data indicate that cognitive and behavioral status alone are not sufficient to identify best responders to a multidomain rehabilitation treatment. Increased neural reserve, especially in the parietal areas, is also relevant for the compensatory mechanisms activated by rehabilitative treatment. These data are relevant to support clinical decision by identifying target patients with high probability of success after rehabilitative programs on cognitive and behavioral functioning.
Highlights
Cognitive disability affects 10.8% of adults living with a chronic condition, and is characterized by a complex impairment in attention, memory and/or decision making
We identified brain reserve neuroimaging biomarkers and clinical features associated with the best rehabilitative outcomes, giving the opportunity to Confusion matrix summarizing the performance of the RF classification algorithm on the cognitive outcome
Considering the cognitive outcome of rehabilitation, our findings show that patients with low cognitive residual capabilities (MMSE level) at the time of admission and a high Posterior Brain (PB) reserve in the parietal hemispheres are the best candidates to benefit from the rehabilitative treatment by achieving a significant improvement in global cognitive level
Summary
Cognitive disability affects 10.8% of adults living with a chronic condition, and is characterized by a complex impairment in attention, memory and/or decision making. With the aging of the general population (World Health Organization, 2012) cognitive disabilities in the adult are often observed as clinical signs of neurodegenerative diseases as in Alzheimer’s continuum conditions, ranging from Mild Cognitive Impairment (MCI) to Alzheimer’s Dementia (AD) (Aisen et al, 2017; Jack et al, 2018). MCI is a mild neurocognitive disorder (American Psychiatric Association, 2013; Stokin et al, 2015), affecting 6–25% of people aged over 60, characterized by isolated impairment in one or more cognitive processes, often involving memory (amnestic MCI), with a complete autonomy in functional activities of daily living (Langa and Levine, 2014; Petersen et al, 2018). Behavioral changes represent a mark of the disease and is strictly linked with the need of hospitalization (Spector et al, 2013; Maki et al, 2018)
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