OBJECTIVES: To identify patient groups with Alzheimer disease (AD) according to the presence of psychological and behavioral syndromes and to determine the clinical differences among these groups. METHODS: Cross-sectional and observational study of 491 patients with probable AD whom were administered the Neuropsychiatric Inventory (NPI) at the baseline visit and reevaluated after 12 months. RESULTS: Principal component analysis (PCA) of baseline NPI data revealed three factors, including a psychosis factor (delusions, hallucinations, and aberrant motor behavior), a depressive factor (depression, anxiety, irritability, agitation, and apathy) and a hypomanic factor (euphoria and disinhibition). Cluster analysis of factor scores indicated the presence of three patient groups: one group was characterized by low scores in factors, a second group including patients with high scores in the depressive factor, and a third group that included patients with high scores in the three factors. The PCA of the NPI scores carried out after 1 year showed the persistence of the three factors. The cluster analysis of their factor scores also showed the presence of the same three patient groups but with a few differences in certain symptoms. A higher frequency of personal psychiatric history but no family history was observed in the cluster with depressive symptoms. CONCLUSIONS: Three neuropsychiatric syndromes have been identified, which have made it possible to classify patients with AD in three distinct large groups. A temporal stability is evidenced among the group with low symptoms. Patients with high scores in depressive factor or in three factors showed greater temporal instability. Certain differences among the groups suggest that different physiopathogenic mechanisms may be involved in neuropsychiatric syndromes.
OBJECTIVES: To identify patient groups with Alzheimer disease (AD) according to the presence of psychological and behavioral syndromes and to determine the clinical differences among these groups. METHODS: Cross-sectional and observational study of 491 patients with probable AD whom were administered the Neuropsychiatric Inventory (NPI) at the baseline visit and reevaluated after 12 months. RESULTS: Principal component analysis (PCA) of baseline NPI data revealed three factors, including a psychosis factor (delusions, hallucinations, and aberrant motor behavior), a depressive factor (depression, anxiety, irritability, agitation, and apathy) and a hypomanic factor (euphoria and disinhibition). Cluster analysis of factor scores indicated the presence of three patient groups: one group was characterized by low scores in factors, a second group including patients with high scores in the depressive factor, and a third group that included patients with high scores in the three factors. The PCA of the NPI scores carried out after 1 year showed the persistence of the three factors. The cluster analysis of their factor scores also showed the presence of the same three patient groups but with a few differences in certain symptoms. A higher frequency of personal psychiatric history but no family history was observed in the cluster with depressive symptoms. CONCLUSIONS: Three neuropsychiatric syndromes have been identified, which have made it possible to classify patients with AD in three distinct large groups. A temporal stability is evidenced among the group with low symptoms. Patients with high scores in depressive factor or in three factors showed greater temporal instability. Certain differences among the groups suggest that different physiopathogenic mechanisms may be involved in neuropsychiatric syndromes.
Authors: Zahinoor Ismail; Chetachi A Emeremni; Patricia R Houck; Sati Mazumdar; Jules Rosen; Tarek K Rajji; Bruce G Pollock; Benoit H Mulsant Journal: Am J Geriatr Psychiatry Date: 2013-01-02 Impact factor: 4.105
Authors: Josh M Krivinko; Susan L Erickson; Eric E Abrahamson; Zachary P Wills; Milos D Ikonomovic; Peter Penzes; Robert A Sweet Journal: Neurobiol Aging Date: 2017-02-16 Impact factor: 4.673
Authors: Kristoffer H Hellton; Jeffrey Cummings; Audun Osland Vik-Mo; Jan Erik Nordrehaug; Dag Aarsland; Geir Selbaek; Lasse Melvaer Giil Journal: Multivariate Behav Res Date: 2020-04-24 Impact factor: 5.923