An Exploration of Subgroups of Neuropsychiatric Symptoms in Mild Cognitive Impairment and Their Risks of Conversion to Dementia or Death.

Objective: To explore the heterogeneity of neuropsychiatric symptom (NPS) complexes in individuals with mild cognitive impairment (MCI) and assess the relative risks of converting to dementia or dying.

Design: Latent class analysis using 7,971 participants with MCI.

Setting: Participants in the Uniform Data Set (UDS) from 39 NIH Alzheimer's Disease Centers.

Participants: Persons with a diagnosis of MCI at initial visit from each center and with either a Mini-Mental State Examination (MMSE) score of 22 or greater or an equivalent education-adjusted Montreal Cognitive Assessment (MoCA) score of 16 or greater.

Measurements: Neuropsychiatric Inventory Questionnaire (NPI-Q) administered at initial visit.

Results: In addition to a subgroup with mild or no NPS (relative frequency, 50%), three empirically-based subgroups of NPS were identified: 1) an "affect" or "negative mood" subgroup (27%) with depression, anxiety, apathy, nighttime disturbance, and change in appetite; 2) a "hyperactive" subgroup (14%) with agitation, irritability, and disinhibition; and 3) a "psychotic with additional severe NPS" subgroup (9%) with the highest risk of delusions and hallucinations, as well as highest risk of all other NPS. Each of these three subgroups had significantly higher risk of converting to dementia than the "mild NPS" class, with the "psychotic with additional severe NPS" subgroup possessing a 64% greater risk. The subgroups did not differ in their risks of death without dementia.

Conclusion: Our findings of three NPS subgroups in MCI characterized by affect, hyperactive, or psychotic features are largely consistent with a previous 3-factor model of NPS found in a demented population. The consistency of these findings across studies and samples, coupled with our results on the associated risks of converting to dementia, suggests that the NPS structure is robust, and warrants further consideration in classification models of MCI.