Objective: To estimate the incidence of psychotic symptoms in Alzheimer's disease.
Methods: The study consists of 776 elderly subjects presenting to the Alzheimer Disease Research Center at the University of Pittsburgh (Pittsburgh, Pennsylvania) between May 9, 2000, and August 19, 2014. All participants were diagnosed with mild cognitive impairment (National Institute on Aging-Alzheimer's Association workgroup criteria) or possible or probable Alzheimer's disease (National Institute of Neurologic and Communicative Disorders and Stroke and the Alzheimer's Disease and Related Disorders Association criteria) and were without psychosis at entry. Psychotic symptoms were evaluated using the Consortium to Establish a Registry for Alzheimer's Disease Behavioral Rating Scale every 6 months. One-, 3- and 5-year cumulative incidences of psychosis were calculated.
Results: The 1-year psychosis incidence was 10% (95% CI, 8%-12%), and this annual rate remained remarkably consistent at 3 and 5 years. Psychosis incidence was related to cognitive status at all time points. However, the incidence rate reached a plateau during the disease course. Cumulative psychosis incidence at 5 years was 61% (95% CI, 52%-69%) in individuals with moderate to severe Alzheimer's disease, not statistically significantly different from the cumulative incidence at 3 years in this group, which was 48% (95% CI, 40%-55%) or from the 5-year incidence in individuals who entered the study with mild Alzheimer's disease, which was 48% (95% CI, 41%-56%).
Conclusions: Psychosis in Alzheimer's disease has been associated with a number of adverse clinical outcomes. We provide estimates of the risk of psychosis onset within clinically defined subgroups of individuals, a tool clinicians can use in treatment planning. Anticipating which subjects are at high risk for psychosis and the poor outcomes associated with it can help with family education and support decisions to implement nonpharmacologic strategies that may reduce or prevent symptoms.
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http://dx.doi.org/10.4088/JCP.15m10617 | DOI Listing |
JCI Insight
January 2025
Dianne Hoppes Nunnally Laboratory Research Division, Joslin Diabetes Center, Boston, United States of America.
Background: We aimed to characterize factors associated with the under-studied complication of cognitive decline in aging people with long-duration type 1 diabetes (T1D).
Methods: Joslin "Medalists" (n = 222; T1D ≥ 50 years) underwent cognitive testing. Medalists (n = 52) and age-matched non-diabetic controls (n = 20) underwent neuro- and retinal imaging.
Inflammopharmacology
January 2025
Neuropharmacology Division, Department of Pharmacology, ISF College of Pharmacy, Moga, 142001, Punjab, India.
Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by the accumulation of amyloid-β plaques and tau tangles, leading to cognitive decline and dementia. Insulin-like Growth Factor-1 (IGF-1) is similar in structure to insulin and is crucial for cell growth, differentiation, and regulating oxidative stress, synaptic plasticity, and mitochondrial function. IGF-1 exerts its physiological effects by binding to the IGF-1 receptor (IGF-1R) and activating PI3K/Akt pathway.
View Article and Find Full Text PDFACS Chem Neurosci
January 2025
Department of Chemistry, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea.
The deposition of amyloid-β (Aβ) aggregates and metal ions within senile plaques is a hallmark of Alzheimer's disease (AD). Among the modifications observed in Aβ peptides, -terminal truncation at Phe4, yielding Aβ, is highly prevalent in AD-affected brains and significantly alters Aβ's metal-binding and aggregation profiles. Despite the abundance of Zn(II) in senile plaques, its impact on the aggregation and toxicity of Aβ remains unexplored.
View Article and Find Full Text PDFACS Appl Mater Interfaces
January 2025
Key Laboratory of the Environmental Medicine and Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing 210009, China.
The single-luminophore-based ratiometric electrochemiluminescence (ECL) sensor coupling bidirectional regulator has become a research hotspot in the detection field because of its simplicity and accuracy. However, the limited bidirectional regulator hinders its further development. In this study, by leveraging the robust predictive capabilities of machine learning, we prepared an Fe-based metal-organic framework (FeMOF) as a bidirectional regulator for modulating the dual-emission ECL signals of a single luminophore for the first time.
View Article and Find Full Text PDFCent Nerv Syst Agents Med Chem
January 2025
International Center of Neuroscience and Genomic Medicine, EuroEspes Biomedical Research Center, Corunna, Spain.
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