Gender Differences in Demographic and Pharmacological Factors in Patients Diagnosed with Late-Onset of Alzheimer’s Disease

Multiple Adverse Reactions Associated With the Use of Second-Generation Antipsychotics in People With Alzheimer's Disease: A Pharmacovigilance Analysis Based on the FDA Adverse Event Reporting System

BACKGROUND

Alzheimer's disease (AD) is a neurodegenerative condition leading to memory loss, cognitive impairment, and neuropsychiatric symptoms. Second-generation antipsychotics (SGAs) are commonly used to manage these neuropsychiatric symptoms, but their safety profile in patients with AD requires further investigation.

OBJECTIVE

The objective was to evaluate the safety of SGAs in patients with AD by analyzing adverse drug reactions (ADRs) using the US Food and Drug Administration Adverse Event Reporting System (FAERS) database.

METHODS

This study conducted a comprehensive analysis of FAERS data from 2014 to 2023, focusing on ADRs in patients with AD treated with SGAs such as risperidone, quetiapine, olanzapine, clozapine, and aripiprazole. Descriptive, disproportionality, time, and dose analysis were performed using the Bayesian confidence propagation neural network, Weibull, and physiologically based pharmacokinetic model.

RESULTS

Out of 1289 patients with AD treated with SGAs, the most common ADRs involved the nervous system, gastrointestinal system, and cardiac disorders. Disproportionality analysis identified significant positive signals in cardiac, renal, and vascular systems. Quetiapine, risperidone, and olanzapine showed more positive signals compared with clozapine and aripiprazole. Time analysis indicated that cardiovascular ADRs occurred randomly, whereas renal ADRs increased with prolonged use. Dose analysis suggested that small doses of SGAs did not elevate the risk of multiple cardiac, renal, or vascular ADRs.

CONCLUSION AND RELEVANCE

The study underscores the importance of monitoring for ADRs, particularly in the cardiac and renal systems, when using SGAs in patients with AD. Future research incorporating more comprehensive clinical data is warranted to support safe and rational drug utilization.

Risk factors of male and female Alzheimer's disease patients with neuropsychiatric symptoms

BACKGROUND

This study investigates risk factors in the population of Alzheimer disease (AD) patients with NPS (ADNPS).

METHOD

Baseline risk factors associated with male and female ADNPS were examined using data from a regional AD care center. Univariate analysis was used to determine factors in male and female patients, while logistic regression models were developed to generate odds ratios (OR) to predict risk factors that are associated with male or female ADNPS.

RESULTS

In the adjusted analysis, dyslipidemia (OR = 0.630, 95 % CI, 0.431-0.992, P = 0.017), thyroid dysfunction (OR = 0.549, 95 % CI, 0.377-0.798, P = 0.002), and cerebral infarction (OR = 0.684, 95 % CI, 0.472-0.991, P = 0.0085) were associated with male ADNPS patients, whereas chronic heart failure (OR = 1.408, 95 % CI, 0.953-2.079, P = 0.0085) was associated with female ADNPS patients.

CONCLUSIONS

Our results reveal that female ADNPS patients were associated with heart failure, whereas male patients were associated with dyslipidemia and cerebral infarction.

Normalized group activations based feature extraction technique using heterogeneous data for Alzheimer's disease classification

Several deep learning networks are developed to identify the complex atrophic patterns of Alzheimer's disease (AD). Among various activation functions used in deep neural networks, the rectifier linear unit is the most used one. Even though these functions are analyzed individually, group activations and their interpretations are still not explored for neuroimaging analysis. In this study, a unique feature extraction technique based on normalized group activations that can be applied to both structural MRI and resting-state-fMRI (rs-fMRI) is proposed. This method is split into two phases: multi-trait condensed feature extraction networks and regional association networks. The initial phase involves extracting features from various brain regions using different multi-layered convolutional networks. Then, multiple regional association networks with normalized group activations for all the regional pairs are trained and the output of these networks is given as input to a classifier. To provide an unbiased estimate, an automated diagnosis system equipped with the proposed feature extraction is designed and analyzed on multi-cohort Alzheimer's Disease Neuroimaging Initiative (ADNI) data to predict multi-stages of AD. This system is also trained/tested on heterogeneous features such as non-transformed features, curvelets, wavelets, shearlets, textures, and scattering operators. Baseline scans of 185 rs-fMRIs and 1442 MRIs from ADNI-1, ADNI-2, and ADNI-GO datasets are used for validation. For MCI (mild cognitive impairment) classifications, there is an increase of 1-4% in performance. The outcome demonstrates the good discriminatory behaviour of the proposed features and its efficiency on rs-fMRI time-series and MRI data to classify multiple stages of AD.

Comorbidities in patients with vascular dementia and Alzheimer's disease with Neuropsychiatric symptoms

INTRODUCTION

This study aimed to examine baseline risk factors in Alzheimer's Disease (AD) and Vascular dementia (VaD) patients with neuropsychiatry symptoms (NPS), and determine whether specific risk factors differ by subtypes of dementia for AD and VaD patients with NPS.

METHODS

A retrospective data analysis was conducted to evaluate similarities and differences in the risk factors for AD and VaD with NPS. The analysis included 2949 patients with VaD and 6341 patients with clinical confirmation of AD and VaD with or without NPS collected between February 2016 and August 2021. The multivariate logistic regression analysis was used to determine the risk factors associated with AD and VaD with NPS, by predicting the increasing odds (odds ratios (ORs) of an association of a specific baseline risk factor with AD or VaD with NPS. The validity of the regression models was tested using a Hosmer-Lemeshow test, while the Receiver Operating Curve (ROC) was used to test the sensitivity of the models.

RESULTS

In the adjusted analysis TSH (OR = 1.781, 95 % CI, p = 0.0025) and CHF (OR = 1.620, 95 %, p = 0.016) were associated with VaD with NPS, while a history of emergency department(ED) admission (OR = 0.277, 95 % CI, p = 0.003) likely to be associated with VaD patients without NPS. For AD patients, a history of CVA (OR = 1.395, 95 % CI, p = 0.032) and cancer (OR = 1.485, 95 % CI, p = 0.013) were associated with AD patients with NPS.

DISCUSSION

The findings of this study indicate that an abnormal thyroid gland and CHF were linked to VaD patients with behavioral disturbances, while CVA and cancer were linked to AD patients with behavioral disturbances. These findings suggest the need to develop management strategies for the care of patients with AD and VaD with NPS.

Differences in pharmacologic and demographic factors in male and female patients with vascular dementia, Alzheimer's disease, and mixed vascular dementia

Background

Increasing evidence suggests that demographic and pharmacologic factors may play a significant role in the epidemiology of dementia. Sex differences in prevalence also depend on dementia subtypes, such as Alzheimer's dementia (AD), vascular dementia (VaD), and mixed vascular-Alzheimer's dementia (MVAD). Therefore, studies are needed to investigate sex-specific differences, and identify potential therapeutic targets for both sexes.

Methods

Data was collected from the Prisma Health-Upstate Alzheimer's registry from 2016 to 2021 for 6,039 VaD patients, 9,290 AD patients, and 412 MVAD patients. A logistic regression was used to determine demographic and pharmacological factors associated with gender differences in patients with VaD, AD, and MVAD.

Results

In patients with VaD, African Americans (OR = 1.454, 95% CI, 1.257-1.682, p < 0.001) with increasing age (OR = 1.023, 95% CI, 1.017-1.029, p < 0.001), treated with aripiprazole (OR = 4.395, 95% CI, 2.880-6.707, p < 0.001), were associated with females, whereas patients treated with galantamine (OR = 0.228, 95% CI, 0.116-0.449, p < 0.001), memantine (OR = 0.662, 95% CI, 0.590-0.744, p < 0.001), with a history of tobacco (OR = 0.312, 95% CI, 0.278-0.349, p < 0.001), and ETOH (OR = 0.520, 95% CI, 0.452-0.598, p < 0.001) were associated with males. Among AD patients, African Americans (OR = 1.747, 95% CI, 1.486-2.053, p < 0.001), and Hispanics (OR = 3.668, 95% CI, 1.198-11.231, P = 0.023) treated with buspirone (OR = 1.541, 95% CI, 1.265-1.878, p < 0.001), and citalopram (OR = 1.790, 95% CI, 1.527-2.099, p < 0.001), were associated with females, whereas patients treated with memantine (OR = 0.882, 95% CI, 0.799-0.974, p = 0.013), and with a history of tobacco (OR = 0.247, 95% CI, 0.224-0.273, p < 0.001), and ETOH (OR = 0.627, 95% CI, 0.547-0.718, p < 0.001) were associated with male AD patients. In patients with MVAD, rivastigmine (OR = 3.293, 95% CI, 1.131-9.585, p = 0.029), memantine (OR = 2.816, 95% CI, 1.534-5.168, p < 0.001), and risperidone (OR = 10.515, 95% CI, 3.409-32.437, p < 0.001), were associated with females while patients with an increased length of stay (OR = 0.910, 95% CI, 0.828-1.000, p = 0.049), with a history of tobacco (OR = 0.148, 95% CI, 0.086-0.254, p < 0.001) and ETOH use (OR = 0.229, 95% CI, 0.110-0.477, p < 0.001) were more likely to be associated with males.

Conclusions

Our study revealed gender differences and similarities in the demographic and pharmacological factors of VaD, AD, and MVAD. Prospective studies are needed to determine the role of demographic and pharmacological factors in reducing sex-based disparities among VaD, AD, and MVAD patients.

The role of ethnicity, biological sex, and psychotropic agents in early and late onset Alzheimer's disease

Objective

This study investigates differences in pharmacological and demographic factors among male and female patients with Late-onset Alzheimer's disease (LOAD) and Early-onset Alzheimer's disease (EOAD).

Method

Data are from 10,126 AD patients, 9,290 were diagnosed with LOAD, while 836 were diagnosed with EOAD. Data were collected from the Prisma Health Upstate Alzheimer's patients' registry between 2016 and 2021. The logistic regression analysis was used to assess the association between pharmacological and demographic factors in males and females with LOAD and EOAD.

Results

In the adjusted analysis for males, patients that were administered memantine [odd ratio (OR) = 1.588, 95% CI, 1.175-2.145, p = 0.003], and buspirone [OR = 1.971, 95% CI, 1.221-3.183, p = 0.006] were more likely to be associated with EOAD, while increasing age [OR = 0.816, 95% CI, 0.799-0.834, p < 0.001] was associated with LOAD. Female patients with a history of alcohol (ETOH) use were more likely to be associated with EOAD while increasing age [OR = 0.845, 95% CI, 0.834-0.857, p < 0.001], treatment with memantine [OR = 0.774, 95% CI, 0.627-0.956, p = 0.017], African Americans [OR = 0.621, 95% CI, 0.462-0.835, p = 0.002] and tobacco use [OR = 0.529, 95% CI, 0.424-0.660, p < 0.001] were associated with LOAD.

Conclusion

Our findings identified specific demographic and pharmacological factors associated with males and females with LOAD and EOAD. These findings suggest the need to develop strategies to eliminate disparity in the care of LOAD or EOAD patients.