AI Article Synopsis
Article Abstract
Background: Later-life depression appears to be different to depression in younger adults. The underlying pathology may also differ. Depression is linked to dementia but whether it is a risk factor or an early sign of a developing dementia remains unclear. Neuroinflammation is increasingly recognised in both depression and Alzheimer's Disease.
Aims: To investigate the link between depression, inflammation and dementia. We hypothesised that recurrent depression has adverse effects on performance in cognitive tests in middle to older age and that this effect is modified by anti-inflammatory medication.
Methods: We identified UK based cohort studies which included individuals aged >50, had medical information, results from detailed cognitive testing and had used reliable measures to assess depression. Individuals with recurrent depression had ≥ 2 episodes of depression. Controls had no history of depression. The presence/absence of inflammatory illness was assessed using a standardised list of inflammatory conditions. Individuals with dementia, chronic neurological and psychotic conditions were excluded. Logistic and linear regression were used to examine the effect of depression on cognitive test performance and the mediating effect of chronic inflammation.
Results: Unexpectedly in both studies there was evidence that those with recurrent depression performed better in some cognitive tasks (e.g Mill Hill vocabulary) but worse in others (e.g. reaction time). In UK Biobank there was no evidence that anti-inflammatories moderated this effect.
Limitations: Cross-sectional assessment of cognition.
Conclusions: Although previous recurrent depression has small effects on cognitive test performance this does not appear to be mediated by chronic inflammatory disease.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.jad.2022.03.043 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Predicting higher risk factors for COVID-19 short-term reinfection in patients with rheumatic diseases: a modeling study based on XGBoost algorithm.
J Transl Med
December 2024
Department of Rheumatology and Immunology, Third Affiliated Hospital of Sun Yat-Sen University, 600 Tianhe Road, Tianhe District, Guangzhou, China.
Background: Corona virus disease 2019 (COVID-19) reinfection, particularly short-term reinfection, poses challenges to the management of rheumatic diseases and may increase adverse clinical outcomes. This study aims to develop machine learning models to predict and identify the risk of short-term COVID-19 reinfection in patients with rheumatic diseases.
Methods: We developed four prediction models using explainable machine learning to assess the risk of short-term COVID-19 reinfection in 543 patients with rheumatic diseases.
Nonspecific cervical spine pain/neck pain/in medical personnel of north-eastern Poland-A cross-sectional study.
Front Med (Lausanne)
December 2024
Department of Integrated Medical Care, Faculty of Health Sciences, Medical University of Bialystok, Bialystok, Podlaskie Voivodeship, Poland.
Unlabelled: Both mechanical and psychological overload are inherent to the work of nurses and paramedics, resulting spondylogenic pain.
Aim Of The Study: To identify potential risk factors influencing the prevalence of non-specific cervical spine pain in professionally active nurses and paramedics.
Material And Methods: 324 nurses (53.
Momentary Depression Severity Prediction in Patients With Acute Depression Who Undergo Sleep Deprivation Therapy: Speech-Based Machine Learning Approach.
JMIR Ment Health
December 2024
Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim / Heidelberg University, Mannheim, Germany.
Background: Mobile devices for remote monitoring are inevitable tools to support treatment and patient care, especially in recurrent diseases such as major depressive disorder. The aim of this study was to learn if machine learning (ML) models based on longitudinal speech data are helpful in predicting momentary depression severity. Data analyses were based on a dataset including 30 inpatients during an acute depressive episode receiving sleep deprivation therapy in stationary care, an intervention inducing a rapid change in depressive symptoms in a relatively short period of time.
View Article and Find Full Text PDFComprehensive analysis of risk factors associated with submucosal invasion in patients with early-stage gastric cancer.
World J Gastroenterol
December 2024
Department of Gastroenterology, Henan Provincial People's Hospital, Zhengzhou University People's Hospital, Zhengzhou 450000, Henan Province, China.
Background: Submucosal invasion in early-stage gastric cancer (GC) is a critical determinant of prognosis and treatment strategy, significantly influencing the risk of lymph node metastasis and recurrence. Identifying risk factors associated with submucosal invasion is essential for optimizing patient management and improving outcomes.
Aim: To comprehensively analyze clinical, imaging, and endoscopic characteristics to identify predictors of submucosal invasion in patients with early-stage differentiated GC.
Complications of Left Ventricular Assist Devices: A Case Study of Recurrent Bacteremia and Implications for Infection Management.
Cureus
November 2024
Internal Medicine, Northeast Georgia Medical Center Gainesville, Gainesville, USA.
Heart failure (HF) is a complex clinical condition with symptoms that result from ineffective ejection of blood due to functional or structural impairment of the heart. The most common causes of HF include ischemic heart disease, myocardial infarction (MI), hypertension, and valvular heart disease (VHD). As HF progresses to advanced stages, interventions, like left ventricular assist devices (LVADs), become essential, especially for patients ineligible for heart transplantation.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!