Background: The influence of duration of type 2 diabetes mellitus (T2DM) on the likelihood of developing new-onset dementia in post-stroke population is not well understood. Therefore, we aimed to clarify the relationship between the duration of T2DM and the risk of developing dementia in the post-stroke population.
Methods: Leveraging the Korean National Health Insurance Database, this study included 118,790 individuals with a history of stroke but no previous dementia diagnosis. We classified diabetes status into five categories: normoglycemia, impaired fasting glucose (IFG), newly diagnosed T2DM, and established T2DM with durations of less than 5 years and 5 years or more. The primary endpoint was the incidence of all-cause dementia.
Results: Among 118,790 participants (average age 64.26 ± 9.95 years, 48% male), 16.7% developed dementia during an average follow-up of 7.3 ± 2.3 years. Participants with a history of T2DM for less than five years at cohort entry had a 26.7% higher risk of developing all-cause dementia compared to those with normoglycemia. Those with T2DM for five years or longer had a 46.7% increased risk, with an adjusted hazard ratio (aHR) of 1.466 (95% confidence interval [CI], 1.408-1.527). Specifically, the risk of developing Alzheimer's disease (AD) and vascular dementia (VaD) rose by 43.4% and 51.4%, respectively, for individuals with T2DM lasting more than five years (aHR 1.434, 95% CI 1.366-1.505; aHR 1.514, 95% CI 1.365-1.679, respectively).
Conclusions: Our findings demonstrated a significant association between an extended duration of T2DM and an increased risk of developing all-cause dementia, including AD and VaD in post-stroke population. These results emphasize proactive dementia prevention approaches in stroke survivors, particularly those with longstanding T2DM.
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http://dx.doi.org/10.1186/s13195-025-01708-8 | DOI Listing |
J Med Internet Res
March 2025
Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China.
Background: Hypertension is a major global health issue and a significant modifiable risk factor for cardiovascular diseases, contributing to a substantial socioeconomic burden due to its high prevalence. In China, particularly among populations living near desert regions, hypertension is even more prevalent due to unique environmental and lifestyle conditions, exacerbating the disease burden in these areas, underscoring the urgent need for effective early detection and intervention strategies.
Objective: This study aims to develop, calibrate, and prospectively validate a 2-year hypertension risk prediction model by using large-scale health examination data collected from populations residing in 4 regions surrounding the Taklamakan Desert of northwest China.
Dermatol Reports
March 2025
Oncology Center, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong Province.
Skin cancer (SC) is a significant public health issue, with increasing incidence rates globally. Although environmental factors such as ultraviolet (UV) exposure are recognized risk factors, the impact of metabolites on SC development has not been thoroughly examined. This study seeks to explore the causal association between metabolites and SC risks using a Mendelian randomization (MR) approach.
View Article and Find Full Text PDFJAMA Dermatol
March 2025
Department of Surgery, Arthur J.E. Child Comprehensive Cancer Centre, University of Calgary, Calgary, Alberta, Canada.
Importance: There is a need to identify the best performing risk prediction model for sentinel lymph node biopsy (SLNB) positivity in melanoma.
Objective: To comprehensively review the characteristics and discriminative performance of existing risk prediction models for SLNB positivity in melanoma.
Data Sources: Embase and MEDLINE were searched from inception to May 1, 2024, for English language articles.
JAMA Netw Open
March 2025
Department of Epidemiology, University of North Carolina at Chapel Hill.
Importance: Numerous efforts have been made to include diverse populations in genetic studies, but American Indian populations are still severely underrepresented. Polygenic scores derived from genetic data have been proposed in clinical care, but how polygenic scores perform in American Indian individuals and whether they can predict disease risk in this population remains unknown.
Objective: To study the performance of polygenic scores for cardiometabolic risk factors of lipid traits and C-reactive protein in American Indian adults and to determine whether such scores are helpful in clinical prediction for cardiometabolic diseases.
Stat Med
March 2025
Vaccine and Infectious Disease and Public Health Sciences Divisions, Fred Hutchinson Cancer Center, Seattle, Washington, USA.
Based on data from a randomized, controlled vaccine efficacy trial, this article develops statistical methods for assessing vaccine efficacy (VE) to prevent COVID-19 infections by a discrete set of genetic strains of SARS-CoV-2. Strain-specific VE adjusting for possibly time-varying covariates is estimated using augmented inverse probability weighting to address missing viral genotypes under a competing risks model that allows separate baseline hazards for different risk groups. Hypothesis tests are developed to assess whether the vaccine provides at least a specified level of VE against some viral genotypes and whether VE varies across genotypes.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!