This study aims to systematically describe the demographic profile, treatment characteristics, disease spectrum, illness severity, comorbidity burden, and clinical outcomes of emergency department (ED) in super-elderly patients and to identify independent factors influencing ED length of stay (LOS). A single-center retrospective cross-sectional study was conducted, enrolling 1313 patients aged u2265 80 years who presented to the ED of a tertiary hospital in Guangzhou between January 2023 and December 2024. Data on demographics, triage levels, diagnoses, comorbidities, outcomes, and LOS were extracted from electronic medical records. Multiple linear regression analysis was used to identify independent predictors of ED LOS. The mean age of patients was (86.0 u00B1 4.5) years, with a male-to-female ratio of 1:1.07. The majority (78.8%) were triaged as Level II (acute and severe). Common diagnoses included dyspnea (12.8%), fever (11.7%), and chest pain (5.0%). The mean number of comorbidities was 3.8 u00B1 1.96, and the mean Charlson Comorbidity Index (CCI) score was 5.6 u00B1 1.63. Patients aged u2265 90 years had a significantly higher rate of palliative care utilization than those aged 80u201389 years (18.5% vs. 7.4%; P u0026lt; 0.01). Multiple linear regression identified month of presentation (u03B2 = u201314.087, P = 0.01), season of presentation (u03B2 = u201339.800, P = 0.02), and number of comorbidities (u03B2 = 87.876, P u0026lt; 0.001) as independent predictors of ED LOS. The model explained 21.4% of LOS variability (adjusted R2 = 0.214). Super-elderly ED patients commonly present with nonspecific symptoms and substantial multimorbidity. Disease patterns and outcomes vary significantly by age and gender, while the longevity group (age u2265 90 years) has a significantly higher palliative care utilization rate. ED LOS is substantially influenced by time factors and the burden of comorbidities. To enhance care efficiency, it is recommended that dynamic resource allocation strategies be adopted and comprehensive geriatric assessments be implemented.
With the accelerating global trend of population aging, health management and science-based education for aging populations have become core public health priorities, and the synergistic integration of medical technology and education provides an innovative pathway to address this challenge. This review finds that theories including Social Cognitive Theory and Self-efficacy Theory offer a robust theoretical foundation for health education among aging populations, and that the application of digital toolsu2014such as smartphone applications and wearable devicesu2014significantly enhances educational effectiveness. However, current practices still face challenges including the digital divide and ethical concerns. Future efforts should promote personalized and intelligent development in science-based education for aging populations through interdisciplinary collaboration, technological optimization, and policy support, ultimately achieving healthy aging objectives.
Background The function of key regulatory genes in shaping the immune microenvironment of Alzheimer's disease (AD) remains elusive. Thus, this investigation aimed to detect key targets and potential mechanisms underlying microglia dysfunction in AD based on GWAS and single-cell transcriptomics. Methods The present investigation utilized single-cell RNA sequencing (scRNA-seq) with microarray data (GSE243292 and GSE53697) to uncover cellular subtypes and critical regulatory genes linked to AD. Differential gene expression analysis, Mendelian randomization (MR), and immune cell infiltration profiling were performed to identify potential causal genes and their biological pathways. Additionally, miRNA and transcription factor network analyses were conducted to explore gene regulation. Lastly, functional pathway enrichment analysis and correlation studies with AD-related genes were conducted to assess biological significance. This study was conducted without using artificial intelligence (AI) tools in accordance with the TITAN Guidelines 2025. Results The findings of scRNA-seq analysis yielded 8 distinct cell subtypes, with microglia being significantly enriched in AD samples. Marker genes of microglia were correlated with pathways like glutamate receptor signaling and actin filament-based processes. Moreover, MR analysis identified EPB41L2, INPP5D, and ZFHX3 as key genes influencing AD risk, which were significantly associated with immune cells like T and B cells. Meanwhile, functional pathway analysis revealed enrichment in the NF-kappa B, TNF signaling, and PI3K-Akt pathways. Finally, miRNA and transcription factor analyses uncovered shared regulatory mechanisms, while correlations with genes such as PSEN1 and NPC1 validated their association with the pathogenesis of AD. Conclusion This investigation offers a new understanding of the immune landscape of AD by identifying key genetic regulators and their associated immune pathways.
