Objectives: To examine the longitudinal association between physical performance and risk of dementia in individuals aged 90 and older without dementia.
Design: Population-based longitudinal study.
Settings: The 90+ Study, Laguna Woods, California.
Participants: Men n = 176 and women n = 402 without dementia from The 90+ Study (n = 578, mean age 93.3). At baseline, 54% of participants were cognitively normal, and 46% had cognitive impairment, no dementia.
Measurements: Physical performance measures (4-m walk, 5 chair stands, handgrip, standing balance) were scored from 0 (unable to perform) to 4 (best performance). The outcome was dementia, diagnosed according to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, criteria. Hazard ratios (HRs) for dementia in relation to baseline physical performance were estimated using Cox regression after adjustment for potential confounders. HRs and P-values for the overall Wald chi-square are reported to show the magnitude of each physical performance measure and the strength of the association between each measure and incident dementia.
Results: Poor physical performance in most measures was associated with greater risk of incident dementia over a mean follow-up of 2.6 years (range 0.6-9.0 years). After controlling for potential confounders, standing balance had the strongest association with incident dementia (HRs = 1.9-2.5, overall P = .02), followed by 4-m walk (HRs = 1.1-1.8, overall P = .04) and handgrip (HRs = 1.0-2.0, overall P = .03). The association with five chair stands was not significant. In a subanalysis limited to cognitively normal participants, HRs were attenuated, but most remained in the same direction.
Conclusion: Poor physical performance is associated with risk of developing dementia over an average 2.6-year follow-up in the oldest-old, indicating that poor physical performance may be an early sign of late-age dementia.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1111/jgs.14224 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Manipulating the interfacial integration mode of a bio-templated porous ZSM-5 platform with an Au/CuZnO catalyst for enhanced efficiency and recycling stability in glycerol conversion to 1,3-dihydroxyacetone.
Nanoscale
January 2025
School of Chemistry and Chemical Engineering, North Minzu University, Yinchuan 750021, PR China.
Despite the potential to significantly enhance the economic viability of biomass-based platforms through the selective conversion of glycerol to 1,3-dihydroxyacetone (DHA), a formidable challenge persists in simultaneously achieving high catalytic activity and stability along this reaction pathway. Herein, we have devised a strategic approach to manipulate the interfacial integration within composite catalysts to address the performance trade-off. Through the modulation of the composite process involving a bio-templated porous ZSM-5 zeolite platform (bZ) and an Au/CuZnO catalyst, three distinct interfacial bonding modes were achieved: physical milling, encapsulation by zeolite, and growth on zeolite.
View Article and Find Full Text PDFLarge-Scale Validation of the Feasibility of GPT-4 as a Proofreading Tool for Head CT Reports.
Radiology
January 2025
From the Departments of Biomedical Systems Informatics (S.K., Jaewoong Kim, C.H., D.Y.) and Neurology (Joonho Kim, J.Y.), Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea; Department of Radiology, Central Draft Physical Examination Office of Military Manpower Administration, Daegu, Republic of Korea (D.K.); Department of Radiology, Research Institute of Radiological Science and Center for Clinical Imaging Data Science (H.J.S. Y.K., S.J.), and Center for Digital Health (H.J.S., D.Y.), Yongin Severance Hospital, Yonsei University College of Medicine, Yongin, Republic of Korea; Department of Radiology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea (S.H.L.); Departments of Radiology (M.H.) and Neurology (S.J.L.), Ajou University Hospital, Ajou University School of Medicine, Suwon, Republic of Korea; and Institute for Innovation in Digital Healthcare, Severance Hospital, Seoul, Republic of Korea (D.Y.).
Background The increasing workload of radiologists can lead to burnout and errors in radiology reports. Large language models, such as OpenAI's GPT-4, hold promise as error revision tools for radiology. Purpose To test the feasibility of GPT-4 use by determining its error detection, reasoning, and revision performance on head CT reports with varying error types and to validate its clinical utility by comparison with human readers.
View Article and Find Full Text PDFAn intelligent decision-making system for embryo transfer in reproductive technology: a machine learning-based approach.
Syst Biol Reprod Med
December 2025
Department of Mathematics and Computer Science, Laboratory of Analysis, Modeling and Simulation, Faculty of Sciences Ben M'sik, Hassan II University of Casablanca, Casablanca, Morocco.
Infertility has emerged as a significant public health concern, with assisted reproductive technology (ART) is a last-resort treatment option. However, ART's efficacy is limited by significant financial cost and physical discomfort. The aim of this study is to build Machine learning (ML) decision-support models to predict the optimal range of embryo numbers to transfer, using data from infertile couples identified through literature reviews.
View Article and Find Full Text PDFInvestigation of the cushioning mechanism of a novel dental implant system with composite hydrogel.
J Dent Sci
January 2025
Graduate Institute of Clinical Dentistry, School of Dentistry, National Taiwan University and National University Hospital, Taipei, Taiwan.
Background/purpose: Dental implants can restore both function and aesthetics in edentulous areas. However, the absence of cushioning mechanical behavior in implants may limit their clinical performance and reduce the long-term survival rates. This study aimed to establish an implant cushion mechanism that mimicked the natural periodontal ligament, utilizing the properties of composite hydrogels.
View Article and Find Full Text PDFEvaluating the image recognition capabilities of GPT-4V and Gemini Pro in the Japanese national dental examination.
J Dent Sci
January 2025
Division of Physiology, Department of Health Promotion, Kyushu Dental University, Kitakyushu, Japan.
Background/purpose: OpenAI's GPT-4V and Google's Gemini Pro, being Large Language Models (LLMs) equipped with image recognition capabilities, have the potential to be utilized in future medical diagnosis and treatment, ands serve as valuable educational support tools for students. This study compared and evaluated the image recognition capabilities of GPT-4V and Gemini Pro using questions from the Japanese National Dental Examination (JNDE) to investigate their potential as educational support tools.
Materials And Methods: We analyzed 160 questions from the 116th JNDE, administered in March 2023, using ChatGPT-4V, and Gemini Pro, which have image recognition functions.
Want 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!