Donmez Guler D, Kemik Z, Ates Bulut E. Frailty models and social frailty. World J Meta-Anal 2025; 13(2): 107388 [DOI: 10.13105/wjma.v13.i2.107388]
Corresponding Author of This Article
Esra Ates Bulut, MD, Associate Professor, Department of Geriatric Medicine, University of Health Sciences, Adana City Research and Training Hospital, No. 1 Yüreğir, Adana 01130, Türkiye. esraates@yahoo.com
Research Domain of This Article
Geriatrics & Gerontology
Article-Type of This Article
Opinion Review
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Dilara Donmez Guler, Zeynep Kemik, Esra Ates Bulut, Department of Geriatric Medicine, University of Health Sciences, Adana City Research and Training Hospital, Adana 01130, Türkiye
Author contributions: Donmez Guler D and Kemik Z contributed to the review of literature, writing the draft; Ates Bulut E contributed to the design of the manuscript, critical revision; and all authors thoroughly reviewed and endorsed the final manuscript.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Esra Ates Bulut, MD, Associate Professor, Department of Geriatric Medicine, University of Health Sciences, Adana City Research and Training Hospital, No. 1 Yüreğir, Adana 01130, Türkiye. esraates@yahoo.com
Received: March 24, 2025 Revised: April 18, 2025 Accepted: June 9, 2025 Published online: June 18, 2025 Processing time: 86 Days and 5.9 Hours
Abstract
Frailty is a geriatric syndrome characterized by a reduced ability to maintain homeostasis due to age-related declines in physiological reserves. It increases the risk of adverse health outcomes such as falls, hospitalization, disability, and mortality, especially in older adults. Key risk factors for frailty include cancer, chronic obstructive pulmonary disease, and cerebrovascular disease. Several models of frailty exist, including the physical frailty phenotype, the deficit accumulation model, and mixed physical-psychosocial models. Numerous tools are available for assessment. Cognitive dysfunction is closely related to frailty, sharing underlying mechanisms such as oxidative stress, inflammation, and vascular pathologies. Additionally, social frailty, which can be exacerbated by isolation and limited social support, further complicates the challenges faced by frail individuals. It is recommended that frailty screening, particularly through gait speed assessment, can be conducted in primary healthcare settings. Despite existing guidelines, there is still no consensus on the definition, screening, and diagnosis of frailty. This emphasizes the necessity for additional research to conduct a conceptual diagnosis and screen the older population. Artificial intelligence approaches show promise in identifying frail patients and managing their care.
Core Tip: Frailty is a geriatric syndrome defined by a diminished capacity to maintain homeostasis with aging. There are several models of frailty, including the physical frailty phenotype, cognitive frailty, social frailty, and mixed physical-psychosocial models. Although there have been suggestions to screen older adults for frailty, there is still no consensus on its definition or diagnosis. Artificial intelligence approaches show promise in identifying frail patients and managing their care.
