ORIGINAL RESEARCH article
Front. Aging
Sec. Healthy Longevity
This article is part of the Research TopicCelebrating Women's Contributions to Healthy Longevity ResearchView all articles
Data-Driven Frailty and Reserve Phenotypes in Older Outpatients: A Cluster Analysis of Complementary Geriatric Assessment
Provisionally accepted
Maristella Belfiori1*
Francesco Salis1,2
Benedetta Puxeddu1
Martina Mulas1
Monica Puligheddu1Antonella Mandas1- 1Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
- 2Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy
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Background: The progressive aging of the population represents a critical public health challenge.Within this context, the management of frailty has emerged as a central priority in geriatric care, with Comprehensive Geriatric Assessment (CGA) widely recognized as the gold-standard tool for its evaluation. This study aimed to stratify a large cohort of older adults using a multidimensional approach based on CGA, employing Principal Component Analysis (PCA) and Cluster Analysis to identify distinct phenotypic profiles. Materials and Methods: A cross-sectional study was conducted on 1055 outpatients aged ≥65 years, assessed at the Geriatric Outpatient Service of the University of Cagliari between 2020 and 2024. All participants underwent a CGA. PCA was performed on selected CGA variables, and the resulting components were used for a hierarchical cluster analysis. Post-hoc comparisons between clusters were conducted using ANOVA, Chi-squared or Fisher tests, as appropriate.Results:PCA identified four principal components explaining 73.5% of total variance. The first component represented a Frailty Axis, while the second reflected Reserve Capacity. Cluster analysis based on these two axes revealed four distinct phenotypes: (I) Vulnerable Low-Complexity (younger patients with low comorbidity but significant cognitive, nutritional, and functional impairments), (II) Resilient High-Reserve (low comorbidity with preserved cognitive, functional, and nutritional status and high educational attainment), (III) Resilient Frailty (high comorbidity, functional and nutritional deficits but preserved cognitive reserve) and (IV) Globally Frail (older patients with high comorbidity with multidomain impairments).Conclusion: These findings demonstrate the ability of CGA, combined with PCA-informed clustering, to identify clinically meaningful frailty and resilience patterns in older adults.The study highlights the role of educational attainment as a key factor contributing to clinical reserve; conversely, it showed that demographic characteristics, laboratory markers, and comorbidities align with frailty.
Keywords: Aging, Cluster analysis, Comprehensive Geriatric Assessment, Frailty, Reserve capacity
Received: 02 Aug 2025; Accepted: 17 Dec 2025.
Copyright: © 2025 Belfiori, Salis, Puxeddu, Mulas, Puligheddu and Mandas. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Maristella Belfiori
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