Factors associated with frailty in primary care: a prospective cohort study. Issue 1 (December 2016) - Diez-Ruiz, Ana; Bueno-Errandonea, Antonio; Nuñez-Barrio, Jazmina; Sanchez-Martín, Inmaculada; Vrotsou, Kalliopi; Vergara, Itziar
Abstract Background Frailty can be defined as a progressive loss of reserve and adaptive capacity associated with an overall deterioration in health that can result in disability, loss of independence, hospitalisation, extensive use of healthcare resources, admission to long-term care and death. Nevertheless, despite widespread use of the term, there is no agreement on the definition of frailty or an instrument to identify it in a straightforward way. The purpose of the current study was to explore which factors are associated with frailty-related adverse outcomes in elderly individuals and to propose a suitable tool for identifying such individuals, particularly in primary care settings. Methods A prospective open cohort study of community dwelling, independent individuals aged 75 or over, followed up for 2 years. The study was entirely conducted in a primary care setting. Study variables included independence status measured by Barthel's Index and the Lawton Instrumental Activities of Daily Living Scale, functional performance, assessed by Timed Up and Go (TUG) and Gait Speed (GS) tests and levels of polipharmacy, comorbidity and social support. Outcome variables were specific frailty-related adverse events, namely, loss of independence and death. Results Overall, 215 community-dwelling independent individuals initiated the study. Of these, 46 were lost to follow-up and 50 had frailty-related adverse events during the follow-up period. Individuals with adverse events during the study had poorer functional status at baseline. The multivariate model that best explained the occurrence of these events included the variables of age, presence of polipharmacy and the TUG time. The AUC (Area under the curve) of this model was 0.822. Conclusions Given the simplicity of assessing the three derived factors and their combined discriminant power, the proposed model may be considered a suitable tool for identifying frail patients, i.e., people more likely to lose their independence or die within a relatively short time interval.