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Implementation of the Frailty Index in hospitalized older patients: Results from the REPOSI register

  • Author Footnotes
    1 Equally contributing authors.
    M. Cesari
    Correspondence
    Corresponding author at: Geriatric Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milano, Italy.
    Footnotes
    1 Equally contributing authors.
    Affiliations
    Department of Clinical Sciences and Community Health, University of Milan, Italy

    Geriatric Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milano, Italy
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  • Author Footnotes
    1 Equally contributing authors.
    C. Franchi
    Footnotes
    1 Equally contributing authors.
    Affiliations
    Department of Neuroscience, IRCCS – Istituto di Ricerche Farmacologiche “Mario Negri”, Milano, Italy
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  • L. Cortesi
    Affiliations
    Department of Neuroscience, IRCCS – Istituto di Ricerche Farmacologiche “Mario Negri”, Milano, Italy
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  • A. Nobili
    Affiliations
    Department of Neuroscience, IRCCS – Istituto di Ricerche Farmacologiche “Mario Negri”, Milano, Italy
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  • Author Footnotes
    1 Equally contributing authors.
    I. Ardoino
    Footnotes
    1 Equally contributing authors.
    Affiliations
    Department of Clinical Sciences and Community Health, University of Milan, Italy
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  • Author Footnotes
    1 Equally contributing authors.
    P.M. Mannucci
    Footnotes
    1 Equally contributing authors.
    Affiliations
    Scientific Direction, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milano, Italy
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  • the REPOSI collaborators
    Author Footnotes
    2 Full list of authors are found in Appendix A.
  • Author Footnotes
    1 Equally contributing authors.
    2 Full list of authors are found in Appendix A.

      Highlights

      • Frailty is a state of late-life characterized by increased vulnerability to stressors and is associated with poor health outcomes
      • Different definitions of frailty have been proposed to help different stakeholders. The Frailty Index (FI) proposed by Rockwood and Mitnitski is one of the most promising tools for measuring frailty.
      • It is defined following a arithmetical model aimed at capturing the age-related accumulation of health deficits concerning different domains, such as cognition and mood, organ diseases, functional autonomy.
      • In this study the FI confirms its predictive value for in-hospital and short term mortality even when it is applied to a large sample of hospitalized older patients.
      • The design and implementation of the FI in the hospital setting will potentially provide both an outcome of interest as well as a possible variable capturing the complexity of the older patient.

      Abstract

      Background

      Frailty is a state of increased vulnerability to stressors, associated to poor health outcomes. The aim of this study was to design and introduce a Frailty Index (FI; according to the age-related accumulation of deficit model) in a large cohort of hospitalized older persons, in order to benefit from its capacity to comprehensively weight the risk profile of the individual.

      Methods

      Patients aged 65 and older enrolled in the REPOSI register from 2010 to 2016 were considered in the present analyses. Variables recorded at the hospital admission (including socio-demographic, physical, cognitive, functional and clinical factors) were used to compute the FI. The prognostic impact of the FI on in-hospital and 12-month mortality was assessed.

      Results

      Among the 4488 patients of the REPOSI register, 3847 were considered eligible for a 34-item FI computation. The median FI in the sample was 0.27 (interquartile range 0.21–0.37). The FI was significantly predictive of both in-hospital (OR 1.61, 95%CI 1.38–1.87) and overall (HR 1.46, 95%CI 1.32–1.62) mortality, also after adjustment for age and sex.

      Conclusions

      The FI confirms its strong predictive value for negative outcomes. Its implementation in cohort studies (including those conducted in the hospital setting) may provide useful information for better weighting the complexity of the older person and accordingly design personalized interventions.

      Keywords

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