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Physical performance measures in frailty screening: diagnostic and prognostic accuracy in the Toledo Study of Healthy Ageing

      Highlights

      • Physical performance measures might ease frailty screening.
      • Exploration of the diagnostic accuracy and predictive validity of available cut-off points is needed.
      • Population-specific cut-off points showed better performance than published thresholds in our study.

      Abstract

      Introduction

      The present study aimed to explore the diagnostic and prognostic accuracy of standard and population-specific Physical Performance Measures (PPMs) cut-off points for frailty screening.

      Design

      Prospective cohort study.

      Setting and participants

      Population-based study including 2328 subjects from the Toledo Study of Healthy Aging (age = 76.37 ± 6.78). Data related to frailty status and PPMs was collected at baseline visit (2011−2013). Mortality and hospitalization were ascertained up to March 2019 and December 2017, respectively, whereas disability onset and worsening were evaluated in the 2015–2017 visit.

      Methods

      Gait speed and Short Physical Performance Battery population-specific cut-off points for frailty were computed using receiver operating characteristics (ROC) curve analysis. Head-to-head comparison of associations with adverse events against existing reference values (SPPB≤6, GS < 0.8 m/s) and classical (Frailty Phenotype, Frailty Index) and newly incorporated frailty tools (12- and 5-item Frailty Trait Scale) were explored through logistic and Cox regressions. Predictive ability was compared through areas under the curves (AUCs) for disability onset/worsening and integrated AUCs for mortality and hospitalization (time-censoring adverse events).

      Results

      PPMs population-specific cut-off points (SPPB ≤7 and GS ≤ 0.75 m/s for males; SPPB ≤4 and GS ≤ 0.5 for females) outperformed published reference thresholds in terms of diagnostic accuracy. Frailty identified through PPMs was associated with adverse events (death, hospitalization and incident disability) similarly to that assessed using the newly incorporated tools and showed similar prognostic accuracy (mortality [IAUCs≈0.7], hospitalization [IAUCs≈0.8] and disability onset/worsening [AUCs≈0.62]), except for the tool used to assess frailty.

      Conclusions

      Our results suggest that PPMs might serve as the first screen to identify candidates for further frailty assessment and exploration of underlying mechanisms, allowing opportunistic on-time screening in different settings (community and primary care) in which frailty instruments are rarely implementable.

      Keywords

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