Falls risk stratification. One size doesn’t fit all

Editorial to accompany: Two simple modifications to the World Falls Guidelines algorithm improves its ability to stratify older people into low, intermediate and high falls risk groups. Gait speed, and alternatively the Timed Up and Go test (TUG), should be used with age-based cut-offs to stratify risk for falls prediction. Prioritising gait speed as the primary predictive measure, with the TUG test as a secondary tool with age-specific cut-offs, will likely enhance prediction and group risk stratification accuracy. Forty years ago, Mathias, Nayak and Isaacs introduced the ‘Get-Up and Go’ test, the first tool designed to assess mobility and risk of falls in older individuals, which has been subsequently widely adopted [1]. Five years later, a timed version of this test, the ‘Timed Up and Go’ (TUG), was developed that showed a strong association with a history of falls and was proposed as a quick and practical falls risk predictor [2]. Both the ‘Get-Up and Go’ test and the TUG test are recommended as overall gait and balance assessment tools by the World Falls Guidelines (WFG) [3]. Additionally, the TUG was incorporated into the novel falls risk stratification algorithm as an alternative to gait speed [3]. The main reason why the TUG was not recommended as the primary test relies in the fact that in prospective cohort studies, the TUG has shown limited ability to accurately predict falls outside groups of lower functioning adults [4]. In contrast, the gait speed test has emerged as a universal ‘geriatric vital sign’ strongly associated with falls, with high-quality clinical practice guidelines consistently recommending gait speed for risk stratification [5]. To note, the WFG were established as an iterative process with the intention that future research on falls, including studies to validate the algorithm, may result in appropriate modifications. During our consensus and Delphi process, the TUG was recommended by the WFG experts to be included in the algorithm as a gait and balance test due to the awareness and use of this test worldwide. Based on available evidence, a conservative 15 seconds cut-off was selected, acknowledging its high specificity as a fall predictor in low functioning individuals [6]. This single and conservative cut-off was chosen to keep the algorithm straightforward and practical for busy clinicians. In this issue of Age and Ageing, Hicks and colleagues present a study proposing modifications to the WFG algorithm, to enhance risk stratification and better categorise individuals into low-, intermediate- and high-risk groups [7]. They found that changing the cut-off from 15 to 10 seconds and applying the gait tests to everyone yielded a better risk stratification distribution by better detecting the intermediate risk group. We are pleased that our guidelines have inspired this forward-thinking approach, and we agree with the authors that refining the original algorithm may improve its predictive ability. As part of the WFG development, a working group was established to identify the most reliable and accurate tests for assessing gait and balance and predicting falls, to inform the stratification algorithm, with a focus on the algorithm’s effectiveness as a predictive tool. While evidence for the TUG test as a falls predictor test remained inconclusive, the working group found that gait speed consistently stood out as the strongest test for predicting falls [4]. Aligned with working group findings, a recent study involving 1548 older adults from the Longitudinal Aging Study Amsterdam tested the WFG algorithm using gait speed as a stratification test and was able to discriminate the three risk groups with good predictive ability [6]. Another recent evaluation of the algorithm’s longitudinal predictive performance in the large Malaysian Elders Longitudinal Research Study (1500 older persons followed over a 9-year period), but using the TUG, found a high specificity in categorising the three risk groups, with low sensitivity in predicting falls and with decreasing sensitivity over time [8]. Despite the TUG’s limited discriminatory ability as a fall predictor, the ‘Get-Up and Go’ test remains essential in the armamentarium of falls risk assessment, as it provides a comprehensive evaluation of mobility and transferring ability. However, we acknowledge that alternative cut-off times may be more appropriate depending on the individual’s age or functional status when used for risk prediction, to avoid ceiling effects and increase discriminative abilities [9]. Age-based stratification of the TUG cut-offs, rather than a single universal cutoff, could further improve accuracy. A seminal study demonstrated that ideal TUG cut-offs vary by age as follows: 8.1 seconds for individuals aged 60–69, 9.2 seconds for those aged 70–79 and 11.3 seconds for those 80 to 99 [10]. Future research using age-specific cut-offs may provide results that enhance the discrimination ability of the WFG algorithm even further. Nevertheless, gait speed remains an excellent initial step in falls risk assessment due to its simplicity and predictive validity, with specific cut-off points for different populations. It is easily measured by timing a person’s usual walking speed over 4 metres, and it is recommended by the WFG and other guidelines. Evidence-based cut-off suggested the range from a cut-off of 1 m/s for community-dwelling older adults without disability to 0.8 m/s for older persons with lower functioning [11]. In addition, dual-task gait testing (i.e. walking while talking) could be particularly useful in older adults who have a gait speed >1 m/s or when subtle cognitive impairment is suspected to impact poor motor control [12]. In summary, Hicks and colleagues present high-quality evidence to support the use of a gait-mobility test universally, such as the TUG, with a different cut-off. We argue that this approach should be applied for gait speed too when used for fall prediction stratification. Since one size does not fit all, adopting age-based cut-offs grounded in current evidence may provide a more tailored approach. Prioritising gait speed as the primary predictive measure, with the TUG test as a secondary tool, with age-specific cut-offs will likely enhance our ability to accurately predict and prevent falls. MMO is President and member of the executive of the Canadian Geriatrics Society and of the World Falls Prevention Society, member of the Advisory Board of the CIHR Institute of Aging, and Associate Editor of the Journal of Alzheimer’s Disease, the Journal Gerontology Medical Sciences and Geriatrics. NvdV is Academic Director of the Executive Board of the European Geriatric Medicine Society and of the World Falls Prevention Society, and Deputy Editor-in-Chief of Age and Ageing. JR is a member of the Executive Committee of World Falls Prevention Society and Academic Board member of the European Geriatric Medicine Society. TM is President Elect and member of the Executive Board of the European Geriatric Medicine and of the World Falls Prevention Society. None declared.

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