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Record W3001297305 · doi:10.1093/ptj/pzaa017

Screening for Preclinical Balance Limitations in Younger Older Adults: Time for a Paradigm Shift?

2020· letter· en· W3001297305 on OpenAlexaff
Marla Beauchamp

Bibliographic record

VenuePhysical Therapy · 2020
Typeletter
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsMcMaster University
Fundersnot available
KeywordsBalance (ability)Paradigm shiftPsychologyMedicineGerontologyPhysical medicine and rehabilitation

Abstract

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The article by Gordt et al1 in the January issue of PTJ describes the development and validation of a balance screening test for younger older adults aged 60 to 70 years of age. The shortened Community Balance & Mobility scale (s-CBM) is a 4-item test that takes 10 minutes to administer and has comparable psychometric properties to the full CBM in younger older adults. This is an important contribution, given that few studies have assessed the measurement properties of balance tests in younger older adults, and many commonly used balance tests provide insufficient challenge to balance to detect early functional loss.2 In addition, the small number of existing higher-level balance tests tend to have long administration times, which make them unfeasible for many practice settings. Early and quick identification of subtle changes in balance with aging or disease is potentially critical for preventing later-life mobility loss and falls. However, in current clinical practice, our focus is often reactive rather than proactive; balance testing is not routinely conducted until after a first fall or injury. Indeed, clinical practice guidelines for fall risk assessment and prevention in community-dwelling older adults only recommend screening for balance and mobility problems in individuals with a previous fall history or who self-report difficulty with standing or walking.3,4 It is likely that this represents a missed opportunity to prevent a first fall for many older adults. In aging research, the term preclinical mobility limitation (often referred to as “preclinical disability”) has been used to describe a stage of early functional loss—an asymptomatic decline in mobility in which individuals are able to compensate for early losses in function without a strong perception of difficulty.5 These compensations, such as modifying the frequency or speed of task performance, can be unconscious, and older adults often perceive no difficulty with their mobility, which may prevent them from seeking treatment. This is problematic, as older adults with preclinical mobility limitation have an increased risk of developing overt mobility loss and disease.6,7 For example, in the Women’s Health and Aging Study II (WHAS II), the probability of developing incident mobility difficulty over 18 months in women with preclinical mobility limitation was 26% to 31%, compared with only 7% to 12% in those with no preclinical mobility limitation at baseline.6 The presence of preclinical mobility limitation has also been shown to increase the risk of falling in older adults.8,9 Identification of preclinical mobility limitation in middle-aged and older adults provides the opportunity for early intervention to delay or reduce mobility decline and prevent adverse health events in later life. Although performance on static standing balance tests can reliably identify those with preclinical mobility limitation,10 some of the most commonly used tests (eg, semitandem and tandem stance, functional reach) are unable to predict the transition from preclinical mobility limitation to mobility loss.6,11 This is perhaps not surprising given the known ceiling effects with many of these measures in younger and higher-functioning participants. In a large population-based Finnish study of adults aged 30 years and older (n = 7979), semitandem and tandem standing balance tasks had a ceiling effect in individuals under the age of 60 years, whereas more sophisticated force platform measures of postural sway were able to show a deterioration in balance by middle age (as early as 40 to 49 years) with a more marked decline after the age of 60.12 In order to detect early declines in mobility with aging, tests with a higher difficulty level are needed.13 For example, longitudinal data from the InCHIANTI study shows that, although performance in the 4-m usual gait speed test declines only after about the age of 65, decline in the 4-m fast gait speed test can be seen as early as 40 to 50 years of age.13 Similar results were observed for the 400-m walk test compared with the shorter tests of gait speed. Thus, for walking-related mobility, longer distance and faster paced tests are needed to detect early changes in mobility with aging. Although longitudinal data on changes in balance performance with aging are scarce, similar trends can be observed with cross-sectional data. For standing balance tests, balance deficits are noted starting in middle age when people close their eyes or stand on a foam pad, or when more challenging positions are used such as standing on one leg.14 In fact, single-leg stance was the only static balance test that predicted the transition from preclinical mobility limitation to mobility difficulty in the WHAS II.9 Additionally, comprehensive balance tests that measure more components of balance, such as the Balance Evaluation Systems Test, can detect deteriorations in balance in each decade of life beginning at age 60 in adults who are healthy.15 Longitudinal data from large and representative samples are needed to better understand age-related changes in balance; however, existing data suggest that screening for balance limitations should begin prior to 65 years of age using tests with higher challenge to balance (ie, narrower base of support, altered visual or somatosensory input, dynamic tasks). The s-CBM developed by Gordt et al includes 3 items performed on one leg (single-leg stance, lateral foot “scooting,” and hopping) as well as a “walk, look, and carry” task that assesses multiple aspects of dynamic balance, including dual-task ability. The authors found no floor or ceiling effects with the s-CBM in their sample of younger older adults (mean age = 66 years) and excellent convergent validity with the longer parent CBM test (originally developed for high-functioning adults with traumatic brain injury),16 suggesting that the test items are sufficiently difficult to detect preclinical balance limitation in younger older adults. Prospective studies including participants with a broader age range will be important for determining if tests such as s-CBM can better detect early age-related changes in balance than traditional tools as well as predict the risk for adverse health events including falls. Weiss et al suggested that there is adequate evidence to warrant screening for preclinical mobility limitation in clinical practice.17 Given that balance follows a similar trajectory to age-related changes in walking, and given the importance of balance for predicting mobility loss and falls, it is time to consider assessing preclinical balance limitation alongside traditional measures of preclinical walking limitation in younger older adults. In particular, more challenging tests are needed to assess early balance decline in adults under the age of 65, and the study by Gordt and colleagues is an important first step in this direction. Further research is required to determine if subclinical balance deficits detected in younger older adults via tests such as the s-CBM can be used to identify those at future risk of falling and developing mobility loss. There also remains a recognized need for empirical evidence to demonstrate that providing early intervention to individuals identified as having preclinical limitations can mitigate mobility loss and adverse health outcomes such as falls in older adulthood. Despite the long road ahead, such upstream approaches could have tremendous benefit in reducing the enormous burden of falls and mobility problems in older adulthood.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.094
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.119
GPT teacher head0.407
Teacher spread0.288 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations3
Published2020
Admission routes1
Has abstractyes

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