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Record W2883998785 · doi:10.1002/jbmr.3556

Measures of Physical Performance and Muscle Strength as Predictors of Fracture Risk Independent of FRAX, Falls, and aBMD: A Meta-Analysis of the Osteoporotic Fractures in Men (MrOS) Study

2018· review· en· W2883998785 on OpenAlexaff
Nicholas C. Harvey, Anders Odén, Eric Orwoll, Jodi Lapidus, Timothy Kwok, Magnus K. Karlsson, Björn E. Rosengren, Eva Ribom, Cyrus Cooper, Peggy M. Cawthon, John А. Kanis, Claes Ohlsson, Dan Mellström, Helena Johansson, Eugène McCloskey

Bibliographic record

VenueJournal of Bone and Mineral Research · 2018
Typereview
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsInstitute of Aging
FundersNational Center for Advancing Translational SciencesNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Institute on AgingMedical Research CouncilVetenskapsrådetNational Institutes of HealthVersus ArthritisNovo Nordisk FondenNational Institute for Health and Care Research
KeywordsMedicineFRAXFemoral neckHip fractureOsteoporosisHazard ratioGrip strengthPoisson regressionPhysical therapyInternal medicineBone mineralOsteoporotic fractureConfidence intervalPopulation

Abstract

fetched live from OpenAlex

ABSTRACT Measures of muscle mass, strength, and function predict risk of incident fractures, but it is not known whether this risk information is additive to that from FRAX (fracture risk assessment tool) probability. In the Osteoporotic Fractures in Men (MrOS) Study cohorts (Sweden, Hong Kong, United States), we investigated whether measures of physical performance/appendicular lean mass (ALM) by DXA predicted incident fractures in older men, independently of FRAX probability. Baseline information included falls history, clinical risk factors for falls and fractures, femoral neck aBMD, and calculated FRAX probabilities. An extension of Poisson regression was used to investigate the relationship between time for five chair stands, walking speed over a 6 m distance, grip strength, ALM adjusted for body size (ALM/height2), FRAX probability (major osteoporotic fracture [MOF]) with or without femoral neck aBMD, available in a subset of n = 7531), and incident MOF (hip, clinical vertebral, wrist, or proximal humerus). Associations were adjusted for age and time since baseline, and are reported as hazard ratios (HRs) for first incident fracture per SD increment in predictor using meta-analysis. 5660 men in the United States (mean age 73.5 years), 2764 men in Sweden (75.4 years), and 1987 men in Hong Kong (72.4 years) were studied. Mean follow-up time was 8.7 to 10.9 years. Greater time for five chair stands was associated with greater risk of MOF (HR 1.26; 95% CI, 1.19 to 1.34), whereas greater walking speed (HR 0.85; 95% CI, 0.79 to 0.90), grip strength (HR 0.77; 95% CI, 0.72 to 0.82), and ALM/height2 (HR 0.85; 95% CI, 0.80 to 0.90) were associated with lower risk of incident MOF. Associations remained largely similar after adjustment for FRAX, but associations between ALM/height2 and MOF were weakened (HR 0.92; 95% CI, 0.85 to 0.99). Inclusion of femoral neck aBMD markedly attenuated the association between ALM/height2 and MOF (HR 1.02; 95% CI, 0.96 to 1.10). Measures of physical performance predicted incident fractures independently of FRAX probability. Whilst the predictive value of ALM/height2 was substantially reduced by inclusion of aBMD requires further study, these findings support the consideration of physical performance in fracture risk assessment. © 2018 The Authors. Journal of Bone and Mineral Research Published by Wiley Periodicals Inc.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.014
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0120.037
Bibliometrics0.0030.004
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.128
GPT teacher head0.462
Teacher spread0.333 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations113
Published2018
Admission routes1
Has abstractyes

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