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Record W3212074987 · doi:10.1123/jab.2020-0156

The Effects of Body Position on Trochanteric Soft Tissue Thickness—Implications for Predictions of Impact Force and Hip Fracture Risk During Lateral Falls

2021· article· en· W3212074987 on OpenAlexaff
Benoît Lafleur, Alyssa M. Tondat, Steven P. Pretty, Marina Mourtzakis, Andrew C. Laing

Bibliographic record

VenueJournal of Applied Biomechanics · 2021
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsSupine positionHip fractureOrthodonticsMedicineExternal rotationRisk factorFracture (geology)Physical medicine and rehabilitationPhysical therapySurgeryMaterials scienceInternal medicineOsteoporosis

Abstract

fetched live from OpenAlex

Trochanteric soft tissue thickness (TSTT) is a protective factor against fall-related hip fractures. This study's objectives were to determine: (1) the influence of body posture on TSTT and (2) the downstream effects of TSTT on biomechanical model predictions of fall-related impact force (Ffemur) and hip fracture factor of risk. Ultrasound was used to measure TSTT in 45 community-dwelling older adults in standing, supine, and side-lying positions with hip rotation angles of -25°, 0°, and 25°. Supine TSTT (mean [SD] = 5.57 [2.8] cm) was 29% and 69% greater than in standing and side-lying positions, respectively. The Ffemur based on supine TSTT (3380 [2017] N) was 19% lower than the standing position (4173 [1764] N) and 31% lower than the side-lying position (4908 [1524] N). As factor of risk was directly influenced by Ffemur, the relative effects on fracture risk were similar. While less pronounced (<10%), the effects of hip rotation angle were consistent across TSTT, Ffemur, and factor of risk. Based on the sensitivity of impact models to TSTT, these results highlight the need for a standardized TSTT measurement approach. In addition, the consistent influence of hip rotation on TSTT (and downstream model predictions) support its importance as a factor that may influence fall-related hip fracture risk.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.763
Threshold uncertainty score0.413

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.008
GPT teacher head0.319
Teacher spread0.311 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations8
Published2021
Admission routes1
Has abstractyes

Explore more

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