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Minute-by-minute Analysis Of Knee Flexion During The Buffalo Concussion Treadmill Test

2024· article· en· W4402662709 on OpenAlexaboutno aff
Monique Passalacqua, Madison Fenner, Kristen G. Quigley, Addie Jane Heithecker, Nora Constantino, Nicholas G. Murray

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2024
Typearticle
Languageen
FieldMedicine
TopicOrthopedic Surgery and Rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsConcussionPhysical medicine and rehabilitationTreadmillMedicinePhysical therapyTest (biology)Knee flexionInjury preventionPoison controlEmergency medicineGeology

Abstract

fetched live from OpenAlex

The Buffalo Concussion Treadmill Test (BCTT) is an assessment to gauge the extent of exercise tolerance for patients recovering from sport-related concussions (SRC). Research suggests that knee kinematics are altered following an SRC seen throughout the BCTT during midstance (MS), but it is unclear if this persists at each minute of the test. PURPOSE: Evaluate knee flexion differences at MS during each minute of BCTT within 72 hours post-SRC compared to symptom free(SF). METHODS: 12 NCAA Division I athletes (avg. age = 20 ± 2 yrs; avg. height = 70.93 ± 5.09in) completed the BCTT within 3 days post-SRC (CON) and after being fully symptom-free (SF) for 24 hours. The BCTT was performed via the standardized guidelines, which involved measurements of Visual Analogue Scale (VAS 0-10), heart rate(HR), and Borg Rating of Perceived Exertion (RPE 6-20). Treadmill speed was contingent upon the participant’s height (3.2mph <70 in; 3.6mph < 70in) and the grade increase (1%) at each minute. The test was stopped after a consecutive 3 pt change on the VAS, RPE > 16, or when 90% of HR predicted maximum was reached. Each minute, the subjects’ joint angles (knee total range of motion in flexion/extension) were tracked using markerless motion capture (120 Hz, Qualisys motion capture, Qualisys, Göteborg, SE), analyzed using Theia (Theia Markerless, Ontario, CA), and processed through Visual 3D (10 Hz Low Pass, C-motion Inc. Germantown, MD, 1997, v.2022.09.1). Paired samples t-tests were run to determine minute by minute differences between CON and SF. Data were normalized to the lowest common denominator of time. RESULTS: A significant difference was found in flexion/extension during mid-stance of varying minutes (Table 1). CONCLUSIONS: These results suggest that SRC demonstrated greater knee flexion during the BCTT at varying time points and it becomes more significant as the time of the task increases.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.011
GPT teacher head0.283
Teacher spread0.271 · 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 designObservational
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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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