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Flexion And Extension Is Reduced Immediately Following Sport-related Concussion During The Buffalo Concussion Treadmill Test

2023· article· en· W4387062504 on OpenAlexaboutno aff
Monique Passalacqua, Joseph McCarley, Dustin Hopfe, Madison Taylor, Kristen Quiglety, Vincentia Owusu-Amankonah, Erica Lee, Greg Ryan, John J. Leddy, Nora Constantino, Nicholas G. Murray

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2023
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsnot available
Fundersnot available
KeywordsConcussionMedicineTreadmillPhysical therapyRange of motionRating of perceived exertionVisual analogue scaleKnee flexionAthletesHip flexionFootballPhysical medicine and rehabilitationHeart ratePoison controlInjury preventionInternal medicineBlood pressure

Abstract

fetched live from OpenAlex

The Buffalo Concussion Treadmill Test (BCTT) is a premier tool to identify the degree of exercise tolerance for patients following sport-related concussions (SRC). Little to no research exists regarding any biomechanical deficits exist during post-SRC during the BCTT. PURPOSE: Examine the knee angle and physiological response among athletes between 3 days post-SRC and their symptom-free BCTT. METHODS: Two NCAA DI football players (avg. age = 20 ± 2 yr) completed the BCTT 3 days post-SRC (CON) and after being fully symptom-free (SF) for 24 hours (24 days post-SRC). The team physician diagnosed them with an SRC using the international consensus guidelines. 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) during the 3.6mph consistent walking and grade increase (1%) at each minute. At CON, the test was stopped after a consecutive 2 pt change on the VAS. Each minute, the subjects’ joint angles (Knee total range of motion in flexion/extension (X) and adduction/abduction (Y)) were tracked using markerless motion capture (120 Hz, Qualisys motion capture, Qualisys, Göteborg, Sweden) and analyzed using Theia (Theia Markerless, Ontario, Canada). Treating each percent incline change during the BCTT as an independent observation, paired samples t-tests (HR, Knee-X, Knee-Y) and Wilcoxon signed-rank test (RPE) were run to determine differences between the CON and SF. Additionally, Spearman Rho correlations determined the relationship between VAS and tested parameters in the CON condition. RESULTS: A significant difference in HR (CON = 124 ± 26 bpm, SF = 132 ± 24 bpm; p < 0.01; ES = -1.02) response, Knee-X (CON = 67.6 ± 1.9°, SF = 70.0 ± 5.7°; p < 0.01; ES = -0.75) and RPE (CON = 11.0 ± 3.0au, SF = 6.0 ± 1.25au; p < 0.01; ES = 1.54) between the two trials. No difference was noted for Knee-Y (CON = 24.4 ± 5.7°, SF = 24.3 ± 7.1°; p = 0.97; ES = 0.01). Additionally, significant, strong, positive correlations were noted between VAS and HR (r = 0.73, p < 0.01) and RPE (r = 0.72, p < 0.01). No significant relationships existed between VAS and either Knee-X (r = 0.27, p = 0.16) or Knee-Y (r = 0.37, p = 0.06). CONCLUSION: These results suggest a reduction (4.8%) in Knee flexion/extension alongside changes in physiological markers post-SRC.

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)0.002
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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.035
GPT teacher head0.336
Teacher spread0.300 · 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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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