Does an Individual's Fitness Level Affect Baseline Concussion Symptoms?
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Bibliographic record
Abstract
CONTEXT: Variables that may influence baseline concussion symptoms should be investigated. OBJECTIVE: To evaluate the effect of physical fitness on self-report of baseline concussion symptoms in collegiate athletes and students. DESIGN: Controlled laboratory study. PATIENTS OR OTHER PARTICIPANTS: A total of 125 undergraduates, including 95 collegiate athletes and 30 recreational athletes (83 males, 42 females). INTERVENTION(S): Participants completed the Standardized Concussion Assessment Tool 2 (SCAT2; symptom report) at baseline, within 10 minutes of completing the Leger test, and within 24 hours of the initial baseline test. The Leger (beep) test is a shuttle-run field test used to predict maximal aerobic power. MAIN OUTCOME MEASURE(S): The total symptom score on the SCAT2 was calculated and analyzed with a repeated-measures analysis of variance. A linear regression analysis was used to determine if 3 variables (sport type, sex, or fitness level) accounted for a significant amount of the variance in the baseline symptom report. RESULTS: Participants reported more symptoms postactivity but fewer symptoms at 24 hours compared with baseline, representing a time effect in our model (F2,234 = 47.738, P < .001). No interactions were seen among the independent variables. We also found an effect for fitness level, with fitter individuals reporting fewer symptoms at all 3 time intervals. The regression analysis revealed that fitness level accounted for a significant amount of the variance in SCAT2 symptoms at baseline (R (2) = 0.22, F3,121 = 11.44, P < .01). CONCLUSIONS: Fitness level affected the baseline concussion symptom report. Exercise seems to induce concussion symptom reporting, and symptom severity may be a function of an athlete's level of conditioning. Sports medicine professionals should consider an athlete's level of fitness when conducting baseline concussion symptom assessments.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it