Concussion-like symptoms Induced by Heat and Dehydration in a Varsity College Soccer Player: A Case Report
Bibliographic record
Abstract
Objective Show light on confounding presentations of heat and environmental related illnesses & mild TBI symptomatology. Identify overlapping symptomatology of heat illness & mild TBI. Background Heat illnesses, mostly heat exhaustion, tends to go under reported and many times, due to the nature of the activity, may be confused with a concussion despite the individual not experiencing any identifiable concussive event. Heat related illnesses are caused when the body is unable to regulate the cooling of itself. Normal physiological mechanisms such as sweating may not be sufficient to respond to the severe increase and change in temperature. As a result, the body temperature will raise to dangerous levels and cause damage to vital organs, including the brain. Today, there is very limited literature available that compares the symptoms of concussion vs heat illnesses. Design/Methods Case obtained from a Barrow Neurological Institute Concussion and Brain Injury patient. Case will reported from available history and clinic follow up visit. Overlapping symptoms of heat and concussion will demostrated in table format. No HIPPA information will be disclosed. Results The Soccer player was prevented from play due to a "Concussion" according to the Athletic trainer. No identifiable event was reported. Patient did experience Migranious headaches that were triggered by dehydration and execisseve heat exposure. Conclusions There is a significant overlap in concussion and heat related symptoms. Family history of migraines is a predisposing factor for both concussion and heat illness. Heat illness is noticeable underreported and may be confused as a concussion in high impact /collision activities; which, provides a challenge in itself due to nature of sports and exercise. Education about heat illness is important. More research is require to determine how much these two process overlap in symptomatology, are confounded & misdiagnosed, and occur concomitantly.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".