Enhancing Protocols for Concussion Management in Professional Soccer Events
Bibliographic record
Abstract
AIM: Every year, there are an estimated 1.7 to 3.8 million sports-related traumatic brain injuries. A sports concussion results from an external force or a blow to the head or body, causing cranial encephalic trauma that can affect motor skills and brain function, producing varying symptoms related to an alteration in neurological functioning. Soccer poses a risk of concussions due to heading, where the player's head directly hits the ball to redirect or accelerate it. However, most concussions are caused by contact between players, such as head-to-head or head-to-elbow contact. This study analyzed the incidence of concussions or mild traumatic brain injuries in professional soccer during the "Copa America 2019" to understand the feasibility of soccer concussion protocols and propose evidence-based enhancements. METHODS: The data were previously collected by our first two authors, O. Pangrazio and F. Forriol, during the 46th edition of the "Copa America 2019," where the South American Football Confederation implemented the Concussion Fast Recognition Protocol to detect traumatic brain injuries. The descriptive basic data will help to raise awareness and motivate further research in this field. We have analyzed and correlated it with global data to provide a comprehensive review and tangible evidence of the population size where soccer protocols are typically applied, thus calculating incidence rates to measure it mathematically. RESULTS: Our study reveals that the incidence rate of concussions during the "Copa America 2019" was 5.3 per 1,000 athlete exposures, with a total of three concussions occurring among 567 players. Despite the effectiveness of current protocols in detecting concussions rapidly and accurately, the relatively low incidence rate at this level of professional competition poses a challenge to validating these protocols. These results indicate that while the protocols in place are efficient, the testing and validation of new tools and approaches would be more beneficial at different levels of play where the incidence rates of concussions are higher. In environments with a greater frequency of concussions, the robustness and reliability of these protocols can be more thoroughly evaluated, ensuring they provide optimal protection and care for athletes. CONCLUSION: The incidence of concussions is low in professional soccer tournaments. Protocols are necessary to protect players and educate sports professionals. However, their validation is difficult given the low incidence of concussions at this level of competition. Our proposed protocol helps unify a basic approach in the field and an advanced approach in any emergency department, providing better detection of concussions and improved outcomes for players. This protocol should be validated in populations with higher incidence rates to demonstrate its effectiveness.
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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 | 0.024 | 0.065 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".