Biomechanical Comparison of Real World Concussive Impacts in Children, Adolescents, and Adults
Bibliographic record
Abstract
Accidental falls occur to people of all ages, with some resulting in concussive injury. At present, it is unknown whether children and adolescents are at a comparable risk of sustaining a concussion compared to adults. This study reconstructed the impact kinematics of concussive falls for children, adolescents, and adults and simulated the associated brain tissue deformations. Patients included in this study were diagnosed with a concussion as defined by the Zurich Consensus guidelines. Eleven child, 10 adolescent, and 11 adult falls were simulated using mathematical dynamic models(MADYMO), with three ellipsoid pedestrian models sized to each age group. Laboratory impact reconstruction was conducted using Hybrid III head forms, with finite element model simulations of the brain tissue response using recorded impact kinematics from the reconstructions. The results of the child group showed lower responses than the adolescent group for impact variables of impact velocity, peak linear acceleration, and peak rotational acceleration but no statistical differences existed for any other groups. Finite element model simulations showed the child group to have lower strain values than both the adolescent and adult groups. There were no statistical differences between the adolescent and adult groups for any variables examined in this study. With the cases included in this study, young children sustained concussive injuries at lower modeled brain strains than adolescents and adults, supporting the theory that children may be more susceptible to concussive impacts than adolescents or adults.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".