Injury patterns in motor vehicle collision-adult pedestrian deaths
Bibliographic record
Abstract
Objectives To describe fatal pedestrian injury patterns in adults 25–64 years old and correlate them with motor vehicle collision (MVC) dynamics and pedestrian kinematics using medicolegal death investigations data of MVCs occurring in the current Canadian MV fleet.Methods MVC-pedestrian injuries were collated in an Injury Data Collection Form (IDCF) and coded using the Abbreviated Injury Scale (AIS) 2015 revision. The AIS of the most frequent severe injury was noted for individual body regions. The Maximum AIS (MAIS) was used to define the most severe injury to the body overall and by body regions (MAISBR). This study focused on serious to maximal injuries (AIS 3–6), that had an increasing likelihood of causing death. The IDCF was used to extract collision and injury data from the Office of the Chief Coroner for Ontario database of postmortem examinations done at the Provincial Forensic Pathology Unit in Toronto, Canada and other provincial facilities between 2013 and 2019. Injury data were correlated with data about the MVs, and MV dynamics and pedestrian kinematics. The study was approved by the Western University Health Science Research Ethics Board.Results There were 318 adults: 200 (62.9%) males and 118 (37.1%) females. Adult pedestrians comprised 47.5% (318/670) of all autopsied pedestrians. Vehicle type was known in 292 cases, and cars (n = 99/292, 33.9%) were the most frequent type of vehicle in single vehicle impacts; however, collectively vehicles with high hood edges (i.e., greater distance between the ground and hood edge) such as light trucks, heavy trucks and buses were in the majority. Pedestrian kinematics were known in 288/299 single impact-related deaths. Forward projection (n = 113/288, 39.2%) was the most frequent type and resulted from impacts with high hood edge vehicles. Compared to car impacts, pedestrians struck by high hood edge vehicles were more likely to be runover. Based on MAISBR ≥3 injuries, the head was the most severely injured (median MAISBR = 4), followed by neck (median MAISBR = 3), thorax (median MAISBR = 4), abdomen/retroperitoneum (median MAISBR = 4) and pelvis (median MAISBR = 3). About 70% of the pedestrians were in circumstances which increased their risk of being struck. More than half (176/318, 55.3%) had a positive toxicology result. About ¼ (27.4%) had a positive blood ethanol result. Nearly all pedestrians with positive alcohol results did not have the right of way when struck.Conclusion The current study was a comprehensive analysis of fatal injury patterns and specific injuries in adult pedestrians struck by motor vehicles. By collation and analysis of comprehensive data derived from postmortem examinations, associations between injury patterns in the adult age group were correlated with a range of factors related to motor vehicle types, reflective of the current Canadian fleet, collision dynamics and pedestrian post-collision kinematics.
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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) | 0.000 | 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 | 0.000 |
| 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".