Injury patterns in motor vehicle collision–youth pedestrian deaths
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to describe fatal pedestrian injury patterns in youth aged 15 to 24 years old and correlate them with motor vehicle collision (MVC) dynamics and pedestrian kinematics using data from medicolegal death investigations of MVCs occurring in the current Canadian motor vehicle (MV) fleet. METHODS: Based on a systematic literature review, MVC-pedestrian injuries were collated in an injury data collection form (IDCF). The IDCF was 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 (OCCO) database of postmortem examinations done at the Provincial Forensic Pathology Unit (PFPU) 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 (Project ID: 113440; Lawson Health Research Institute Approval No. R-19-066). RESULTS: = 34/88, 38.6%) was the most frequent type of pedestrian kinematics. Regardless of the type of vehicle, there was a tendency in most cases for the median MAISBR ≥ 3 to involve the head and thorax. A similar trend was seen in most of the pedestrian kinematics involving the various frontal impacts. Of the 88 cases, at least 63 (71.6%) were known to be engaged in risk-taking behaviors (e.g., activity on roadway). At least 12 deaths were nonaccidental (8 suicides and 4 homicides). Some activities may have been impairment related, because 26/63 (41.3%) pedestrians undertaking risk-taking behavior on the roadway were impaired. Toxicological analyses revealed that over half of the cases (47/88, 53.4%) tested positive for a drug that could have affected behavior. Ethanol was the most common. Thirty-one had positive blood results. CONCLUSION: A fatal dyad of head and thorax trauma was observed for pedestrians struck by cars. For those pedestrians hit by vehicles with high hood edges, which were involved in the majority of cases, a fatal triad of injuries to the head, thorax, and abdomen/retroperitoneum was observed. Most deaths occurred from frontal collisions and at speeds more than 35 km/h.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".