Characteristics of firearm injury by injury intent: The need for tailored interventions
Bibliographic record
Abstract
INTRODUCTION: While the United States has high quality data on firearm-related deaths, less information is available on those who arrive at trauma centers alive, especially those discharged from the emergency department. This study sought to describe characteristics of patients arriving to trauma centers alive following a firearm injury, postulating that significant differences in firearm injury intent might provide insights into injury prevention strategies. METHODS: This was a multicenter prospective cohort study of patients treated for firearm-related injuries at 128 US trauma centers from March 2021 to February 2022. Data collected included patient-level sociodemographic, injury and clinical characteristics, community characteristics, and context of injury. The outcome of interest was the association between these factors and the intent of firearm injury. Measures of urbanicity, community distress, and strength of state firearm laws were used to characterize patient communities. RESULTS: A total of 15,232 patients presented with firearm-related injuries across 128 centers in 41 states. Overall, 9.5% of patients died, and deaths were more common among law enforcement and self-inflicted firearm injuries (80.9% and 50.5%, respectively). These patients were also more likely to have a history of mental illness. Self-inflicted firearm injuries were more common in older White men from rural and less distressed communities, whereas firearm assaults were more common in younger Black men from urban and more distressed communities. Unintentional injuries were more common among younger patients and in states with lower firearm safety grades, whereas law enforcement-related injuries occurred most often in unemployed patients with a history of mental illness. CONCLUSION: Injury, clinical, sociodemographic, and community characteristics among patients injured by a firearm significantly differed between intents. With the goal of reducing firearm-related deaths, strategies and interventions need to be tailored to include community improvement and services that address specific patient risk factors for firearm injury intent. LEVEL OF EVIDENCE: Prognostic and Epidemiological; Level III.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".