Article 1
Firearm Injuries in Young Children: Surgical Resource Utilization and Implications for Prevention. Collins CE, et al. J Surg Res. 2024 Oct:302:64-70.
“Firearm Injuries in Young Children: Surgical Resource Utilization and Implications for Prevention” examines a cohort of 489 pediatric patients, ages 15 and younger, presenting with firearm-related injuries, focusing on injury patterns, operative needs, and resource utilization. Using a retrospective database from 10 trauma centers in the State of Florida from 2016 to 2021, the authors describe mechanisms of injury and quantify rates of operative intervention, ICU admission, length of stay, and mortality. Unintentional shootings in the home were the most common mechanism of injury. The study demonstrates that pediatric firearm injuries frequently require surgical intervention and critical care resources, with a significant mortality rate. These injury patterns strongly implicate unsafe firearm storage and caregiver access as key modifiable risk factors. These clinical findings therefore suggest prevention opportunities.
The study is limited by its retrospective design and reliance on registry data. This design reduces granularity around social context, firearm storage practices, supervision, and intent. Selection bias toward higher-acuity, trauma centers may overestimate resource utilization and miss prehospital fatalities or minor injuries. Heterogeneity across institutions might affect consistency in reporting operative indications and outcomes. The study is relevant to trauma surgeons because it translates epidemiologic patterns into clinical burden, strengthening the case for surgeon involvement in primary prevention. By linking resource-intensive care to preventable mechanisms, including unsecured firearms, this study provides a data-driven rationale for integrating safe-storage counseling, caregiver education, and advocacy into surgical practice and trauma system design. Article 2Assault-Related Versus Accidental Pediatric and Adolescent Firearm Injuries: Trends and Types of Extremity Trauma. Wilson DR, et al. Journal of Pediatric Orthopedics. 2026 Mar 1;46(3):154-159. The authors present a single-center retrospective review of patients age 18 or younger with a firearm injury involving an extremity presenting to a single, pediatric level I trauma center between January 1, 2018, and December 31, 2023. A total of 230 patients were included, and demographic data, injury characteristics, and clinical outcomes were compared between assault-related and accidental injuries. From the cohort, 74.3% were assault-related injuries and 25.6% accidental. Assault-related injuries primarily affected older African American males and were associated with higher injury severity scores, multisystem trauma, ICU admission, multiple gunshot wounds, and multiple extremity involvement. Accidental injuries were more common in younger patients and had higher rates of fractures (69.5% vs. 52.1%; P =0.020), orthopedic consults (79.7% vs. 59.2%; P =0.005), and surgical intervention (50.9% vs. 27.5%; P =0.001. When assessing for seasonal patterns, the authors found that while assault-related injuries peaked in October, there was a statistically significant spike in accidental injuries in January. They concluded that these findings underscore the need for targeted, time-sensitive firearm safety initiatives, particularly those focused on safe storage and education during the winter months and around the holiday break. These findings support the current trends that assault-related firearm injuries were more common overall and primarily involved older African American male adolescents. One novel finding from this study is the seasonal spike in non-accidental injury in January. It is speculated that this may be correlated with new gun purchases over the holiday season, possible hunting accidents, or reduced supervision of adolescents during school breaks. This study was limited to pediatric orthopedic surgery patients focusing on extremity injuries, warranting further studies on injury patterns in head and thoracoabdominal trauma. This study was based on data from Little Rock, Arkansas. It would be interesting to investigate regional differences in areas with different gun laws. Taken together, the presented findings may inspire updates in firearm safety initiatives. EAST guidelines for firearm injury prevention currently recommend safe storage and conditionally recommend gun locks. In its next update, perhaps seasonal factors may also impact the inclusion criteria and recommendations. Article 3The Association Between Vacant Lot Redevelopment and Violent/Firearm Violent Crime: A Difference-in-Difference Analysis From 2007 to 2023. Asa N. et al. American Journal of Public Health. 2026 Jan;116(1):95-102. This study by Asa et al. evaluates the association between vacant lot redevelopment and violent and firearm-related crime in Philadelphia from 2007 to 2023 using a quasi-experimental difference-in-differences (DID) design. The authors analyzed 254 formerly vacant lots, defining redevelopment primarily as conversion into housing or business structures, and secondarily as any form of physical restriction (including fences or other structures). Violent crime outcomes were derived from geocoded police data and analyzed using kernel density estimation. Over their study period, 41 (16.1%) were redeveloped under their primary redevelopment definition. Redeveloped lots were more likely to be areas with higher percentage white (20.5% vs. 9.9%) and higher average median income ($24,981 vs $21,156) The primary analysis demonstrated significant reductions in aggravated assault (−56.6 crimes per square mile per year), firearm aggravated assault (−35.1), and overall firearm violent crime (−27.3) following redevelopment, corresponding to relative decreases of approximately 30% and 14.7%, respectively. However, no significant associations were observed for other crime subtypes. Secondary analyses using a broader redevelopment definition showed weaker and less consistent findings, with only firearm homicide demonstrating a significant reduction. Importantly, spillover analyses using a “donut vs. donut-hole” spatial buffer approach showed no evidence of crime displacement to surrounding areas, and event study analyses supported the parallel trends assumption (that in the absence of intervention [redevelopment], the difference between treatment and control groups would have remained constant over time). This study contributes to a growing body of literature supporting built environment interventions as a strategy for violence prevention. The authors strengthen prior work on vacant lot greening by examining redevelopment, a more resource-intensive but potentially more impactful intervention. Strengths include the use of a staggered DID design, longitudinal data over 16 years, and robust spatial analytic methods. However, several limitations warrant consideration, including potential residual confounding from gentrification and neighborhood-level socioeconomic changes, as redevelopment was more common in higher-income areas. Additionally, reliance on police-reported crime may underestimate true violence rates, and the assumption of parallel trends, while supported, cannot be fully verified. The finding that only structural redevelopment (rather than simple access restriction) was associated with meaningful reductions in violence suggests that investment signaling and neighborhood revitalization may play a critical role beyond physical deterrence alone. Overall, this study is highly relevant to trauma and public health research, as it highlights upstream, place-based interventions that may reduce firearm injury risk and complement clinical and hospital-based violence prevention programs. Article 4Development and validation of a concussion risk prediction model using 2023 National Health Interview Survey (NHIS) data. Yang S, Chen Y, Huang S, Deng Y, Zhou X, Li Y. Medicine (Baltimore). 2026 Mar 6;105(10):e47935. This cross-sectional observation study utilized the 2023 National Health Interview Survey (NHIS) to develop a concussion risk prediction model addressing a critical gap in sports safety and general health assessments. The study included 14,275 adults (aged ≥ 18 years) who self-reported concussion status. Exclusion criteria included individuals <18 years of age, those with ambiguous responses to concussion-related questions, and those with missing data on other variables. These participants were then classified using 5 questionnaires related to concussion to affirmatively determine the diagnosis of concussion (N=363) versus those without (N=13,912). Covariates were included to account for their potential influence on concussion and were categorized into demographic characteristics, health status, comorbidities, lifestyle data, and occupational data. A greater proportion of concussion patients received more education (74.4% vs. 70.5%, P=0.0484), were divorced, separated, widowed, or never married (54.8% vs. 43.1%, P <.0001), had incomes of <35,000 USD (9.9% vs. 6.3%) and 35,000-64,999 USD (16.8% vs 14.1%),reported abnormal physical and mental health states, and were working in performing arts, spectator sports, or related industries. A LASSO regression analysis was performed utilizing the aforementioned baseline characteristics to identify 9 predictive indicators (age, industry, mental health, martial status, general health status, education level, family income-to-poverty ratio, behavior, and anxiety). A practical and stable nomogram was developed with an AUC value of 0.712, signifying high diagnostic value that outperformed individual variables in predicting concussion. This study comprehensively considered the impact of demographic characteristics, socioeconomic status, mental health conditions, occupational exposure, and lifestyle factors on the risk of concussion, developing a promising tool to detect high-risk individuals. Existing brain injury prediction models focus mainly on prognostic evaluation after injury and rely on clinical measurement indicators. This nomogram has a high specificity and accuracy, enabling physicians to identify high-risk patients early for close monitoring and tailored management. All 9 indicators included in the study are derived from routine health survey and require no additional laboratory testing or imaging. Since this model was developed and validated exclusively utilizing the 2023 NHIS dataset, further study is needed to externally validate this predictive model across diverse cohorts. The use of self-reported questionnaire data introduces the potential for recall bias and misclassification. The cross-sectional design of the study also precludes it from capturing dynamic changes in concussion outcomes over time. Despite these limitations, this study presents the foundational framework for development of concussion risk stratification tools pivotal in early detection, management, and improving patient outcomes.
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