Abstract
The majority of firearm injuries involve the extremities and have concomitant orthopaedic injuries. National data on the epidemiology of wounds caused by firearms may better inform physicians and identify areas of public health intervention. We conducted an analysis of a national database to describe the epidemiology of orthopaedic firearm injuries in the United States. The Nationwide Inpatient Sample 2001–2013 database was queried for adult patients with fractures excluding those of the skull using injury billing codes. Characterization of injury was determined using External Cause of Injury billing codes. Sociodemographic and geographic variables were reported. Chi square and multinomial logistic regression analyses were performed to identify predictors of type of firearm implicated in injury. 334,212 firearm injuries were reported in the database and about half had concomitant orthopaedic fractures. Most patients were between the ages 19 and 29, were African American, and were male. The most frequent circumstance of injury was assault/homicide, the most common firearm used was a handgun, and the most common fracture site was the femur. Patients without insurance and patients of lower income were most commonly afflicted. Knowing this distribution of the burden of this class of injury provides the opportunity to identify and intervene on behalf of at-risk populations, potentially reducing injuries by promoting firearm safety to these groups and advocating sensible practices to reduce inequitable outcomes caused by these injuries.
1. Introduction
Gun violence has been the subject of recent contentious debate in the United States. Approximately 29% of adult residents own firearms,1 contributing to the comparatively high rates of gun-related homicides and accidental deaths.2,3 In addition to the high incidence of consequent mortality and disability, estimates on healthcare expenditure on these injuries are greater than $2 billion dollars annually4 and cause over $20 billion in lifetime work loss and medical costs.5 National data suggests an increasing burden of firearm related injuries in the United States, but the risk of injury is not evenly distributed within society, with variations in race, social status, gender, and geographic location.6, 7, 8 As the profession responsible for treating these injuries, physicians must be aware of the epidemiology and nature of wounds due to firearms. Understanding the mechanism and nature of trauma in this way is paramount to developing new practice guidelines on an individual and public health level.
Musculoskeletal injuries constitute a large proportion of firearm-related admissions, with reports of frequent involvement of the hand (30%),9 extremities (48–76%),10,11 spine (26%),12 and pelvis (31%).12 The majority of these injuries are caused by assault or accident.5,12 Most of the available literature reports the epidemiology of gunshot wounds in various subsets of patients, such as pediatric patients,12,13 or in specific anatomic locations, such as the spine14 or hand,9 or are limited to single institutions or small geographic areas. Other studies in orthopaedics report national trends but do not specify the specific bone involved in the fracture.8,10 Few studies aggregate data on the type of firearm used, nature of injury, and specific clinicopathologic factors on the same set of patients to provide a comprehensive picture of firearm epidemiology in the United States. We therefore performed an analysis of a nationwide dataset that synthesizes this information relevant to the study of orthopaedic firearm injuries.
2. Methods
2.1. Data set
A retrospective analysis was conducted on the Nationwide Inpatient Sample (NIS) 2001–2013 database. The NIS is a national database created by the Agency for Healthcare Research and Quality and maintained by the Healthcare Cost and Utilization Project (HCUP). It approximates a 20% stratified sample of all discharges from U.S. community hospitals, including specialty hospitals and academic medical centers while excluding rehabilitation centers, surgical centers, and long-term acute care hospitals.15 The NIS is the largest publicly available all-payer inpatient database in the United States, and its utilization continues to increase due to its accessibility and validated methodology.16
Its unique design requires specific methodological considerations that are detailed in the available online tutorials and documentation prior to analysis.17 In particular, a change in sampling strategy took place beginning with 2012 data, resulting in the need to apply trend weights for all subsequent years. Following these recommendations, data were weighted using HCUP provided trend and discharge weights for their appropriate years.
The NIS 2001–2013 dataset was queried for adult patients discharged with a diagnosis of a fracture of bones excluding those of the skull using ICD-9 diagnosis codes. Mechanism and characterization of injury was determined by using ICD-9 External Cause of Injury codes (E-codes, Table 1). The ICD-9 E-code system specifies type of firearm used, including handgun, shotgun, hunting rifle, military firearm, and air gun, and classification of injury, including assault/homicide, suicide, accident, or legal intervention. Patients were only included if they had E-codes specifically related to firearms. Patients with missing E-code data were not included, as the cause of injury was not specified. As this study does not involve human subjects, it was exempt from Institutional Review Board (IRB) approval as per our institution’s policy.
Table 1.
Definitions of external cause of injury codes used for data extraction.
| E code | Description |
|---|---|
| E922.0 | Accident caused by handgun |
| E922.1 | Accident caused by shotgun |
| E922.2 | Accident caused by hunting rifle |
| E922.3 | Accident caused by military firearms |
| E922.4 | Accident caused by air gun |
| E955.0 | Suicide and self-inflicted injury by handgun |
| E955.1 | Suicide and self-inflicted injury by shotgun |
| E955.2 | Suicide and self-inflicted injury by hunting rifle |
| E955.3 | Suicide and self-inflicted injury by military firearms |
| E955.4 | Suicide and self-inflicted injury by other and unspecified firearm |
| E955.6 | Suicide and self-inflicted injury by air gun |
| E965.0 | Assault by handgun |
| E965.1 | Assault by shotgun |
| E965.2 | Assault by hunting rifle |
| E965.3 | Assault by military firearms |
| E965.4 | Assault by other and unspecified firearm |
| E970 | Injury due to legal intervention by firearms |
| E985.0 | Injury by handgun, undetermined whether accidently or purposely inflicted |
| E985.1 | Injury by shotgun, undetermined whether accidently or purposely inflicted |
| E985.2 | Injury by hunting rifle, undetermined whether accidently or purposely inflicted |
| E985.3 | Injury by military firearms, undetermined whether accidently or purposely inflicted |
| E985.4 | Injury by other and unspecified firearm, undetermined whether accidently or purposely |
| E985.6 | Injury by air gun, undetermined whether accidental or purposely inflicted |
2.2. Outcomes and statistical analysis
In order to assess epidemiology of firearm related fractures, the frequency of implicated firearm type and characterization of injury was extracted. Sociodemographic, geographic, insurance, and median income quartile data were also extracted. In each case, the presence of fracture was assumed to be caused by the firearm specified in the corresponding E-code. We also analyzed our data for variables associated with type of firearm implicated in the injury through chi square and multinomial logistic regression analyses. Significance was defined as p < 0.05.
3. Results
3.1. Demographic data
There 334,212 gunshot injuries were reported in the NIS database, and 162,424 (50%) had concomitant orthopaedic fractures. Patients between the ages of 19 and 29, African Americans, and males were the predominant demographics in this population. The majority of patients were uninsured and were admitted in the South Atlantic region, though only 18% had data available on geographic location (Table 2).
Table 2.
Demographic data.
| Variable | Frequency |
|---|---|
| Age | |
| 19-29 | 39,237 (47.6%) |
| 30-50 | 25,119 (30.5%) |
| 51-60 | 3858 (4.7%) |
| 61-79 | 2203 (2.7%) |
| ≥80 | 306 (0.4%) |
| Race | |
| Caucasian | 16,878 (20.5%) |
| African American | 36,703 (44.5%) |
| Hispanic | 11,242 (13.6%) |
| Other | 3131 (3.8%) |
| Unknown | 14,435 (17.5%) |
| Gender | |
| Female | 7294 (8.9%) |
| Median Income Quartiles | |
| 1 | 42,152 (51.2%) |
| 2 | 19,357 (23.5%) |
| 3 | 12,391 (15%) |
| (highest) 4 | 5863 (7.1%) |
| Insurance Status | |
| Private | 18,286 (22.2%) |
| Medicaid | 22,240 (27%) |
| Medicare | 3309 (4.0%) |
| Uninsured | 27,941 (33.9%) |
| Other | 9682 (11.8%) |
| Region | |
| New England | 325 (0.4%) |
| Middle Atlantic | 1855 (2.3%) |
| East North Central | 2505 (3%) |
| West North Central | 890 (1.1%) |
| South Atlantic | 3405 (4.1%) |
| East South Central | 1345 (1.6%) |
| West South Central | 1665 (2%) |
| Mountain | 830 (1%) |
| Pacific | 1960 (2.4%) |
| Missing | 67,609 (82.1%) |
3.2. Firearm-related data
Mortality was low in our study population (0.4%). Weekend admissions comprised 37% of the cohort, and the most frequent circumstance of injury was assault/homicide. The most common firearm used was a handgun, and the most common fracture site was the femur (Table 3). After accounting for other sociodemographic variables, African American patients were more likely to have been injured by handguns, shotguns, and military-style firearms when compared to Caucasians. Patients who were uninsured had increased likelihood of injury by handguns, shotguns, and hunting rifles compared to those with private insurance. Patients with Medicare had decreased likelihood of injury by shotgun, and patients with Medicaid had decreased likelihood of injury by hunting rifles. Patients in the highest income quartile had decreased risk of injury across all firearm types (Table 4).
Table 3.
Descriptive data on firearm injuries.
| Variable | Frequency | Variable | Frequency |
|---|---|---|---|
| Nature of Injury | Admission month | ||
| Accident | 23,402 (28.4%) | January | 5841 (7.1%) |
| Assault/Homicide | 51,710 (62.8%) | February | 4588 (5.6%) |
| Suicide | 1738 (2.1%) | March | 5409 (6.6%) |
| Legal Intervention | 1477 (1.8%) | April | 6035 (7.3%) |
| Undetermined | 4201 (5.1%) | May | 6477 (7.9%) |
| Firearm Used | June | 6521 (7.9%) | |
| July | 7231 (8.8%) | ||
| Handgun | 26,296 (31.9%) | August | 6928 (8.4%) |
| Shotgun | 5558 (6.7%) | September | 6687 (8.1%) |
| Hunting Rifle | 2621 (3.2%) | October | 6231 (7.6%) |
| Military | 302 (0.4%) | November | 6485 (7.9%) |
| Air gun | 230 (0.3%) | December | 6579 (8.0%) |
| Unspecified | 46,759 (56.8%) | ||
| Location of Fracture | Mortality | 367 (0.4%) | |
| Clavicle | 1176 (1.4%) | Weekend Admission | 30,071 (36.5%) |
| Radius/Ulna | 9408 (11.4%) | ||
| Humerus | 9251 (11.2%) | ||
| Spine | 8743 (10.6%) | ||
| Carpal | 1196 (1.5%) | ||
| Metacarpal | 5503 (6.7%) | ||
| Phalanx | 5633 (6.8%) | ||
| Sacrum/Coccyx | 160 (0.2%) | ||
| Rib | 3464 (4.2%) | ||
| Scapula | 3259 (4.0%) | ||
| Pelvis | 4564 (5.5%) | ||
| Femur | 21,044 (25.5%) | ||
| Patella | 1765 (2.1%) | ||
| Tibia/Fibula | 14,740 (17.9%) | ||
| Foot/Ankle | 7111 (8.6%) | ||
| Multiple/Ill-Defined | 954 (1.2%) | ||
Table 4.
Predictors of type of firearm implicated in injury.
| Handgun | Shotgun | Hunting Rifle | Military | |||||
|---|---|---|---|---|---|---|---|---|
| OR (95% CI) | P value | OR (95% CI) | P value | OR (95% CI) | P value | OR (95% CI) | P value | |
| Age (years) | 1.05 (1.04–1.07) | <0.001a | 1.05 (1.03–1.06) | <0.001a | 1.04 (1.02–1.05) | <0.001a | 1.06 (1.04–1.07) | <0.001a |
| Race | ||||||||
| Caucasian | Reference | |||||||
| Hispanic | 0.96 (0.66–1.39) | 0.822 | 0.86 (0.59–1.26) | 0.437 | 0.21 (0.14–0.32) | <0.001a | 0.93 (0.54–1.62) | 0.800 |
| African American | 4.98 (3.18–7.79) | <0.001a | 2.72 (1.73–4.28) | <0.001a | 1.17 (0.74–1.85) | 0.513 | 5.52 (3.2–9.53) | <0.001a |
| Other | 0.53 (0.33–0.84) | 0.008a | 0.53 (0.33–0.86) | 0.010a | 0.21 (0.13–0.36) | <0.001a | 1.19 (0.61–2.32) | 0.615 |
| Males (vs. Females) | 0.42 (0.22–0.82) | 0.011a | 0.41 (0.21–0.81) | 0.010a | 0.43 (0.22–0.85) | 0.016a | 0.29 (0.14–0.62) | 0.001a |
| Insurance Status | ||||||||
| Private | Reference | |||||||
| Uninsured | 1.97 (1.29–3.01) | 0.002a | 2.64 (1.72–4.07) | <0.001a | 1.74 (1.12–2.69) | 0.014a | 1.38 (0.79–2.43) | 0.257 |
| Medicare | 0.47 (0.22–1) | 0.051 | 0.41 (0.19–0.9) | 0.025a | 0.63 (0.29–1.37) | 0.244 | – | – |
| Medicaid | 0.89 (0.62–1.29) | 0.543 | 1.28 (0.88–1.87) | 0.191 | 0.61 (0.41–0.91) | 0.014a | 0.87 (0.52–1.46) | 0.594 |
| Other | 3.08 (1.57–6.06) | 0.001a | 3.4 (1.71–6.72) | <0.001a | 2.2 (1.1–4.41) | 0.026a | 7.29 (3.41–15.57) | <0.001a |
| Median Income Quartile | ||||||||
| 1 | Reference | |||||||
| 2 | 0.79 (0.55–1.14) | 0.211 | 0.71 (0.49–1.03) | 0.072 | 0.71 (0.49–1.05) | 0.083 | 1.09 (0.68–1.75) | 0.715 |
| 3 | 1.03 (0.66–1.6) | 0.913 | 0.84 (0.53–1.32) | 0.448 | 0.67 (0.42–1.07) | 0.093 | 1.4 (0.8–2.43) | 0.236 |
| 4 (highest) | 0.44 (0.28–0.67) | <0.001a | 0.36 (0.23–0.56) | <0.001a | 0.36 (0.23–0.57) | <0.001a | 0.1 (0.04–0.27) | <0.001a |
Δ Reference.
- Not included due to insufficient numbers for analysis.
Indicates significance defined as p < 0.05 with air gun as reference category.
4. Discussion
This study presents a comprehensive epidemiologic study of bone fractures caused by firearms using a nationally representative dataset. Our data highlight the magnitude, mechanism, and epidemiology of these injuries. We find that half of firearm-related injuries involve orthopaedic fractures and that there is considerable variability in the sociodemographic and clinicopathologic characteristics of these injuries.
Studies investigating firearm violence report a disproportionately large majority of injuries among non-Caucasian patients, immigrants, and those in low-income areas.5,18,19 This contributes, among many other factors, to the lower life expectancy of African Americans males compared to that of Caucasian males.20 This effect may be explainable by differing life experiences in children of different races. In environments where gun violence is more prevalent, children may have more interactions with firearms, increasing the likelihood of injury.21 While ethnic minorities are more likely to experience violence from firearms, Caucasians are at increased risk of unintentional harm and/or suicide.21 Public health interventions that target these group are needed to address structural differences in society related to gun injuries.
Our data on age and gender is in further agreement with the existing literature,9,22,23 with the majority of patients being younger (48% between age 19 and 29) and male (91%). Younger patients may be more likely to sustain injuries due to inexperience in handling firearms, behavioral factors, or improper transport of weapons. Notably, studies have shown that children develop a curiosity for firearms at a young age,24 emphasizing the importance of proper handling and storage of firearms.25 While our study did not include pediatric patients, education about gun safety may be necessary to preventing unnecessary injury and has been shown to be effective when provided with free or low-cost safety devices.26, 27, 28
Patients in our population were often uninsured (34%) or had publicly funded health insurance (31% Medicare and Medicaid, combined), which has also been found in pediatric populations.11 Most patients were also in the lowest income quartile (51%), fitting with existing data on firearm violence and income levels.29,30 It is well established that patients with low income are at an increased risk for interpersonal violence.26 This discrepancy is corroborated by our findings and, in addition to differences in education and housing, may represent a target area of public health intervention. Although the majority of patients with available geographic data were in the southern United States (43%), similar to other studies,5 most data were missing, so meaningful conclusions cannot be made.
Mortality was low in our study population (0.4%). While some studies report the majority of firearm deaths are caused by suicide,5,31 we find that only 13% of deaths were by means of suicide. However, most suicides caused by firearms involve wounds to the head and oral cavity,31 which were not identified in this dataset, and are often fatal, with only about one-third of patients surviving long enough to arrive at a hospital.32 Of those that died in our population, 75% (n = 272) involved fractures to the spine and 53% were by means of assault/homicide. We therefore show that most patients with firearm-related orthopaedic fractures survive their injuries but are at greatest risk of mortality if spinal injuries are present. A possible mechanistic explanation might be that spinal injuries are more likely to have concomitant injuries to the nearby critical organs and vessels.
The most common firearm implicated in these injuries is a handgun (32%). The majority of firearms owned in the United States are handguns,31 but studies show shotguns are also used in a large number of suicides and homicides.33,34 We find that assault/homicide was the most common mechanism of injury (63%), and the most frequently used firearm was a handgun (83% of assault/homicide victims with a record of a specified firearm), though 63% of cases did not have a specified firearm. Similarly, of patients who attempted suicide and had record of a specified firearm, handguns were most frequently implicated (66%).
The healthcare burden of firearms extends well beyond the immediate consequences of the injury. Patients hospitalized with gunshot wounds often have long term sequelae, such as permanent disability,35 early osteoarthritis and bone loss,36 and development of post-traumatic mental health disorders.37 We find that a large proportion of fractures took place in the hand (15%), upper extremity (39%), and lower extremity (54%), reflecting the impact these injuries have on lifestyle and executive function. Management typically involves fracture fixation, debridement, revascularization, amputations, replantations, nerve repair, bone lengthening, or tendon transfers and is not without considerable risk. Medium to poor functional outcomes can occur in up to 31% of patients with extremity injuries caused by shotguns or rifles, and these patients are also at risk for ICU admission, reoperation, and infection,38 reflecting the burden these fractures have on patients and the healthcare system.
Numerous initiatives have been developed to target use of firearms in the United States in recent years, which reflects a change from previous policy. Congressional restrictions have prevented research and study of firearm violence for the past several decades.39, 40, 41 In patient populations that are afflicted by firearm violence, however, knowledge of firearm-related injuries can be invaluable in creating policies directed at education about proper handling of firearms and the development of appropriate access to them. Physicians where permitted may consider screening patients for gun ownership, knowledge of proper handling, substance use, and general safety in their environment. Such data will also allow for proper resource allocation and development of programs to improve organization and socioeconomic status of community members, both independent risk factors for gun violence.42
There are several important limitations to our study. While the NIS database offers the advantage of providing national epidemiologic information on firearm-related injuries, it does not provide detailed, granular information about each patient. Furthermore, some variables of interest were missing from a large number of patients, such as geographic area and type of firearm used, which may have altered our results if they were included. As our study focused primarily on orthopaedic fractures (i.e., fractures below the skull), patients with head trauma were not specifically evaluated, which may affect our mortality data. The database also has inherent selection bias, since data only comes from patients who have been treated as inpatients. Finally, the reliability of our data is dependent on the accurate reporting of all studied variables. While use of ICD-9 and E-codes are highly useful for analysis, it is important to remember that limitations in the codes’ specificity or in the coders’ ability to gauge the situation may impact their accuracy. Importantly, it may not always be apparent the type of weapon used in the injury, which adds some small degree of uncertainty to the conclusion. The NIS reports billing data from a patient’s discharge record, so any errors made during this process may change our conclusions.
5. Conclusions
African Americans and males between the ages of 19 and 29 were the demographic populations most commonly afflicted with firearm injuries. The most common location of fracture was the femur and the mechanism is most commonly by assault or homicide with a handgun. These patients are often from a low-income background and commonly do not have insurance. The geographic and demographic diversity of the data set used will hopefully provide physicians and educators with a more complete picture of the orthopaedic impacts of firearms.
These data may better inform the debate about the magnitude of gun violence in the United States and lead to sound public health interventions that can be applied to clinical practice. With a clearer image of the landscape, this may also be the basis of further work to develop treatment algorithms targeted toward specific subsets of these injuries.
Funding sources
None.
CRediT authorship contribution statement
Dominick V. Congiusta: Conceptualization, Investigation, Methodology, Project administration, Writing - original draft, Writing - review & editing, Resources. Jason Paul Oettinger: Investigation, Writing - original draft, Writing - review & editing, Resources. Aziz M. Merchant: Conceptualization, Project administration, Writing - original draft, Writing - review & editing, Supervision. Michael M. Vosbikian: Conceptualization, Project administration, Writing - original draft, Writing - review & editing, Supervision. Irfan H. Ahmed: Conceptualization, Project administration, Writing - original draft, Writing - review & editing, Supervision.
Declarations of competing interest
None.
Acknowledgements
None.
Contributor Information
Dominick V. Congiusta, Email: dvc33@njms.rutgers.edu.
Jason Paul Oettinger, Email: jason.oettinger@rutgers.edu.
Aziz M. Merchant, Email: am1771@njms.rutgers.edu.
Michael M. Vosbikian, Email: vosbikmm@njms.rutgers.edu.
Irfan H. Ahmed, Email: ahmedi2@njms.rutgers.edu.
References
- 1.Kalesan B., Villarreal M.D., Keyes K.M., Galea S. Gun ownership and social gun culture. Inj Prev. 2016;22:216–220. doi: 10.1136/injuryprev-2015-041586. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Richardson E.G., Hemenway D. Homicide, suicide, and unintentional firearm fatality: comparing the United States with other high-income countries. J Trauma. 2003;70:238–243. doi: 10.1097/TA.0b013e3181dbaddf. 2011. [DOI] [PubMed] [Google Scholar]
- 3.National Center for Injury Prevention and Control: Centers for Disease Control and Prevention . WISQARS; 2019. Leading Causes of Injury Death Highlighting Violence. 2016. [Google Scholar]
- 4.Cook P.J., Lawrence B.A., Ludwig J., Miller T.R. The medical costs of gunshot injuries in the United States. J Am Med Assoc. 1999;282:447–457. doi: 10.1001/jama.282.5.447. [DOI] [PubMed] [Google Scholar]
- 5.Fowler K.A., Dahlberg L.L., Haileyesus T., Annest J.L. Firearm injuries in the United States. Prev Med. 2015;79:5–14. doi: 10.1016/j.ypmed.2015.06.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Kalesan B., Dabic S., Vasan S., Stylianos S., Galea S. Racial/ethnic specific trends in pediatric firearm-related hospitalizations in the United States, 1998-2011. Matern Child Health J. 2016;20:1082–1090. doi: 10.1007/s10995-015-1894-8. [DOI] [PubMed] [Google Scholar]
- 7.Guileyardo J.M., Carmody T.J., Lene W.J., Stone I.C. Racial and ethnic patterns in firearms deaths. Am J Forensic Med Pathol. 1994;15:328–330. doi: 10.1097/00000433-199412000-00008. [DOI] [PubMed] [Google Scholar]
- 8.Jehan F., Pandit V., O’Keeffe T. The burden of firearm violence in the United States: stricter laws result in safer states. J Inj Violence Res. 2018;10:11–16. doi: 10.5249/jivr.v10i1.951. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Hutchinson A.J., Kusnezov N.A., Dunn J.C., Rensing N., Prabhakar G., Pirela-Cruz M.A. Epidemiology of gunshot wounds to the hand. Hand Surg Rehabil. 2019;38:14–19. doi: 10.1016/j.hansur.2018.10.240. [DOI] [PubMed] [Google Scholar]
- 10.Vyrostek S.B., Annest J.L., Ryan G.W. Surveillance for fatal and nonfatal injuries--United States, 2001. MMWR Surveill Summ. 2004;53:1–57. [PubMed] [Google Scholar]
- 11.Carter P.M., Cook L.J., Macy M.L. Individual and neighborhood characteristics of children seeking emergency department care for firearm injuries within the PECARN network. Acad Emerg Med. 2017;24:803–813. doi: 10.1111/acem.13200. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Blumberg T.J., DeFrancesco C.J., Miller D.J., Pandya N.K., Flynn J.M., Baldwin K.D. Firearm-associated fractures in children and adolescents: trends in the United States 2003-2012. J Pediatr Orthop. 2018;38:e387–e392. doi: 10.1097/BPO.0000000000001193. [DOI] [PubMed] [Google Scholar]
- 13.Carter CW, Sharkey MS, Fishman F. Firearm-related musculoskeletal injuries in children and adolescents. J Am Acad Orthop Surg.35:169-178. [DOI] [PubMed]
- 14.Piatt J. Penetrating spinal injury in childhood: the influence of mechanism on outcome. An epidemiological study. J Neurosurg Pediatr. 2018;22:384–392. doi: 10.3171/2018.3.PEDS1890. [DOI] [PubMed] [Google Scholar]
- 15.Healthcare Cost and Utilization Project. Overview of the National (Nationwide) Inpatient Sample (NIS) 2018. [Google Scholar]
- 16.Shourt C.A., Crowson C.S., Gabriel S.E., Matteson E.L. Orthopedic surgery among patients with rheumatoid arthritis 1980-2007: a population-based study focused on surgery rates, sex, and mortality. J Rheumatol. 2012;39:481–485. doi: 10.3899/jrheum.111056. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Nikiphorou E., Carpenter L., Morris S. Hand and foot surgery rates in rheumatoid arthritis have declined from 1986 to 2011, but large-joint replacement rates remain unchanged: results from two UK inception cohorts. Arthritis Rheum. 2014;66:1081–1089. doi: 10.1002/art.38344. [DOI] [PubMed] [Google Scholar]
- 18.Saunders N.R., Lee H., Macpherson A., Guan J., A G. Risk of firearm injuries among children and youth of immigrant families. CMAJ (Can Med Assoc J) 2017;189:e452–e458. doi: 10.1503/cmaj.160850. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Crutcher C.L., 2nd, Fannin E.S., Wilson J.D. Racial disparities in cranial gunshot wounds: intent and survival. J Racial Ethn Health Disparities. 2016;3:687–691. doi: 10.1007/s40615-015-0187-7. [DOI] [PubMed] [Google Scholar]
- 20.Kochanek K.D., Arias E., Anderson R.N. How did cause of death contribute to racial differences in life expectancy in the United States in 2010? NCHS Data Briefe. 2013;125:1–8. [PubMed] [Google Scholar]
- 21.Kalesan B., Vyliparambil M.A., Bogue E. Race and ethnicity, neighborhood poverty and pediatric firearm hospitalizations in the United States. Ann Epidemiol. 2016;26:1–6. doi: 10.1016/j.annepidem.2015.10.009. e1-2. [DOI] [PubMed] [Google Scholar]
- 22.Turker T., Capdarest-Arest N. Management of gunshot wounds to the hand: a literature review. J Hand Surg Am. 2013;38:1641–1650. doi: 10.1016/j.jhsa.2013.02.011. [DOI] [PubMed] [Google Scholar]
- 23.Karaca M.A., Kartal N.D., Erbil B. Evaluation of gunshot wounds in the emergency department. Ulus Travma Acil Cerrahi Derg. 2015;21:248–255. doi: 10.5505/tjtes.2015.64495. [DOI] [PubMed] [Google Scholar]
- 24.Hardy M.S., Armstrong F.D., Martin B.L., Strawn K.N. A firearm safety program for children: they just can’t say no. J Dev Behav Pediatr. 1996;17:216–221. [PubMed] [Google Scholar]
- 25.Kellermann A.L., Rivara F.P. Silencing the science on gun research. J Am Med Assoc. 2013;309:549–550. doi: 10.1001/jama.2012.208207. [DOI] [PubMed] [Google Scholar]
- 26.Bulger E.M., Kuhls D.A., Campbell B.T. Proceedings from the medical summit on firearm injury prevention: a public health approach to reduce death and disability in the US. J Am Coll Surg. 2019;S1072–7515 doi: 10.1016/j.jamcollsurg.2019.05.018. 30339-30334. [DOI] [PubMed] [Google Scholar]
- 27.Rowhani-Rahbar A., Simonetti J.A., Rivara F.P. Effectiveness of interventions to promote safe firearm storage. Epidemiol Rev. 2016;38:111–124. doi: 10.1093/epirev/mxv006. [DOI] [PubMed] [Google Scholar]
- 28.Barkin S.L., Finch S.A., Ip E.H. Is office-based counseling about media use, timeouts, and firearm storage effective? Results from a cluster-randomized, controlled trial. Pediatrics. 2008;122:e15–e25. doi: 10.1542/peds.2007-2611. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Rowhani-Rahbar A., Quistberg D.A., Morgan E.R., Hajat A., Rivara F.P. Income inequality and firearm homicide in the US: a county-level cohort study. Inj Prev. 2019;25(Suppl 1):i25–i30. doi: 10.1136/injuryprev-2018-043080. Epub 2019 Feb 19. [DOI] [PubMed] [Google Scholar]
- 30.Beard J.H., Morrison C.N., Jacoby S.F. Quantifying disparities in urban firearm violence by race and place in philadelphia, Pennsylvania: a cartographic study. Am J Publ Health. 2017;107:371–373. doi: 10.2105/AJPH.2016.303620. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Molina D.K., DiMaio V.J., Cave R. Handgun wounds: a review of range and location as pertaining to manner of death. Am J Forensic Med Pathol. 2013;34:342–347. doi: 10.1097/PAF.0000000000000048. [DOI] [PubMed] [Google Scholar]
- 32.Blissitt P. Care of the critically ill patient with penetrating head injury. Crit Care Nurs Clin. 2006;18:321–332. doi: 10.1016/j.ccell.2006.05.006. [DOI] [PubMed] [Google Scholar]
- 33.Avis S.P. Suicidal gunshot wounds. Forensic Sci Int. 1994;67:41–47. doi: 10.1016/0379-0738(94)90410-3. [DOI] [PubMed] [Google Scholar]
- 34.Molina D.K., Wood L.E., DiMaio V.J. Shotgun wounds: a review of range and location as pertaining to manner of death. Am J Forensic Med Pathol. 2007;28:99–102. doi: 10.1097/01.paf.0000257415.82728.d7. [DOI] [PubMed] [Google Scholar]
- 35.DiScala C., Sege R. Outcomes in children and young adults who are hospitalized for firearms-related injuries. Pediatrics. 2004;113:1306–1312. doi: 10.1542/peds.113.5.1306. [DOI] [PubMed] [Google Scholar]
- 36.Schildhauer T.A., Bellabarba C., Selznick H.S., McRoberts D., Vedder N.B., Chapman J.R. Unstable pediatric sacral fracture with bone loss caused by a high-energy gunshot injury. J Trauma. 2007;63:e95–e99. doi: 10.1097/01.ta.0000246879.13468.32. [DOI] [PubMed] [Google Scholar]
- 37.Greenspan A.I., Kellermann A.L. Physical and psychological outcomes 8 months after serious gunshot injury. J Trauma. 2002;53:709–716. doi: 10.1097/00005373-200210000-00015. [DOI] [PubMed] [Google Scholar]
- 38.Ignatiadis I.A., Mavrogenis A.F., Igoumenou V.G. Gunshot and blast injuries of the extremities: a review of 45 cases. Eur J Orthop Surg Traumatol. 2019;29:295–305. doi: 10.1007/s00590-018-2350-4. [DOI] [PubMed] [Google Scholar]
- 39.Nance M.L., Krummel T.M., Oldham K.T. Firearm injuries and children: a policy statement of the American Pediatric Surgical Association. J Am Coll Surg. 2013;217:940–946. doi: 10.1016/j.jamcollsurg.2013.07.381. [DOI] [PubMed] [Google Scholar]
- 40.Omnibus consolidated appropriations act. 104th Congress. 1997 Accessed October 12, 2020. [Google Scholar]
- 41.Omnibus consolidated appropriations act. 112th Congress. 2012 [Google Scholar]
- 42.Schmidt C.J., Rupp L., Pizarro J.M., Lee D.B., Branas C.C., Zimmerman M.A. Risk and protective factors related to youth firearm violence: a scoping review and directions for future research. J Behav Med. 2019;42:706–723. doi: 10.1007/s10865-019-00076-7. [DOI] [PMC free article] [PubMed] [Google Scholar]