Boxing-Related Maxillofacial and Orbital Trauma: A Retrospective NEISS Database Analysis of Injury Patterns and Emergency Diagnostic Prioritization (2014–2023)

Boxing-Related Maxillofacial and Orbital Trauma: A Retrospective NEISS Database Analysis of Injury Patterns and Emergency Diagnostic Prioritization (2014–2023) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Boxing-Related Maxillofacial and Orbital Trauma: A Retrospective NEISS Database Analysis of Injury Patterns and Emergency Diagnostic Prioritization (2014–2023) Daniel Lynch, Lorenzo Petralia, John Komlos, Troy Puetz, Sarah Peterson, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9431789/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Introduction/Background: Using the National Electronic Injury Surveillance System (NEISS) database, this study analyzes boxing-related maxillofacial and orbital injuries presenting to emergency departments nationwide, identifying injury patterns to better equip clinicians for accurate diagnosis and optimized patient outcomes. Objective(s): To characterize the distribution of boxing-related maxillofacial injuries requiring hospitalization from 2014–2023 and to establish evidence-based diagnostic and management priorities for emergency physicians, ophthalmologists, and surgeons. Methods — Design: Retrospective national database analysis. IRB approval was not required as only publicly available data were utilized. Setting: Statistically representative sample of U.S. hospital emergency departments via the NEISS database. Participants: Patients presenting to emergency departments with boxing-related head and neck injuries (eye, head, face, mouth, ear) from 2014–2023 (n = 1,012 maxillofacial hospitalizations from 37,203 total national admissions). Excluded: extremity/torso injuries; burns, toxicology, amputation, electroshock, or submersion. Interventions: Not applicable (observational/database study). Main Outcome Measures: Annual incidence of boxing-related maxillofacial injuries, anatomical distribution of injury location, frequency of specific diagnoses at hospitalization, and burden index (maxillofacial injuries per 1,000 boxing ER admissions). Results: Analysis of NEISS data from 2014–2023 revealed mandibular fractures (35%) and orbital floor blowout fractures (30%) as the predominant causes of hospitalized boxing-related maxillofacial injuries. Concussions accounted for 15%, followed by nasal septal hematomas (10%), subdural hematomas (5%), and other facial fractures (5%). Head (43.0%) and face (37.3%) together accounted for >80% of all admissions. A strong positive Pearson correlation was identified between ER admissions and maxillofacial injuries (r = 0.893, p = 0.0005). Diagnosis distribution was significantly non-uniform (χ² = 139.1, p < 0.001). Conclusion: These findings give emergency physicians and surgeons actionable diagnostic guidance for boxing-related trauma. The predominance of orbital floor blowout and mandibular fractures supports maxillofacial CT with fine-cut orbital views as the initial imaging modality, while altered mental status, concussive syndromes, or neurologic compromise should prompt non-contrast head CT to rule out acute intracranial hemorrhage. Recognizing these patterns enables faster, more accurate management of ophthalmic and maxillofacial injuries, reducing morbidity and improving outcomes. Boxing injuries Maxillofacial trauma Orbital floor fracture Mandibular fracture NEISS database Emergency diagnostic prioritization Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction This study employs the National Electronic Injury Surveillance System (NEISS) database to examine boxing-related maxillofacial and orbital injuries presenting to emergency departments across the United States. For the purposes of this study, maxillofacial injuries are defined as injuries involving the bones and soft tissues of the face, including the mandible, maxilla, zygomatic bones, nasal bones, and associated soft tissues. Orbital injuries are defined as those affecting the bony orbit and its contents, such as the orbital floor, surrounding rim, or globe. Boxing is characterized by repeated high-velocity closed-fist impacts, primarily directed at the head and face, which pose a substantial risk for maxillofacial and intracranial trauma. Despite this risk, sport-specific, hospitalization-level data on injury distribution and diagnostic priorities remain limited in the literature. The biomechanical features of boxing, particularly the concentration of force on the orbital and mandibular regions, elevate the risk of fractures, concussions, and vision-threatening injuries that require coordinated, subspecialty-informed management. The objective of this study is to characterize the distribution of boxing-related maxillofacial injuries requiring hospitalization from 2014–2023 using national emergency department data, and to establish evidence-based diagnostic and management priorities for emergency physicians, ophthalmologists, and surgeons. By identifying the most prevalent injury types and their statistical patterns, this analysis provides a data-driven foundation for optimizing emergency workup and expediting surgical intervention for this patient population. Methods Data for this study were sourced from the National Electronic Injury Surveillance System (NEISS), which compiles injury-related information from a representative sample of hospital emergency departments across the United States. NEISS data were accessed via the publicly available online NEISS query tool provided by the U.S. Consumer Product Safety Commission. The database employs standardized data entry and routine quality control procedures. For this analysis, all data fields required for case selection and variable construction were complete. Records lacking information on injury diagnosis, body part, or product code were excluded during the initial filtering process. As this investigation constitutes a retrospective national database analysis using only publicly available data, institutional review board (IRB) approval was not required. Inclusion criteria required the use of the Product Code for sports equipment, specifically focusing on the boxing equipment subcategory. Injuries to the head and neck region, including the eye, head, face, mouth, and ear, were selected to identify maxillofacial injuries. Eligible injury types comprised concussions, fractures, contusions, abrasions, lacerations, hematomas, dislocations, and hemorrhages reported from 2014 onward. Exclusion criteria eliminated injuries to the upper extremity, lower extremity, and torso, as well as cases classified as burns, toxicology, amputation, electroshock, or submersion. The dataset was filtered to include only records meeting these criteria. Outcome measures included the annual incidence of boxing-related maxillofacial injuries, anatomical distribution of injury locations, frequency of specific diagnoses at hospitalization, and a burden index defined as the number of maxillofacial injuries per 1,000 boxing-related emergency room admissions per year. Statistical analyses comprised Pearson and Spearman rank correlations to assess the relationship between annual boxing-related emergency room admissions and annual maxillofacial injury counts; linear regression to evaluate temporal trends; chi-square tests to examine the distribution of injury locations and diagnoses; and z-score analysis to identify statistical outliers. All analyses were conducted using standard statistical methods, and the NEISS database was accessed and queried through its public interface. Results Table 1. Total summary of ER admissions and boxing-related maxillofacial injuries (2014–2023) Total National ER Admissions: 37,203 • Total Maxillofacial Hospitalizations: 1,012 • Overall Rate: 2.7% Summary of Findings The total number of maxillofacial injuries related to boxing was calculated annually (Table 1 / Fig. 1 ). Correlation analysis was conducted to examine the relationship between annual boxing-related ER admissions and annual maxillofacial injury counts. A strong positive Pearson correlation was identified (r = 0.893, p = 0.0005), confirmed by Spearman rank correlation (ρ = 0.903, p = 0.0003). As overall boxing-related emergency visits rose nationally, the number of maxillofacial injuries rose in near-equal proportion. Linear regression produced a positive slope of + 3.55 cases/year (R² = 0.282, p = 0.114), suggesting an upward trend that did not reach statistical significance given the sample size. Notably, 2023 recorded the highest single-year maxillofacial injury count (n = 148), representing a z-score of 4.41 against the prior nine-year mean — an extreme statistical outlier more than four standard deviations above average. To further characterize the nature of this trend, a burden index was calculated as the number of maxillofacial injuries per 1,000 boxing-related ER admissions each year. This metric assesses whether individual boxing visits are becoming more dangerous over time, or whether increased case numbers reflected greater participation. Notably, the burden index remained stable over the decade, averaging 27.4 per 1,000 admissions (SD = 2.3), suggesting per-visit injury risk did not change substantially. The increase in raw maxillofacial case numbers is therefore driven by growth in overall boxing participation and ER visit volume, not by a worsening of per-encounter injury risk (Fig. 5 ). Examining the distribution of injuries provides further insight into boxing-related trauma. The head (43.0%) and face (37.3%) represented the most common anatomical sites for boxing-related injuries, together accounting for over 80% of admissions (Fig. 2 ). A chi-square test confirmed that this concentration was statistically significant (χ² = 384.3, p < 0.001), indicating that boxing trauma is predominantly localized to the head and face. The most frequent diagnoses at hospitalization were mandibular fractures and orbital floor blowout fractures (Figs. 3 , 4 ). A chi-square test applied to the diagnosis distribution likewise confirmed it was significantly non-uniform (χ² = 139.1, p < 0.001), indicating that fractures and concussions occur far more often than other injury types. Importantly, when concussions (15%) and subdural hematomas (5%) are considered together, approximately one in five hospitalized boxing maxillofacial patients carries a diagnosis with potential intracranial involvement. Discussion The data indicates that the head and face are the most common sites of injury in boxing, accounting for 43.0% and 37.3% of all maxillofacial injuries, respectively (Fig. 2 ). This distribution is statistically non-random; chi-square analysis demonstrates that boxing trauma is overwhelmingly concentrated in these two regions well beyond what chance would predict (χ² = 384.3, p < 0.001). This trend is consistent with the mechanics of boxing, where strikes primarily target the head and upper body, and protective gear, while helpful, does not entirely shield these areas. The burden index remained stable over the decade, with a mean of 27.4 per 1,000 admissions (SD = 2.3), indicating that per-visit injury risk did not change significantly during the study period. The observed increase in raw case numbers is attributable to growth in overall boxing participation and emergency department visit volume. Based on NEISS data, mandibular fractures and orbital floor blowout fractures are the most frequent causes of hospitalized boxing-related maxillofacial injuries, accounting for 35% and 30% of cases, respectively (Fig. 4 ). These injuries are particularly common in boxing due to frequent, high-impact blows to the lower face and orbital region. The mandibular region absorbs significant force during impact, increasing its susceptibility to fractures. Similarly, the orbital floor is prone to blowout fractures due to direct force transmitted to the thin bone in this area, resulting in muscle and tissue herniation into the maxillary sinus, which can lead to double vision and limited eye movement. The resulting herniation of the inferior rectus muscle produces the hallmark clinical presentation of diplopia on upgaze, enophthalmos, and periorbital ecchymosis — findings that should prompt immediate ophthalmology consultation, as untreated extraocular muscle entrapment can lead to ischemic myopathy and permanent restrictive strabismus. Given the predominance of orbital floor and mandibular fractures in this dataset, initial diagnostic evaluation for boxing-related maxillofacial injuries presenting to the emergency department should prioritize maxillofacial CT with fine-cut orbital views. This imaging modality offers the resolution required to identify fracture extent, assess the position of the inferior rectus muscle, quantify orbital volume loss, and guide oculoplastic surgical planning [3]. Concussions and subdural hematomas are also significant complications, accounting for 20% of hospitalizations in this dataset, which underscores the substantial risk of head trauma in boxing (Fig. 4 ). When a patient presents with altered mental status, concussive symptoms, or any neurological signs, the imaging workflow should prioritize ruling out intracranial hemorrhage. Specifically, a non-contrast CT of the head should be performed urgently prior to any maxillofacial imaging. After acute neurological injury has been excluded, maxillofacial CT can be obtained to assess facial injuries. This sequential approach ensures efficient and safe triage for patients with suspected facial and neurological trauma. Comparison with Existing Literature The findings of this study reveal both parallels and distinctions when compared to two major studies in combat sports injury research. The JETS study (2010) reported a 79.2% incidence of facial injuries in combat sports, with 45.1% involving bone fractures [5]. Although comprehensive, the JETS study included multiple combat disciplines (boxing, taekwondo, kickboxing, and Muay Thai), whereas the present research focuses exclusively on boxing. In this study, the majority of injuries by location were to the head (43.0%) and face (37.3%) (Fig. 2 ). This indicates a shared trend, as the JETS study identified that over 70% of injuries in combat sports are associated with facial trauma with nasal fractures as the most common type across all combat sports (84.7% of fractures) [5]. Differences in injury patterns likely reflect distinct mechanisms of injury among combat sports. Specifically, the direct anterior orbital impact from a closed fist in boxing produces a force distribution that is particularly conducive to orbital floor blowout fractures, which carry the greatest vision-threatening risk among maxillofacial boxing injuries. When comparing the findings of the present study with those of “Incidence Rates and Pathology Types of Boxing-Specific Injuries: A Systematic Review and Meta-analysis of Epidemiology Studies in the 21st Century,” both supporting and contrasting findings emerged. When analyzing NEISS data, Mao et al. reported fracture rates of 26.8% and 27.4%. These findings closely align with those of the present study. Here, mandibular fractures (35%) and orbital floor blowout fractures (30%) were the primary diagnoses at the hospitalization level. This concurrence is expected, as both studies use the same database. In contrast, the meta-analysis found a lower overall fracture rate when combining NEISS and non-NEISS studies. The rate decreased to 11.4% (95% CI, 2.7%–20.1%). This difference may reflect methodological factors such as non-NEISS studies capturing a broader range of injury severities, including minor injuries that do not require emergency care. This reduces the proportion of fractures. Conversely, NEISS and the present study focus on injuries severe enough to require emergency department presentation and admissions. This approach is better suited for characterizing high-severity injuries [6]. Regarding concussion rates, the present study identified concussion as the third most common diagnosis among hospitalized boxing patients (15% of maxillofacial hospitalizations; 20.9% of all boxing diagnoses, Fig. 3 ). This aligns with the overall concussion rate of 12.3% (95% CI, 8.7%–15.9%) reported by Mao et al. Collectively, the fracture and concussion data from Mao et al. support the methodology of the present study. While most studies, including the meta-analysis, broadly categorized injuries (laceration, contusion, fracture), our specific identification of fracture locations provides more clinically relevant data for emergency medicine and trauma providers. The NEISS database allows access to the diagnostic notes written during the time of hospitalization which may describe trends in commonly found diagnoses (Fig. 4 ). This anatomical specificity represents a meaningful contribution to the existing literature on boxing injuries. Conclusions This retrospective analysis of NEISS data (2014–2023) identifies orbital floor blowout and mandibular fractures as the leading maxillofacial injuries in boxing, making up 65% of cases (Fig. 4 ). This is consistent with boxing's biomechanics, in which fast, closed-fist impacts focus force on these vulnerable facial areas. The orbital floor, formed by thin bones, is especially prone to fracture from direct impact [1]. When fractured, orbital fat and muscle—mainly the inferior rectus—can herniate into the maxillary sinus, causing double vision, sunken eye, and limited upward gaze. The literature shows that untreated muscle entrapment can cause lasting eye movement problems [2]. Orbital floor fractures account for 30% of boxing-related hospitalizations in this dataset. Thus, maxillofacial CT with detailed orbital images should be the first scan for boxers with periorbital trauma or eye movement issues. This provides the detail needed to guide eye surgery planning [3]. Surgery is indicated for muscle entrapment, more than 2 mm of enophthalmos, or large defects, using a transconjunctival or subciliary approach and titanium mesh or polyethylene implants [2]. The literature supports the diagnostic value of a structured clinical examination prior to imaging, which is consistent with the injury profile observed in this study. H-pattern ocular motility testing evaluates muscular and neural function across all gaze directions and reliably identifies upgaze restriction indicative of inferior rectus entrapment [1]. An absent or asymmetric pupillary light response may indicate traumatic optic neuropathy or oculomotor nerve injury, both of which influence the urgency of surgical intervention. Comprehensive ophthalmic assessment should include best-corrected visual acuity, Hertel exophthalmometry to assess enophthalmos, and dilated funduscopic examination to exclude globe injury, hyphema, vitreous hemorrhage, or retinal pathology. Synthesizing these clinical findings with CT imaging establishes the evidence base for oculoplastic triage and surgical decision-making [3]. Mandibular fractures represent 35% of boxing-related maxillofacial hospitalizations and carry the greatest risk of airway compromise [4]. The anatomical structure of the mandible predisposes it to multiple fracture sites. Condylar fractures may result in temporomandibular joint dislocation and trismus. The tongue blade test provides a rapid bedside assessment of mandibular integrity, while CT imaging remains the gold standard for diagnosis and surgical planning [4]. Concussions constitute 15% of hospitalizations in this dataset, ranking as the third most common diagnosis, with subdural hematomas accounting for an additional 5%. Overall, approximately 20% of patients hospitalized for boxing-related maxillofacial injuries received a diagnosis of possible brain injury. In cases where patients present with altered mental status, concussion symptoms, or neurological deficits, clinical attention should prioritize urgent non-contrast head CT to exclude acute intracranial hemorrhage before further evaluation. The observation that one in five cases involves intracranial injury stresses the need for systematic triage protocols. The frequent co-occurrence of mandibular and orbital injuries in the zygomaticomaxillary region underscores the need for comprehensive evaluation and multidisciplinary management involving emergency medicine, radiology, ophthalmology, oculoplastic surgery, oral and maxillofacial surgery, and plastic surgery [4]. The injury distribution identified in this study indicates that orbital floor blowout fractures and mandibular fractures constitute nearly two-thirds of boxing-related maxillofacial hospitalizations. This finding supports the implementation of two distinct emergency diagnostic pathways as outlined above. The burden index, defined as the number of maxillofacial injuries per 1,000 boxing-related emergency room admissions per year, remained stable during the study period (mean 27.4, SD 2.3), indicating that the per-visit injury risk has not changed significantly over the past decade. The observed increase in maxillofacial case numbers is attributable to greater boxing participation and higher emergency room visit volumes. In 2023, maxillofacial injuries reached a peak of 148 cases, representing an extreme outlier more than four standard deviations above the previous nine-year mean. This year also recorded the highest national total of boxing-related emergency room admissions (n = 5,296). The strong correlation between emergency room visit volume and maxillofacial injury burden (Pearson r = 0.893, p < 0.001) indicates that institutions with higher boxing-related emergency volumes should anticipate proportionally increased oculoplastic and maxillofacial surgical demands (Fig. 1 ). The distribution of diagnoses was significantly non-uniform (χ² = 139.1, p < 0.001), with injuries concentrated in fractures and concussions rather than being randomly distributed. This enables emergency physicians to better anticipate the types of injuries likely to present in hospitalized boxing patients. Future research employing standardized ophthalmic outcome measures, such as visual acuity, diplopia quantification, Hertel exophthalmometry, and surgical intervention rates, would enhance the evidence base and facilitate more detailed assessment of injury severity and medical outcomes. Limitations This study has several notable limitations that should be considered when interpreting its findings. The sample size of directly confirmed maxillofacial trauma cases from boxing in the NEISS dataset is small, which restricts the statistical power of the diagnosis-level analysis and limits the ability to draw definitive conclusions about the precise prevalence of specific injuries such as mandibular and orbital floor fractures in the broader boxing population. Subgroup analyses by age, skill level (amateur versus professional), or use of protective equipment were not possible given these constraints. This study employs two separate denominators for different analyses, a methodological consideration that should be made explicit. The trend and correlation analyses use NEISS national estimates — weighted projections extrapolated to represent the full U.S. population — while the diagnosis-level breakdown is derived from the smaller set of raw hospitalization cases. These two analyses answer different questions and are not directly interchangeable; readers should interpret them in their respective contexts. The NEISS database does not capture granular ophthalmic or surgical outcome data — including visual acuity at presentation or discharge, presence and degree of diplopia, enophthalmos measurements, extraocular muscle entrapment status, surgical intervention rates, or length of stay. The database also does not record injury laterality, mechanism beyond the sport category, or post-discharge follow-up outcomes. A notable year-to-year fluctuation is observed in 2020, which recorded the lowest national boxing ER admission count (n = 2,746) and lowest maxillofacial injury count (n = 75) of the entire study period; most likely due to the COVID-19 pandemic. To address these limitations, future studies should incorporate larger datasets by combining NEISS data with complementary national databases such as the National Inpatient Sample (NIS) or the Nationwide Emergency Department Sample (NEDS). Prospective cohort studies tracking boxers over time for injury incidence and ophthalmic outcomes would offer the most comprehensive and clinically actionable data, enabling risk stratification by age, skill level, and protective equipment use, and allowing for the development of evidence-based, subspecialty-specific management guidelines. Declarations Disclosure: This research received no specific grant from funding agencies in the public, commercial, or not-for-profit sectors. IRB Statement IRB approval was not required for this manuscript as only publicly available data was included in the investigation. Competing Interests: The authors have no relevant financial or non-financial interests to disclose. Ethics Approval: This research study was conducted retrospectively using data from the National Electronic Injury Surveillance System (NEISS), a publicly available database administered by the U.S. Consumer Product Safety Commission. All data are de-identified and freely accessible. Institutional Review Board (IRB) approval was not required as no individually identifiable patient data were accessed. Consent to Participate: Not applicable. This study used only publicly available, de-identified surveillance data. Funding: No funds, grants, or other support were received for conducting this study. Author Contribution Daniel Lynch (DL): Methodology, Formal Analysis, Writing – Original Draft, (primary author)Lorenzo Petralia (LP): Formal Analysis, Writing – Original Draft (corresponding author)John Komlos (JK): Formal Analysis, Literature Review, Writing – Original Draft, Writing – Review & Editing (corresponding author)Troy Puetz (TP): Conceptualization, Writing – Original Draft, (corresponding author)Sarah Peterson (SP): Formal Analysis, Writing – Review & EditingSteiv Shore (SS): Validation, Formal Analysis, Writing – Original Draft, Writing – Review & EditingBenjamin Tinker (BT): Writing – Original Draft, Writing – Review & EditingMichael N. Megafu (MNM): Supervision, Project Administration Data Availability The data used in this study are publicly available through the NEISS online query tool provided by the U.S. Consumer Product Safety Commission at https://www.cpsc.gov/Research--Statistics/NEISS-Injury-Data. References Koenen L, Waseem M. Orbital Floor Fracture. StatPearls Publishing; updated December 15, 2023. Available at: www.ncbi.nlm.nih.gov/books/NBK534825/. Accessed October 27, 2024. Grob S, et al. Orbital Fracture Repair. Seminars in Plastic Surgery. 2017;31(01):031–039. https://doi.org/10.1055/s-0037-1598191. Grove AS. Computed Tomography in the Management of Orbital Trauma. Ophthalmology. 1982;89(5):433–440. https://doi.org/10.1016/s0161-6420(82)34770-3. Mayersak RJ, Moreira ME, Ganetsky M. Initial Evaluation and Management of Facial Trauma in Adults. UpToDate. Retrieved October 27, 2024. Caputo ND, Raja A, Shields C, Menke N. Re-evaluating the Diagnostic Accuracy of the Tongue Blade Test: Still Useful as a Screening Tool for Mandibular Fractures? J Emerg Med. 2013;45(1):8–12. doi:10.1016/j.jemermed.2012.11.078. Motamedi MHK, et al. Prevalence and Patterns of Combat Sport Related Maxillofacial Injuries. Journal of Emergencies, Trauma, and Shock. 2010;3(4):314. https://doi.org/10.4103/0974-2700.70744. Mao Y, et al. Incidence Rates and Pathology Types of Boxing-Specific Injuries: A Systematic Review and Meta-Analysis of Epidemiology Studies in the 21st Century. Orthopaedic Journal of Sports Medicine. 2023;11(3). https://doi.org/10.1177/23259671221127669. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 20 Apr, 2026 Editor assigned by journal 19 Apr, 2026 Submission checks completed at journal 19 Apr, 2026 First submitted to journal 15 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9431789","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":625990252,"identity":"224ee9c1-118b-4665-9073-97393b26e2e1","order_by":0,"name":"Daniel Lynch","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAy0lEQVRIiWNgGAWjYFAC5gMHEgzY5PihXMYGwlrYEg88KOAzlmxgJloLj/HBBx/kEjccIFaLfPsBA6DDzIyNj58//JmHwUZ2wwECWgzOJCQAtaTJmZ1JZpPmYUgzJqyFIQHk/WPGZgeS2Zh5GA4nEtQi3/+wAajlf+Lm/sfMQIf9J6yF4UYyAyiQEzdIJDMAHXaAsBaDG8/AWowlbjw2k5xjkGw8k7DD8j9//PEHGJX9iY8/vKmwk+0j6DA0S0lTPgpGwSgYBaMABwAA/vRIUCnPDZkAAAAASUVORK5CYII=","orcid":"","institution":"A.T. 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Still University – Kirksville College of Osteopathic Medicine (ATSU-KCOM)","correspondingAuthor":false,"prefix":"","firstName":"Benjamin","middleName":"","lastName":"Tinker","suffix":""},{"id":625990259,"identity":"90cba0e7-5371-4f22-8e31-1e862d9a9204","order_by":7,"name":"Michael Megafu","email":"","orcid":"","institution":"A.T. Still University – Kirksville College of Osteopathic Medicine (ATSU-KCOM)","correspondingAuthor":false,"prefix":"","firstName":"Michael","middleName":"","lastName":"Megafu","suffix":""}],"badges":[],"createdAt":"2026-04-16 01:23:44","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9431789/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9431789/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108027992,"identity":"5794e8ce-e33d-4d26-b8a8-51430564f8e6","added_by":"auto","created_at":"2026-04-28 15:29:49","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":417976,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eMaxillofacial injuries vs. national ER admissions (2014–2023). Blue bars = total national boxing ER admissions; black line = annual maxillofacial injuries with linear trend. Pearson r = 0.893, p = 0.0005. Trend slope: +3.55 cases/year (R² = 0.282, p = 0.114, NS)\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Fig1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9431789/v1/e7d87353c7fd8e5a493c735d.jpg"},{"id":108180941,"identity":"c139d2a3-f3fb-4ced-8fa2-526cae79ba82","added_by":"auto","created_at":"2026-04-30 08:55:28","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":123102,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eMost common body location of boxing injuries associated with hospital admissions (2014–2023). Head (43.0%) and face (37.3%) together account for \u0026gt;80% of all admissions\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9431789/v1/db54f11911275434498b6008.jpg"},{"id":108027994,"identity":"ec7e4099-1f24-4504-8844-03d40bdb74a4","added_by":"auto","created_at":"2026-04-28 15:29:49","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":221798,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eMost common diagnoses at hospitalization for boxing-related injuries (2014–2023). Concussion (20.9%) and internal organ injury (19.9%) were most prevalent. Distribution is significantly non-uniform (χ² = 139.1, p \u0026lt; 0.001)\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Fig3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9431789/v1/db6a22b3b1fe5d4fe544838b.jpg"},{"id":108181070,"identity":"877494ac-0532-4095-b51c-fa12d6f1e196","added_by":"auto","created_at":"2026-04-30 08:56:54","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":286908,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eMost common maxillofacial diagnoses associated with boxing trauma (2014–2023). Mandible fracture (35%) and orbital floor blowout/fracture (30%) collectively represent 65% of all maxillofacial hospitalizations\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Fig4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9431789/v1/057872a1346510e391f5fe89.jpg"},{"id":108027996,"identity":"9a3c5526-e654-47de-8aeb-73e1b33408c8","added_by":"auto","created_at":"2026-04-28 15:29:49","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":318653,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eMaxillofacial injury rate as a percentage of total boxing ER admissions per year (2014–2023). Mean annual rate was 2.7% (dashed line). Trend slope: +0.012%/year (R² = 0.020, p = 0.697, NS), indicating a stable proportional burden over the study period\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Fig5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9431789/v1/46f9714b23c5f9bab1ec2141.jpg"},{"id":108184536,"identity":"ce2f8537-bb44-45ed-848f-a1fdafa4becd","added_by":"auto","created_at":"2026-04-30 09:04:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1630910,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9431789/v1/5be54b56-b5d6-4f6f-b60e-6f4ba1b94c54.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Boxing-Related Maxillofacial and Orbital Trauma: A Retrospective NEISS Database Analysis of Injury Patterns and Emergency Diagnostic Prioritization (2014–2023)","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThis study employs the National Electronic Injury Surveillance System (NEISS) database to examine boxing-related maxillofacial and orbital injuries presenting to emergency departments across the United States. For the purposes of this study, maxillofacial injuries are defined as injuries involving the bones and soft tissues of the face, including the mandible, maxilla, zygomatic bones, nasal bones, and associated soft tissues. Orbital injuries are defined as those affecting the bony orbit and its contents, such as the orbital floor, surrounding rim, or globe. Boxing is characterized by repeated high-velocity closed-fist impacts, primarily directed at the head and face, which pose a substantial risk for maxillofacial and intracranial trauma. Despite this risk, sport-specific, hospitalization-level data on injury distribution and diagnostic priorities remain limited in the literature. The biomechanical features of boxing, particularly the concentration of force on the orbital and mandibular regions, elevate the risk of fractures, concussions, and vision-threatening injuries that require coordinated, subspecialty-informed management.\u003c/p\u003e \u003cp\u003eThe objective of this study is to characterize the distribution of boxing-related maxillofacial injuries requiring hospitalization from 2014\u0026ndash;2023 using national emergency department data, and to establish evidence-based diagnostic and management priorities for emergency physicians, ophthalmologists, and surgeons. By identifying the most prevalent injury types and their statistical patterns, this analysis provides a data-driven foundation for optimizing emergency workup and expediting surgical intervention for this patient population.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eData for this study were sourced from the National Electronic Injury Surveillance System (NEISS), which compiles injury-related information from a representative sample of hospital emergency departments across the United States. NEISS data were accessed via the publicly available online NEISS query tool provided by the U.S. Consumer Product Safety Commission. The database employs standardized data entry and routine quality control procedures. For this analysis, all data fields required for case selection and variable construction were complete. Records lacking information on injury diagnosis, body part, or product code were excluded during the initial filtering process. As this investigation constitutes a retrospective national database analysis using only publicly available data, institutional review board (IRB) approval was not required.\u003c/p\u003e \u003cp\u003eInclusion criteria required the use of the Product Code for sports equipment, specifically focusing on the boxing equipment subcategory. Injuries to the head and neck region, including the eye, head, face, mouth, and ear, were selected to identify maxillofacial injuries. Eligible injury types comprised concussions, fractures, contusions, abrasions, lacerations, hematomas, dislocations, and hemorrhages reported from 2014 onward. Exclusion criteria eliminated injuries to the upper extremity, lower extremity, and torso, as well as cases classified as burns, toxicology, amputation, electroshock, or submersion. The dataset was filtered to include only records meeting these criteria.\u003c/p\u003e \u003cp\u003eOutcome measures included the annual incidence of boxing-related maxillofacial injuries, anatomical distribution of injury locations, frequency of specific diagnoses at hospitalization, and a burden index defined as the number of maxillofacial injuries per 1,000 boxing-related emergency room admissions per year. Statistical analyses comprised Pearson and Spearman rank correlations to assess the relationship between annual boxing-related emergency room admissions and annual maxillofacial injury counts; linear regression to evaluate temporal trends; chi-square tests to examine the distribution of injury locations and diagnoses; and z-score analysis to identify statistical outliers. All analyses were conducted using standard statistical methods, and the NEISS database was accessed and queried through its public interface.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003eTable\u0026nbsp;1. Total summary of ER admissions and boxing-related maxillofacial injuries (2014\u0026ndash;2023)\u003c/b\u003e \u003c/p\u003e\u003cp\u003e\u003cimg 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\" width=\"724\" height=\"414\"\u003e\u003c/p\u003e \u003cp\u003eTotal National ER Admissions: 37,203 \u0026bull; Total Maxillofacial Hospitalizations: 1,012 \u0026bull; Overall Rate: 2.7%\u003c/p\u003e "},{"header":"Summary of Findings","content":"\u003cp\u003eThe total number of maxillofacial injuries related to boxing was calculated annually (Table\u0026nbsp;1 / Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Correlation analysis was conducted to examine the relationship between annual boxing-related ER admissions and annual maxillofacial injury counts. A strong positive Pearson correlation was identified (r\u0026thinsp;=\u0026thinsp;0.893, p\u0026thinsp;=\u0026thinsp;0.0005), confirmed by Spearman rank correlation (ρ\u0026thinsp;=\u0026thinsp;0.903, p\u0026thinsp;=\u0026thinsp;0.0003). As overall boxing-related emergency visits rose nationally, the number of maxillofacial injuries rose in near-equal proportion. Linear regression produced a positive slope of +\u0026thinsp;3.55 cases/year (R\u0026sup2; = 0.282, p\u0026thinsp;=\u0026thinsp;0.114), suggesting an upward trend that did not reach statistical significance given the sample size. Notably, 2023 recorded the highest single-year maxillofacial injury count (n\u0026thinsp;=\u0026thinsp;148), representing a z-score of 4.41 against the prior nine-year mean \u0026mdash; an extreme statistical outlier more than four standard deviations above average.\u003c/p\u003e \u003cp\u003eTo further characterize the nature of this trend, a burden index was calculated as the number of maxillofacial injuries per 1,000 boxing-related ER admissions each year. This metric assesses whether individual boxing visits are becoming more dangerous over time, or whether increased case numbers reflected greater participation. Notably, the burden index remained stable over the decade, averaging 27.4 per 1,000 admissions (SD\u0026thinsp;=\u0026thinsp;2.3), suggesting per-visit injury risk did not change substantially. The increase in raw maxillofacial case numbers is therefore driven by growth in overall boxing participation and ER visit volume, not by a worsening of per-encounter injury risk (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eExamining the distribution of injuries provides further insight into boxing-related trauma. The head (43.0%) and face (37.3%) represented the most common anatomical sites for boxing-related injuries, together accounting for over 80% of admissions (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). A chi-square test confirmed that this concentration was statistically significant (χ\u0026sup2; = 384.3, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), indicating that boxing trauma is predominantly localized to the head and face. The most frequent diagnoses at hospitalization were mandibular fractures and orbital floor blowout fractures (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). A chi-square test applied to the diagnosis distribution likewise confirmed it was significantly non-uniform (χ\u0026sup2; = 139.1, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), indicating that fractures and concussions occur far more often than other injury types. Importantly, when concussions (15%) and subdural hematomas (5%) are considered together, approximately one in five hospitalized boxing maxillofacial patients carries a diagnosis with potential intracranial involvement.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe data indicates that the head and face are the most common sites of injury in boxing, accounting for 43.0% and 37.3% of all maxillofacial injuries, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). This distribution is statistically non-random; chi-square analysis demonstrates that boxing trauma is overwhelmingly concentrated in these two regions well beyond what chance would predict (χ\u0026sup2; = 384.3, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This trend is consistent with the mechanics of boxing, where strikes primarily target the head and upper body, and protective gear, while helpful, does not entirely shield these areas. The burden index remained stable over the decade, with a mean of 27.4 per 1,000 admissions (SD\u0026thinsp;=\u0026thinsp;2.3), indicating that per-visit injury risk did not change significantly during the study period. The observed increase in raw case numbers is attributable to growth in overall boxing participation and emergency department visit volume.\u003c/p\u003e \u003cp\u003eBased on NEISS data, mandibular fractures and orbital floor blowout fractures are the most frequent causes of hospitalized boxing-related maxillofacial injuries, accounting for 35% and 30% of cases, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). These injuries are particularly common in boxing due to frequent, high-impact blows to the lower face and orbital region. The mandibular region absorbs significant force during impact, increasing its susceptibility to fractures. Similarly, the orbital floor is prone to blowout fractures due to direct force transmitted to the thin bone in this area, resulting in muscle and tissue herniation into the maxillary sinus, which can lead to double vision and limited eye movement. The resulting herniation of the inferior rectus muscle produces the hallmark clinical presentation of diplopia on upgaze, enophthalmos, and periorbital ecchymosis \u0026mdash; findings that should prompt immediate ophthalmology consultation, as untreated extraocular muscle entrapment can lead to ischemic myopathy and permanent restrictive strabismus.\u003c/p\u003e \u003cp\u003eGiven the predominance of orbital floor and mandibular fractures in this dataset, initial diagnostic evaluation for boxing-related maxillofacial injuries presenting to the emergency department should prioritize maxillofacial CT with fine-cut orbital views. This imaging modality offers the resolution required to identify fracture extent, assess the position of the inferior rectus muscle, quantify orbital volume loss, and guide oculoplastic surgical planning [3]. Concussions and subdural hematomas are also significant complications, accounting for 20% of hospitalizations in this dataset, which underscores the substantial risk of head trauma in boxing (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). When a patient presents with altered mental status, concussive symptoms, or any neurological signs, the imaging workflow should prioritize ruling out intracranial hemorrhage. Specifically, a non-contrast CT of the head should be performed urgently prior to any maxillofacial imaging. After acute neurological injury has been excluded, maxillofacial CT can be obtained to assess facial injuries. This sequential approach ensures efficient and safe triage for patients with suspected facial and neurological trauma.\u003c/p\u003e\n\u003ch3\u003eComparison with Existing Literature\u003c/h3\u003e\n\u003cp\u003eThe findings of this study reveal both parallels and distinctions when compared to two major studies in combat sports injury research. The JETS study (2010) reported a 79.2% incidence of facial injuries in combat sports, with 45.1% involving bone fractures [5]. Although comprehensive, the JETS study included multiple combat disciplines (boxing, taekwondo, kickboxing, and Muay Thai), whereas the present research focuses exclusively on boxing. In this study, the majority of injuries by location were to the head (43.0%) and face (37.3%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). This indicates a shared trend, as the JETS study identified that over 70% of injuries in combat sports are associated with facial trauma with nasal fractures as the most common type across all combat sports (84.7% of fractures) [5]. Differences in injury patterns likely reflect distinct mechanisms of injury among combat sports. Specifically, the direct anterior orbital impact from a closed fist in boxing produces a force distribution that is particularly conducive to orbital floor blowout fractures, which carry the greatest vision-threatening risk among maxillofacial boxing injuries.\u003c/p\u003e \u003cp\u003eWhen comparing the findings of the present study with those of \u0026ldquo;Incidence Rates and Pathology Types of Boxing-Specific Injuries: A Systematic Review and Meta-analysis of Epidemiology Studies in the 21st Century,\u0026rdquo; both supporting and contrasting findings emerged. When analyzing NEISS data, Mao et al. reported fracture rates of 26.8% and 27.4%. These findings closely align with those of the present study. Here, mandibular fractures (35%) and orbital floor blowout fractures (30%) were the primary diagnoses at the hospitalization level. This concurrence is expected, as both studies use the same database. In contrast, the meta-analysis found a lower overall fracture rate when combining NEISS and non-NEISS studies. The rate decreased to 11.4% (95% CI, 2.7%\u0026ndash;20.1%). This difference may reflect methodological factors such as non-NEISS studies capturing a broader range of injury severities, including minor injuries that do not require emergency care. This reduces the proportion of fractures. Conversely, NEISS and the present study focus on injuries severe enough to require emergency department presentation and admissions. This approach is better suited for characterizing high-severity injuries [6]. Regarding concussion rates, the present study identified concussion as the third most common diagnosis among hospitalized boxing patients (15% of maxillofacial hospitalizations; 20.9% of all boxing diagnoses, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). This aligns with the overall concussion rate of 12.3% (95% CI, 8.7%\u0026ndash;15.9%) reported by Mao et al. Collectively, the fracture and concussion data from Mao et al. support the methodology of the present study. While most studies, including the meta-analysis, broadly categorized injuries (laceration, contusion, fracture), our specific identification of fracture locations provides more clinically relevant data for emergency medicine and trauma providers. The NEISS database allows access to the diagnostic notes written during the time of hospitalization which may describe trends in commonly found diagnoses (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). This anatomical specificity represents a meaningful contribution to the existing literature on boxing injuries.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis retrospective analysis of NEISS data (2014\u0026ndash;2023) identifies orbital floor blowout and mandibular fractures as the leading maxillofacial injuries in boxing, making up 65% of cases (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). This is consistent with boxing's biomechanics, in which fast, closed-fist impacts focus force on these vulnerable facial areas. The orbital floor, formed by thin bones, is especially prone to fracture from direct impact [1]. When fractured, orbital fat and muscle\u0026mdash;mainly the inferior rectus\u0026mdash;can herniate into the maxillary sinus, causing double vision, sunken eye, and limited upward gaze. The literature shows that untreated muscle entrapment can cause lasting eye movement problems [2]. Orbital floor fractures account for 30% of boxing-related hospitalizations in this dataset. Thus, maxillofacial CT with detailed orbital images should be the first scan for boxers with periorbital trauma or eye movement issues. This provides the detail needed to guide eye surgery planning [3]. Surgery is indicated for muscle entrapment, more than 2 mm of enophthalmos, or large defects, using a transconjunctival or subciliary approach and titanium mesh or polyethylene implants [2].\u003c/p\u003e \u003cp\u003eThe literature supports the diagnostic value of a structured clinical examination prior to imaging, which is consistent with the injury profile observed in this study. H-pattern ocular motility testing evaluates muscular and neural function across all gaze directions and reliably identifies upgaze restriction indicative of inferior rectus entrapment [1]. An absent or asymmetric pupillary light response may indicate traumatic optic neuropathy or oculomotor nerve injury, both of which influence the urgency of surgical intervention. Comprehensive ophthalmic assessment should include best-corrected visual acuity, Hertel exophthalmometry to assess enophthalmos, and dilated funduscopic examination to exclude globe injury, hyphema, vitreous hemorrhage, or retinal pathology. Synthesizing these clinical findings with CT imaging establishes the evidence base for oculoplastic triage and surgical decision-making [3].\u003c/p\u003e \u003cp\u003eMandibular fractures represent 35% of boxing-related maxillofacial hospitalizations and carry the greatest risk of airway compromise [4]. The anatomical structure of the mandible predisposes it to multiple fracture sites. Condylar fractures may result in temporomandibular joint dislocation and trismus. The tongue blade test provides a rapid bedside assessment of mandibular integrity, while CT imaging remains the gold standard for diagnosis and surgical planning [4]. Concussions constitute 15% of hospitalizations in this dataset, ranking as the third most common diagnosis, with subdural hematomas accounting for an additional 5%. Overall, approximately 20% of patients hospitalized for boxing-related maxillofacial injuries received a diagnosis of possible brain injury. In cases where patients present with altered mental status, concussion symptoms, or neurological deficits, clinical attention should prioritize urgent non-contrast head CT to exclude acute intracranial hemorrhage before further evaluation. The observation that one in five cases involves intracranial injury stresses the need for systematic triage protocols. The frequent co-occurrence of mandibular and orbital injuries in the zygomaticomaxillary region underscores the need for comprehensive evaluation and multidisciplinary management involving emergency medicine, radiology, ophthalmology, oculoplastic surgery, oral and maxillofacial surgery, and plastic surgery [4].\u003c/p\u003e \u003cp\u003eThe injury distribution identified in this study indicates that orbital floor blowout fractures and mandibular fractures constitute nearly two-thirds of boxing-related maxillofacial hospitalizations. This finding supports the implementation of two distinct emergency diagnostic pathways as outlined above. The burden index, defined as the number of maxillofacial injuries per 1,000 boxing-related emergency room admissions per year, remained stable during the study period (mean 27.4, SD 2.3), indicating that the per-visit injury risk has not changed significantly over the past decade. The observed increase in maxillofacial case numbers is attributable to greater boxing participation and higher emergency room visit volumes. In 2023, maxillofacial injuries reached a peak of 148 cases, representing an extreme outlier more than four standard deviations above the previous nine-year mean. This year also recorded the highest national total of boxing-related emergency room admissions (n\u0026thinsp;=\u0026thinsp;5,296). The strong correlation between emergency room visit volume and maxillofacial injury burden (Pearson r\u0026thinsp;=\u0026thinsp;0.893, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) indicates that institutions with higher boxing-related emergency volumes should anticipate proportionally increased oculoplastic and maxillofacial surgical demands (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The distribution of diagnoses was significantly non-uniform (χ\u0026sup2; = 139.1, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with injuries concentrated in fractures and concussions rather than being randomly distributed. This enables emergency physicians to better anticipate the types of injuries likely to present in hospitalized boxing patients. Future research employing standardized ophthalmic outcome measures, such as visual acuity, diplopia quantification, Hertel exophthalmometry, and surgical intervention rates, would enhance the evidence base and facilitate more detailed assessment of injury severity and medical outcomes.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eThis study has several notable limitations that should be considered when interpreting its findings. The sample size of directly confirmed maxillofacial trauma cases from boxing in the NEISS dataset is small, which restricts the statistical power of the diagnosis-level analysis and limits the ability to draw definitive conclusions about the precise prevalence of specific injuries such as mandibular and orbital floor fractures in the broader boxing population. Subgroup analyses by age, skill level (amateur versus professional), or use of protective equipment were not possible given these constraints.\u003c/p\u003e \u003cp\u003eThis study employs two separate denominators for different analyses, a methodological consideration that should be made explicit. The trend and correlation analyses use NEISS national estimates \u0026mdash; weighted projections extrapolated to represent the full U.S. population \u0026mdash; while the diagnosis-level breakdown is derived from the smaller set of raw hospitalization cases. These two analyses answer different questions and are not directly interchangeable; readers should interpret them in their respective contexts.\u003c/p\u003e \u003cp\u003eThe NEISS database does not capture granular ophthalmic or surgical outcome data \u0026mdash; including visual acuity at presentation or discharge, presence and degree of diplopia, enophthalmos measurements, extraocular muscle entrapment status, surgical intervention rates, or length of stay. The database also does not record injury laterality, mechanism beyond the sport category, or post-discharge follow-up outcomes. A notable year-to-year fluctuation is observed in 2020, which recorded the lowest national boxing ER admission count (n\u0026thinsp;=\u0026thinsp;2,746) and lowest maxillofacial injury count (n\u0026thinsp;=\u0026thinsp;75) of the entire study period; most likely due to the COVID-19 pandemic.\u003c/p\u003e \u003cp\u003eTo address these limitations, future studies should incorporate larger datasets by combining NEISS data with complementary national databases such as the National Inpatient Sample (NIS) or the Nationwide Emergency Department Sample (NEDS). Prospective cohort studies tracking boxers over time for injury incidence and ophthalmic outcomes would offer the most comprehensive and clinically actionable data, enabling risk stratification by age, skill level, and protective equipment use, and allowing for the development of evidence-based, subspecialty-specific management guidelines.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eDisclosure:\u003c/h2\u003e \u003cp\u003e \u003cem\u003eThis research received no specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/em\u003e \u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eIRB Statement\u003c/strong\u003e \u003cp\u003e \u003cem\u003eIRB approval was not required for this manuscript as only publicly available data was included in the investigation.\u003c/em\u003e \u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting Interests:\u003c/h2\u003e \u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eEthics Approval:\u003c/strong\u003e \u003cp\u003eThis research study was conducted retrospectively using data from the National Electronic Injury Surveillance System (NEISS), a publicly available database administered by the U.S. Consumer Product Safety Commission. All data are de-identified and freely accessible. Institutional Review Board (IRB) approval was not required as no individually identifiable patient data were accessed.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent to Participate:\u003c/strong\u003e \u003cp\u003eNot applicable. This study used only publicly available, de-identified surveillance data.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eNo funds, grants, or other support were received for conducting this study.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eDaniel Lynch (DL): Methodology, Formal Analysis, Writing \u0026ndash; Original Draft, (primary author)Lorenzo Petralia (LP): Formal Analysis, Writing \u0026ndash; Original Draft (corresponding author)John Komlos (JK): Formal Analysis, Literature Review, Writing \u0026ndash; Original Draft, Writing \u0026ndash; Review \u0026amp;amp; Editing (corresponding author)Troy Puetz (TP): Conceptualization, Writing \u0026ndash; Original Draft, (corresponding author)Sarah Peterson (SP): Formal Analysis, Writing \u0026ndash; Review \u0026amp;amp; EditingSteiv Shore (SS): Validation, Formal Analysis, Writing \u0026ndash; Original Draft, Writing \u0026ndash; Review \u0026amp; EditingBenjamin Tinker (BT): Writing \u0026ndash; Original Draft, Writing \u0026ndash; Review \u0026amp;amp; EditingMichael N. Megafu (MNM): Supervision, Project Administration\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data used in this study are publicly available through the NEISS online query tool provided by the U.S. Consumer Product Safety Commission at https://www.cpsc.gov/Research--Statistics/NEISS-Injury-Data.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eKoenen L, Waseem M. Orbital Floor Fracture. StatPearls Publishing; updated December 15, 2023. Available at: www.ncbi.nlm.nih.gov/books/NBK534825/. Accessed October 27, 2024.\u003c/li\u003e\n\u003cli\u003eGrob S, et al. Orbital Fracture Repair. Seminars in Plastic Surgery. 2017;31(01):031\u0026ndash;039. https://doi.org/10.1055/s-0037-1598191.\u003c/li\u003e\n\u003cli\u003eGrove AS. Computed Tomography in the Management of Orbital Trauma. Ophthalmology. 1982;89(5):433\u0026ndash;440. https://doi.org/10.1016/s0161-6420(82)34770-3.\u003c/li\u003e\n\u003cli\u003eMayersak RJ, Moreira ME, Ganetsky M. Initial Evaluation and Management of Facial Trauma in Adults. UpToDate. Retrieved October 27, 2024.\u003c/li\u003e\n\u003cli\u003eCaputo ND, Raja A, Shields C, Menke N. Re-evaluating the Diagnostic Accuracy of the Tongue Blade Test: Still Useful as a Screening Tool for Mandibular Fractures? J Emerg Med. 2013;45(1):8\u0026ndash;12. doi:10.1016/j.jemermed.2012.11.078.\u003c/li\u003e\n\u003cli\u003eMotamedi MHK, et al. Prevalence and Patterns of Combat Sport Related Maxillofacial Injuries. Journal of Emergencies, Trauma, and Shock. 2010;3(4):314. https://doi.org/10.4103/0974-2700.70744.\u003c/li\u003e\n\u003cli\u003eMao Y, et al. Incidence Rates and Pathology Types of Boxing-Specific Injuries: A Systematic Review and Meta-Analysis of Epidemiology Studies in the 21st Century. Orthopaedic Journal of Sports Medicine. 2023;11(3). https://doi.org/10.1177/23259671221127669.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-emergency-and-disaster-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Journal of Emergency and Disaster Medicine](https://link.springer.com/journal/44467)","snPcode":"44467","submissionUrl":"https://submission.springernature.com/new-submission/44467/3?","title":"Journal of Emergency and Disaster Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Open","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Boxing injuries, Maxillofacial trauma, Orbital floor fracture, Mandibular fracture, NEISS database, Emergency diagnostic prioritization","lastPublishedDoi":"10.21203/rs.3.rs-9431789/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9431789/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eIntroduction/Background: \u003c/strong\u003eUsing the National Electronic Injury Surveillance System (NEISS) database, this study analyzes boxing-related maxillofacial and orbital injuries presenting to emergency departments nationwide, identifying injury patterns to better equip clinicians for accurate diagnosis and optimized patient outcomes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective(s): \u003c/strong\u003eTo characterize the distribution of boxing-related maxillofacial injuries requiring hospitalization from 2014–2023 and to establish evidence-based diagnostic and management priorities for emergency physicians, ophthalmologists, and surgeons.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods — Design: \u003c/strong\u003eRetrospective national database analysis. IRB approval was not required as only publicly available data were utilized.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSetting: \u003c/strong\u003eStatistically representative sample of U.S. hospital emergency departments via the NEISS database.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eParticipants: \u003c/strong\u003ePatients presenting to emergency departments with boxing-related head and neck injuries (eye, head, face, mouth, ear) from 2014–2023 (n = 1,012 maxillofacial hospitalizations from 37,203 total national admissions). Excluded: extremity/torso injuries; burns, toxicology, amputation, electroshock, or submersion.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInterventions: \u003c/strong\u003eNot applicable (observational/database study).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMain Outcome Measures: \u003c/strong\u003eAnnual incidence of boxing-related maxillofacial injuries, anatomical distribution of injury location, frequency of specific diagnoses at hospitalization, and burden index (maxillofacial injuries per 1,000 boxing ER admissions).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eAnalysis of NEISS data from 2014–2023 revealed mandibular fractures (35%) and orbital floor blowout fractures (30%) as the predominant causes of hospitalized boxing-related maxillofacial injuries. Concussions accounted for 15%, followed by nasal septal hematomas (10%), subdural hematomas (5%), and other facial fractures (5%). Head (43.0%) and face (37.3%) together accounted for \u0026gt;80% of all admissions. A strong positive Pearson correlation was identified between ER admissions and maxillofacial injuries (r = 0.893, p = 0.0005). Diagnosis distribution was significantly non-uniform (χ² = 139.1, p \u0026lt; 0.001).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003e\u0026nbsp;These findings give emergency physicians and surgeons actionable diagnostic guidance for boxing-related trauma. The predominance of orbital floor blowout and mandibular fractures supports maxillofacial CT with fine-cut orbital views as the initial imaging modality, while altered mental status, concussive syndromes, or neurologic compromise should prompt non-contrast head CT to rule out acute intracranial hemorrhage. Recognizing these patterns enables faster, more accurate management of ophthalmic and maxillofacial injuries, reducing morbidity and improving outcomes.\u003c/p\u003e","manuscriptTitle":"Boxing-Related Maxillofacial and Orbital Trauma: A Retrospective NEISS Database Analysis of Injury Patterns and Emergency Diagnostic Prioritization (2014–2023)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-28 15:29:39","doi":"10.21203/rs.3.rs-9431789/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2026-04-20T05:26:09+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-19T22:51:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-19T22:50:25+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Emergency and Disaster Medicine","date":"2026-04-16T01:14:57+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-emergency-and-disaster-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Journal of Emergency and Disaster Medicine](https://link.springer.com/journal/44467)","snPcode":"44467","submissionUrl":"https://submission.springernature.com/new-submission/44467/3?","title":"Journal of Emergency and Disaster Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Open","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5d63e67a-8d19-480b-96bf-dd2342a0ff18","owner":[],"postedDate":"April 28th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-28T15:29:45+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-28 15:29:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9431789","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9431789","identity":"rs-9431789","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}