Firearm injuries in a conflict affected region: A multicenter study of epidemiological trends, injury patterns, management, and outcomes in the West Bank of Palestine

Hala Alkhoury; Mira Hallak; Mohammad Shakshir; Iyad Maqboul; Mohammad Jaber; Ramzi Shawahna

doi:10.1371/journal.pone.0358566

. 2026 Sep 22;21(9):e0358566. doi: 10.1371/journal.pone.0358566

Firearm injuries in a conflict affected region: A multicenter study of epidemiological trends, injury patterns, management, and outcomes in the West Bank of Palestine

Hala Alkhoury ¹, Mira Hallak ¹, Mohammad Shakshir ¹, Iyad Maqboul ^1,^2,^*, Mohammad Jaber ^1,^2,^*, Ramzi Shawahna ^3,^4,^*

Editor: Pawan Acharya⁵

PMCID: PMC13596805 PMID: 42771656

Abstract

Firearm injuries represent a major source of trauma in conflict‑affected regions, yet multicenter data from Palestine remain scarce. This multicenter study provides the first large epidemiological analysis of firearms injuries across eight hospitals in the West Bank, encompassing 392 patients treated between 2020 and 2025. The cohort was overwhelmingly male (98.0%) and predominantly young, with a median age of 19.0 years [17.0–26.0]. Extremity injuries were most common, affecting 265 (67.6%) patients, while thoracoabdominal and vascular injuries, though less frequent, were associated with disproportionately severe outcomes. Fractures were the most frequent associated injury, affecting 152 patients (38.8%), followed by vascular trauma in 54 patients (13.8%) and hollow viscus gastrointestinal injuries in 45 patients (11.5%). Surgical interventions were required in more than half of patients, with orthopedic fixation and vascular repair dominating the workload. During hospitalization, 81 (20.7%) patients required intensive care unit (ICU) admission, while in‑hospital mortality was 3.3%. Functional dependence at discharge was common, affecting more than half of survivors. Multivariable regression showed that elevated heart rate at presentation was independently associated with ICU admission (OR: 1.04, 95% CI: 1.02–1.05, p < 0.001). Abdominal injuries were also significant predictors of ICU admission (OR: 3.81, 95% CI: 1.64–8.87, p = 0.002). Increasing age (OR: 0.93, 95% CI: 0.87–0.99, p = 0.024) and elevated heart rate (OR: 0.93, 95% CI: 0.90–0.97, p = 0.001) were independently associated with in‑hospital mortality. This study shows that while extremity injuries dominate the epidemiological profile of firearm trauma in the West Bank, thoracoabdominal and vascular injuries were associated with greater resource demands and more severe outcomes. The findings underscore the urgent need to strengthen orthopedic and vascular surgical capacity, expand ICU and blood bank resources, and develop rehabilitation services.

Introduction

Firearm injuries remain a major cause of preventable death and disability worldwide, exerting a disproportionate impact on trauma systems in regions affected by violence and instability [1,2]. According to a Global Burden of Disease analysis, firearm violence accounted for over 3.1 million incident cases worldwide in 2019, including 710,600 cases of physical violence by firearm, 335,200 cases of firearm-related self-harm, and 2.1 million unintentional firearm injuries [3]. The age‑standardized mortality rate from firearm violence was 2.23 per 100,000 population, with disability-adjusted life years (DALYs) reaching 127.6 per 100,000 for physical violence alone [3]. Importantly, firearm injuries disproportionately affect younger populations, ranking among the leading causes of death in individuals aged 5–29 years, and show increasing trends in regions such as Tropical Latin America and the Middle East/North Africa, where socioeconomic instability and conflict exacerbate risk [3,4].

From a clinical perspective, firearm injuries differ from other mechanisms of trauma because their severity depends on ballistic characteristics, anatomical trajectory, and the timeliness of definitive care [4–6]. Presentations may range from isolated soft‑tissue injuries or fractures to complex vascular, thoracic, abdominal, pelvic, genitourinary, or neurologic involvement [1–4]. This variability necessitates rapid triage, early resuscitation, timely imaging when available, and coordinated multidisciplinary care involving emergency medicine, surgery, orthopedics, vascular teams, critical care, and rehabilitation services [7,8].

Although firearm injuries are a global concern, their burden is particularly pronounced in low‑resource and conflict‑affected regions, where fragile health systems face limited prehospital care, constrained surgical capacity, and inadequate rehabilitation services [3]. The Middle East and Africa have been identified as regions with rising age‑standardized rates of firearm violence, reflecting the combined effects of political instability, socioeconomic disparities, and recurrent episodes of armed conflict [9–11]. In these settings, patients often present directly to hospitals without prior stabilization, and trauma registries are either absent or incomplete, limiting the ability to anticipate resource needs or benchmark outcomes. Within Palestine, and specifically the West Bank, firearm injuries represent a significant form of penetrating trauma, yet multicenter data describing injury patterns, management strategies, and outcomes remain scarce. Addressing this gap is essential for strengthening trauma system preparedness, guiding resource allocation, and informing policy interventions tailored to the realities of a conflict‑affected healthcare environment.

In the Middle East, firearm injuries have been consistently reported as a leading cause of trauma-related morbidity and mortality, particularly in conflict-affected settings where health systems face chronic resource limitations [9,10]. Regional studies highlight the predominance of young male victims, high rates of extremity injuries, and the frequent need for surgical interventions such as vascular repair, laparotomy, and orthopedic fixation. In Palestine, the burden of firearm injuries has been documented in both the West Bank and Gaza, with several reports describing severe thoracoabdominal trauma, vascular injuries, and amputations that contribute to long-term disability [10,12–14]. Analyses from Gaza during periods of armed conflict emphasize the overwhelming demand for surgical and critical care services, while smaller case series from the West Bank have noted the disproportionate impact on adolescents and young adults, limited prehospital stabilization, and the absence of standardized trauma registries [10,12–14]. Collectively, these studies underscore the dual challenge of high injury incidence and constrained trauma system capacity, yet most available data remain single-center, event-specific, or descriptive in nature. This lack of multicenter, systematically collected evidence limits the ability to anticipate resource requirements, benchmark outcomes, and design targeted interventions.

Although firearm injuries have been widely recognized as a major contributor to trauma‑related morbidity and mortality in the Middle East [10,12,13], the existing literature from Palestine remains scarce and fragmented despite the persistently high levels of violence. Most available reports have been limited to single‑center case series or conflict‑specific accounts, often focusing narrowly on acute presentations without systematically describing epidemiological trends, injury distribution, management strategies, or hospital outcomes [9,10,12–14]. Critical domains such as intensive care unit (ICU) utilization, transfusion requirements, functional status at discharge, and mortality have rarely been examined in a comprehensive manner, and the absence of standardized trauma registries has further hindered the ability to generate reliable multicenter evidence. In addition, triage of firearm‑related trauma in Palestine remains challenging due to the lack of standardized severity scoring systems, limited prehospital stabilization, and variability in hospital documentation practices. These gaps make it difficult to identify patients at highest risk of requiring intensive care or experiencing in‑hospital mortality, underscoring the need for evidence‑based predictors to guide triage decisions. This gap in knowledge is particularly striking given the recurrent exposure of Palestinian communities to firearm‑related trauma and the strain it imposes on already fragile healthcare systems. To address these limitations, the present study was undertaken as the first multicenter retrospective cohort analysis of firearm injuries in the West Bank, with the objective of providing a detailed account of epidemiological characteristics, injury patterns, management approaches, and in‑hospital outcomes. By consolidating data across eight hospitals, this study aims to generate robust evidence that can inform trauma system preparedness, guide resource allocation, and support policy development in conflict‑affected healthcare settings.

Methods

Study design and settings

This study was designed as a multicenter retrospective observational cohort study conducted across hospitals in the West Bank of Palestine. Patients presenting with documented firearm injuries between 2020 and 2025 were included. Data were collected retrospectively from electronic medical records (EMRs), with extraction performed between 01/09/2025 and 30/01/2026 using a standardized data collection form to ensure consistency across centers. The participating hospitals represented a mix of governmental and private institutions geographically distributed across the northern and southern regions of the West Bank. Cases were managed at Rafidia Surgical Hospital, Nablus Specialty Hospital, An-Najah National University Hospital, Beit Jala Governmental Hospital (Al-Hussein), Jenin Governmental Hospital, Tubas Turkish Governmental Hospital, Martyr Dr. Thabet Thabet Governmental Hospital, and the Palestinian Medical Complex. Reporting of this study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist [15], provided as S1 Table, to ensure methodological transparency and alignment with international reporting standards.

Study population and eligibility criteria

The study population comprised patients with documented firearm injuries who presented to and were managed at the participating hospitals in the West Bank during the study period. Eligible cases required clear documentation of a firearm injury and a verifiable hospital encounter within one of the included centers. Records were excluded if injuries were caused by other mechanisms (e.g., stab wounds, blunt trauma), if patients were treated entirely outside the study hospitals, or if documentation was insufficient to confirm a firearm injury event.

Partial missingness in selected clinical variables (e.g., Glasgow Coma Scale [GCS]) did not result in exclusion. Instead, missing data were quantified and transparently reported, with analyses conducted using available-case denominators for each variable. Patients were followed from hospital admission until discharge, transfer, or death during the index hospitalization.

Sample size and sampling approach

The sample size required for this study was estimated using the Raosoft sample size calculator (https://www.raosoft.com), assuming a 95% confidence level, a 5% margin of error, and a population size approximating all patients presenting with firearm injuries to hospitals in the West Bank during the study period. Based on these parameters, the minimum required sample size was calculated to be 385 participants, ensuring sufficient statistical power to generate stable descriptive estimates and allow meaningful subgroup analyses.

To maximize representativeness, all eligible cases documented between 2020 and 2025 across the eight participating hospitals were included. No sampling or case selection was performed beyond the predefined eligibility criteria, thereby minimizing selection bias. The final analytic dataset comprised 392 patients with confirmed firearm injuries, exceeding the calculated minimum requirement. This complete inclusion approach strengthened the external validity of the findings and ensured that rare injury types and less frequent outcomes were adequately captured.

Definition of variables

Variables were defined a priori based on clinical relevance and consistency with published firearm trauma literature. Baseline demographic variables included sex, age, and place of residence. Temporal variables captured the year, month, and day of presentation. Prehospital medical attention was also collected. Prehospital medical attention was categorized into three groups: “none” (patients arriving without any documented care prior to hospital presentation), “first aid” (basic wound care or stabilization provided at the scene or by non‑specialized personnel), and “care in another hospital/center” (patients who received initial medical or surgical management in a different facility before transfer to the study hospital).

Clinical status at emergency presentation included blood pressure, heart rate, hemodynamic stability, and neurological status. Blood pressure was categorized pragmatically to ensure consistency across hospitals. We applied American College of Cardiology (ACC)/American Heart Association (AHA) thresholds, adapted to trauma settings, as follows: hypotension (systolic blood pressure <90 mmHg), normotension (systolic blood pressure 90–139 mmHg with diastolic blood pressure <90 mmHg), and hypertension (systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg) [16]. These categories were used to provide a standardized and reproducible framework for analysis rather than to imply chronic cardiovascular risk. In the context of firearm trauma, this classification was intended to capture acute physiological status at presentation, recognizing that trauma‑specific thresholds (such as systolic blood pressure <90 mmHg for shock) may be more clinically meaningful. Heart rate was categorized as bradycardia (< 60 bpm), normal (60–100 bpm), or tachycardia (> 100 bpm). Hemodynamic instability was defined as heart rate <50 or > 120 bpm, systolic blood pressure <90 mmHg, or diastolic blood pressure <60 mmHg. Neurological status was assessed separately using the Glasgow Coma Scale [17], categorized as ≥13, 9–12, 3–8, or not recorded.

Injury variables were classified by anatomical region and by injury type. Associated injuries and fractures were also classified by anatomical region and by injury type. Management variables included wound management, bullet/foreign body removal, fracture stabilization/fixation, and surgical interventions were also collected.

Outcome variables included ICU admission, blood transfusion, antibiotic administration, length of hospital stay, discharge disposition, functional status at discharge, and mortality status (alive/deceased). Functional status at discharge was assessed based on documentation in medical records and categorized into three groups: “independent” (patients discharged with preserved mobility and self‑care capacity without the need for assistance), “dependent” (patients discharged with impaired mobility, need for caregiver support, or functional limitations requiring rehabilitation services), and “deceased.” This pragmatic categorization reflects routine clinical documentation practices in the participating hospitals and was used to capture functional outcomes in the absence of standardized assessment instruments.

Data collection

Data were abstracted using a standardized, customized collection form developed specifically for this study (S2 Table). The form captured demographics, injury characteristics, physiological parameters, comorbidities, interventions, and outcomes. A structured variable dictionary accompanied the form, defining each variable and its coding framework to ensure reproducibility.

Data abstraction was performed retrospectively from EMRs by trained research team members who were final year medical students. Abstractors underwent orientation to the standardized protocol and variable dictionary to ensure consistent interpretation across hospitals. Systematic data cleaning procedures were applied to harmonize category labels, standardize anatomical and procedural terminology, and perform logical consistency checks (e.g., alignment between recorded procedures and number of surgeries).

Missing data were preserved as a distinct category (not recorded) rather than reclassified, minimizing misclassification bias and maintaining transparency. The approach was informed by methodologies commonly used in retrospective trauma research and relied on routinely documented clinical records generated during standard patient care.

Statistical analysis

Data were coded, cleaned, and analyzed using IBM SPSS Statistics for Windows, version 26. Categorical variables were summarized as frequencies (n) and percentages (%), while continuous variables were reported as median with interquartile range [Q1, Q3].

Bivariate analyses were conducted to explore associations between baseline characteristics, injury patterns, management procedures, and clinical outcomes. For categorical comparisons, Pearson’s chi-square test was applied, with Fisher’s exact test used when expected cell counts were <5. For continuous outcomes compared between two groups, Mann-Whitney U tests were used. For comparisons across more than two groups, Kruskal-Wallis tests were employed.

To identify factors independently associated with ICU admission and in‑hospital mortality, multivariable logistic regression models were constructed. Candidate variables were selected a priori through a two‑step process: (1) screening for statistical significance in bivariate analyses (p < 0.10), and (2) evaluation of clinical relevance based on prior trauma literature. Specifically, age and pulse rate on arrival were included because they are consistently reported as strong predictors of mortality and ICU utilization [2,6,9,10]. Chest trauma and abdominal trauma were entered separately into the models, as both regions are recognized in global and regional firearm injury studies as major determinants of severity and resource demand [2,6,9,10,12–14]. Other variables (e.g., limb injuries, soft tissue injuries, minor fractures) were excluded because they did not reach statistical significance in univariate analyses, lacked established evidence of independent prognostic value, or were collinear with included predictors. Given the small number of deaths (n = 13), the mortality model was deliberately restricted to a parsimonious set of variables to minimize overfitting. This strategy ensured that the models balanced explanatory power with interpretability while maintaining transparency.

Model fit was assessed using the Hosmer-Lemeshow goodness-of-fit test, and explanatory power was reported using Cox & Snell R² and Nagelkerke R². Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated to quantify associations. To further evaluate model performance, the area under the curve (AUC) was reported to assess discriminatory ability.

Missing data were not imputed; instead, analyses were conducted using available-case denominators, allowing denominators to vary by variable. Missing or non-recordable fields were explicitly reported in tables and supplementary materials to maintain transparency. All statistical tests were two-sided, and a p-value < 0.05 was considered statistically significant.

Ethical considerations

This study was conducted in full compliance with national and international ethical principles governing biomedical research. All procedures adhered to the ethical standards outlined in the Declaration of Helsinki. Formal approval was obtained from the Institutional Review Board of An‑Najah National University (approval number: Pharm. Dec.2024/60). In addition, administrative permissions were secured from all participating hospitals prior to data collection.

Because this study involved a retrospective analysis of routinely collected clinical data, informed consent requirements were addressed in accordance with IRB regulations. In view of the observational and non‑interventional design, and the exclusive reliance on existing medical records, the Institutional Review Board of An‑Najah National University formally waived the requirement for obtaining written informed consent. All data were managed in strict accordance with confidentiality and data protection standards. Patient identifiers were removed prior to analysis, and datasets were fully de‑identified and stored on secure, access‑restricted devices available only to the research team. These measures ensured that data were used exclusively for research purposes and safeguarded patient privacy throughout the study.

Results

Characteristics of the patients in the cohort

The cohort included 392 patients with firearm injuries, of whom the vast majority were male (n = 384; 98.0%) (Table 1). The median age was 19.0 years [17.0, 26.0], reflecting a predominantly young population. More than half of the cohort were young adults aged 18–29 years (n = 201; 51.3%), while adolescents aged 13–17 years represented nearly one‑third of the population (n = 122; 31.1%). Pediatric patients aged ≤12 years were less common (n = 10; 2.6%), and older adults aged ≥45 years accounted for only a small minority (n = 16; 4.1%). These findings underscore that while firearm injuries affect individuals across age groups, the largest burden was observed among young adults aged 18–29 years, who comprised more than half of the cohort. The full distribution across age groups is presented in S1 Fig.

Table 1. Demographic characteristics and clinical presentation of the study cohort (n = 392).

Variable	n (%) or median [Q1, Q3]
Gender
Male, n (%)	384 (98.0)
Female, n (%)	8 (2.0)
Age (years), median [Q1, Q3]	19.0 [17.0-26.0]
Place of Residence
City, n (%)	175 (44.6)
Village, n (%)	96 (24.5)
Refugee Camp, n (%)	78 (19.9)
Undisclosed/not documented, n (%)	43 (11.0)
Blood pressure
Non-recordable/not documented, n (%)	9 (2.3)
Normotensive, n (%)	176 (44.9)
Hypotensive, n (%)	38 (9.7)
Hypertensive, n (%)	169 (43.1)
Heart rate
Non-recordable/not documented, n (%)	7 (1.8)
Normal, n (%)	292 (74.5)
Bradycardia, n (%)	4 (1.0)
Tachycardia, n (%)	89 (22.7)
Glasgow coma scale recorded at time of arrival to the emergency room
> 13, n (%)	308 (78.6)
9–12, n (%)	19 (4.8)
3–8, n (%)	13 (3.3)
Not recorded/not documented, n (%)	52 (13.3)
Hemodynamic stability of the patient at the time of arrival to the emergency room
Stable, n (%)	314 (80.1)
Unstable, n (%)	78 (19.9)
Medical attention patient received prior to arriving to the emergency room
None/not documented, n (%)	46 (11.7)
First aid, n (%)	305 (77.8)
Care in another hospital/center, n (%)	41 (10.5)

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Q1: first quartile, Q3: third quartile.

Nearly half of the cohort resided in cities (n = 175; 44.6%), while villages (n = 96; 24.5%) and refugee camps (n = 78; 19.9%) (Table 1). At presentation, most patients were hemodynamically stable (n = 314; 80.1%), although instability was documented in 78 (19.9%) patients. Normotension was the most frequent blood pressure category (n = 176; 44.9%), followed closely by hypertension (n = 169; 43.1%). Tachycardia was observed in 89 (22.7%) patients. Neurological status was generally preserved, with GCS scores > 13 in 308 (78.6%) patients, while moderate in 19 patients (4.8%) and severe impairment in 13 (3.3%). Pre‑arrival care was documented in most cases, with 305 (77.8%) receiving first aid, whereas 46 (11.7%) arrived without prior medical attention.

Temporal distribution of firearm injury presentations

The occurrence of firearm injury presentations varied considerably across years, months, and days of the week (Fig 1). The highest burden was observed in 2023, with 137 (34.9%) cases, followed by 2024 with 112 (28.6%) and 2025 with 75 (19.1%). Earlier years contributed fewer cases, including 2022 (n = 45; 11.5%), 2021 (n = 18; 4.6%), and 2020 (n = 5; 1.3%). Monthly distribution revealed a peak in October (n = 62; 15.8%), while March (n = 21; 5.4%) and September (n = 17; 4.3%) recorded the lowest frequencies. Weekly distribution showed that Tuesday accounted for the largest proportion of cases (n = 73; 18.6%), whereas Monday had the fewest (n = 41; 10.5%). These findings highlight temporal clustering, with notable surges in specific years, months, and weekdays, while the full distribution is detailed in Fig 1.

Anatomical distribution of injuries

Firearm injuries most frequently involved the lower extremities, affecting 265 (67.4%) patients, with nearly equal distribution between the right (n = 140; 35.6%) and left (n = 125; 31.8%) sides (Fig 2). Injuries to the trunk, including thoracoabdominal and pelvic regions, were also common (n = 136; 34.6%), while upper limb injuries were documented in 76 (19.3%). Within the upper limb category, left‑sided injuries (n = 42; 10.7%) slightly outnumbered right‑sided injuries (n = 34; 8.7%). Less frequent sites included the chest (n = 41; 10.5%) and head/neck (n = 19; 4.8%). Only a small proportion of cases were classified as unspecified (n = 4; 1.0%). These findings highlight the predominance of extremity involvement, particularly the lower limbs, with trunk injuries representing the second most common anatomical region (Fig 2). A detailed breakdown of injury distribution by anatomical site is shown in S3 Table.

Fig 2 — Anatomical injury locations are not mutually exclusive, and individual patients may have sustained injuries in more than one anatomical region.

Associated injuries

Associated injuries were common among patients with firearm injuries, with fractures representing the most frequent category (n = 152; 38.8%) (Table 2). Within fracture subtypes, tibial fractures (n = 38; 9.7%) and femoral fractures (n = 32; 8.2%) were the most prevalent, followed by upper limb fractures (n = 21; 5.4%) and pelvic fractures (n = 17; 4.3%). Vascular injuries were also notable, affecting 54 (13.8%) patients, while hollow viscus gastrointestinal injuries were documented in 45 (11.5%). Thoracic injuries occurred in 39 (10.0%), and abdominal solid organ injuries were observed in 25 (6.4%). Less frequent but clinically significant injuries included nerve injury (n = 15; 3.8%), genitourinary injury (n = 17; 4.3%), vertebral column fracture (n = 8; 2.0%), and cranial or intracranial injury (n = 9; 2.3%). Rare injuries such as ruptured globe (n = 2; 0.5%) and major abdominal vascular injury (n = 3; 0.8%) were also recorded. These findings highlight the predominance of fractures and vascular involvement, with thoracoabdominal injuries contributing substantially to morbidity. A detailed breakdown of associated injuries is shown in S4 Table.

Table 2. Distribution of injuries among the study cohort.

Associated injury	n (%)^*
Vascular injury	54 (13.8)
Nerve injury	15 (3.8)
Thoracic injury (any)	39 (10.0)
Cranial and intracranial injury (any)	9 (2.3)
Facial bone fracture (any)	7 (1.8)
Ruptured globe	2 (0.5)
Neck injury (any)	6 (1.5)
Vertebral column fracture (any)	8 (2.0)
Thoracic girdle fracture (any)	12 (3.1)
Diaphragmatic injury	6 (1.5)
Abdominal solid organ injury (any)	25 (6.4)
Hollow viscus gastrointestinal injury (any)	45 (11.5)
Major abdominal vascular injury (any)	3 (0.8)
Pelvic/retroperitoneal hematoma (any)	8 (2.0)
Genitourinary injury (any)	17 (4.3)
All fractures (any location)	152 (38.8)
Pelvic fracture (any)	17 (4.3)
Femoral fracture (any)	32 (8.2)
Tibial fracture (any)	38 (9.7)
Foot and ankle fracture (any)	11 (2.8)
Upper limb fracture (any)	21 (5.4)
Hand injury (any)	2 (0.5)
Tendon injury (any)	4 (1.0)
Muscle injury	9 (2.3)

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* Percentages were calculated using the total number of patients in the cohort (n = 392). Injury categories are not mutually exclusive, and individual patients may have sustained multiple injuries.

Management and discharge outcomes

Surgical procedures were frequently required in the management of firearm injuries, with fracture stabilization or fixation being the most common intervention (n = 92; 23.5%) (Table 3). Vascular surgery was also prominent, performed in 64 (16.3%), while wound management procedures were documented in 64 (16.3%). Exploratory surgeries were undertaken in 60 (15.3%), and abdominal visceral surgeries in 44 (11.2%). Bullet or foreign body removal was performed in 44 (11.2%), highlighting the complexity of trauma care. Less frequent but clinically significant procedures included thoracic surgery (n = 17; 4.3%), genitourinary/scrotal surgery (n = 11; 2.8%), tendon/nerve repair (n = 13; 3.3%), and neurosurgical interventions (n = 5; 1.3%). Rare procedures such as tracheostomy (n = 1; 0.3%) and ocular evisceration (n = 1; 0.3%) were also recorded. These findings underscore the predominance of orthopedic and vascular interventions, reflecting the injury burden in this cohort. A detailed breakdown of surgical and management interventions is shown in S5 Table.

Table 3. Surgical interventions performed in patients in the cohort.

Surgical intervention	n (%)^*
Wound management (any)	64 (16.3)
Bullet or foreign body removal	44 (11.2)
Grafting procedures (any)	6 (1.5)
Fracture stabilization/fixation (any)	92 (23.5)
Exploratory surgery (any)	60 (15.3)
Thoracic surgery (any)	17 (4.3)
Vascular surgery (any)	64 (16.3)
Endoscopic procedures (any)	4 (1.0)
Fasciotomy	8 (2.0)
Neurosurgical intervention (any)	5 (1.3)
Tracheostomy	1 (0.3)
Ocular evisceration	1 (0.3)
Abdominal visceral surgery (any)	44 (11.2)
Genitourinary/scrotal surgery (any)	11 (2.8)
Tendon/nerve surgery (any)	13 (3.3)
Maxillofacial surgery	2 (0.5)
Other surgical interventions	9 (2.3)

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* Percentages were calculated using the total number of patients in the cohort (n = 392). Surgical procedure categories are not mutually exclusive, and individual patients may have undergone more than one procedure during admission.

During hospitalization, 81 (20.7%) patients required admission to the ICU, and 106 (27.0%) received blood products (Table 4). Antibiotic therapy was administered to nearly all patients (n = 367; 93.6%). Surgical intervention was common, with 228 (58.2%) undergoing at least one procedure; specifically, 122 (31.1%) had a single surgery, 75 (19.1%) had two, and 31 (7.9%) required three or more. At discharge, most patients returned home (n = 304; 77.6%), while 59 (15.1%) were referred to other facilities. In‑hospital mortality was documented in 13 (3.3%), and 16 (4.1%) left against medical advice. Functional outcomes revealed that only 177 (45.2%) were discharged as independent with normal status, whereas more than half (n = 202; 51.5%) were dependent, underscoring the substantial morbidity associated with firearm trauma.

Table 4. Clinical management and discharge outcomes of patients in the study cohort.

Variable	n (%) or median [Q1, Q3]
ICU admission, n (%)	81 (20.7)
Blood transfusion, n (%)	106 (27.0)
Antibiotic administration, n (%)	367 (93.6)
Number of surgeries
None, n (%)	164 (41.8)
1, n (%)	122 (31.1)
2, n (%)	75 (19.1)
≥ 3, n (%)	31 (7.9)
Discharge status
Home, n (%)	304 (77.6)
Referral, n (%)	59 (15.1)
Died, n (%)	13 (3.3)
Left against medical advice, n (%)	16 (4.1)
Length of hospital stay (days), median [Q1, Q3]	3.0 [1.0, 6.0]
Functional outcome at discharge
Independent, n (%)	177 (45.2)
Dependent, n (%)	202 (51.5)
Dead, n (%)	13 (3.3)

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ICU, intensive care unit.

Factors associated with ICU admission and mortality

In univariate analyses, patients admitted to the ICU had significantly higher heart rates on arrival (median 100.0 [87.0–122.0] vs. 87.0 [78.0–93.0] beats/min, p < 0.001), and both chest injuries (p < 0.001) and abdominal injuries (p < 0.001) were more frequent among patients admitted to the ICU as shown in S6 Table. In multivariate analysis, heart rate on arrival remained independently associated (Table 5), with each unit increase associated with higher odds of ICU admission (B = 0.04, p < 0.001; OR = 1.04, 95% CI: 1.02–1.05). Abdominal injuries were also independently associated with ICU admission (B = 1.34, p = 0.002; OR = 3.81, 95% CI: 1.64–8.87). The overall model was statistically significant (χ² = 58.35, df = 3, p < 0.001), demonstrated acceptable calibration (Hosmer–Lemeshow χ² = 11.79, p = 0.161), and yielded an AUC of 0.78, indicating good discriminatory ability. The model correctly classified 81.3% of cases, underscoring the importance of hemodynamic parameters and torso trauma in determining the need for intensive care.

Table 5. Factors independently associated with ICU admission and mortality.

					95% CI for OR
Domain/factor	B	SE	p-value	OR	Lower	Upper
ICU admission
Heart rate on arrival	0.04	0.01	< 0.001	1.04	1.02	1.05
Chest injury	−0.66	0.47	0.163	0.52	0.21	1.30
Abdomen (any)	1.34	0.43	0.002	3.81	1.64	8.87
Mortality
Age	−0.07	0.03	0.024	0.93	0.87	0.99
Heart rate on arrival	−0.07	0.02	0.001	0.93	0.90	0.97

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CI, confidence interval; ICU, intensive care unit; OR, odds ratio; SE, standard error; statistically significant p-values are in boldface.

Similarly, univariate analyses showed that patients who died were significantly older (median 30.5 [29.0–35.0] years vs. 19.0 [17.0–26.0] years, p = 0.004) and had markedly higher heart rates on arrival (median 113.5 [112.0–130.0] vs. 87.0 [79.0–99.0] beats/min, p = 0.002) (S7 Table). In multivariate analysis, increasing age was associated with higher likelihood of death (B = –0.07, p = 0.024; OR = 0.93, 95% CI: 0.87–0.99), and elevated heart rate on arrival was independently associated with mortality (B = –0.07, p = 0.001; OR = 0.93, 95% CI: 0.90–0.97) (Table 5). The overall model was statistically significant (χ² = 14.84, df = 2, p = 0.001), demonstrated acceptable fit (Hosmer–Lemeshow χ² = 2.99, p = 0.93), and yielded an AUC of 0.81, indicating good discriminatory ability. The model correctly classified 98.4% of cases.

Discussion

This study provides the first multicenter epidemiological analysis of firearm injuries in the West Bank of Palestine, offering a comprehensive account of injury patterns, management strategies, and outcomes across eight hospitals. By analyzing 392 patients treated between 2020 and 2025, it delivers unprecedented insight into the burden of firearm trauma in a conflict‑affected healthcare system. The findings highlight the predominance of extremity injuries, the disproportionate severity of thoracoabdominal and vascular trauma, the high demand for surgical and critical care interventions, and the substantial functional dependence among survivors despite relatively low in‑hospital mortality. These results are directly relevant to clinicians, hospital administrators, trauma system planners, and policymakers, underscoring the urgent need to strengthen surgical capacity, expand intensive care resources, and develop rehabilitation services. Beyond their local importance, the findings contribute to the global discourse on trauma care in conflict zones, offering evidence to guide preparedness strategies and policy development in similarly constrained environments.

The predominance of extremity injuries observed in this cohort is consistent with international firearm injury series, where limbs are often the most exposed and vulnerable anatomical regions [1,5]. Regional studies report similar extremity‑dominant profiles, while reports from Gaza have documented higher proportions of thoracoabdominal trauma and vascular involvement [10,12–14]. Although less frequent in our cohort, thoracoabdominal and vascular injuries were associated with disproportionately severe outcomes in descriptive analyses, including higher rates of ICU admission, transfusion, and mortality. In multivariable models, abdominal injuries remained significantly associated with ICU admission. These associations, together with the observed burden of vascular trauma, highlight the need to strengthen orthopedic and vascular surgical capacity, ensure adequate critical care resources, and expand rehabilitation services to address long‑term disability [2,6].

Associated injuries, particularly fractures and vascular trauma, highlight the substantial burden on surgical services. Extremity fractures, especially tibial and femoral, were the most frequent injuries, consistent with both civilian firearm trauma series and regional reports from Gaza [12,13]. Vascular injuries, though less common, carried significant clinical implications, echoing studies that underscore the urgent need for repair and transfusion support [10,14]. Thoracoabdominal injuries, while less frequent, were associated with severe outcomes in descriptive analyses, consistent with global trauma literature emphasizing the high mortality risk of torso involvement [2,6]. Taken together, these findings suggest that orthopedic and vascular surgical services are critical components of trauma care in this setting. The observed associations with ICU admission and transfusion further indicate that critical care and blood bank resources are frequently required. Establishing multicenter trauma registries would enable systematic monitoring of associated injuries, facilitate benchmarking against regional and international data, and guide evidence‑based resource allocation [9,10].

Management strategies and discharge outcomes reveal both strengths and vulnerabilities within the trauma care system. The high frequency of orthopedic and vascular procedures parallels findings from regional studies in Gaza, where extremity fractures and vascular trauma dominate the surgical workload [12,13]. International reports similarly emphasize orthopedic fixation and vascular repair as central to firearm trauma care [1,5]. Despite relatively low in‑hospital mortality (3.3%), more than half of survivors were discharged with functional dependence, consistent with regional literature documenting long‑term disability in resource‑limited settings [6,9]. In this cohort, the combination of complex surgical needs, intensive care utilization, transfusion requirements, and high rates of functional dependence underscores the importance of structured rehabilitation programs. Strengthening rehabilitation services, alongside surgical and critical care infrastructure, is therefore a justified priority to improve long‑term outcomes for survivors of firearm trauma.

Associations with ICU admission and mortality provide important insights into early risk stratification. Elevated heart rate at presentation was consistently associated with both ICU admission and mortality, in line with global trauma literature identifying tachycardia and hypotension as markers of physiological compromise [2,6]. Abdominal injuries showed significant associations with ICU admission, reflecting the severity of intra‑abdominal firearm trauma and its need for emergent laparotomy and intensive postoperative monitoring. In contrast, chest injuries did not reach statistical significance in multivariable analysis, though descriptive findings suggest they remain clinically important. Comparable studies have reported that abdominal and thoracic injuries are associated with higher transfusion requirements, prolonged ICU stays, and increased mortality [1,5,12,13]. These exploratory findings highlight the importance of structured triage protocols that integrate hemodynamic assessment and anatomical injury site to identify patients at higher risk. Hospitals in Palestine should prioritize rapid stabilization and expedited surgical intervention for patients presenting with tachycardia or abdominal trauma, while ensuring adequate ICU capacity. At the system level, multicenter trauma registries would allow continuous monitoring of associations and outcomes, enabling refinement of triage algorithms and benchmarking against regional and international standards [9,10].

In summary, this study differs from previous reports by providing the first multicenter, systematically collected evidence on firearm injuries in the West Bank. Unlike earlier single‑center or conflict‑specific case series, it offers consolidated data across eight hospitals, standardized variable definitions, and transparent statistical analyses. By documenting epidemiological trends, injury patterns, management strategies, and outcomes, it fills a critical gap in the literature and establishes a foundation for trauma system preparedness, resource allocation, and policy development in Palestine. The observed associations contribute to local understanding and highlight areas for strengthening trauma care, while also offering insights relevant to other conflict‑affected healthcare systems. These findings should be interpreted cautiously, particularly regarding exploratory regression analyses, but they nonetheless provide valuable lessons that can inform both regional and global approaches to firearm trauma.

Strengths and limitations

This study has several notable strengths. First, it represents the largest multicenter cohort of firearm injuries ever reported from the West Bank, encompassing eight hospitals and nearly 392 patients, which enhances the generalizability of the findings. Second, the use of a standardized data collection form and variable dictionary ensured consistency across centers, reducing misclassification and improving methodological rigor. Third, the inclusion of both governmental and private hospitals provided a diverse representation of trauma care settings, capturing variability in resources and practices. Fourth, the study adhered to the STROBE reporting guidelines, strengthening transparency and alignment with international standards. Fifth, the analysis incorporated detailed outcome measures, including ICU admission, transfusion, functional status, and mortality, providing a comprehensive picture of the clinical burden beyond simple descriptive accounts. Finally, by situating the findings within regional and global literature, the study offers comparative insights that are directly relevant to trauma system planning in conflict‑affected environments.

Nonetheless, several limitations must be acknowledged. First, the retrospective design relied on medical record documentation, which may have introduced information bias due to incomplete or inconsistent recording of clinical variables. Second, the absence of a national trauma registry limited the ability to capture cases treated outside the participating hospitals, potentially underestimating the true burden. Third, blood pressure was categorized using ACC/AHA thresholds, which are designed for chronic cardiovascular risk stratification and may not be clinically meaningful in the context of acute firearm trauma. This pragmatic choice was made to ensure consistency across hospitals, but future studies should incorporate trauma‑specific measures such as systolic blood pressure thresholds for shock, the Shock Index, or standardized injury severity scores to better capture acute physiological derangements. Fourth, the study did not include long‑term follow‑up, restricting assessment of functional recovery and disability beyond hospital discharge. Fifth, the lack of detailed data on weapon type, ballistic characteristics, and prehospital care constrained interpretation of injury mechanisms and contextual factors. Sixth, while the multicenter design improved representativeness, variability in documentation practices across hospitals may have introduced heterogeneity in data quality. Seventh, functional status was assessed pragmatically from medical record documentation rather than using a standardized instrument such as the Barthel Index or Functional Independence Measure. This may limit comparability with other studies. Future research should incorporate validated functional assessment tools to provide more precise and generalizable measures of disability. Eighth, the study did not include standardized injury severity measures such as the Injury Severity Score, the Abbreviated Injury Scale (AIS), the Revised Trauma Score (RTS), or the Trauma and Injury Severity Score (TRISS). The absence of these widely used scoring systems may have affected the precision of risk stratification and the robustness of multivariable analyses, since residual confounding by injury severity is likely. In addition, the lack of standardized severity adjustment limits comparability with other trauma cohorts and registries, making it difficult to benchmark outcomes across settings. Without these measures, the discriminatory ability and calibration of the prediction models may be influenced by unmeasured injury complexity, and the associations observed should therefore be interpreted with caution. Future studies should incorporate standardized severity scoring systems to improve comparability, strengthen predictive modeling, and reduce residual confounding. Establishing a national trauma registry that systematically collects ISS, AIS, RTS, and TRISS would further enhance external validity and allow more reliable benchmarking of outcomes in conflict‑affected regions. Ninth, the vast majority of injuries were conflict‑related; however, to avoid political polarization and maintain a strictly scientific focus, we did not categorize cases by intent and mechanism of firearm injury (such as conflict‑related, assault, accidental, or self‑inflicted). This limits interpretation of the epidemiological findings, and future studies should incorporate standardized documentation of injury intent and mechanism to enable more nuanced analyses and comparisons across settings. Tenth, the small number of deaths (n = 13) limited the stability of the mortality regression model, raising the potential for model instability and overfitting. Therefore, the mortality findings should be interpreted cautiously and considered exploratory. Future studies should aim to include larger cohorts with higher event counts to enable more robust and stable modeling of mortality outcomes. Establishing a national trauma registry would facilitate comprehensive data collection across hospitals and regions, improving representativeness and statistical power. In addition, prospective multicenter studies with standardized documentation practices and long‑term follow‑up would allow for more accurate assessment of prognostic factors, functional recovery, and disability. Collecting detailed information on weapon type, ballistic characteristics, and prehospital care would further strengthen the contextual interpretation of injury mechanisms and outcomes. Finally, although the models reported AUC values, Hosmer–Lemeshow statistics, and classification accuracy, internal validation measures such as bootstrap resampling or optimism‑corrected performance were not performed because these procedures are not available in standard SPSS logistic regression output. As such, the predictive performance estimates may be optimistic. Therefore, future studies should consider assessing the external validation of these estimates.

Taken together, these strengths and limitations highlight both the novelty and the challenges of conducting trauma research in conflict‑affected settings. Despite these constraints, the study provides robust multicenter evidence that fills a critical gap in the literature and establishes a foundation for future prospective registries, long‑term outcome studies, and policy interventions tailored to the realities of Palestine and comparable regions.

Conclusion

The findings reveal a predominance of extremity injuries, yet show that thoracoabdominal and vascular trauma were associated with disproportionately severe outcomes, including higher ICU utilization, transfusion requirements, and functional dependence at discharge. Despite relatively low in‑hospital mortality, the high burden of disability underscores the need for expanded orthopedic, vascular, and critical care capacity, alongside structured rehabilitation services. By filling a critical gap in the literature, this study establishes a foundation for trauma system preparedness, evidence‑based resource allocation, and policy development in Palestine, while contributing to the global understanding of firearm injuries in conflict‑affected healthcare systems. These associations should be interpreted cautiously, particularly regarding exploratory regression findings, but they nonetheless highlight important priorities for strengthening trauma care.

Supporting information

S1 Table. Adherence to the STROBE Statement.

(DOCX)

pone.0358566.s001.docx^{(23.5KB, docx)}

S2 Table. Data collection form.

(DOCX)

pone.0358566.s002.docx^{(23.7KB, docx)}

S3 Table. A detailed breakdown of injury distribution by anatomical site.

(DOCX)

pone.0358566.s003.docx^{(20.4KB, docx)}

S4 Table. A detailed breakdown of associated injuries.

(DOCX)

pone.0358566.s004.docx^{(23.3KB, docx)}

S5 Table. A detailed breakdown of surgical interventions.

(DOCX)

pone.0358566.s005.docx^{(21.4KB, docx)}

S6 Table. Univariate analysis of factors associated with ICU admission.

(DOCX)

pone.0358566.s006.docx^{(18.6KB, docx)}

S7 Table. Univariate analysis of factors associated with mortality outcome.

(DOCX)

pone.0358566.s007.docx^{(18.2KB, docx)}

S1 Fig. Full distribution of patients across age groups.

(TIF)

pone.0358566.s008.tif^{(84.5KB, tif)}

S1 Data. Anonymized raw data.

(XLSX)

pone.0358566.s009.xlsx^{(236.2KB, xlsx)}

Acknowledgments

The participating hospitals are acknowledged for facilitating this study. An-Najah National University (https://www.najah.edu) and An-Najah National University Hospital (https://www.nnuh.org) are acknowledged for making this study possible.

Abbreviations

ACC: American College of Cardiology
AHA: American Heart Association
CI: confidence interval
DALYs: disability-adjusted life years
EMRs: electronic medical records
GCS: Glasgow Coma Scale
ICU: intensive care unit
OR: odds ratio
Q1: first quartile
Q3: third quartile
SE: standard error
STROBE: Strengthening the Reporting of Observational Studies in Epidemiology

Data Availability

All relevant data are within the paper and its Supporting information files.

Funding Statement

The author(s) received no specific funding for this work.

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PLoS One. doi: 10.1371/journal.pone.0358566.r001

Decision Letter 0

Pawan Acharya

1 Jul 2026

Dear Dr. shawahna,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

==============================

Editorial Comments:

The reviewers have identified several important issues that require careful attention, particularly regarding the interpretation of the regression analyses, the limited number of mortality events, and clarification of the analytical approach. I encourage the authors to address each reviewer comment comprehensively. Please address all reviewer comments on a point-by-point basis and clearly indicate the corresponding revisions made in the manuscript.

More broadly, I believe the principal contribution of this manuscript lies in its descriptive epidemiology rather than in the multivariable prediction models. Strengthening the presentation and discussion of the descriptive findings, while presenting the regression analyses more cautiously and acknowledging their limitations, would improve the overall impact and credibility of the manuscript.

Clarify the multivariable model-building strategy and rationale for variable selection.
Given the novelty of this multicenter cohort, consider emphasizing the descriptive epidemiologic findings—which represent the principal contribution of the study—while presenting the regression analyses more cautiously.
Because mortality was uncommon, avoid overinterpreting classification accuracy and provide more informative measures of model performance if predictive analyses remain a major focus.

……………………….

Comments from Reviewer 1:

This manuscript addresses an important public health and trauma-care issue and provides valuable multicenter data from a region where firearm injury research remains limited. The multicenter design, relatively large sample size, inclusion of multiple hospitals, and availability of anonymized raw data are important strengths. The study has the potential to make a meaningful contribution to the literature after revision.

Major comments:

1. There is a major inconsistency in the mortality regression model. The manuscript reports odds ratios below 1 for both age and heart rate (OR=0.93 for each), yet interprets these variables as predictors of increased mortality. Please verify outcome coding, regression coefficients, odds ratios, confidence intervals, and interpretation throughout the manuscript.

2. Only 13 deaths occurred in the study cohort. The authors should justify the modeling strategy used for mortality prediction and discuss the potential for model instability and overfitting.

3. The study does not include standardized injury severity measures such as ISS, AIS, RTS, or TRISS. This limitation should be acknowledged more explicitly, and the potential impact on multivariable analyses should be discussed.

4. Functional dependence at discharge is reported as a major outcome; however, no clear definition or measurement instrument is provided. The authors should clarify how functional status was assessed and categorized.

5. Information regarding the intent and mechanism of firearm injury (conflict-related, assault, accidental, self-inflicted, etc.) is absent. This substantially limits interpretation of the epidemiological findings and should be discussed as an important limitation.

6. The rationale for classifying blood pressure according to ACC/AHA hypertension thresholds in an acute trauma population should be clarified. These categories may not be clinically meaningful in the context of firearm trauma.

7. There appears to be inconsistency between the regression results described in the text and Table 5. Lung injury is discussed in the Results section but is not included in the final regression table.

8. Several recommendations regarding expansion of ICU capacity, blood bank resources, and surgical infrastructure extend beyond the data directly collected in the study. These statements should be moderated or better justified.

Minor comments:

1. Clarify the definition of prehospital care categories.

2. Report the extent of missing data for key variables more explicitly.

3. Consider reporting ROC/AUC and additional measures of model performance.

4. Avoid speculative statements regarding firearm velocity, shooting distance, or injury circumstances unless supporting data are available.

5. Revise statements claiming disproportionate burden among individuals younger than 18 years, as the largest age group in the cohort was 18–29 years.

…………………..

Reviewer 2:

1. Lines 151–152: Regarding the assessment of hemodynamic instability, I think it is inappropriate to include systolic blood pressure of more than 170 mmHg and a GCS score of less than 13.

2. Please clearly state in the Introduction what issues currently exist regarding the triage of fire-arm related trauma in Palestine. It is not clear from the main text why this study needs to examine factors associated with ICU admission and in-hospital mortality.

3. Lines 183–188: Regarding the multivariate analysis examining factors associated with ICU admission and in-hospital mortality, it is unclear why “age,” “pulse rate on arrival,” “chest trauma,” and “abdominal trauma” were selected as covariates. Please cite the prior literature and describe the process used to select these variables. Please also explain why other variables were not selected. Also, please explain why other variables were not selected. Furthermore, while this study classified “chest trauma” and “abdominal trauma” into the same category regardless of severity or the affected organ, I think it is inappropriate to group them together in this way.

4. Supplementary Figure 1 was not included in the main text; please add it.

==============================

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Reviewers' comments:

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Reviewer #1: Partly

Reviewer #2: Partly

**********

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Reviewer #1: No

Reviewer #2: No

**********

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Reviewer #1: Yes

Reviewer #2: Yes

**********

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Reviewer #1: Yes

Reviewer #2: Yes

**********

Reviewer #1: Dear authors

Major comments:

2. Only 13 deaths occurred in the study cohort. The authors should justify the modeling strategy used for mortality prediction and discuss the potential for model instability and overfitting.

Minor comments:

1. Clarify the definition of prehospital care categories.

2. Report the extent of missing data for key variables more explicitly.

3. Consider reporting ROC/AUC and additional measures of model performance.

4. Avoid speculative statements regarding firearm velocity, shooting distance, or injury circumstances unless supporting data are available.

5. Revise statements claiming disproportionate burden among individuals younger than 18 years, as the largest age group in the cohort was 18–29 years.

Overall recommendation: Major Revision.

Reviewer #2: 1. Lines 151–152: Regarding the assessment of hemodynamic instability, I think it is inappropriate to include systolic blood pressure of more than 170 mmHg and a GCS score of less than 13.

4. Supplementary Figure 1 was not included in the main text; please add it.

**********

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Reviewer #1: No

Reviewer #2: No

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PLoS One. 2026 Sep 22;21(9):e0358566. doi: 10.1371/journal.pone.0358566.r002

Author response to Decision Letter 1

20 Jul 2026

MANUSCRIPT ID/NUMBER: PONE-D-26-16621

MANUSCRIPT TITLE: Firearm injuries in a conflict affected region: A multicenter study of epidemiological trends, injury patterns, management, and outcomes in the West Bank of Palestine

JOURNAL: PLOS One

EDITOR: Prof. Dr. Pawan Acharya, PhD, MSPH

Dear editor,

Many thanks for sharing your comments and comments of the reviewers on our manuscript submitted for publication in your highly esteemed journal. We are very delighted to learn that you and the reviewers have found the manuscript to be relevant, interesting, and consideration worthy. We are also thankful for all the insightful and constructive comments which we believe have improved the quality, clarity, and flow of the revised manuscript.

Please note that we have found all comments and suggestions provided by the reviewers as relevant and consideration worthy. In this revision, we have addressed all the comments and suggestions raised by the reviewers and the manuscript was amended accordingly. Please find below a point-to-point detailed account of responses to reviewers’ comments and how the manuscript was revised accordingly. For your convenience and to expedite the decision, all revisions and amendments were highlighted in red font.

EDITORIAL COMMENTS

1. Comment: The reviewers have identified several important issues that require careful attention, particularly regarding the interpretation of the regression analyses, the limited number of mortality events, and clarification of the analytical approach. I encourage the authors to address each reviewer comment comprehensively. Please address all reviewer comments on a point-by-point basis and clearly indicate the corresponding revisions made in the manuscript.

Response: We would like to sincerely thank you for the time and effort devoted to reading, reviewing, commenting on our manuscript, and for finding suitable reviewers to provide their valuable feedback. We are very grateful for the constructive and helpful comments, which we found highly insightful.

Please note that all comments raised by you and the reviewers have been carefully addressed in this revised version, and we believe that the changes have improved the quality, focus, and clarity of the manuscript. For ease of review, all revisions and amendments have been highlighted in red font in the revised manuscript. Please see below how all your comments and the comments of the reviewers were addressed.

2. Comment: More broadly, I believe the principal contribution of this manuscript lies in its descriptive epidemiology rather than in the multivariable prediction models. Strengthening the presentation and discussion of the descriptive findings, while presenting the regression analyses more cautiously and acknowledging their limitations, would improve the overall impact and credibility of the manuscript.

Response: Many thanks for this comment. We fully agree with your observation that the principal contribution of this manuscript lies in its descriptive epidemiology rather than in the multivariable prediction models. As you have suggested, we have improved the focus of the presentation by placing greater emphasis on the descriptive epidemiological findings. The presentation and discussion of descriptive results have been strengthened, while the regression analyses are now presented more cautiously with explicit acknowledgment of their limitations as you and the reviewers have suggested. We believe these revisions have enhanced the overall impact and credibility of the manuscript. Please see Lines 95-106, 303-322, and 400-436.

3. Comment: Clarify the multivariable model-building strategy and rationale for variable selection.

Response: Many thanks for this comment. As you have suggested, we clarified the multivariable model‑building strategy and provided a clear rationale for variable selection. Specifically, we explained that candidate variables were chosen based on their statistical significance in bivariate analyses and their clinical relevance as supported by prior literature. We also clarified why certain variables were included and why others were not, ensuring transparency in the modeling process. Please see Lines 202-215.

4. Comment: Given the novelty of this multicenter cohort, consider emphasizing the descriptive epidemiologic findings—which represent the principal contribution of the study—while presenting the regression analyses more cautiously.

Response: Many thanks for this comment. We fully agree that the novelty of this multicenter cohort lies primarily in its descriptive epidemiologic findings. As you have suggested, we have emphasized these descriptive results more prominently, as they represent the principal contribution of the study in this revision. Please see Lines 303-322.

At the same time, the regression analyses are now presented more cautiously, with explicit acknowledgment of their limitations. This balanced approach ensures that the descriptive epidemiology is highlighted while the regression findings are contextualized appropriately. Please see Lines 400-436.

5. Comment: Because mortality was uncommon, avoid overinterpreting classification accuracy and provide more informative measures of model performance if predictive analyses remain a major focus.

Response: We sincerely thank you and reviewers for this constructive observation. We fully acknowledge that mortality was uncommon in our cohort, and therefore the predictive analyses must be interpreted with caution. In the revised manuscript, we avoided overinterpreting classification accuracy and instead provided more informative measures of model performance, including AUC values, to better contextualize the regression results. Please see Lines 303-322.

These revisions ensure that the predictive analyses are presented more cautiously and transparently, in line with the limitations of the dataset. Please see Lines 400-436.

REVIEWER 1:

1. Comment: This manuscript addresses an important public health and trauma-care issue and provides valuable multicenter data from a region where firearm injury research remains limited. The multicenter design, relatively large sample size, inclusion of multiple hospitals, and availability of anonymized raw data are important strengths. The study has the potential to make a meaningful contribution to the literature after revision. Dear authors: This manuscript addresses an important public health and trauma-care issue and provides valuable multicenter data from a region where firearm injury research remains limited. The multicenter design, relatively large sample size, inclusion of multiple hospitals, and availability of anonymized raw data are important strengths. The study has the potential to make a meaningful contribution to the literature after revision.

Response: We would like to sincerely thank you for the time and effort devoted to reading, reviewing, and commenting on our manuscript. We are delighted to learn that you have found the manuscript important, interesting, and addressing a significant public health and trauma‑care issue by providing valuable multicenter data from a region where firearm injury research remains limited.

We are also grateful for highlighting the strengths of the work, including the multicenter design, relatively large sample size, inclusion of multiple hospitals, and availability of anonymized raw data. We greatly appreciate your encouraging words and recommendation for acceptance after addressing the comments.

All comments have been carefully considered and addressed in this revised version, which we believe has improved the quality, clarity, and focus of the manuscript. For ease of review, all changes have been highlighted in red font. Please see below.

Major comments:

2. Comment: There is a major inconsistency in the mortality regression model. The manuscript reports odds ratios below 1 for both age and heart rate (OR=0.93 for each), yet interprets these variables as predictors of increased mortality. Please verify outcome coding, regression coefficients, odds ratios, confidence intervals, and interpretation throughout the manuscript.

Response: Many thanks for this comment. To ensure accuracy, we sought professional statistical advice and carefully re‑examined the regression coding, coefficients, odds ratios, and confidence intervals. As part of this process, we conducted univariate analyses and added them as supplementary files (S6 and S7 Tables) to provide clearer insight into the associations. These analyses confirmed that patients who died were significantly older and had higher heart rates on arrival, and that patients admitted to the ICU also had higher heart rates and more frequent chest and abdominal injuries. We then re‑conducted the multivariate logistic regression analyses with corrected coding and diagnostics. The text in the Results section has been revised accordingly to ensure consistency with the statistical outputs, and the interpretation of odds ratios has been revised accordingly. Please see Lines 303-322, S6 Table, S7 Table, and Table 5.

3. Comment: Only 13 deaths occurred in the study cohort. The authors should justify the modeling strategy used for mortality prediction and discuss the potential for model instability and overfitting.

Response: Many thanks for this comment. As you have suggested, we have now explicitly cautioned that the mortality model should be considered exploratory due to the small number of events, and that the findings may be subject to model instability and overfitting. To further strengthen transparency, we added AUC values to provide more informative measures of model performance beyond classification accuracy. Please see Lines 303-322.

In addition, a dedicated limitation has been added to the Discussion section to discuss this. Please see Lines 400-436.

4. Comment: The study does not include standardized injury severity measures such as ISS, AIS, RTS, or TRISS. This limitation should be acknowledged more explicitly, and the potential impact on multivariable analyses should be discussed.

Response: Many thanks for this comment. As you have suggested, we have now explicitly discussed this in the limitations. In addition, we also discussed the impact of these on the results. Please see Lines 417-422.

5. Comment: Functional dependence at discharge is reported as a major outcome; however, no clear definition or measurement instrument is provided. The authors should clarify how functional status was assessed and categorized.

Response: Many thanks for this comment. As you have suggested, we have now explicitly added a definition of this outcome. Again, the limitation of this measure was also discussed in the limitations. Please see Lines 171-178.

6. Comment: Information regarding the intent and mechanism of firearm injury (conflict-related, assault, accidental, self-inflicted, etc.) is absent. This substantially limits interpretation of the epidemiological findings and should be discussed as an important limitation.

Response: We thank the reviewer for this important observation. Indeed, the study was conducted in a conflict‑affected area, and the injuries were overwhelmingly conflict‑related. However, to avoid political polarization and maintain a neutral scientific tone, we did not categorize cases by intent in the main analyses. To address this, we have added a dedicated limitation in the Discussion section acknowledging the absence of intent and mechanism data, and we recommend that future studies incorporate standardized documentation of injury intent to strengthen interpretation of epidemiological findings. Please see Lines 422-427.

7. Comment: The rationale for classifying blood pressure according to ACC/AHA hypertension thresholds in an acute trauma population should be clarified. These categories may not be clinically meaningful in the context of firearm trauma.

Response: Many thanks for this comment. As you have suggested, the reasons for adopting these thresholds were added to the revised methods. Please see Lines 154-162.

We also added to the limitations the implications of using these thresholds. Please see Lines 403-408.

8. Comment: There appears to be inconsistency between the regression results described in the text and Table 5. Lung injury is discussed in the Results section but is not included in the final regression table.

Response: Many thanks for this comment. As you have suggested, univariate analysis was conducted in this revision. Again, the multivariate regression analysis was also re-conducted. The Results section has been harmonized with Table 5, ensuring that only variables retained in the final multivariate model are described in the text. Please see Lines 315-322.

9. Comment: Several recommendations regarding expansion of ICU capacity, blood bank resources, and surgical infrastructure extend beyond the data directly collected in the study. These statements should be moderated or better justified.

Response: Many thanks for this comment. As you have suggested, we have revised these discussions and better justified these recommendations. Please see Lines 339-344, 351-355, and 362-366.

Minor comments:

10. Comment: Clarify the definition of prehospital care categories.

Response: Many thanks for this comment. As you have suggested, we have added clearer definition for prehospital care categories. Please see Lines 149-152.

11. Comment: Report the extent of missing data for key variables more explicitly.

Response: Many thanks for this comment. As you have suggested, we have explicitly added to the tables missing variables as not documented or not recorded, etc. Please see Lines 189-192 and Table 1.

12. Comment: Consider reporting ROC/AUC and additional measures of model performance.

Response: Many thanks for this comment. As you have suggested, we have explicitly reported the AUC and additional measures of model performance. Please see Lines 212-215 and 303-322.

13. Comment: Avoid speculative statements regarding firearm velocity, shooting distance, or injury circumstances unless supporting data are available.

Response: Many thanks for this comment. As you have suggested, we have revised the discussion to avoid these speculative statements. Please see Lines 339-344, 351-355, 363-366.

14. Comment: Revise statements claiming disproportionate burden among individuals younger than 18 years, as the largest age group in the cohort was 18–29 years.

Response: Many thanks for this observation. As you have suggested, we have revised the text and ensured that S1 Fig was uploaded. Please see Lines 237-243 and S1 Fig.

REVIEWER 2:

1. Comment: Lines 151–152: Regarding the assessment of hemodynamic instability, I think it is inappropriate to include systolic blood pressure of more than 170 mmHg and a GCS score of less than 13.

We thank the reviewer for this valuable observation. As you have suggested, the definition of hemodynamic instability was clarified. Please see Lines 153-166.

2. Comment: Please clearly state in the Introduction what issues currently exist regarding the triage of fire-arm related trauma in Palestine. It is not clear from the main text why this study needs to examine factors associated with ICU admission and in-hospital mortality.

Response: Many thanks for this comment. As you have suggested, we have clearly added the rationale for this study by adding more on the challenges regarding the triage of fire-arm related trauma in Palestine. Please see Lines XXX.

3. Comment: Lines 183–188: Regarding the multivariate analysis examining factors associated with ICU admission and in-hospital mortality, it is unclear why “age,” “pulse rate on arrival,” “chest trauma,” and “abdominal trauma” were selected as covariates. Please cite the prior literature and describe the process used to select these variables. Please also explain why other variables were not selected. Also, please explain why other variables were not selected. Furthermore, while this study classified “chest trauma” and “abdominal trauma” into the same category regardless of severity or the affected organ, I think it is inappropriate to group them together in this way.

Response: Many thanks for this comment. As you have suggested, we have clearly added the rationale for selecting these variables. Please see Lines 95-106.

4. Comment: Supplementary Figure 1 was not included in the main text; please add it.

Response: Many thanks for pointing this out. As you have pointed, we have included the S1 Fig in this revision.

COMMENTS TO THE AUTHOR

1. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

Reviewer #2: Partly

Response: Many thanks for this comment. By addressing your comments, we have strengthened the methodological clarity, explicitly defined variable selection, corrected inconsistencies between text and tables, and moderated speculative statements. The analyses were reconducted where needed, predictors were justified with prior literature, and missing data were transparently reported. With these revisions, the data now fully support the conclusions, and the manuscript presents a technically sound piece of research with appropriate rigor, controls, and sample size.

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

Reviewer #2: No

Response: Many thanks for this comment. By addressing your comments, we have clarified the process of variable selection, justified covariates with reference to prior trauma literature. We also reconducted univariate and multivariate analyses, reported missing data transparently, and added model performance metrics including ROC curves and AUC values. These revisions strengthen the methodological rigor and ensure that the statistical analyses are appropriate, transparent, and robust.

3. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

Response: We thank both reviewers for acknowledging that all data underlying the findings have been made fully available in accordance with the PLOS Data policy. We appreciate this recognition and have ensured that the dataset, supporting tables, and supplementary materials remain accessible without restriction, safeguarding transparency and reproducibility.

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

Response: We thank both reviewers for confirming that the manuscript is presented in an intelligible fashion and written in standard English. We appreciate this recognition and have carefully corrected typographical and grammatical errors during revision to ensure clarity, accuracy, and readability.

Once again, we would like to thank you and the reviewers for the constructive feedback and comments, which we believe have improved the quality, clarity and flow of the revised manuscript.

Having addressed all comments and revised the manuscript accordingly, we are looking forward to hearing from you soon.

Kind regards

Ramzi Shawahna

Attachment

Submitted filename: 02. Response to Reviewers.docx

pone.0358566.s011.docx^{(69.6KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0358566.r003

Decision Letter 1

Pawan Acharya

12 Aug 2026

Dear Dr. shawahna,

Comments from the reviewer:

I believe the manuscript is close to being suitable for publication. However, a few issues should still be addressed before acceptance.

Major remaining concern

The principal remaining concern relates to the multivariable regression analyses. Although the statistical methods are now more clearly described, the mortality model is based on only 13 deaths. This very small number of events substantially limits the stability of logistic regression estimates and increases the risk of overfitting. While the authors appropriately acknowledge this limitation in the Discussion, the interpretation of the mortality model should be further softened throughout the manuscript. Statements suggesting independent prediction should be presented more cautiously, emphasizing that these findings are exploratory and require external validation.

Additional comments

The discrepancy between the Results text and Table 5 regarding chest injury should be corrected. The Results section reports chest injury as an independent predictor of ICU admission, whereas Table 5 reports a non-significant association (OR 0.52, p = 0.163). This inconsistency must be resolved.

The rationale for selecting variables included in the multivariable models should be described more explicitly. Although the manuscript states that variables were chosen based on clinical relevance and univariate analyses, the exact selection strategy would benefit from clearer explanation.

Because standardized trauma severity scores (such as ISS, AIS, RTS, or TRISS) were unavailable, the limitations of the prediction models should be emphasized once more, since residual confounding by injury severity is likely.

The manuscript reports AUC values, Hosmer-Lemeshow statistics, and classification accuracy, which are helpful. If feasible, the authors may also consider reporting internal validation measures (for example, bootstrap validation or optimism-corrected performance). If this is not possible, it should be acknowledged as a limitation.

The manuscript would benefit from one final careful language edit to improve consistency in terminology and remove a few minor typographical and formatting inconsistencies.

Please submit your revised manuscript by Oct 11 2026 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

A letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
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We look forward to receiving your revised manuscript.

Kind regards,

Pawan Acharya, PhD, MSPH

Academic Editor

PLOS One

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Please address all comments from the reviewer on point-to-point basis.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #1: (No Response)

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions??>

Reviewer #1: Partly

Reviewer #2: Yes

**********

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Reviewer #1: No

Reviewer #2: Yes

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The PLOS Data policy

Reviewer #1: (No Response)

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English??>

Reviewer #1: Yes

Reviewer #2: Yes

**********

Reviewer #1: Thank you for the careful revision of the manuscript. The authors have addressed many of the concerns raised in the previous review, and the manuscript has improved substantially in terms of organization, methodological transparency, and discussion. The multicenter design and the inclusion of patients from eight hospitals provide valuable information on firearm injuries in the West Bank, and the study represents an important contribution to the literature.

I believe the manuscript is close to being suitable for publication. However, a few issues should still be addressed before acceptance.

Major remaining concern

Additional comments

The manuscript would benefit from one final careful language edit to improve consistency in terminology and remove a few minor typographical and formatting inconsistencies.

Overall, the manuscript has improved considerably since the previous version. After addressing the points above, I believe it will be suitable for publication.

Reviewer #2: The author has appropriately addressed my questions, and I believe the submitted paper has been suitably revised. Good job.

**********

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Reviewer #1: No

Reviewer #2: No

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PLoS One. 2026 Sep 22;21(9):e0358566. doi: 10.1371/journal.pone.0358566.r004

Author response to Decision Letter 2

20 Aug 2026

MANUSCRIPT ID/NUMBER: PONE-D-26-16621

MANUSCRIPT TITLE: Firearm injuries in a conflict affected region: A multicenter study of epidemiological trends, injury patterns, management, and outcomes in the West Bank of Palestine

JOURNAL: PLOS One

EDITOR: Prof. Dr. Pawan Acharya, PhD, MSPH

Dear editor,

We would like to sincerely thank the you and both reviewers for the time, effort, and thoughtful feedback devoted to our manuscript. We greatly appreciate the recognition of the improvements made in organization, methodological transparency, and discussion, as well as the acknowledgment of the importance of this multicenter study in documenting firearm injuries in the West Bank.

All additional comments and final edits have been carefully addressed as suggested. Specifically, the interpretation of the mortality model has been softened throughout the manuscript to emphasize its exploratory nature given the small number of deaths, and the limitations of residual confounding have been further highlighted. The discrepancy between the Results text and Table 5 regarding chest injury has been corrected, and the rationale for variable selection in the multivariable models has been clarified. We have also acknowledged the absence of standardized trauma severity scores and the lack of internal validation measures as limitations. Finally, the manuscript has undergone a careful language edit to ensure consistency in terminology and formatting.

We are grateful for the constructive guidance provided, which has helped us refine the manuscript and ensure accuracy, clarity, and transparency. Thank you once again for recognizing the importance of our work and for supporting its improvement toward publication.

Please find below a point-to-point detailed account of responses to reviewers’ comments and how the manuscript was revised accordingly. For your convenience and to expedite the decision, all revisions and amendments were highlighted in red font.

Reviewer #1:

1. Comment: Thank you for the careful revision of the manuscript. The authors have addressed many of the concerns raised in the previous review, and the manuscript has improved substantially in terms of organization, methodological transparency, and discussion. The multicenter design and the inclusion of patients from eight hospitals provide valuable information on firearm injuries in the West Bank, and the study represents an important contribution to the literature.

Response: We sincerely thank the reviewer for the time and effort devoted to evaluating our revised manuscript. We are delighted that the improvements in organization, methodological transparency, and discussion were recognized, and we greatly appreciate the acknowledgment of the value of our multicenter design and inclusion of patients from eight hospitals. Your encouraging feedback reinforces the importance of this study, and we are grateful for your thoughtful review.

2. Comment: I believe the manuscript is close to being suitable for publication. However, a few issues should still be addressed before acceptance.

Response: We are very delighted to learn that you will recommend the acceptance of the manuscript after addressing the final comments and suggestions. Thank you for your thoughtful evaluation and constructive guidance, which have been invaluable in refining our work. Please see below how all comments and suggestions were addressed and how the manuscript was amended accordingly.

Major remaining concern

3. Comment: The principal remaining concern relates to the multivariable regression analyses. Although the statistical methods are now more clearly described, the mortality model is based on only 13 deaths. This very small number of events substantially limits the stability of logistic regression estimates and increases the risk of overfitting. While the authors appropriately acknowledge this limitation in the Discussion, the interpretation of the mortality model should be further softened throughout the manuscript. Statements suggesting independent prediction should be presented more cautiously, emphasizing that these findings are exploratory and require external validation.

Response: We thank the reviewer for this important observation. We fully acknowledge that the mortality model was based on only 13 deaths, which substantially limits the stability of logistic regression estimates and increases the risk of overfitting. As you have suggested, we have carefully revised the manuscript to soften the interpretation of these results throughout. Specifically, statements that previously suggested “independent prediction” have been replaced with phrasing that emphasizes observed associations. We now consistently describe the mortality findings as exploratory and highlight the need for external validation in larger cohorts. These changes ensure that the limitations of the mortality model are appropriately reflected in both the Results and Discussion sections. Please see Lines 341-359, 371-395, and 441-450.

Additional comments

4. Comment: The discrepancy between the Results text and Table 5 regarding chest injury should be corrected. The Results section reports chest injury as an independent predictor of ICU admission, whereas Table 5 reports a non-significant association (OR 0.52, p = 0.163). This inconsistency must be resolved.

Response: Many thanks for pointing this out. In this revision, the inconsistency was resolved. Please see Lines 33-35 and 309-312.

5. Comment: The rationale for selecting variables included in the multivariable models should be described more explicitly. Although the manuscript states that variables were chosen based on clinical relevance and univariate analyses, the exact selection strategy would benefit from clearer explanation.

Response: Many thanks for this comment. As you have suggested, the rationale for selecting variables included in the multivariable models was described more explicitly. Please see Lines 202-213.

6. Comment: Because standardized trauma severity scores (such as ISS, AIS, RTS, or TRISS) were unavailable, the limitations of the prediction models should be emphasized once more, since residual confounding by injury severity is likely.

Response: Many thanks for this comment. As you have suggested, we have expanded the limitation discussing unavailability of standardized trauma severity scores (such as ISS, AIS, RTS, or TRISS) emphasizing the limitations of the prediction models as residual confounding by injury severity is likely. Please see Lines 425-436.

7. Comment: The manuscript reports AUC values, Hosmer-Lemeshow statistics, and classification accuracy, which are helpful. If feasible, the authors may also consider reporting internal validation measures (for example, bootstrap validation or optimism-corrected performance). If this is not possible, it should be acknowledged as a limitation.

Response: Many thanks for this comment. As SPSS was used to analyze the data, these could not be performed. As you have suggested, these were discussed in the limitations. Please see Lines 450-455.

8. Comment: The manuscript would benefit from one final careful language edit to improve consistency in terminology and remove a few minor typographical and formatting inconsistencies.

Response: Many thanks for this comment. The manuscript was proofread and the language was edited. Please see Lines 341-455.

9. Comment: Overall, the manuscript has improved considerably since the previous version. After addressing the points above, I believe it will be suitable for publication.

Response: We sincerely thank you for your time, effort, and constructive feedback. We are very pleased to learn that the manuscript has improved considerably and is now you will recommend it for publication. All remaining points have been carefully addressed, and we are grateful for the guidance that has helped us refine the work to this stage.

Reviewer #2:

1. Comment: The author has appropriately addressed my questions, and I believe the submitted paper has been suitably revised. Good job.

Response: We sincerely thank the reviewer for the time and effort devoted to evaluating our revised manuscript. We are delighted that the reviewer has approved all revisions and recommended the acceptance of the revised manuscript.

Once again, we would like to thank you and the reviewers for the constructive feedback and comments, which we believe have improved the quality, clarity and flow of the revised manuscript.

Having addressed all comments and revised the manuscript accordingly, we are looking forward to hearing from you soon.

Kind regards

Ramzi Shawahna

Attachment

Submitted filename: 03. Response to Reviewers.docx

pone.0358566.s012.docx^{(61.8KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0358566.r005

Decision Letter 2

Pawan Acharya

2 Sep 2026

Firearm injuries in a conflict affected region: A multicenter study of epidemiological trends, injury patterns, management, and outcomes in the West Bank of Palestine

PONE-D-26-16621R2

Dear Dr. shawahna,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Pawan Acharya, PhD, MSPH

Academic Editor

PLOS One

Additional Editor Comments (optional):

Reviewers' comments:

PLoS One. doi: 10.1371/journal.pone.0358566.r006

Acceptance letter

Pawan Acharya

PONE-D-26-16621R2

PLOS One

Dear Dr. shawahna,

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS One. Congratulations! Your manuscript is now being handed over to our production team.

At this stage, our production department will prepare your paper for publication. This includes ensuring the following:

* All references, tables, and figures are properly cited

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Thank you for submitting your work to PLOS One and supporting open access.

Kind regards,

PLOS One Editorial Office Staff

on behalf of

Dr. Pawan Acharya

Academic Editor

PLOS One

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Table. Adherence to the STROBE Statement.

(DOCX)

pone.0358566.s001.docx^{(23.5KB, docx)}

S2 Table. Data collection form.

(DOCX)

pone.0358566.s002.docx^{(23.7KB, docx)}

S3 Table. A detailed breakdown of injury distribution by anatomical site.

(DOCX)

pone.0358566.s003.docx^{(20.4KB, docx)}

S4 Table. A detailed breakdown of associated injuries.

(DOCX)

pone.0358566.s004.docx^{(23.3KB, docx)}

S5 Table. A detailed breakdown of surgical interventions.

(DOCX)

pone.0358566.s005.docx^{(21.4KB, docx)}

S6 Table. Univariate analysis of factors associated with ICU admission.

(DOCX)

pone.0358566.s006.docx^{(18.6KB, docx)}

S7 Table. Univariate analysis of factors associated with mortality outcome.

(DOCX)

pone.0358566.s007.docx^{(18.2KB, docx)}

S1 Fig. Full distribution of patients across age groups.

(TIF)

pone.0358566.s008.tif^{(84.5KB, tif)}

S1 Data. Anonymized raw data.

(XLSX)

pone.0358566.s009.xlsx^{(236.2KB, xlsx)}

Attachment

Submitted filename: 02. Response to Reviewers.docx

pone.0358566.s011.docx^{(69.6KB, docx)}

Attachment

Submitted filename: 03. Response to Reviewers.docx

pone.0358566.s012.docx^{(61.8KB, docx)}

Data Availability Statement

All relevant data are within the paper and its Supporting information files.

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PERMALINK

Firearm injuries in a conflict affected region: A multicenter study of epidemiological trends, injury patterns, management, and outcomes in the West Bank of Palestine

Hala Alkhoury

Mira Hallak

Mohammad Shakshir

Iyad Maqboul

Mohammad Jaber

Ramzi Shawahna

Roles

Abstract

Introduction

Methods

Study design and settings

Study population and eligibility criteria

Sample size and sampling approach

Definition of variables

Data collection

Statistical analysis

Ethical considerations

Results

Characteristics of the patients in the cohort

Table 1. Demographic characteristics and clinical presentation of the study cohort (n = 392).

Temporal distribution of firearm injury presentations

Fig 1. Temporal distribution of firearm injury presentations by year, month, and day of the week.

Anatomical distribution of injuries

Fig 2. Distribution of firearm injury by anatomical location and body region.

Associated injuries

Table 2. Distribution of injuries among the study cohort.

Management and discharge outcomes

Table 3. Surgical interventions performed in patients in the cohort.

Table 4. Clinical management and discharge outcomes of patients in the study cohort.

Factors associated with ICU admission and mortality

Table 5. Factors independently associated with ICU admission and mortality.

Discussion

Strengths and limitations

Conclusion

Supporting information

Acknowledgments

Abbreviations

Data Availability

Funding Statement

References

Decision Letter 0

Pawan Acharya

Roles

Author response to Decision Letter 1

Decision Letter 1

Pawan Acharya

Roles

Author response to Decision Letter 2

Decision Letter 2

Pawan Acharya

Roles

Acceptance letter

Pawan Acharya

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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