Abstract
Background:
The United States (US) leads all high-income countries in gunshot wound (GSW) deaths. However, previous US studies have not evaluated the national blood transfusion utilization patterns in hospitalized GSW patients.
Methods:
Data from 2016 to 2017 were analyzed from the Nationwide Emergency Department Sample (NEDS) and Nationwide Inpatient Sample (NIS), the largest all-payer emergency department (ED) and inpatient databases, respectively. Using stratified probability sampling, weights were applied to generate nationally representative estimates. Multivariable Poisson-regression models were used to estimate prevalence ratios (PR) of blood transfusion.
Results:
There were 168,315 ED visits and 58,815 hospitalizations (age = 18–90 years) following a GSW. The majority of hospitalizations were men (88.5%), age 18–24 years (31.8%), and assault-related GSW (51.3%). Blacks had the largest proportion (48.7%) overall of all GSW hospitalizations; Whites accounted for the highest proportion of intentional self-harm injuries (72.4%). Blood transfusions occurred in 12.7% of hospitalizations (12.0% red blood cell [RBC], 4.9% plasma, and 2.5% platelet transfusions). Only 1.9% of cases were associated with transfusion of all three blood components. Hospitalizations with major/extreme severity of illness had significantly higher prevalence of transfusion versus those with mild/moderate severity [crude PR = 4.79 (95% CI:4.15–5.33, p < .001)]. Overall, 8.2% of hospitalizations with GSW died, of whom 26.8% required blood transfusions, which was significantly higher than survivors [crude PR = 2.34 (95%CI:2.10–2.61, p < .001)]. The vast majority (95%) of the transfusions among those who died were within 48 h since admission.
Conclusions:
Gun-related violence is a public health emergency in the US, and GSWs are a source of significant mortality, blood utilization, and health care costs.
Keywords: blood transfusion, firearm injury, gunshot wound, plasma, platelets, red blood cells
1 |. BACKGROUND
The United States (US) leads all high-income countries in gunshot wound (GSW) deaths.1,2 Per the US Centers for Disease Control and Prevention, GSW-related deaths in the US reached their highest level in nearly 40 years in 2019.3 While the US population is less than 5% of the global population, nearly half of the world’s civilian firearms are owned by individuals in the US. Firearm injuries are a major public health problem in the US,4,5 substantially contributing to health care utilization, and causing short and long-term disability as well as premature death.6–8 Studies have presented the epidemiology of firearm injury-related presentations in the emergency department (ED) and hospitalized patients.5,9 However, despite the national burden of civilian GSW injuries, the blood transfusion utilization in these patients is underexplored and not well understood.
Hemorrhage is the leading cause of preventable death in military and civilian traumatic injuries. Blood transfusion is a vital component of resuscitation of patients who are in hemorrhagic shock from GSW and other penetrating injuries.10,11 Use of massive transfusion protocols that hasten treatment with adequate quantities and ratios of various blood products, improve hemostasis and reduce hemorrhagic death in adult trauma victims.12,13 Most of the published literature pertains to blood utilization during combat, battlefield, and military trauma.14 In-hospital and ED utilization for civilian firearm injuries is relatively understudied. A recent 10-year analysis of Maryland state trauma registry found that GSW victims are approximately five times more likely to require blood transfusions, require 10 times more blood units, and are 14 times more likely to die than people suffering non-GSW traumatic injuries.15 However, no previous US studies have evaluated the national blood transfusion utilization patterns in GSW injuries in hospitalized patients.
This study evaluated the ED and in-hospital presentation and blood transfusion utilization for fatal and nonfatal firearm injuries among adults in the United States.
2 |. STUDY DESIGN/METHODS
2.1 |. Data source
The National Inpatient Sample (NIS) and the Nationwide Emergency Department Sample (NEDS) are the largest all-payer inpatient hospitalizations and ED databases in the US, respectively. Data from the 2016 and 2017 NIS and NEDS were used in this analysis. These databases were developed as part of the Healthcare Cost and Utilization Project (HCUP) by the Agency for Healthcare Research and Quality (AHRQ).
The NIS is a stratified systematic random sample of discharges, and the sample unit was a 20% stratified sample of discharges from US hospitals. A stratified random sample of discharges was systematically drawn from a list of discharges sorted on discharge characteristics such as DRG and admission month. The hospitals were stratified according to census division, location, teaching status, ownership, and bed size. The NIS represented approximately 96% of the US population. The NEDS is a 20% stratified sample of hospital-owned EDs, using stratified single-stage cluster sample strategy. The hospital strata include geographic region, location, teaching status, ownership, and trauma-level designation. After stratified random samples of hospitals or clusters were drawn, discharges were included from selected cluster. The NEDS represented approximately 82.8% of all US ED visits.
Since the NIS and NEDS are de-identified, publicly available datasets, the Johns Hopkins Medical Institutions Institutional Review Board deemed the study exempt from review. HCUP data use agreement guidelines were followed.
2.2 |. Study population
The unit of analysis was a GSW-related ED visit for NEDS and GSW-related inpatient hospitalization for NIS. Since the unit of observation is an ED visit or a hospitalization, patients may be included more than once in the database. For this analysis, GSW-related injuries coded as initial encounter only were used, while all subsequent visits and/or encounters related to GSW sequela were excluded. Only adult hospitalizations (patient age ≥ 18 years) were analyzed in this study. Each record included information on patient demographics (age, sex, and race), hospital characteristics (hospital ownership, bed size, census region, location, and teaching status), patient outcomes (inpatient mortality), up to 25 International Classification of Diseases, Tenth Revisions, Clinical Modification (ICD-10-CM) diagnosis codes, and up to 15 ICD-10-CM procedure codes (25 codes for NIS 2017). Procedure codes of ED were not available). External cause of morbidity/ICD-10-CM codes were used to identify GSW-related injuries. The GSW-related injuries were categorized according to ICD-10 conventions as “Accident,” “Assault,” “Intentional,” and “Legal” (i.e., law enforcement-related) (Appendix 1 lists the details of injury types and ICD-10 codes). ICD-10-CM procedure codes were used to identify transfusion procedures including red blood cell (RBC), plasma, and platelet transfusions (Appendix 2).
2.3 |. Statistical analyses
Data analysis was conducted using svy commands in Stata/MP version 15.1 (Statacorp, College Station, TX) and R version 4.0.2. Sampling weights, provided by HCUP, were applied to generate nationally representative estimates. The distribution of characteristics was estimated among adult GSW patients who were admitted to the ED and hospital using both NEDS and NIS, respectively, stratified by GSW type. NEDS does not provide data on blood transfusion. For NIS, the primary outcome was percentage of hospitalizations with at least one blood transfusion (RBC, plasma, or platelet transfusion). Univariable and multivariable Poisson regression analyses were performed to generated curde and adjusted prevalence ratios (adjPR) and determine independent and non-independent risk factors of blood product transfusion in patients with GSW hospitalizations. Covariates included for Model 1 were GSW type by mechanism of injury, age, sex, race/ethnicity, primary payer, hospital control, hospital bed size, teaching status, patient census division-based location, median ZIP code household income, and geographical location. A second multivariable Poisson regression (Model 2) was performed including APR-DRG risk severity subclass and in-hospital mortality. The gross aggregate annual bill for hospital charges was estimated using the product of mean total charges per GSW hospitalization and total number of GSW hospitalizations per year.
3 |. RESULTS
3.1 |. Emergency department
The NEDS included data from 66 million ED visits in the US during 2016 and 2017. This study was restricted to the 168,315 adults who were treated in the ED following an initial encounter including a GSW. Table 1 presents the weighted characteristics of the study population. Accidental GSW injuries (50.0%) accounted for the highest proportion, followed by assault (43.2%), intentional self-harm (5.3%), and legal intervention (1.5%). The vast majority of adult patients with GSWs were male (87.8%) and many were young adults aged 18–24 years (33.2%). Medicaid was the primary insurance for 31.0%, whereas 32.0% were self-pay. ED GSW admissions were most commonly treated in teaching hospitals (76.1%) and Level I or II trauma centers (66.9%). The largest proportion of GSWs was in central counties of metropolitan areas (43.7%) and low-income zip code areas (52.8%). Most of the GSW admissions in the ED were treated and released (52.3%), although 6.0% died in the ED. Female GSW admissions were lowest in the legal intervention (8.0%) category and highest in the intentional self-harm (18.8%) category. Compared to other types of GSW, intentional self-harm injuries were more likely among admissions over age 50 years (40.4%), who live in micropolitan or non-metropolitan counties (28.3%), or middle-income zip codes (52.4%). Intentional self-harm admissions also had a higher proportion of Medicare (22.3%) and a lower proportion of Medicaid (18.0%) as their primary payer, in contrast to other types of GSW. The majority of accidental GSW in adults (62.4%) were treated and released from the ED. In contrast, intentional self-harm patients were more often admitted as an inpatient or transferred to another hospital (69.2%) unless they died in the ED (19.5%).
TABLE 1.
Nationally representative estimates of characteristics of adults with gunshot wound presenting to emergency departments in 2016–2017 (data derived from NEDS)
| Total (n = 168,315) | Accidental (n = 84,204) | Assault (n = 72,737) | Intentional (n = 8906) | Legal (n = 2468) | |
|---|---|---|---|---|---|
| Sex | |||||
| Female | 20,337 (12.1) | 10,225 (12.1) | 8243 (11.3) | 1671 (18.8) | 198 (8.0) |
| Male | 147,835 (87.8) | 73,922 (87.8) | 64,427 (88.6) | 7226 (81.1) | 2260 (91.6) |
| Age | |||||
| 18–24 | 55,863 (33.2) | 27,136 (32.2) | 26,830 (36.9) | 1344 (15.1) | 553 (22.4) |
| 25–29 | 32,448 (19.3) | 15,689 (18.6) | 15,322 (21.1) | 958 (10.8) | 479 (19.4) |
| 30–39 | 37,892 (22.5) | 17,920 (21.3) | 17,571 (24.2) | 1588 (17.8) | 813 (32.9) |
| 40–49 | 18,978 (11.3) | 9695 (11.5) | 7509 (10.3) | 1421 (16.0) | 353 (14.3) |
| 50+ | 23,132 (13.7) | 13,764 (16.3) | 5504 (7.6) | 3595 (40.4) | 269 (10.9) |
| Total charge for ED services | 8469.2 (424.7) | 8301.9 (421.7) | 8766.0 (599.0) | 7791.5 (407.4) | 8240.7 (727.7) |
| Primary payer | |||||
| Medicare | 10,534 (6.3) | 6248 (7.4) | 2197 (3.0) | 1984 (22.3) | 105 (4.3) |
| Medicaid | 52,164 (31.0) | 21,797 (25.9) | 28,026 (38.5) | 1600 (18.0) | 741 (30.0) |
| Private insurance | 37,038 (22.0) | 21,017 (25.0) | 12,967 (17.8) | 2682 (30.1) | 372 (15.1) |
| Self-pay | 53,932 (32.0) | 27,841 (33.1) | 23,321 (32.1) | 2065 (23.2) | 705 (28.6) |
| No charge/Other | 14,063 (8.4) | 6982 (8.3) | 6030 (8.3) | 531 (6.0) | 520 (21.1) |
| Teaching status of hospital | |||||
| Non-teaching | 40,229 (23.9) | 24,566 (29.2) | 12,487 (17.2) | 2606 (29.3) | 570 (23.1) |
| Teaching | 128,086 (76.1) | 59,638 (70.8) | 60,250 (82.8) | 6300 (70.7) | 1898 (76.9) |
| Hospital trauma level designation | |||||
| Level I or II | 112,549 (66.9) | 49,510 (58.8) | 55,126 (75.8) | 6183 (69.4) | 1730 (70.1) |
| Level III or non-trauma center | 55,767 (33.1) | 34,694 (41.2) | 17,611 (24.2) | 2723 (30.6) | 739 (29.9) |
| Patient location | |||||
| Central counties of metro areas | 73,595 (43.7) | 32,463 (38.6) | 38,358 (52.7) | 1907 (21.4) | 867 (35.1) |
| Fringe counties of metro areas | 24,866 (14.8) | 12,715 (15.1) | 10,236 (14.1) | 1494 (16.8) | 421 (17.0) |
| Counties in metro areas of 50,000–999,999 population | 44,453 (26.4) | 23,468 (27.9) | 17,286 (23.8) | 2950 (33.1) | 749 (30.4) |
| Micropolitan or not metropolitan counties | 23,453 (13.9) | 14,608 (17.3) | 5980 (8.2) | 2523 (28.3) | 342 (13.8) |
| Median ZIP code household income | |||||
| $1-$43,999 | 88,905 (52.8) | 42,740 (50.8) | 42,336 (58.2) | 2957 (33.2) | 872 (35.3) |
| $44,000-$73,999 | 62,487 (37.1) | 32,924 (39.1) | 23,850 (32.8) | 4664 (52.4) | 1049 (42.5) |
| $74,000+ | 12,852 (7.6) | 6583 (7.8) | 4783 (6.6) | 1125 (12.6) | 361 (14.6) |
| ED event | |||||
| treated and released | 87,970 (52.3) | 52,545 (62.4) | 33,467 (46.0) | 965 (10.8) | 993 (40.2) |
| admitted or transferred | 69,785 (41.5) | 27,176 (32.3) | 35,262 (48.5) | 6161 (69.2) | 1186 (48.0) |
| died in ED | 10,181 (6.0) | 4342 (5.2) | 3863 (5.3) | 1740 (19.5) | 236 (9.6) |
| not admitted, alive | 379 (0.2) | 141 (0.2) | 145 (0.2) | a | 54 (2.2) |
| Mortality | |||||
| Did not die | 152,976 (90.9) | 78,647 (93.4) | 67,149 (92.3) | 5093 (57.2) | 2087 (84.6) |
| Died in the ED | 10,181 (6.0) | 4342 (5.2) | 3863 (5.3) | 1740 (19.5) | 236 (9.6) |
| Died in the hospital | 4770 (2.8) | 1082 (1.3) | 1579 (2.2) | 2037 (22.9) | 72 (2.9) |
Note: Categorical variables were presented in n (%), and continuous variables were presented in mean (SD). Column percentages may not sum to 100% due to missingness.
Weighted numbers <50 were suppressed per HCUP guidelines.
3.2 |. Inpatient hospitalizations
After weighting, the study population contained 58,815 adults in the NIS database who had an initial encounter for GSW and were hospitalized. Weighted characteristics of these patients are presented in Table 2. The majority were male (88.5%) and age 18–24 years (31.8%). The largest proportion of adults with a GSW were from central counties of metropolitan (42.1%), and low-income zip code areas (52.0%). Medicaid (41.9%) was the most common primary payer. Most hospitalizations were in private, nonprofit (66.3%), large bed size (68.6%), teaching (89.2%) hospitals. Half of the patients had major or extreme severity of illness (50.0%), and 8.2% of patients died in hospital. Blacks (48.7%) accounted for the highest proportion of GSW injuries; Blacks also accounted for the highest proportions among assault (58.0%) and accidental (47.7%) GSW injury types. Whites accounted for the highest proportion of intentional self-harm (72.4%) and legal intervention (45.9%). Legal intervention injuries had the smallest proportion of females (7.2%), while intentional self-harm injury types had the largest proportion of females (20.6%). Compared to other types of GSW, hospitalizations with intentional self-harm were more likely to be >50 years old (41.1%), live in micropolitan or non-metropolitan counties (23.2%), and be insured by Medicare (23.4%). Among the GSW hospitalizations of patients who died, the most common injury type was intentional (41.8%), followed by assault (30.2%), and accidental injuries (26.3%).
TABLE 2.
Nationally representative estimates of characteristics of adults with gunshot wound hospitalized in 2016–2017 (data derived from NIS)
| Total (n = 58,815) | Accidental (n = 21,910) | Assault (n = 30,180) | Intentional (n = 5680) | Legal (n = 1045) | |
|---|---|---|---|---|---|
| Sex | |||||
| Female | 6720 (11.4) | 2370 (10.8) | 3105 (10.3) | 1170 (20.6) | 75 (7.2) |
| Male | 52,065 (88.5) | 19,520(89.1) | 27,070 (89.7) | 4505 (79.3) | 970 (92.8) |
| Age | |||||
| 18–24 | 18,695 (31.8) | 6865 (31.3) | 10,695 (35.4) | 945 (16.6) | 190 (18.2) |
| 25–29 | 11,635 (19.8) | 4265 (19.5) | 6490 (21.5) | 660(11.6) | 220 (21.1) |
| 30–39 | 13,520 (23.0) | 5125 (23.4) | 7160 (23.7) | 920 (16.2) | 315 (30.1) |
| 40–49 | 6765 (11.5) | 2505 (11.4) | 3290 (10.9) | 820 (14.4) | 150 (14.4) |
| 50+ | 8200 (13.9) | 3150 (14.4) | 2545 (8.4) | 2335 (41.1) | 170 (16.3) |
| Race | |||||
| White | 16,305 (27.7) | 6885 (31.4) | 4830 (16.0) | 4110 (72.4) | 480 (45.9) |
| Black | 28,620 (48.7) | 10,460 (47.7) | 17,495 (58.0) | 435 (7.7) | 230 (22.0) |
| Hispanic | 7970 (13.6) | 2580 (11.8) | 4790 (15.9) | 405 (7.1) | 195 (18.7) |
| Other | 2880 (4.9) | 920 (4.2) | 1650 (5.5) | 235 (4.1) | 75 (7.2) |
| APRDRG severity | |||||
| Minor or moderate severity of illness | 29,360 (49.9) | 12,635 (57.7) | 14,840 (49.2) | 1465 (25.8) | 420 (40.2) |
| Major or extreme severity of illness | 29,425 (50.0) | 9275 (42.3) | 15,325 (50.8) | 4200 (73.9) | 625 (59.8) |
| In hospital mortality | |||||
| Lived | 53,895 (91.6) | 20,605 (94.0) | 28,680 (95.0) | 3660 (64.4) | 950 (90.9) |
| Died | 4835 (8.2) | 1270 (5.8) | 1460 (4.8) | 2020 (35.6) | 85 (8.1) |
| Total charges ($) | 128507.8 (3048.0) | 112658.2 (3472.4) | 137503.2 (4300.5) | 132275.6 (6434.8) | 181651.9 (16205.2) |
| Primary payer | |||||
| Medicare | 4085 (6.9) | 1655 (7.6) | 1005 (3.3) | 1330 (23.4) | 95 (9.1) |
| Medicaid | 24,645 (41.9) | 8035 (36.7) | 14,860 (49.2) | 1295 (22.8) | 455 (43.5) |
| Private insurance | 11,905 (20.2) | 4845 (22.1) | 5235 (17.3) | 1725 (30.4) | 100 (9.6) |
| Self-pay | 12,515 (21.3) | 5280 (24.1) | 6115 (20.3) | 930 (16.4) | 190 (18.2) |
| No charge/Other | 5415 (9.2) | 2040 (9.3) | 2800 (9.3) | 380 (6.7) | 195 (18.7) |
| Hospital control | |||||
| Government, nonfederal | 13,945 (23.7) | 4765 (21.7) | 7560 (25.0) | 1290 (22.7) | 330 (31.6) |
| Private, nonprofit | 39,020 (66.3) | 14,050 (64.1) | 20,535 (68.0) | 3800 (66.9) | 635 (60.8) |
| Private, investor-owned | 5850 (9.9) | 3095 (14.1) | 2085 (6.9) | 590 (10.4) | 80 (7.7) |
| Bed size of hospital | |||||
| Small or medium | 18,440 (31.4) | 6640 (30.3) | 9820 (32.5) | 1650 (29.0) | 330 (31.6) |
| Large | 40,375 (68.6) | 15,270 (69.7) | 20,360 (67.5) | 4030 (71.0) | 715 (68.4) |
| Teaching status of hospital | |||||
| Nonteaching | 6350 (10.8) | 2860 (13.1) | 2605 (8.6) | 805 (14.2) | 80 (7.7) |
| Teaching | 52,465 (89.2) | 19,050 (86.9) | 27,575 (91.4) | 4875 (85.8) | 965 (92.3) |
| Patient location | |||||
| Central counties of metro areas | 24,780 (42.1) | 8000 (36.5) | 15,245 (50.5) | 1135 (20.0) | 400 (38.3) |
| Fringe counties of metro areas | 9575 (16.3) | 3840 (17.5) | 4585 (15.2) | 995 (17.5) | 155 (14.8) |
| Counties in metro areas of 50,000–999,999 population | 17,050 (29.0) | 6795 (31.0) | 7755 (25.7) | 2165 (38.1) | 335 (32.1) |
| Micropolitan or not metropolitan counties | 6690 (11.4) | 3060 (14.0) | 2180 (7.2) | 1315 (23.2) | 135 (12.9) |
| Median ZIP code household income | |||||
| $1-$43,999 | 30,590 (52.0) | 11,125 (50.8) | 17,110 (56.7) | 1980 (34.9) | 375 (35.9) |
| $44,000-$73,999 | 21,965 (37.3) | 8615 (39.3) | 10,205 (33.8) | 2685 (47.3) | 460 (44.0) |
| $74,000+ | 4830 (8.2) | 1730 (7.9) | 2140 (7.1) | 810 (14.3) | 150 (14.4) |
| Division | |||||
| Mountain | 3500 (6.0) | 1260 (5.8) | 1550 (5.1) | 555 (9.8) | 135 (12.9) |
| New England | 1260 (2.1) | 470 (2.1) | 585 (1.9) | 175(3.1) | a |
| Middle Atlantic | 5575 (9.5) | 1640 (7.5) | 3490(11.6) | 325 (5.7) | 120 (11.5) |
| East North Central | 7855 (13.4) | 2505 (11.4) | 4645 (15.4) | 640 (11.3) | 65 (6.2) |
| West North Central | 4185(7.1) | 1535 (7.0) | 2195 (7.3) | 405 (7.1) | 50 (4.8) |
| South Atlantic | 14,260 (24.2) | 6245 (28.5) | 6485 (21.5) | 1400 (24.6) | 130 (12.4) |
| East South Central | 6000 (10.2) | 2560 (11.7) | 2500 (8.3) | 835 (14.7) | 105 (10.0) |
| West South Central | 7815 (13.3) | 3160 (14.4) | 3725 (12.3) | 785 (13.8) | 145 (13.9) |
| Pacific | 8365 (14.2) | 2535 (11.6) | 5005 (16.6) | 560 (9.9) | 265 (25.4) |
Note: Categorical variables were presented in n (%), and continuous variables were presented in mean (SD). Column percentages may not sum to 100% due to missingness.
Weighted numbers <50 were suppressed per HCUP guidelines.
Figure 1 presents the number of GSW adult hospitalizations per 100,000 population in each census division across the US. The New England census division had the lowest adjusted number of GSW inpatients (4.26 per 100,000), while the East South Central census division had the highest (15.77 per 100,000).
FIGURE 1.
Geographic distribution of gunshot would inpatients per 100,000 population in the US (data derived from NIS). A darker color and a larger circle represent a higher number of GSWs per 100,000 population. Source of division population: Annual estimates of the population for the United States, regions, states, and Puerto Rico: April 1, 2010 to July 1, 2018 (NST-EST2018–01). U.S. Census Bureau, population division. Release date: December 2018 [Color figure can be viewed at wileyonlinelibrary.com]
For 2016–2017, the gross aggregate annual bill for hospital charges for GSW-related 58,815 hospitalizations adults with a mean (SD) length of hospital stay of 7.57 (0.13) days was $3,779,099,010 (approximately 3.8 billion US dollars). The Mean (SD) of charges per hospitalization for GSW was USD $128,508 (3048) and significantly higher than the mean overall charges per hospitalization in NIS of USD $48,415 (414), p < .001.
Among the 58,815 GSW-related hospitalizations in NIS, 12.7% received at least one transfusion (Figure 2A). Overall, RBCs (12.0%) were the most common blood component transfused, followed by plasma (4.9%) and platelets (2.5%). Assessing the combination of blood products used, the largest utilization was RBC alone (7.3%), followed by RBCs and plasma (2.5%), and RBC and platelets (0.3%). There were 1.9% of hospitalizations that had all three components (RBC, plasma, and platelets) transfused. By contrast, on a subgroup analysis of patients with GSW who died (n = 4835) during hospitalization, 26.8% (1295/4835) were transfused and 7.3% received all three blood components (i.e. RBC, platelets, and plasma). (Figure 2B). Admissions with any reported blood transfusions had significantly longer mean length of hospital stay than those without transfusions (11 days versus 8 days, p < .001).
FIGURE 2.
GSW inpatient hospitalizations with relative utilization of red blood cell, plasma, and platelet transfusion (A). Relative utilization of red blood cell, plasma, and platelet transfusion in hospitalizations with gunshot wound who died during hospitalization (B). Data derived from the NIS in 2016 and 2017. *Weighted numbers <50 were suppressed per HCUP guidelines [Color figure can be viewed at wileyonlinelibrary.com]
Analyzing the timing of transfusions among all GSW hospitalizations, 75.2% of the transfused patients were transfused within the first 24 h after admission and 82.2% were transfused within the first 48 h of admission. In comparison, 90.1% of the patients who died received blood transfusions within the first 24 h after admission and 95.3% within 48 h after admission. The median (IQR) for length of stay in GSW subjects who died was 1 (0–2) days as compared to median (IQR) 4 (2–9) days in GSW hospitalizations who did not die. The prevalence of death among hospitalizations with early transfusion (within 48 h) was almost three times higher than hospitalizations with late transfusion (prevalence ratio: 2.99 [95%CI = 1.82–4.91] p < .001).
Based on the results of the multivariable model (Model 1, Table 3), race, gunshot type, hospital control type, bed size of hospital, and census division were independently related to any transfusion. A higher prevalence of any transfusion was associated with race (Blacks compared to Whites; adjPR = 1.31; 95%CI = 1.12–1.53). GSW caused by intentional self-harm had the highest prevalence of any transfusion (intentional self-harm compared to accidental; adjPR = 1.54; 95%CI = 1.28–1.86). Comparing to government nonfederal hospitals, private investor-owned hospitals had lower transfusion prevalence (adjPR = 0.68; 95%CI = 0.50–0.94). Hospitals with large bed size were associated with lower prevalence of any transfusion than hospitals with small or medium bed size (adjPR = 0.76; 95% CI = 0.64–0.91). Comparing to the Mountain division, which had the lowest prevalence of any transfusion, New England (adjPR = 1.83; 95%CI = 1.09–3.07), South Atlantic (adjPR = 1.96; 95%CI = 1.28–3.01), West South Central (adjPR = 1.86; 95%CI = 1.14–3.02) and Pacific (adjPR = 2.14; 95%CI = 1.39–3.30) were associated with a significantly higher prevalence of transfusion. After additionally including APR-DRG severity and in-hospital mortality in the multivariable regression (Model 2, Table 3) that are often co-linear with transfusion, results were similar except the type of GSW was not independently associated with any transfusion.
TABLE 3.
Factors associated with any transfusion among adults with gunshot wound during inpatient hospitalizations, NIS 2016–2017
| Any transfusion (n = 7485) | No transfusion (n = 51,330) | Crude model (PR (95% CI)) | Model 1 (adjPR (95% CI)) | Model 2 (adjPR (95% CI)) | |
|---|---|---|---|---|---|
| Sex | |||||
| Female | 845 (12.6) | 5875 (87.4) | Ref. | Ref. | Ref. |
| Male | 6640 (12.8) | 45,425 (87.2) | 1.01 (0.88–1.17) | 1.03 (0.88–1.20) | 0.96 (0.82–1.11) |
| Age group | |||||
| 18–24 | 2275 (12.2) | 16,420 (87.8) | Ref. | Ref. | Ref. |
| 25–29 | 1515 (13.0) | 10,120 (87.0) | 1.07 (0.94–1.22) | 1.06 (0.92–1.22) | 1.01 (0.89–1.16) |
| 30–39 | 1770 (13.1) | 11,750 (86.9) | 1.08 (0.94–1.23) | 1.10 (0.96–1.27) | 1.03 (0.90–1.18) |
| 40–49 | 895 (13.2) | 5870 (86.8) | 1.09 (0.93–1.27) | 1.15(0.98–1.36) | 1.06 (0.90–1.25) |
| 50+ | 1030 (12.6) | 7170 (87.4) | 1.03 (0.87–1.23) | 1.04 (0.84–1.27) | 0.98 (0.80–1.20) |
| Race/ethnicity | |||||
| White | 1745 (10.7) | 14,560 (89.3) | Ref. | Ref. | Ref. |
| Black | 3950 (13.8) | 24,670 (86.2) | 1.29 (1.12–1.49) | 1.31 (1.12–1.53) | 1.29 (1.11–1.49) |
| Hispanic | 950 (11.9) | 7020 (88.1) | 1.11 (0.91–1.36) | 1.00 (0.81–1.23) | 0.97 (0.80–1.18) |
| Other | 410 (14.2) | 2470 (85.8) | 1.33 (1.03–1.72) | 1.24 (0.95–1.62) | 1.13 (0.88–1.46) |
| Gunshot type | |||||
| Accidental | 2335 (10.7) | 19,575 (89.3) | Ref. | Ref. | Ref. |
| Assault | 4170 (13.8) | 26,010 (86.2) | 1.30 (1.13–1.49) | 1.22 (1.06–1.41) | 1.12 (0.98–1.28) |
| Intentional | 825 (14.5) | 4855 (85.5) | 1.36 (1.15–1.61) | 1.54 (1.28–1.86) | 0.92 (0.76–1.12) |
| Legal | 155 (14.8) | 890 (85.2) | 1.39 (1.00–1.94) | 1.53 (1.08–2.15) | 1.24 (0.90–1.73) |
| APR-DRG risk severity subclass | |||||
| Minor or moderate severity of illness | 1290 (4.4) | 28,070 (95.6) | Ref. | - | Ref. |
| Major or extreme severity of illness | 6190 (21.0) | 23,235 (79.0) | 4.79 (4.15–5.53) | - | 4.53 (3.88–5.29) |
| In-hospital mortality | |||||
| No | 6165 (11.4) | 47,730 (88.6) | Ref. | - | Ref. |
| Yes | 1295 (26.8) | 3540 (73.2) | 2.34 (2.10–2.61) | - | 1.59 (1.40–1.81) |
| Primary payer | |||||
| Medicaid | 560 (13.7) | 3525 (86.3) | Ref. | Ref. | Ref. |
| Medicare | 3470 (14.1) | 21,175 (85.9) | 1.03 (0.84–1.26) | 0.96 (0.76–1.22) | 0.98 (0.78–1.23) |
| Private | 1375 (11.5) | 10,530 (88.5) | 0.84 (0.68–1.05) | 0.83 (0.65–1.05) | 0.90 (0.72–1.13) |
| Self | 1475 (11.8) | 11,040(88.2) | 0.86 (0.70–1.06) | 0.81 (0.64–1.03) | 0.92 (0.73–1.16) |
| No charge/Other | 595 (11.0) | 4820 (89.0) | 0.80 (0.62–1.04) | 0.73 (0.54–0.98) | 0.81 (0.62–1.07) |
| Hospital control | |||||
| Government, nonfederal | 1990 (14.3) | 11,955 (85.7) | Ref. | Ref. | Ref. |
| Private, nonprofit | 4910 (12.6) | 34,110 (87.4) | 0.88 (0.72–1.08) | 0.87 (0.71–1.07) | 0.86 (0.70–1.05) |
| Private, investor-owned | 585 (10.0) | 5265 (90.0) | 0.70 (0.51–0.96) | 0.68 (0.50–0.94) | 0.70 (0.51–0.96) |
| Bed size of hospital | |||||
| Small or Medium | 2725 (14.8) | 15,715 (85.2) | Ref. | Ref. | Ref. |
| Large | 4760 (11.8) | 35,615 (88.2) | 0.80 (0.67–0.95) | 0.76 (0.64–0.91) | 0.71 (0.59–0.84) |
| Teaching status of hospital | |||||
| Nonteaching | 725 (11.4) | 5625 (88.6) | Ref. | Ref. | Ref. |
| Teaching | 6760 (12.9) | 45,705 (87.1) | 1.13 (0.86–1.48) | 0.95 (0.72–1.25) | 0.84(0.64–1.11) |
| Patient location | |||||
| Central counties of metro areas | 3245 (13.1) | 21,535 (86.9) | Ref. | Ref. | Ref. |
| Fringe counties of metro areas | 1320 (13.8) | 8255 (86.2) | 1.05 (0.89–1.24) | 1.11 (0.93–1.32) | 1.11 (0.94–1.31) |
| Counties in metro areas of 50,000–999,999 population | 2055 (12.1) | 14,995 (87.9) | 0.92 (0.76–1.11) | 0.93 (0.77–1.13) | 0.92 (0.77–1.10) |
| Micropolitan or not metropolitan counties | 730 (10.9) | 5960 (89.1) | 0.83 (0.67–1.04) | 0.93 (0.73–1.18) | 0.95 (0.75–1.21) |
| Median ZIP code household income | |||||
| $1-$43,999 | 3900 (12.7) | 26,690 (87.3) | Ref. | Ref. | Ref. |
| $44,000-$73,999 | 2665 (12.1) | 19,300 (87.9) | 0.95 (0.85–1.06) | 0.96 (0.86–1.07) | 0.96 (0.86–1.07) |
| $74,000+ | 710 (14.7) | 4120 (85.3) | 1.15 (0.95–1.39) | 1.09 (0.88–1.34) | 1.05 (0.87–1.29) |
| Division | |||||
| Mountain | 220 (6.3) | 3280 (93.7) | Ref. | Ref. | Ref. |
| New England | 160 (12.7) | 1100 (87.3) | 2.02 (1.21–3.38) | 1.83 (1.09–3.07) | 1.85 (1.13–3.02) |
| Middle Atlantic | 670 (12.0) | 4905 (88.0) | 1.91 (1.20–3.04) | 1.45 (0.90–2.32) | 1.55 (0.98–2.46) |
| East North Central | 890 (11.3) | 6965 (88.7) | 1.80 (1.09–2.99) | 1.41 (0.84–2.37) | 1.42 (0.86–2.34) |
| West North Central | 340 (8.1) | 3845 (91.9) | 1.29 (0.70–2.38) | 1.04 (0.56–1.92) | 1.01 (0.56–1.84) |
| South Atlantic | 2030 (14.2) | 12,230 (85.8) | 2.26 (1.51–3.40) | 1.96 (1.28–3.01) | 1.95 (1.29–2.93) |
| East South Central | 690 (11.5) | 5310 (88.5) | 1.83 (1.14–2.95) | 1.52 (0.93–2.51) | 1.45 (0.90–2.36) |
| West South Central | 1070 (13.7) | 6745 (86.3) | 2.18 (1.35–3.51) | 1.86 (1.14–3.02) | 1.84 (1.14–2.95) |
| Pacific | 1415 (16.9) | 6950 (83.1) | 2.69 (1.76–4.11) | 2.14 (1.39–3.30) | 2.22 (1.47–3.35) |
Note: Model 1 included sex, age group, race/ethnicity, gunshot type, primary payer, hospital control, hospital bed size, teaching status of hospital, patient location, and census division. Model 2 additionally included APR-DRG risk severity subclass and in-hospital mortality. Bold text indicates a statistically significant PR with p < .05.
Abbreviations: adjPR, adjusted prevalence ratio; PR, prevalence ratio.
Table S1 shows the population characteristics of gunshot hospitalizations in the NIS, years 2016–2017, by observation included and excluded due to missingness in the full multivariable model.
4 |. DISCUSSION
This is one of the first nationwide study presenting the in-hospital blood transfusion utilization among adults with GSW in the United States. Among hospitalizations due to GSW injuries, blood transfusions were common, especially among those who died. However, massive transfusion with all three blood components was limited.
GSW violence is a major public health emergency in the US with the morbidity, mortality and health costs related to firearm injury continuing to escalate at an unrelenting pace.6,16,17 Despite the high numbers of victims (many of whom are young) and large health care and social burdens resulting from the aftermath of gun violence, the US has made limited progress in combating fire-arm-related violence or injuries in the last 50 years. Firearm violence/injury remains understudied and under-addressed, prompting calls to action from professional health organizations, medical communities, and health care personnel.18–22
While mass shootings comprise <1% of all firearm deaths, homicides and suicides comprise the major reason for firearm-related deaths.23 Importantly, firearms are the means in approximately half of suicides nationwide,24 again magnifying the impact of gun violence on vulnerable populations predisposed to suicide. This is not to minimize the impact of mass shootings, but rather to convey that mass shootings account for a very small part of overall burden posed by gun violence.
Bleeding is identified as the leading cause of preventable death in combat or civilian traumatic injury.25–27 Penetrating or perforating injury from GSW can lead to rapid exsanguination and hemorrhagic shock. Timely administration of blood products is important for resuscitation of patients in shock, where it may prevent the coagulopathy of trauma, which can become rapidly irreversible.11 The ratio of blood products transfused—specifically access to plasma prior to the development of significant coagulopathy—has been shown to affect mortality outcomes in adult patients receiving massive transfusions for combat injuries.28,29 In this study, both RBC and plasma transfusions occurred in ∼2.5% of GSW cases and all three components (i.e., RBCs, platelets, and plasma) were rarely transfused (∼2%) in GSW-related admissions. While it is speculative, these RBC plus plasma transfusion or RBC, platelet, and plasma combined transfusion statistics in the era of the massive transfusion protocol would suggest that between 4% and 5% of GSW hospitalizations are massively transfused. These numbers are aligned with expectations, as an estimated 3% to 5% of civilian trauma patients and up to 10% of military trauma patients undergo massive transfusion.30 While the incidence of massive transfusion is relatively low, GSW patients who undergo massive transfusion have a high mortality rate.15 The highest proportion of blood transfusion was in the intentional self-harm injuries and lowest proportion was in accidental trauma.
Among GSW hospitalizations requiring transfusion, the higher transfusion prevalence was noted in Black patients as compared to White patients. Higher transfusion prevalence was found among assault and intentional injuries versus accidental injuries, as well as for cases with highest overall severity of injury. Transfusions were associated with higher prevalence of mortality, likely indicating that transfusions are used disproportionally in the most severely injured patients, although this deserves further study. It is also noteworthy that after adjustment for severity of illness and GSW injury type, there was lower overall prevalence of transfusions in teaching hospitals as well as large hospitals as compared to small-/medium-sized hospitals which might indicate that transfusion practice employed to treat GSWs is variable among hospitals, which also should be studied further. In contrast, there was no difference in transfusion practice by sex, age, or insurance status. While there was difference in GSW injury by median household income and patient geographic location, these factors were not associated with differences in transfusion practice.
According to this analysis, the average annual billed charges for GSW cases is ∼$3,800,000,000. This number is similar to those from earlier projections.31,32 However, only GSW-related injuries coded as initial encounter were used for this analysis, whereas all subsequent visits or and encounters related to sequela from visits were excluded. Thus, these expenses still represent only a fraction of the total expenses and the true financial burden for the healthcare system and society in general from firearm injuries is higher.
While this is the largest epidemiologic analysis on the transfusion use in GSW hospitalizations, there are limitations. First, the study captures only GSW-related cases which arrive alive to the ED or were admitted. Any deaths that occur before arrival to the ED would not be captured in the NEDS or NIS databases. While this study provides information on whether or not blood components were utilized during a GSW admission, further details (e.g. number of units or total volumes of blood transfused) were not available. While this study assessed predictors of transfusion in GSW admissions, transfusion ratios or transfusion deficits or associated outcomes could not be calculated. There is renewed interest in low-titer type O whole blood (LTOWB) as a universal resuscitation product for hemorrhagic shock. This study did not analyze data on whole blood utilization for GSW. Lastly, this study was not able to capture the long-term impact of gun violence on survivors and communities. Costs (economic and beyond) were significant and deserve further study.
In conclusion, among hospitalizations due to GSW injuries, blood transfusions were required in 1 in 8 (∼12.5%) hospitalizations due to firearm injury and 1 in 4 (∼25%) of all admissions resulting in death. The majority of individuals requiring transfusion support received RBCs, while few received other blood components. A higher prevalence of transfusions was associated with Blacks compared to Whites; and in GSW injuries caused by intentional self-harm than other injury types. Gun-related violence is a public health emergency in the US, and GSWs are a source of significant mortality, blood utilization, and health care costs.
Supplementary Material
ACKNOWLEDGEMENTS
This study was supported in part by grants from the National Institutes of Health (R01AI120938 and R01AI128779 to A.A.R.T; K23HL151826 to EMB).
Funding information
Division of Intramural Research, National Institute of Allergy and Infectious Diseases, Grant/Award Numbers: R01AI120938, R01AI28779; National Heart, Lung, and Blood Institute, Grant/Award Number: K23HL151826
Abbreviations:
- adjPR
adjusted prevalence ratio
- AHRQ
Agency for Healthcare Research and Quality
- GSW
gunshot wound
- HCUP
Healthcare Cost and Utilization Project
- ICD-10-CM
International Classification of Diseases, Tenth Revisions, Clinical Modification, 10th edition
- NEDS
Nationwide Emergency Department Sample
- NIS
National Inpatient Sample
- RBC
red blood cell
- US
United States
APPENDIX
APPENDIX A
Intentional
Intentional self-harm by handgun discharge: X72.XXXA
Intentional self-harm by shotgun discharge: X73.0XXA
Intentional self-harm by hunting rifle discharge: X73.1XXA
Intentional self-harm by machine gun discharge: X73.2XXA
Intentional self-harm by other larger firearm discharge: X73.8XXA
Intentional self-harm by unspecified larger firearm discharge: X73.9XXA
Intentional self-harm by other firearm discharge: X74.8XXA
Intentional self-harm by unspecified firearm discharge: X74.9XXA
Accidental
Accidental handgun discharge: W32.0XXA
Accidental handgun malfunction: W32.1XXA
Accidental discharge of unspecified larger firearm: W33.00XA
Accidental discharge of shotgun: W33.01XA
Accidental discharge of hunting rifle: W33.02XA
Accidental discharge of machine gun: W33.03XA
Accidental discharge of other larger firearm: W33.09XA
Accidental malfunction of unspecified larger firearm: W33.10XA
Accidental malfunction of shotgun: W33.11XA
Accidental malfunction of hunting rifle: W33.12XA
Accidental malfunction of machine gun: W33.13XA
Accidental malfunction of other larger firearm: W33.19XA
Accidental discharge from unspecified firearms or gun: W34.00XA
Accidental discharge from other specified firearms: W34.09XA
Accidental malfunction from unspecified firearms or gun: W34.10XA
Accidental malfunction from other specified firearms: W34.19XA
Assault
Assault by handgun discharge: X93.XXXA
Assault by shotgun: X94.0XXA
Assault by hunting rifle: X94.1XXA
Assault by machine gun: X94.2XXA
Assault by other larger firearm discharge: X94.8XXA
Assault by other firearm discharge: X95.8XXA
Assault by unspecified firearm discharge: X95.9XXA
Terrorism involving firearms, public safety official injured: Y38.4X1A
Terrorism involving firearms, civilian injured: Y38.4X2A
Terrorism involving firearms, terrorist injured: Y38.4X3A
Legal intervention
Legal intervention involving unspecified firearm discharge, law enforcement official injured: Y35.001A
Legal intervention involving unspecified firearm discharge, bystander injured: Y35.002A
Legal intervention involving unspecified firearm discharge, suspect injured: Y35.003A
Legal intervention involving unspecified firearm discharge, unspecified person injured: Y35.009A
Legal intervention involving injury by machine gun, law enforcement official injured: Y35.011A
Legal intervention involving injury by machine gun, bystander injured: Y35.012A
Legal intervention involving injury by machine gun, suspect injured: Y35.013A
Legal intervention involving injury by machine gun, unspecified person injured: Y35.019A
Legal intervention involving injury by handgun, law enforcement official injured: Y35.021A
Legal intervention involving injury by handgun, bystander injured: Y35.022A
Legal intervention involving injury by handgun, suspect injured: Y35.023A
Legal intervention involving injury by handgun, unspecified person injured: Y35.029A
Legal intervention involving other firearm discharge, law enforcement official injured: Y35.091A
Legal intervention involving other firearm discharge, bystander injured: Y35.092A
Legal intervention involving other firearm discharge, suspect injured: Y35.093A
Legal intervention involving other firearm discharge, unspecified person injured: Y35.099A
APPENDIX B
Red blood cell transfusion
Transfusion of Nonautologous Red Blood Cells into Peripheral Vein, Percutaneous Approach: 30233N1
Transfusion of Nonautologous Frozen Red Cells into Peripheral Vein, Percutaneous Approach: 30233P1
Transfusion of Nonautologous Red Blood Cells into Central Vein, Percutaneous Approach: 30243N1
Transfusion of Nonautologous Frozen Red Cells into Central Vein, Percutaneous Approach: 30243P1
Transfusion of Nonautologous Red Blood Cells into Peripheral Artery, Percutaneous Approach: 30253N1
Transfusion of Nonautologous Frozen Red Cells into Peripheral Artery, Percutaneous Approach: 30253P1
Transfusion of Nonautologous Red Blood Cells into Central Artery, Percutaneous Approach: 30263N1
Transfusion of Nonautologous Frozen Red Cells into Central Artery, Percutaneous Approach: 30263P1
Transfusion of Nonautologous Red Blood Cells into Peripheral Vein, Open Approach: 30230N1
Transfusion of Nonautologous Frozen Red Cells into Peripheral Vein, Open Approach: 30230P1
Transfusion of Nonautologous Red Blood Cells into Central Vein, Open Approach: 30240N1
Transfusion of Nonautologous Frozen Red Cells into Central Vein, Open Approach: 30240P1
Plasma transfusion
Transfusion of Nonautologous Frozen Plasma into Peripheral Vein, Percutaneous Approach: 30233K1
Transfusion of Nonautologous Fresh Plasma into Peripheral Vein, Percutaneous Approach: 30233L1
Transfusion of Nonautologous Frozen Plasma into Central Vein, Percutaneous Approach: 30243K1
Transfusion of Nonautologous Fresh Plasma into Central Vein, Percutaneous Approach: 30243L1
Transfusion of Nonautologous Frozen Plasma into Peripheral Vein, Open Approach: 30230K1
Transfusion of Nonautologous Fresh Plasma into Peripheral Vein, Open Approach: 30230L1
Transfusion of Nonautologous Frozen Plasma into Central Vein, Open Approach: 30240K1
Transfusion of Nonautologous Fresh Plasma into Central Vein, Open Approach: 30240L1
Transfusion of Nonautologous Frozen Plasma into Peripheral Artery, Percutaneous Approach: 30253K1
Transfusion of Nonautologous Fresh Plasma into Peripheral Artery, Percutaneous Approach: 30253L1
Transfusion of Nonautologous Frozen Plasma into Central Artery, Percutaneous Approach: 30263K1
Transfusion of Nonautologous Fresh Plasma into Central Artery, Percutaneous Approach: 30263L1
Platelet transfusion
Transfusion of Nonautologous Platelets into Peripheral Vein, Percutaneous Approach: 30233R1
Transfusion of Nonautologous Platelets into Central Vein, Percutaneous Approach: 30243R1
Transfusion of Nonautologous Platelets into Peripheral Artery, Percutaneous Approach: 30253R1
Transfusion of Nonautologous Platelets into Central Artery, Percutaneous Approach: 30263R1
Transfusion of Nonautologous Platelets into Peripheral Vein, Open Approach: 30230R1
Transfusion of Nonautologous Platelets into Central Vein, Open Approach: 30240R1
Footnotes
SUPPORTING INFORMATION
Additional supporting information may be found online in the Supporting Information section at the end of this article.
CONFLICT OF INTEREST
The authors have disclosed no conflicts of interest.
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