JULY 2018 Volume 25 Number 7 PAGE 2 Incidence of acute injuries, active component, U.S. Armed Forces, 2008 Shauna Stahlman, PhD, MPH; Stephen B. Taubman, PhD PAGE 10 Major deployment-related amputations of lower and upper limbs, active and reserve components, U.S. Armed Forces, 2001 Shawn Farrokhi, PT, PhD; Katheryne Perez, MPH, CPH; Susan Eskridge, PT, PhD; Mary Clouser, PhD PAGE 17 Update: Medical evacuations, active and reserve components, U.S. Armed Forces, 2017 PAGE 23 Food-allergy anaphylaxis and epinephrine autoinjector prescription fills, active component service members, U.S. Armed Forces, 2007 Shawn S. Clausen, MD, MPH; Shauna L. Stahlman, PhD, MPH PAGE 30 Surveillance snapshot: Cardiovascular-related deaths during deploy ment, U.S. Armed Forces, October 2001 December 2012 Leslie L. Clark, PhD, MS CE/CME
Page 2 Injuries have consistently ranked among the top morbidity burdens among U.S. military service members. is report describes the incidence, trends, types, causes, and dispositions of acute injuries among active component service members by anatomic region. From 2008 through 2017, there were more than 3.6 million acute incident injuries among more than 1.6 million individuals. e highest rates were for injuries to the foot/ankle, head/neck, and hand/wrist. Injury incidence decreased during the surveillance period for all anatomic sites except for the leg and knee. In addition, incidence var ied by military/demographic characteristics and anatomic site. Overall, ser vice members in the Army and service members in motor transport and/or combat-related occupations tended to have higher incidence rates than their respective counterparts. Sprains and strains was the most common type of injury (48.5%), and most injuries were due to undocumented or undetermined causes (69.7%). e most common disposition was returned to duty with no limitations (69.8%). Findings suggest that injury prevention strategies should be tailored to dierent populations with dierent risk factors. Future analyses will describe the epidemiology of cumulative traumatic injuries. Incidence of Acute Injuries, Active Component, U.S. Armed Forces, 2008 Shauna Stahlman, PhD, MPH; Stephen B. Taubman, PhD ervice members in the U.S. Armed Forces frequently engage in high lev els of physical activity to perform their duties, and such activity can potentially result in trainingor duty-related injuries. Injuries have consistently ranked among the highest burden of disease categories for numbers of associated medical encoun ters and of individuals aected in the U.S. Armed Forces. In 2017, injuries accounted for more medical encounters (n=2,775,393) among active component service members than any other morbidity category and approximately one-quarter of all medical encounters. 1 Knee injuries ranked third in total number of medical encounters, with arm/shoulder and foot/ankle and leg inju ries ranking fourth and sixth, respectively. 1 According to the U.S. Army Public Health Centers 2016 Health of the Force Report, approximately half of all soldiers sustained at least one injury in 2015, with 1,361 new injuries per 1,000 person-years (p-yrs). 2 e incidence rate of injuries was about 34% higher among female sol diers (1,735 per 1,000 p-yrs) than among male soldiers (1,299 per 1,000 p-yrs), and was highest among those in the oldest age category ( yrs). 2 Other risk factors for increased injuries identied in studies of U.S. Army service members or recruits include high amounts of running (fre quency and mileage), tobacco use, lack of previous experience with sports and exer cise, and having a sedentary lifestyle. 3,4 Some of the most common causes of nonbattle-related injuries identied in mili tary populations include military training, sports, falls, and motor vehicle accidents. 5,6 Injuries are of major signicance to the U.S. military because of their potential impact on lost duty or training time, costs, and military readiness. However, much of the Department of Defenses (DoD) research and eld investigations of injuries has focused on specic populations such as recruit trainees, Army infantry soldiers, and special operations forces. 7 As such, this report is intended to expand the routine surveillance of injuries among all active component service members, with the goal of identifying high-risk populations and providing data to support the prioritiza tion of research and prevention programs. e focus of this report is on acute injuries associated with a single traumatic event, as opposed to overuse injuries that are the result of cumulative trauma or repetitive use and stress. is report summarizes the incidence, trends, types, external causes, and dispositions of acute injuries among active component U.S. service members over a 10-year surveillance period. METHODS e surveillance period was 1 January 2008 through 31 December 2017. e sur veillance population included all individu als who served in the active component of the Army, Navy, Air Force, or Marine Corps at any time during the surveillance period. All data used to determine incident acute injury diagnoses were derived from records routinely maintained in the Defense Medical Surveillance System (DMSS). ese records document both ambulatory encounters and hospitalizations of active component mem bers of the U.S. Armed Forces in xed mili tary and civilian (if reimbursed through the Military Health System [MHS]) treatment facilities. For surveillance purposes, acute injuries were dened using records of inpatient and outpatient medical encounters that included injury-specic diagnoses in the rst diagnos tic position. ICD-9 and ICD-10 codes used to dene acute injuries were extracted from
Page 3 the MSMR burden dictionary of ICD codes, and included ICD-9 codes in the 800 range, ICD-10 codes beginning with S, and ICD-10 codes in the T07T32 range. Injuries were categorized by aected ana tomic site: head/neck, arm/shoulder, hand/ wrist, back/abdomen, knee, leg, and foot/ ankle. Excluded were diagnoses of injuries that did not fall under one of these anatomic site categories (e.g., injuries to unspecied or other anatomic sites); environmental inju ries (e.g., eects of radiation, reduced tem perature, heat and light, air pressure, insect bites, or other external causes); and poison ing. To identify incident cases of injury, a 60-day gap rule was applied. To be counted as a new incident case, at least 60 days must have passed since the last medical encoun ter with a qualifying injury diagnosis in the rst diagnostic position. Incident cases were counted separately for each anatomic site category. For example, an individual could be counted for both head and neck and arm and shoulder within the same 60-day period but could not be counted twice for head and neck injury within the same 60-day period. Injuries that occurred during a period of deployment were excluded, and deploy ment-related person-time was excluded from the denominators of incidence rate calculations. In addition, all warand bat tle-related causes of injuries were excluded from the analysis. Causes of injuries were assessed based on North Atlantic Treaty Organization Standard Agreement 2050 (STANAG) and ICD-9/ICD-10 exter nal cause of injury codes. e same list of cause of injury and external cause of injury codes that was being used in the Armed Forces Health Surveillance Branch (AFHSB) Installation Injury Report at the time of writing was used in the analyses for this report. 8 For inpatient encounters, STANAG and Trauma codes were priori tized over external cause of injury codes when assigning cause of injury (if both were coded in the same encounter). For encounters that had multiple causes indi cated, prioritization was assigned to the rst-occurring diagnostic position (second diagnostic position was prioritized over third diagnostic position, etc.). e type of injury for each acute inci dent injury was also described, using a modied version of the Centers for Disease Control and Prevention/National Cen ter for Health Statistics Barell Matrix and Injury Mortality Diagnosis Matrix. 9 e codes used to dene these type of injury categories are shown in Table 1 Finally, this report presents the dis position of each acute injury (returned to duty with no limitations, returned to duty with limitations, or not returned to duty). Incident acute injuries that were diagnosed in outsourced care settings were excluded from the disposition analysis because dis position data were not available for out sourced care encounters. If there was no indication of disposition in the medical encounter (roughly 7% of outpatient cases and 11% of inpatient cases), then the ser vice member was assumed to be returned to duty with no limitations. is was done to be consistent with the way that disposi tions are assigned and categorized in the AFHSB Installation Injury Report. 8 TABLE 1. ICD-9/ ICD-9 ICD-10 800 S02, S12, S22, S32, S42, S490S491, S52, S590S592, S62, S72, S790S791, S82, S890S893, S92, S992 830 S030S033, S130S132, S230S232, S330S334, S430S433, S530S531, S630S632, S730, S830, S831, S930S933 840 S034, S038, S039, S0911, S134S135, S138, S139, S161, S233S234, S238, S239, S2901, S335S336, S338S339, S3901, S434S436, S438S439, S4601, S4611, S4621, S4631, S4681, S4691, S534, S5601, S5611, S5621, S5631, S5641, S5651, S5681, S5691, S635S636, S638 S639, S6601, S6611, S6621, S6631, S6641, S6651, S6681, S6691, S731, S7601, S7611, S7621, S7631, S7681, S7691, S834S836, S838S839, S8601, S8611, S8621, S8631, S8681, S8691, S934S936, S9601, S9611, S9621, S9681, S9691 850, 860, 952 S06, S140S141, S240S241, S260, S261, S27, S2690, S2691, S2699, S340, S341, S343, S36, S37 870, 890 S01, S052S057, S080, S092, S11, S21, S31, S41, S51, S61, S71, S7602, S81, S91 885, 895 S081, S088, S089, S281, S282, S382, S383, S48, S58, S68, S78, S88, S98 900 S090, S15, S25, S35, S45, S55, S65, S75, S85, S95 910 S00, S050, S051, S10, S20, S30, S40, S50, S60, S70, S80, S90 925 S07, S17, S280, S380, S381, S47, S57, S67, S77, S87, S97 940 T20T28, T30T32 950, 953 S04, S142S146, S148, S149, S242S244, S248, S249, S342, S344S349, S44, S54, S64, S74, S84, S94 800
Page 4 RESULTS Incidence of injuries During the surveillance period, more than 3.6 million acute incident injuries were diagnosed among more than 1.6 mil lion individuals (Table 2) e vast majority of acute incident injuries were diagnosed in outpatient settings (99.2%) (data not shown) e highest overall rates were for injuries to the foot/ankle (61.8 per 1,000 p-yrs) (Table 2) From 2008 through 2017, there was a 50% decrease in the annual incidence rates of back/abdomen injuries, a 32% decrease in the rates of foot/ankle injuries, and a 26% decrease in the rates of head/neck injuries. Annual rates of injuries to the hand/wrist and arm/shoulder both decreased by 21% during the surveillance period (Figure) Incidence rates of knee and leg injuries were either stable or decreased from 2008 through 2014 but then increased from 2014 through 2017. Overall incidence rates of acute inju ries to the head/neck and hand/wrist were highest among service members aged 20 years (Table 3) Incidence rates of acute inju ries to the leg and foot/ankle were high est among those less than 20 years of age and decreased with increasing age. In con trast, overall incidence of acute injuries to the knee and arm/shoulder increased with increasing age. Back/abdomen acute inju ries were highest among service members aged 35 years. ese age trends were similar for both men and women (Table 3) Male and female service members had similar rates of acute injuries to the head/ neck (47.5 per 1,000 p-yrs and 49.4 per 1,000 p-yrs, respectively) as well as to the knee (20.9 per 1,000 p-yrs and 19.5 per 1,000 p-yrs, respectively) (Table 3) Males had higher rates of injury to the arm/shoul der as well as to the hand/wrist, whereas females had higher rates of injury to the back/abdomen, leg, and foot/ankle. In gen eral, rates of acute injuries were relatively similar among the dierent race/ethnic ity groups. However, compared to their respective counterparts, rates of acute inju ries to the knee and leg were somewhat higher among non-Hispanic black service members, and rates of injuries to the head/ neck and arm/shoulder were somewhat higher among non-Hispanic white service members. Junior enlisted service members had the highest overall rates of injuries to the head/neck, hand/wrist, leg, and foot/ ankle. Senior enlisted service members had the highest rates of injuries to the arm/shoulder, back/abdomen, and knee. In addition, recruits had higher overall rates of injuries to the knee, leg, and foot/ ankle. In particular, the rate of acute inju ries to the foot/ankle for recruits was three times that among non-recruits (175.4 per 1,000 p-yrs vs. 59.3 per 1,000 p-yrs, respectively). Rates of acute injuries to all other anatomic sites among recruits were similar to or less than rates among nonrecruits (Table 3) Service members in the Army had higher overall rates of acute injuries to all anatomic sites, compared to those in the other service branches. In general, rates of injuries to most anatomic sites tended to be higher among service members in motor transport and/or combat-related occupations relative to those in other military occupations. However, rates of TABLE 2. 594,454 482,515 561,197 412,209 562,400 456,073 502,658 400,099 257,009 184,856 435,754 357,102 768,973 589,338 3,682,445 1,622,586 FIGURE. 0.01 0 0 2 0 0 3 0 0 4 0 05 0 .06 0 07 0 .08 0 0 9 0 0 1 0 0.0 2 0 0 8 2 0 0 9 2 0 1 0 2 0 1 1 2 0 1 2 2 0 1 3 20 14 2 0 1 5 20 16 2 0 1 7p 0 0 0 1 r e p e t a R y rs Fo o t/a n k l e He a d /n e c k Ba c k /a bdo m e n Ha n d /wri s t Arm /s h ould e r L e g Kn e e
Page 5 TABLE 3. 41,650 31,000 37,767 25,834 15,297 39,875 80,778 20 24 218,846 168,361 206,785 149,008 75,864 146,994 280,683 25 144,140 132,055 138,306 124,513 59,457 100,390 183,741 30 82,273 85,364 78,558 82,499 38,365 61,601 102,869 35 56,669 71,192 54,626 64,039 32,766 45,998 67,758 40 45,912 66,182 42,124 51,861 31,706 37,196 48,629 > 50 4,964 7,043 4,234 4,904 3,554 3,700 4,515 Sex 500,759 488,515 484,387 414,527 220,089 357,315 626,578 93,695 72,682 78,013 88,131 36,920 78,439 142,395 34,244 25,350 31,413 19,187 11,766 28,357 60,748 20 24 184,756 145,776 177,795 119,142 63,976 118,650 229,357 25 120,932 115,136 118,933 102,826 50,919 83,298 151,370 30 69,233 74,745 68,098 69,824 33,449 52,211 84,977 35 48,357 63,232 47,789 54,806 28,945 39,672 56,456 40 39,218 58,426 36,915 44,763 28,029 32,095 40,326 > 50 4,019 5,850 3,444 3,979 3,005 3,032 3,344 7,406 5,650 6,354 6,647 3,531 11,518 20,030 20 24 34,090 22,585 28,990 29,866 11,888 28,344 51,326 25 23,208 16,919 19,373 21,687 8,538 17,092 32,371 30 13,040 10,619 10,460 12,675 4,916 9,390 17,892 35 8,312 7,960 6,837 9,233 3,821 6,326 11,302 40 6,694 7,756 5,209 7,098 3,677 5,101 8,303 > 50 945 1,193 790 925 549 668 1,171 368,483 354,098 346,884 307,684 150,965 252,594 462,190 96,036 86,945 92,628 84,726 48,087 86,691 127,745 74,109 67,984 69,769 62,566 33,564 57,759 102,158 19,037 18,200 17,220 16,792 8,200 13,565 28,198 36,789 33,970 35,899 30,890 16,193 25,145 48,682 306,896 246,419 290,019 226,746 112,142 226,835 431,270 219,444 238,105 206,237 214,842 109,068 156,317 257,865 38,827 36,979 36,991 30,626 16,811 27,871 47,191 23,078 31,490 23,478 23,800 15,637 19,682 26,078 6,209 8,204 5,675 6,644 3,351 5,049 6,569 Yes 10,140 11,436 8,720 9,299 6,430 16,250 47,499 No 584,314 549,761 553,680 493,359 250,579 419,504 721,474 273,809 252,623 238,045 229,106 108,758 210,962 343,882 106,427 99,835 110,071 91,781 47,736 65,575 134,212 123,626 125,215 134,208 117,800 62,968 99,271 174,735 90,592 83,524 80,076 63,971 37,547 59,946 116,144 106,979 86,216 79,777 66,274 36,841 61,473 102,334 20,850 17,842 18,256 16,595 8,158 14,085 24,794 13,975 14,849 13,535 12,474 6,969 9,428 15,181 166,830 161,683 175,480 145,309 73,237 115,248 209,566 124,952 123,430 115,847 118,522 58,150 102,257 176,394 51,187 49,956 51,909 46,577 22,120 36,221 64,754 109,681 107,221 107,596 96,907 51,534 97,042 175,950
Page 6 TABLE 4. % % % % % % 32,003 1,498 120,594 104,407 109,532 6 51,987 51,010 338,523 0 21,575 408 119,883 11,597 142,524 0 154,998 1,646 28,626 1,367 373,618 11,216 11,395 4 3,873 78,957 120,923 0 1,631 0 38,614 893 191,910 0 27,441 3,188 112,030 4,344 499,062 0 27,505 307 387,016 149,666 1,787,154 115,623 354,077 5,559 % % % % % % 415 130,146 198 6,797 1,389 87,469 245 42,401 400 6,292 7,605 40,751 518 87,803 7,877 11,810 773 22,971 342 55,695 311 2,033 549 17,502 0 36,708 197 243 0 14,477 389 49,333 481 4,103 3,027 116,375 44 112,080 2,979 2,228 218 8,176 1,953 514,166 12,443 33,506 13,561 307,721 injuries to the leg and foot/ankle were highest among service members in other occupations (Table 3) Type of injury Overall, sprains/strains (48.5%) was the most common type of injury for all 3,682,445 acute incident injuries to all ana tomic sites (Table 4) Sprains/strains com prised 74.3% of back/abdomen injuries, 64.9% of foot/ankle injuries, 60.3% of arm/ shoulder injuries, 47.1% of knee injuries, 44.0% of leg injuries. Of all incident head/ neck injuries, the largest proportions of injury type categories were for contusion/ supercial (21.9%), followed by sprains/ strains (20.3%). For hand/wrist injuries, open wounds (27.6%) followed by sprains/ strains (25.3%) were most common. External causes e majority (69.7%) of acute incident injuries for all anatomic sites were due to undocumented or undetermined causes (Table 5) is percentage remained rela tively stable during the surveillance period; however, there was a peak in injuries due to undocumented or undetermined causes in 2010 (79.5%) (data not shown) Knee inju ries had the highest percentage of undoc umented causes (84.4%) and hand/wrist injuries had the lowest percentage (60.5%) (Table 5) Miscellaneous (9.9%), overexer tion (5.3%), slips/trips/falls (4.9%), ath letics (3.2%), land transport (3.0%), and machinery/tools (2.4%) were the next most commonly documented external causes of injury for all acute incident injuries. ese external causes made up 32.6%, 17.5%, 16.1%, 10.7%, 9.7%, and 7.8% of acute inci dent injuries with documented external causes of injury, respectively. Compared to other anatomic sites, a relatively high percentage of head/neck injuries were caused by land transport acci dents (7.2% of all head/neck injuries, 20.0% of head/neck injuries with documented external causes) (Table 5) Similarly, a rela tively high percentage of leg (5.5% of total, 19.2% of documented) and foot/ankle (4.7% of total, 14.8% of documented) acute incident injuries were caused by athlet ics. Also of note, 8.3% of total (30.9% of documented) back/abdomen injuries and 9.8% of total (30.8% of documented) foot/ ankle injuries were caused by overexer tion, and 11.2% of total (28.5% of docu mented) hand/wrist injuries were caused by machinery/tools. Disposition Overall, the most common disposi tion for incident injuries to all anatomic sites was returned to duty with no limita tions (69.8%), followed by returned to duty with limitations (25.9%), and not returned to duty (4.3%) (Table 6) Compared to other anatomic sites, head/neck injuries most commonly resulted in being returned to duty with no limitations (83.6%), whereas
Page 7 service members from 2008 through 2017. e highest overall incidence rates during the surveillance period were for injuries to the foot/ankle, followed by head/neck, and hand/wrist. Rates of injuries to the leg and those to the foot/ankle were higher among younger service members, whereas inci dence of injuries to the knee and to the arm/shoulder increased with increasing age. Males had higher rates of injuries to the arm/shoulder as well as to the hand/ wrist, whereas females had higher rates of injuries to the back/abdomen, leg, and foot/ankle. Recruits also had higher rates of injuries to the knee, leg, and foot/ankle. Service members in the Army had higher rates of acute injuries to all anatomic sites, compared to the other service branches. In general, rates of injuries to most anatomic sites tended to be higher among service members in motor transport and/or com bat-related occupations. Data presented in this report suggest that injury prevention strategies should be tailored to dierent populations with dierent risk factors, including training and occupational exposures. For exam ple, female soldiers have traditionally been TABLE 5. % % % % --------179,720 30,278 28,750 26,763 108,499 42,869 17,657 8,427 1,776 682 194 111 7,243 2,189 755 127 648 184 65 95 119,125 8,785 17,203 11,476 194,883 7,316 27,461 8,669 87,226 4,881 4,371 63,210 20,547 3,171 2,873 10,299 2,480 678 408 782 4,322 1,381 402 1,166 363,779 94,888 30,866 86,815 --------3,481 490 1,165 1,435 22,570 16,132 1,527 2,692 2,566,146 380,530 427,500 340,333 % % % % --------19,136 10,910 20,878 43,005 20,085 3,762 9,796 5,903 273 40 166 310 1,154 183 1,097 1,738 82 31 90 101 13,490 7,778 24,096 36,297 41,637 5,957 28,172 75,671 1,457 224 5,304 7,779 668 117 2,324 1,095 118 19 298 177 368 22 728 255 35,045 11,059 32,204 72,902 --------177 7 146 61 1,272 124 510 313 367,696 216,776 309,945 523,366 foot/ankle injuries were the least common (60.2%). In 2010, there was a spike in inci dent injuries that resulted in being returned to duty with no limitations accompanied by a corresponding drop in injuries that resulted in being returned to duty with lim itations (data not shown) EDITORIAL COMMENT is report summarizes the incidence, type, external causes, and disposition of acute injuries among active component U.S.
Page 8 TABLE 6. % % % % 1,960,104 344,894 304,800 322,713 727,710 33,839 107,408 85,115 120,175 33,864 12,763 12,142 2,807,989 412,597 424,971 419,970 % % % % 280,193 116,770 202,090 388,644 92,375 60,741 112,320 235,912 24,900 4,055 11,839 20,612 397,468 181,566 326,249 645,168 shown to be at much higher risk of lower extremity musculoskeletal injuries during training, and this is further supported by the high rate of foot/ankle injuries among young female service members observed in this study. 10 Physical training is also the leading cause of injuries among service members, which is supported by the nd ing of high rates of lower extremity injuries among recruit trainees identied in this study. 5,7,10,11 However, aside from increas ing physical tness requirements, there is little opportunity for military intervention to prevent injuries among recruits before the start of basic training. Instead, inter ventions for training-related injuries must focus on the training regimens themselves. In addition, dierent occupations for active component service members have dierent physical demands. Such dierences should be considered when deciding whether spe cialized protective equipment or training is needed. For example, paratroopers have traditionally been identied as being at high risk of ankle injuries and have bene tted by the use of parachute ankle braces during airborne operations. 13 In 2004, the Military Training Task Force of the Defense Safety Oversight Council chartered a working group to identify, evaluate, and assess the level of scientic evidence for various physi cal training-related injury prevention strategies through an expedited system atic review process. 13 is working group identied six interventions that were rec ommended for implementation in the mili tary: prevention of overtraining, agility-like training, mouthguards, semirigid ankle braces, nutrient replacement, and synthetic socks. 13 In contrast, the use of back braces and pre-exercise administration of antiinammatory medication were not recom mended due to evidence of ineectiveness or harm. 13 e working group also identi ed education, leader support, and surveil lance as essential factors that are needed for successful injury prevention programs. 13 ere are several limitations to this study. e high level of missing data for external cause codes hinders the ability to make prevention recommendations based on the causes of injury. Although external cause coding is not mandatory, the ICD10-CM Ocial Guidelines for Coding and Reporting strongly encourage medi cal professionals to code external causes to provide valuable data for injury research and evaluation of injury prevention strat egies. 14 ere were several substantial changes in the number and structure of injury codes in the transition from ICD-9 to ICD-10 coding systems (which occurred on 1 October 2015); the impact of this tran sition on coding practices is not yet fully understood. 9 erefore, time trends should be interpreted with caution. Not all types of injuries were included in this report. Because one of the goals of this report was to categorize incidence of injury by anatomic site, injuries to unspeci ed or other sites, environmental inju ries, and poisonings were excluded. Other studies have included selected diagnoses of musculoskeletal disorders (e.g., stress frac tures, tendonitis, bursitis) in the denition of injury 6 ; however, this analysis focused on only acute injuries included in the ICD-9 800 and ICD-10 S-T code series. Inju ries that occur during deployment were also not included in this analysis. How ever, some injuries that occurred during deployment may have been unintentionally included if a service member was medi cally evacuated out of theater and treated in an inpatient or outpatient setting. Because data were based on diagnoses made using ICD-9 and ICD-10 codes, the severity of various injuries could not be quantied (aside from the type of injuries). In addi tion, data were not available to quantify time lost due to injuries. MHS GENESIS, the new electronic health record for the MHS, was imple mented at several military treatment facil ities during 2017. Medical data from sites that are using MHS GENESIS are not available in DMSS. ese sites include Naval Hospital Oak Harbor, Naval Hospi tal Bremerton, Air Force Medical Services Fairchild, and Madigan Army Medical Center. erefore, medical encounter and person-time data for individuals seeking care at one of these facilities during 2017 were excluded from analysis.
Page 9 is report aims to broaden the sur veillance of acute injuries across the DoD. Future eorts could provide additional data on cumulative traumatic injuries, as well as breakdowns by installation and/or region. e epidemiology of overuse inju ries resulting from cumulative trauma or repetitive use and stress will be particularly important to quantify to provide a more complete picture of the burden of injuries in the U.S. Armed Forces. Coupled with the most recent research ndings on the eec tiveness of various injury prevention strat egies, the surveillance data presented here can help to identify the militarys most atrisk groups and target them for injury pre vention interventions. REFERENCES MSMR J Occup Med and Toxicol Sports Med Am J Prev Med Am J Prev Med Am J Prev Med Mil Med Mil Med Am J Prev Med Am J Prev Med
Page 10 Major amputations of the lower and upper limbs are among the most lifealtering and debilitating combat injuries. From 1 January 2001 through 31 October 2017, a total of 1,705 service members sustained major deploymentrelated lower and upper limb amputations. Lower limb amputations were far more common than upper limb amputations, with a total of 1,914 lower limb amputations, compared to 302 upper limb amputations. e greatest singleyear number of amputations occurred in 2011, with a reported total of 273 service members who sustained 403 major limb amputations. e injured cohort mostly comprised non-Hispanic white male service members aged 21 years. Furthermore, the majority of the injured cohort included active component, mid-level or junior enlisted members of the Army or Marine Corps, in combat-specic occupations. ese ndings reiterate and extend previous reports of the annual numbers, types, and anatomic locations of deployment-related limb amputations, along with the demographics and military characteristics of the injured cohort from the Iraq and Afghanistan conicts. Major Deployment-related Amputations of Lower and Upper Limbs, Active and Reserve Components, U.S. Armed Forces, 2001 Shawn Farrokhi, PT, PhD; Katheryne Perez, MPH, CPH; Susan Eskridge, PT, PhD; Mary Clouser, PhD ajor limb amputations are lifethreatening and life-altering events for service members injured in combat. While amputations are viewed as lifesaving procedures in many cases, limb loss can oen result in imme diate and long-term decline in physi cal, social, and nancial well-being of the injured service members. 1 Additionally, caring for service members with limb loss places a tremendous burden on their fami lies, as well as the Departments of Defense (DoD) and Veteran Aairs (VA) health sys tems. 2,3 As a result of the extensive advanced medical and rehabilitative care provided within the DoD and VA healthcare systems, young, otherwise healthy combat amputees may now live active and productive lives. 4-7 As a result, better understanding of the size and characteristics of the combat-injured amputee population is critical to formulate sound strategies for current and future pol icy, healthcare, and readiness decisions. On 8 April 2015, the Defense Health Board published a series of recommenda tions in a report entitled Sustainment and Advancement of Amputee Care focused on maintaining the current level of military competency and clinical readiness in the event of future conicts. 8 One of the core recommendations of this report described the need for better characterization of the current landscape of military amputee care, to gain a better understanding for the health, healthcare needs, and health care utilization of the amputee population. 8 A fundamental step toward achieving this goal requires a thorough and up-to-date understanding of the numbers, types, and anatomic locations of the upper and lower limb amputations, along with demographic and military characteristics of this injured cohort. In 2012, the MSMR reported a sum mary of the annual numbers and the types of upper and lower limb traumatic amputations in service members between the years 2000 and 2011. 9 Not surpris ingly, relatively large numbers of major limb amputations (i.e., loss of a hand or foot or more) were reported during the period of more widespread and intense ground combat operational activities in Afghanistan and Iraq. For example, there were large numbers of major lower limb amputations from 2003 through 2007 and again during 2010 and 2011 among junior enlisted members of the Marine Corps and Army serving in combat-specic military occupations (i.e., infantry/artillery/com bat engineering/armor). e current report reiterates and extends details from the pre vious report on the numbers, types, and anatomic locations of deployment-related major lower and upper limb amputations, along with the demographics and military characteristics of this cohort from 2001 through 2017. METHODS e surveillance period for this report was 1 January 2001 through 31 October 2017. e surveillance population con sisted of all individuals who served in an active and/or reserve component of the U.S. Armed Forces at any time during the sur veillance period. Diagnosis codes from the International Classication of Diseases, 9th and 10th Revisions, Clinical Modications (ICD-9/ICD-10) specic for amputations were used to identify major amputations among service members during the surveil lance period (Table 1) All data to determine the numbers, types, and anatomic locations of lower and upper limb amputations were derived from records routinely maintained in the Expe ditionary Medical Encounter Database (EMED). e EMED is a comprehensive
Page 11 deployment-related data repository that provides a high-quality source of clinical, tactical, and personnel data for each casu alty, sickness or injury, during deployment. 10 ese data are used for determining the ater medical requirements (modeling and simulation) and for performing research. For each casualty, sick or injured, in over seas contingency operations, a compre hensive clinical record is established beginning with the rst medical treatment at the point of injury. As the patient moves through the medical chain of evacuation, additional clinical data are added to the EMED, including injury, disease, and psy chiatric prole, procedures administered, clinical complications of care, and patient outcomes. In addition, ICD-9 and ICD-10 clinical diagnoses and injury severity codes are assigned by trained clinicians. Finally, tactical data describing the circumstances that generated the casualty and person nel data describing the casualtys preand post-injury military and medical histories are added. For surveillance purposes, the EMED was queried for case-dening ICD-9 (for amputations before 1 October 2015) and ICD-10 (for amputations on or aer 1 Octo ber 2015) diagnostic codes for all amputa tions of partial hand or foot and greater from 1 January 2001 through 31 October 2017. e Extremity Trauma and Amputa tion Center of Excellence Amputation Reg istry also was utilized for conrmation of identied cases. Additional data collected from the EMED included anatomic ampu tation information, gender, age, branch of service, and military paygrade, all at time of injury. Other demographic variables such as active or reserve status, race/ethnic ity, and military occupation were obtained from the Defense Manpower Data Center Contingency Tracking System. Amputations of ngers or toes were excluded. Service members who were determined to have been killed in action or to have died of wounds were also excluded from this report. Service members with multiple amputations were counted only once in the population as individuals; however, each amputation was included separately in total counts and analyses of amputations. RESULTS During the surveillance period, a total of 1,705 service members sustained deploy ment-related, major amputations (Table 2) Lower limb amputations were far more common than upper limb amputations, with 1,496 service members sustaining a total of 1,914 lower limb amputations com pared to 284 service members sustaining a total 302 upper limb amputations. Dur ing the surveillance period, bilateral ampu tations were more common in the lower extremities (n=418; 25% of all individu als who had amputations), compared to the upper extremities (n=18; 1%; Table 2 ). Additionally, there were 46 service mem bers who sustained triple amputations and six service members who sustained qua druple amputations during the surveillance period (data not shown) Of the lower limb amputations, the most common type was transtibial (n=995; 52%), followed by transfemoral (n=469; 25%), knee disarticulation (n=266; 14%), foot or partial foot (n=115; 6%), ankle TABLE 1. ICD-9/ ICD-9 ICD-10
Page 12 (n=46; 2%), and hip disarticulation (n=23; 1%) (Figure 1) During the surveillance period, the number of lower limb amputa tions increased each year from 80 in 2003 to 234 in 2007, before decreasing to 117 and 111 in 2008 and 2009, respectively. e number of lower limb amputations began to increase again in 2010, peaking at 377 in 2011, the most of any year during the sur veillance period (Figure 1) Bilateral lower limb amputations followed a similar trend (data not shown) with spikes in 2007 (n=46) and 2011 (n=111). Of the upper limb amputations, the most common type was transradial (n=114; 38%), followed by transhumeral (n=78; 26%), hand or partial hand (n=51; 17%), wrist disarticulation (n=32; 11%), elbow disarticulation (n=18; 6%), and shoulder disarticulation (n=8; 3%) (Fig ure 2) e highest numbers of upper limb amputations were observed in 2004 (n=47) and 2005 (n=42), followed by 2007 (n=39). Declines in upper limb amputations were observed in 2008 (n=13) and 2009 (n=12), before again increasing in 2010 (n=35). Aer 2012, the number of upper limb amputations declined sharply from 23 in 2012 to six in 2013 followed by two in 2014 (Figure 2) e number of bilateral upper limb amputations was relatively stable and low throughout the surveillance period, with none occurring in 2001, 2002, 2006, 2008, or aer 2013 (data not shown) e injured cohort mostly comprised male service members (n=1,677; 98%), of non-Hispanic white race/ethnicity (n=1,299; 76%), and aged 21 (n=1,132; 66%) (Table 3) Furthermore, the major ity of the injured cohort were members of the active component (n=1,497; 88%), served in the Army (n=1,141; 67%) or Marine Corps (n=493; 29%), were junior or mid-level enlisted (E1E6; n=1,494; 88%), in combat-specic occupations (n=1,067; 63%) (Table 3) Additionally, the most fre quent cause of major limb amputation for the cohort was a blast injury (n = 1,545; 91%) (Table 3) From 2003 through 2009, more than three-quarters of those with limb ampu tations were Army members (Figure 3) TABLE 2. 23 2 1,053 1,078 44 6 368 418 199 10 209 266 18 1,421 1,705 FIGURE 1. 4 1 5 6 9 89 8 1186 5 7 3 113 199 9 9 2 2 1 8 4 43 34 5 6 0 2 1 2 1 8 8 9 3 3 81 7 2 02 4 1 7 3 1 6 6 5 1 0 5 0 100 150 200 250 300350 4002001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017N o. of am pu t at i on s H i p di s ar t i c ulat i on K n ee dis a r t i c u l at i on T r an s f emor al T r an s t i bial A n k l e Foo t / par t ial f oot8 0 132 162 172 234 266 117 111 377 4 3 8 2 1 3 2 2200
Page 13 However, aer 2009, the frequency of Marine Corps members sustaining amputa tions increased dramatically, going from 22 in 2009 to 91 in 2010 and 155 in 2011, repre senting 23%, 43% and 57% of injured service members for each year, respectively. In 2011, the year with the most amputations for the whole surveillance period, members of the Marine Corps made up the majority of ser vice members with amputations (Figure 3) roughout the entire surveillance period, mid-level enlisted (E4E6) service members comprised the majority of the deployment-related amputation popula tion, followed by junior enlisted (E1E3) service members (Figure 4) However, the numbers and proportions of junior enlisted service members sustaining amputations increased markedly from 2010 through 2011, with junior enlisted service members representing 32% and 40% of all injured service members, respectively. e vast majority of deploymentrelated major amputations were sustained by active component service members as compared to those in the Reserve/Guard components (Figure 5) Between 2003 and 2006, the active component service mem bers accounted for 74%% of each years total amputation injuries. However, from 2007 through 2014, the annual propor tions for the active component increased to 91%% (Figure 5) EDITORIAL COMMENT is report reiterates and extends the ndings of previous surveillance reports in describing the annual numbers, types, and anatomic locations of deploymentrelated major limb amputations during the 16 years and 10 months of the surveillance period. e report also compares trend dif ferences regarding major lower and upper limb amputations, overall and in relation to various demographic and military char acteristics. During 2001, there were a total of 2,216 reported cases of deploy ment-related, major lower and upper limb amputations sustained by 1,705 service members. e greatest number of ampu tations in a single year occurred in 2011 at the height of the surge in operations in Afghanistan, with a reported total of 403 major lower and upper limb amputations sustained by 273 service members. Overall, and consistent with a previous report, 9 relatively large numbers of major limb amputations were observed during periods of more widespread and intense ground combat operational activities. More specically, an increasing number of major lower limb amputations were observed between 2003 through 2007 and again FIGURE 2. 3 2 9 1 01 6 5 8 451 1462 2 3 31 0 1 91 4 1 0 1 6 6 61 1 1 16 3 336 6 2 3 33 2 31 07 36 7 6 5 20 51 0 1 5 2 0 2 53 0 3 54 0 4 5 5 0 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017N o. of am pu t ati on s H and o r par t i a l hand W r is t d is a r t ic u l a t io n Tr ansr ad ial E lbo w dis ar t ic ula t ion Tr ans hum e r a l S h oulder d i s a r t ic u l a t io n212 6 4 74 22 6 3 9 1 31 23 5 2 6 2 362 1
Page 14 TABLE 3. N % 1,705 Sex 28 1,677 272 21 694 25 438 30 180 35 82 > 40 38 1 1,299 112 174 45 20 55 1,141 46 25 493 1,497 195 13 484 1,010 80 129 2 1,067 257 213 76 58 12 22 1,545 73 87 between 2010 through 2012. Of note, the time period between 2009 and 2011 repre sented a sharp increase in numbers of lower limb amputationsparticularly among junior enlisted members of the Marine Corps and the Army, reecting a surge in the extent and intensity of dismounted ground combat operations. Although 2012 marked a decline in the number of major lower limb amputations, compared to the previous 2 years, a substantial number of almost 200 lower limb amputations were still sustained. During the surveillance period, the numbers of major amputations of the upper limbs were much smaller, compared to the numbers of major amputations of the lower limbs. e highest numbers of upper limb amputation occurred between 2004 and 2005, in 2007, and between 2010 and 2012. e smaller number of upper limb amputations (n=302), compared to lower limb amputations (n=1,914) is most likely the result of the lower limbs accounting for a greater body surface area and being more exposed to blast trauma. 11 e results of this report should be interpreted with consideration of its limi tations. For example, the analyses were based on high-quality clinical, tactical, and personnel data from the EMED for ser vice members injured during deployment. As such, the summaries reported here do not include non-deployment limb amputa tions due to training accidents, motor vehi cle accidents, or sports-related injuries in the military. In addition, minor traumatic amputations of the ngers and toes were also not considered, due to the imprecise nature of reporting such procedures within the medical records. Misclassifcation and incomplete capture of limb amputations in the military medical surveillance data were also possible, given the reliance of coders on provider documentation, which may be nonspecifc or unclear. Finally, some injured service members, especially those with delayed amputations, may have received care outside of the Military Health System (e.g., at civilian trauma centers and VA hospitals); in such cases, amputations were not documented in records used for this analysis. In summary, a large number of deploy ment-related, major amputations of the upper and lower limbs have occurred since 2001. In general, lower limb amputations have occurred at a much higher rate com pared to upper limb amputations, due to the predominance of blast injuries caused by improvised explosive devices. Addition ally, the demographics and military char acteristics of the injured cohort includes a substantially greater proportion of young, white male, junior to mid-level enlisted members of the Army and the Marine Corps. Although improvements in protec tive gear and body armor, and advance ments in military medicine, particularly in acute in-eld care and aeromedical patient transport, have signicantly improved survival from traumatic injury, limb loss continues to pose new challenges for the military and VA health systems. 8 To this end, the growing number of young, highperforming service members living with amputated limbs has created a unique amputee population with specic, longterm needs requiring considerable atten tion and resource allocation. Author aliations: DoD-VA Extremity Trauma and Amputation Center of Excel lence, Fort Sam Houston, TX (Dr. Farrokhi, Ms. Perez); Department of Physical and Occupational erapy, Naval Medical Cen ter San Diego, CA (Dr. Farrokhi); Leidos, San Diego, CA (Ms. Perez, Dr. Eskridge, Dr. Clouser). Funding source: Support was provided by the DoD-VA Extremity Trauma and Ampu tation Center of Excellence under Work Unit No. N1333. Conicts of interest: None. Previous publications: is original work has not been published elsewhere prior to submittal. Disclaimer: e views expressed herein are those of the author(s) and do not necessar ily reect the ocial policy or position of the Department of the Navy, Department of the Army, Department of Defense, or the United States Government.
Page 15 FIGURE 3. FIGURE 4. 8 4 107 119 121 1908 06 9 113 105 1102 94 6 4 2 3 8 2 5 2 2 2 2 9 1 155 3 4 9 0 5 0 100 150 200 250 300 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017s r e b m e m e c i v r e s f o o N A ir Force N a v y Mar ine C o r p s A r m y3 9 5162169165 273 213 3 71512181059 7 8 1 224 2 0 4 0 3 8 4 2 4 6 3 2 3 0 6 9 1094 76 2 102 105 110 149 5 9 5 4 114 143 7 92 19 1 2 1 1 1 7 1 7 1 5 8 1 8 1 51 40 5 0 100 150200250 300 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017No. of service members Of f i c er E 7 E 9 E 4 E 6 E 1 E 3 43162 9 5 169 2181049 7 213 272 151 3 781 165 2 2
Page 16 FIGURE 5. 7 7 123 124 138 198 9 88 7200 254 144 3 7 1 7 3 6 4 3 2 6 2 0 1 3 1 8 0 5 0 100 150 200 250 3002001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017s r e b m e m e c i v r e s f o o N R e s erve/ Gu ard A c t iv e 213 2722183 2 159 167 164 104 9 5 151 3 7 8 1 2 2 9 4 REFERENCES US J J Am Acad Orthop
Page 17 In 2017, a total of 626 medical evacuations of service members from the U.S. Central Command area of responsibility were followed by at least one medi cal encounter in a xed medical facility outside the operational theater. ere were more medical evacuations for mental health disorders than for any other category of illnesses or injuries. Annual rates of medical evacuations attributable to battle injuries decreased from 3.5 per 1,000 deployed personyears [dp-yrs] (n=317) in 2013 to a low of 0.73 per 1,000 dp-yrs (n=28) in 2016, and then increased to 1.4 per 1,000 dp-yrs (n=53) in 2017. Annual rates of medical evacuations attributable to non-battle injuries and illnesses were relatively stable from 2015 through 2017. Compared to their respective counterparts, medical evacuation rates were highest among non-Hispanic black service members, among those aged 19 years or younger or aged 45 years or older, among Army members, and among those in combat-specic occupations. Most service members who were evacuated were returned to normal duty status following their post-evacuation hospitalizations or out patient encounters. Update: Medical Evacuations, Active and Reserve Components, U.S. Armed Forces, 2017 n recent years, there have been sub stantial reductions in combat opera tions taking place in the U.S. Central Command (CENTCOM) area of responsi bility (AOR) in Southwest Asia. 1-3 However, the number of service members deployed to CENTCOM AOR since 2012 is still sig nicant. From 1 January 2013 through 31 December 2017, there were more than 650,000 deployments in support of CENT COM AOR operations, including Opera tion Enduring Freedom (OEF), Operation Freedoms Sentinel (OFS), Operation New Dawn (OND), and Operation Inherent Resolve (OIR). In theaters of operations such as Afghanistan, most medical care is provided by deployed military medical personnel; however, some injuries and ill nesses require medical management out side the operational theater. In these cases, the aected individuals are usually trans ported by air to a xed military medical facility in Europe or the U.S. At the xed facility, the service members receive the specialized, technically advanced, and/ or prolonged diagnostic, therapeutic, and rehabilitative care required. Medical air transports (medical evac uations) are costly and generally indica tive of serious medical conditions. Some serious conditions are directly related to participation in or support of combat oper ations (e.g., battle wounds); however, many others are unrelated to combat and may be preventable. is report summarizes the natures, numbers, rates, and trends of con ditions for which male and female military members were medically evacuated from CENTCOM AOR operations during 2017 and compares them to the previous 4 years. METHODS e surveillance period was 1 January 2013 through 31 December 2017. e sur veillance population included all members of the active and reserve components of the U.S. Army, Navy, Air Force, and Marine Corps who were deployed as part of CENT COM AOR operations during the period. e outcomes of interest in this analysis reected individuals who were medically evacuated during the surveillance period from CENTCOM AOR (e.g., Afghanistan, Iraq) to a medical treatment facility out side the CENTCOM AOR. Evacuations were included in analyses if the aected service member had at least one inpatient or outpatient medical encounter in a per manent military medical facility in the U.S. or Europe during a time interval extend ing from 5 days before to 10 days aer the reported evacuation date. Evacuations were included only if they occurred during the time frames documented in service mem bers CENTCOM AOR deployment records or within 90 days aer. Deployment records were available from the Defense Manpower Data Center Contingency Tracking System in the Defense Medical Surveillance System (DMSS). Records of all medical evacuations conducted by the U.S. Transportation Com mand (TRANSCOM), maintained in the TRANSCOM Regulating and Command & Control Evacuation System (TRAC2ES), were also utilized. Medical evacuations included in the analyses were classied by the causes and natures of the precipitating medical con ditions (based on information reported in relevant evacuation and medical encounter records). First, all medical conditions that resulted in evacuations were classied as battle injuries or non-battle injuries and illnesses (based on entries in an indicator eld of the TRAC2ES evacuation record). Evacuations due to non-battle injuries and illnesses were subclassied into 17 illness/ injury categories based on International Classication of Diseases (ICD-9/ICD10) diagnostic codes reported on records of medical encounters aer evacuation. For this purpose, all records of hospital izations and ambulatory visits from 5 days before to 10 days aer the reported date of each medical evacuation were identied. In
Page 18 most cases, the primary (rst-listed) diag nosis for either a hospitalization (if one occurred) or the earliest ambulatory visit aer evacuation was considered indicative of the condition responsible for the evacu ation. However, if the rst-listed diagnos tic code specied the external cause (rather than the nature) of an injury (ICD-9 E-code/ICD-10 V-, W-, X-, Y-code) or an encounter for something other than a cur rent illness or injury (e.g., observation, medical examination, vaccination [ICD-9 V-codes/ICD-10 Z-codes other than those related to pregnancy]), then secondary diagnoses that specied illnesses and inju ries (ICD-9: 001/ICD-10: A00T88) were considered the likely reasons for the subject evacuations. If there was no sec ondary diagnosis, or the secondary diagno sis also was an external cause code, then the rst-listed diagnostic code of a subsequent encounter was used. For this analysis, one medical evacuation per deployment per service member was counted. Denominators for rates of medical evacuations were calculated by determin ing the length of each individuals deploy ment and summing the person-time of all deployers. If the deployment end date was missing, the end date was imputed based on average deployment times per service, component, and deployment location. e disposition aer each medical evacuation was determined by using the disposition code associated with the medi cal encounter that was used for determin ing the category of the medical evacuation. Inpatient disposition categories were: returned to duty (code: 01), transferred/ discharged to other facility (codes: 02, 09, 21, 43, 61), died (codes: 20, 30, 40, 50, 51), separated from service (codes: 10), and other/unknown. Out patient disposition categories were: released without limitation (code: 1), released with work/duty limitation (code: 2), immedi ate referral (code: 4), sick at home/quar ters (codes: 3, S), admitted/transferred to civilian hospital (codes: 7, 9, AD, U), died (codes: 8, G), discharged home (code: F), and other/unknown. TABLE 1. % % % 148 119 29 132 116 16 74 68 6 69 59 10 53 52 1 37 31 6 23 22 1 21 11 10 20 17 3 14 12 2 9 7 2 6 6 0 --6 4 2 5 3 2 5 5 0 3 2 1 1 1 0 0 ---0 --626 535 91
Page 19 RESULTS In 2017, a total of 626 medical evacu ations of service members from CENT COM AOR were followed by at least one medical encounter in a xed medical facil ity outside the operational theater (Table 1) Overall, there were more medical evacua tions for mental health disorders (n=148, 23.6% of all evacuations; rate: 3.8 per 1,000 deployed person-years [dp-yrs]) than for any other category of illnesses or injuries (Table 1) In addition, rates of evacuation for non-battle injuries and poisonings (3.4 per 1,000 dp-yrs), musculoskeletal system disorders (1.9 per 1,000 dp-yrs), and signs and symptoms (1.8 per 1,000 dp-yrs) were higher than the rate for battle injuries (1.4 per 1,000 dp-yrs). During 2013, annual rates of medical evacuations attributable to battle injuries decreased from 3.5 per 1,000 dp-yrs (n=317) in 2013 to a low of 0.73 per 1,000 dp-yrs (n=28) in 2016, and then increased to 1.4 per 1,000 dp-yrs (n=53) in 2017. ese data represent an overall decline of 61.1% in the rate of battle injury medi cal evacuations from 2013 through 2017. Annual rates of medical evacuations attrib utable to non-battle injuries and illnesses were relatively stable during 2015. In general, the numbers of medical evacua tions over the course of the period varied in relation to the numbers of deployed service members with most medical evacuations occurring during the period of deployment to OEF. In addition, numbers of medical evacuations decreased considerably in the months leading up to 1 January 2015, when U.S. Forces-Afghanistan formally ended its combat mission, OEF, and commenced its new mission, OFS (Figure) In 2017, three categories of illnesses and non-battle injuries accounted for more than half (56.6%) of all evacuations (Table 1) Mental health disorders (most frequently adjustment and depressive dis orders) accounted for almost one-quarter (23.6%) of evacuations; non-battle injuries (primarily fractures of extremities, strains, and sprains) accounted for approximately one in ve (21.1%) evacuations; and mus culoskeletal disorders (primarily aecting the back and knee) accounted for roughly one in nine (11.8%) medical evacuations. Similarly, signs, symptoms, and ill-dened conditions (primarily pain and swelling) accounted for slightly less than one in nine (11.0%) evacuations. Demographic and military characteristics e rate of medical evacuations in 2017 was 26.0% higher among females (19.6 per 1,000 dp-yrs) than males (15.6 per 1,000 dpyrs) (Table 2) e diagnoses with the high est rates of medical evacuations among male service members were mental health disor ders (3.5 per 1,000 dp-yrs), non-battle injury and poisoning (3.4 per 1,000 dp-yrs), mus culoskeletal disorders (2.0 per 1,000 dp-yrs), and signs, symptoms, and ill-dened condi tions (1.7 per 1,000 dp-yrs) (Table 1) Among female service members, the highest rates of medical evacuations were for mental health disorders (6.3 per 1,000 dp-yrs), non-bat tle injury and poisoning (3.5 per 1,000 dpyrs), genitourinary system disorders (2.2 per 1,000 dp-yrs), and signs, symptoms, and illdened conditions (2.2 per 1,000 dp-yrs). FIGURE. Figure. N u m bers o f battl e i n j ury and d i s eas e / non-battl e i n j ury m edi c a l e v a c uat i ons o f U S s erv i c e m e m bers b y m ont h 2013 2017 O I R O perat i on I nherent R e s o l v e ; O E F O perat i on E nduri ng F reedom ; O F S O perat i on F reedom s S ent i nel ; O R S O perat i on R e s o l u t e S upport 0 5 0 1 0 0 1 5 0 2 0 0 2 5 0J a n F e b M a r Ap r M a y J u n J u l Au g Se p O c t N o v D e c J a n F e b M a r Ap r M a y J u n J u l Au g Se p O c t N o v D e c J a n F e b M a r Ap r M a y J u n J u l Au g Se p O c t N o v D e c J a n F e b M a r Ap r M a y J u n J u l Au g Se p O c t N o v D e c J a n F e b M a r Ap r M a y J u n J u l Au g Se p O c t N o v D e c 2 0 1 3 2 0 1 4 2 0 1 5 2 0 1 6 2 0 1 7 N o of m edi c a l e v a c uat i o n-lin k ed m edi c a l enc ount e rs Ba t t l e i n j u ry D i s eas e n on-b a ttl e i n j u ri e s O R S begi n s O I R begi n s O EF ends ; O F S begi n s
Page 20 Despite having a much lower number of medical evacuations compared to males (n=535), females (n=91) had higher rates of evacuations for almost all illness and injury categories. Female service mem bers had particularly higher rates of med ical evacuations for genitourinary system disorders (female:male rate ratio [RR]: 6.7; rate dierence [RD]: 1.8 per 1,000 dp-yrs) and mental health disorders (RR: 1.8; RD: 2.8 per 1,000 dp-yrs), compared to males (Table 1) In contrast, male service members had higher evacuation rates for battle inju ries (RR: 0.14; RD: -1.30 per 1,000 dp-yrs), disorders of the nervous system and sense organs (RR: 0.3; RD: -0.43 per 1,000 dpyrs), and musculoskeletal disorders (RR: 0.65; RD: -0.7 per 1,000 dp-yrs). However, there was only one medical evacuation of a female service member during 2017 for each of the categories of battle injury and nervous system disorders. Overall, medical evacuation rates were highest among non-Hispanic black ser vice members (19.7 per 1,000 dp-yrs) and lowest among service members of other or unknown race/ethnicity (12.7 per 1,000 dp-yrs) (Table 2) Rates of medical evacua tion were lowest among those aged 25 years (12.9 per 1,000 dp-yrs) and high est among those aged 19 years or younger (29.8 per 1,000 dp-yrs) or aged 45 years or older (25.6 per 1,000 dp-yrs). Compared to their respective counterparts, rates of evac uation were higher among deployers who were in the Army (23.5 per 1,000 dp-yrs), senior ocer rank (19.0 per 1,000 dp-yrs), and in combat-specic occupations (23.3 per 1,000 dp-yrs). Most medical evacuations (83.7%) were characterized as having routine prece dence. e remainder had priority (14.1%) or urgent (2.2%) precedence. All but six (1.0%) of the total medical evacuations were accomplished through military trans port (Table 2) Among both males and females, reac tion to severe stress, and adjustment dis orders was the most frequent specic diagnosis (three-digit ICD-10 diagnosis code: F43) during initial medical encoun ters aer evacuations; however, the rates of TABLE 2. 626 Sex 535 91 376 116 90 19 25 27 20 200 25 127 30 95 35 68 40 43 > 45 66 507 23 70 26 434 192 263 250 64 49 194 20 137 146 40 89 524 88 14 c 620 6 c these adjustment disorderrelated evacu ations were 79.8% higher among females (3.7 per 1,000 dp-yrs) than males (2.0 per 1,000 dp-yrs) (Table 3) All of the ve most common three-digit diagnoses associated with evacuations of males were mental health disorders, musculoskeletal disor ders, or injuries (Table 3) Of the top six diagnoses most fre quently associated with evacuations of female service members, two were mental health disorders (reaction to severe stress, and adjustment disorders and major depressive disorder, single episode); one was a condition that primarily aects women (unspecied lump in breast); two were injuries (fracture at wrist and hand level and intracranial injury); and one was a sign, symptom, and ill-dened con dition (abdominal and pelvic pain) (Table 3) Abdominal and pelvic pain and intra cranial injury aected equal numbers of female evacuees. Of note, four of the 10 genitourinary system disorders diagnosed among women were for unspecied lump in breast and one was for benign mam mary dysplasia, solitary cyst of le breast ( data not shown ). Disposition Of the 626 medical evacuations reported in 2017, a total of 219 (35.0%) resulted in inpatient encounters. More than one-half (61.2%) of all service mem bers who were hospitalized aer medical evacuations were discharged back to duty. Slightly more than one-third (37.4%) of service members who were hospitalized aer medical evacuations were transferred or discharged to other facilities (Table 4) Return to duty dispositions were much more likely aer hospitalizations for nonbattle injuries (74.3%) than for battle inju ries (11.4%). In addition, the majority (88.6%) of battle injuryrelated hospital izations and a little more than one-quarter (25.7%) of non-battle injuryrelated hospi talizations resulted in transfers/discharges to other facilities (Table 4) Almost two-thirds (n=407, 65.0%) of the total medical evacuations reported resulted in outpatient encounters only. Of the service members who were treated exclusively in outpatient settings aer
Page 21 TABLE 3. ICD-10 ICD-10 F43 70 F43 17 M54 26 F32 6 F32 20 N63 4 S06 17 S62 4 M25 14 R10 3 S06 3 TABLE 4. % % % 219 44 35 134 5 26 82 39 9 0 0 0 0 0 0 0 0 0 3 0 0 407 9 97 338 9 71 57 0 23 1 0 0 1 0 1 1 0 1 0 0 0 0 0 0 9 0 1 evacuations, the majority (83.0%) were discharged back to duty without work/ duty limitations; 14.0% were released with work/duty limitations; and less than 1% each were admitted/transferred to a civil ian hospital, immediately referred, or dis charged to home sick for recuperation. Service members treated as outpatients aer battle injuryrelated evacuations were more likely to be released without limita tions (n=9, 100.0%) than medical evacuees treated as outpatients for non-battle inju ries (n=71, 73.2%) (Table 4) EDITORIAL COMMENT is report documented that only 8.5% of all medical evacuations during 2017 were associated with battle injuries. Rates of evacuations for battle injuries were con siderably lower in 2017 than in 2013, the rst year of the surveillance period, which is likely a reection of both the reduction in troop levels that took place during this period and the change in mission away from direct combat. Most evacuations in 2017 as well as during the overall 2013 2017 surveillance period were attributed to mental health disorders, followed by nonbattle injuries, signs and symptoms, and musculoskeletal disorders. Rates of evacu ation in 2017 were higher among females than males, as in previous years. Of the major diagnostic categories for which there was more than one medical evacuation for both men and women, only rates of mus culoskeletal disorders evacuations were noticeably higher among males compared to females. e majority of service mem bers who were evacuated were returned to normal duty status following their postevacuation hospitalizations or outpatient encounters, as in previous years. However, only about one-quarter of those evacuated for battle injuries were returned to duty immediately aer their initial healthcare encounters. Overall, the changes in numbers of medical evacuations over the course of the surveillance period reect the drawdown of U.S. troops from Afghanistan leading up to the end of Operation Enduring Freedom. 4 As Operation Freedom's Sentinel began, U.S. troop withdrawal slowed and began to level o in 2015. 4 e relatively low rate of medical evacuation (16.1 evacuations per 1,000 dp-yrs in 2017) suggests that most deployers were suciently healthy and ready for their deployments, and received the medical care in theater necessary to complete their assignments without having to be evacuated. is level of health is fur ther supported by the generally low rates of medical evacuations for chronic conditions
Page 22 such as hematologic disorders and congen ital anomalies. However, deployed service members are not immune to such condi tions. For example, there was one medi cal evacuation for congenital anomalies in 2017 that was due to a congenital renal cyst (data not shown) Because congenital anom alies may not be identied and diagnosed until later in life, 5 such diagnoses should not be ruled out. e rate of medical evacuations attrib uted to mental health disorders was similar to the rate reported in an earlier MSMR anal ysis of medical evacuations between 2001 and 2012. 3 Although some studies have indi cated improved access to mental health care in deployed settings, the results from the current analysis do not demonstrate an obvi ous correlation between improved access and the rate of mental health medical evacu ations out of CENTCOM deployment oper ations. 6 is could be due, at least in part, to variations in the availability of mental health care in deployed settings. In these settings, the distribution of providers and clinics that deliver such services is uneven and varies according to factors such as the number of deployed personnel and the assessed needs of the particular unit. 6 In addition, although the number of mental healthcare providers in Afghanistan increased from 2005 through 2010, this number decreased aer 2013 as part of the overall drawdown of U.S. troops from the region. 6 Several important limitations should be considered when interpreting the results of this analysis. Direct comparisons of numbers and rates of medical evacuations by cause, as between males and females, can be misleading. For example, such com parisons do not account for dierences between the groups in other characteristics (e.g., age, grade, military occupation, loca tions and activities while deployed) that are signicant determinants of medical evacuation risk. Also, for this report, most causes of medical evacuations were esti mated from primary (rst-listed) diagnoses that were recorded during hospitalizations or initial outpatient encounters aer evac uation. In some cases, clinical evaluations in xed medical treatment facilities aer medical evacuations may have ruled out serious conditions that were clinically sus pected in the theater. For this analysis, the causes of such evacuations reect diagno ses that were determined aer evaluations outside of the theater rather than diagno sesperhaps of severe diseasethat were clinically suspected in the theater. To the extent that this occurred, the causes of some medical evacuations may seem sur prisingly minor. Overall, results highlight the contin ued need to tailor force health protection policies, training, supplies, equipment, and practices based on characteristics of the deployed force (e.g., combat vs. support; male vs. female) and the nature of the mil itary operations (e.g., combat vs. humani tarian assistance). REFERENCES MSMR MSMR
Page 23 Food-allergy anaphylaxis is an immunoglobulin Emediated, systemic reac tion that is oen unanticipated and can rapidly lead to death. Active duty service members with a history of food-allergy anaphylaxis or a systemic reaction to food do not meet military accession or retention standards. In spite of this, the incidence rate of food-allergy anaphylaxis among active component service members approximates that found in the general pop ulation and appears to be increasing. e overall incidence of food-allergy anaphylaxis among active component service members was 39.1 cases per 100,000 person-years (p-yrs) during the 2007 surveillance period. e incidence increased over the surveillance period from 32.0 per 100,000 p-yrs in 2007 to 55.8 per 100,000 p-yrs in 2016. First-line treatment of anaphy laxis includes rapid administration of epinephrine. In this study, 29% and 58% of incident anaphylaxis cases had lled a prescription for an epinephrine autoinjector (EAI) within 18 months before or 3 months aer the incident diagnosis, respectively. Increasing awareness of food-allergy anaphylaxis, properly identifying at-risk individuals, and ensuring availability of EAIs have the potential to mitigate the risk associated with anaphylaxis. Food-allergy Anaphylaxis and Epinephrine Autoinjector Prescription Fills, Active Component Service Members, U.S. Armed Forces, 2007 Shawn S. Clausen, MD, MPH (CDR, USN); Shauna L. Stahlman, PhD, MPH ood-allergy anaphylaxis is an immunoglobulin E (IgE)-mediated, systemic reaction that is oen unan ticipated and can rapidly lead to death. Prevention of anaphylaxis includes identi cation of individuals at risk for anaphylaxis and avoidance of both the oending agent as well as cofactors that have the potential to induce or exacerbate reactions to an oth erwise tolerated allergen. 1 e Joint Task Force on Practice Parameters recommends that patients with a history of food-allergy anaphylaxis and those who are at risk for anaphylaxis due to a previous systemic reac tion to foods or other factors be prescribed an epinephrine autoinjector (EAI). 2 3 In spite of this recommendation, studies indi cate that EAIs are underutilized. 4 5 Knowledge related to the epidemiology of anaphylaxis in the general population comes from multiple sources, including surveys, 6 medical claims data from hospital admissions, 7 8 emergency room visits, 9 and medically coded encounters from popula tion-based databases (Table 1) 10-18 Incidence rate estimates vary widely due to variable case denitions, populations, data sources, and study design. Among retrospective studies utilizing medically coded encoun ters, rates range from 6.7 per 100,000 person-years (p-yrs) in the general popu lation 17 to 109.0 per 100,000 p-yrs among asthmatics. 13 Studies in the U.S. and else where suggest that the incidence of ana phylaxis is increasing (Table 1) 11 14 15 17 Individuals with a history of anaphy laxis or a systemic reaction to food do not meet military accession standards. 19 Waiv ers may be granted, however, based on the severity of a reaction, risk of recurrence, occupation, and the needs of the military. Service members with a history of foodallergy anaphylaxis who are not identied at accession, and those who develop foodallergy anaphylaxis while on active duty warrant referral to a medical evaluation board for a tness for duty determination. Establishing the incidence of anaphy laxis within the U.S. military and tracking trends over time would increase aware ness of the condition, including the risk of potentially devastating outcomes in aus tere environments. It may also assist with development and implementation of acces sion and retention standards. Quantify ing EAI prescription ll rates could guide prevention and treatment eorts. To date, there are no studies related to the epidemi ology of food-allergy anaphylaxis or EAI prescription ll rates among active com ponent service members. e purpose of this study is to determine the incidence of food-allergy anaphylaxis over time, and to describe EAI prescription ll rates. METHODS Anaphylaxis incidence is was a retrospective cohort study. An incident case of food-allergy anaphy laxis was dened as any inpatient, out patient, or eater Medical Data Store (TMDS) medical encounter identied using ICD-9 code 995.6* and ICD-10 code T78.0* in any diagnostic position. Ser vice members who had been diagnosed with food-allergy anaphylaxis prior to the surveillance period were excluded from the study population. e surveillance period for an incident case of food-allergy This article provides continuing education (CE) and continuing medical education (CME) credit. Please see information at the end of the article. CE/CME
Page 24 anaphylaxis was 1 January 2007 through 31 December 2016. e surveillance popula tion included all individuals, deployed and non-deployed, who served in the active component of the Army, Navy, Air Force, or Marine Corps at any time during the surveillance period. All data used to determine incident food-allergy anaphylaxis were derived from records routinely maintained in the Defense Medical Surveillance System (DMSS). ese records document both ambulatory encounters and hospitalizations of active component members of the U.S. Armed Forces in xed military and civilian (if reimbursed through the Military Health System) treatment facilities. Individuals with an incident case of food-allergy anaphylaxis or an incident diagnosis of food allergy from 30 June 2008 through 30 September 2016 were consid ered candidates for an EAI prescription. An incident diagnosis of food allergy was dened by having a rst-ever inpatient, outpatient, or TMDS medical encoun ter with ICD-9 codes V15.01V15.05 and ICD-10 codes Z91.010Z91.013 or Z91.018 in any diagnostic position during the sur veillance period. Individuals were consid ered candidates for an EAI prescription ll for 18 months prior to and 3 months aer a diagnosis of food allergy or food-allergy anaphylaxis. Prescription information was obtained from the Pharmacy Data Transaction Ser vice, a central data repository that con tains medication records for all TRICARE TABLE 1. 10 1991 WA No 16 1983 MN 30 Not 11 1990 MN 14 2001 MN 42 15 2008 17 2001 18 2010 Not 12 1996 10 Not 13 1996 CA Not
Page 25 beneciaries, regardless of point of service (i.e., military, retail, and mail-order phar macies). Descriptive statistics were used to describe the number of EAI prescriptions dispensed to those identied as candidates for an EAI based on a prior diagnosis of food allergy or food-allergy anaphylaxis. RESULTS During 2007, the crude over all incidence of food-allergy anaphylaxis among active component service members was 39.1 cases per 100,000 p-yrs (Table 2) e crude annual incidence increased dur ing the surveillance period from 32.0 per 100,000 p-yrs in 2007 to 55.8 per 100,000 p-yrs in 2016 (Figure 1) e incidence of food-allergy anaphylaxis among females was almost three times that of males (85.4 and 31.1 cases per 100,000 p-yrs, respec tively) and this was consistent across much of the surveillance period (Table 2, Figure 2) Across race/ethnicity groups, the high est overall incidence of food-allergy ana phylaxis was found among non-Hispanic blacks (72.6 cases per 100,000 p-yrs), fol lowed by service members in the other/ unknown category (47.0 cases per 100,000 p-yrs). Non-Hispanic blacks had the high est annual incidence rates throughout the entire surveillance period (Figure 3) e lowest overall incidence was found among non-Hispanic whites (28.8 cases per 100,000 p-yrs) (Table 2) Across the age groups, the overall incidence of food-allergy anaphy laxis was lowest among those aged 20 years and highest among those aged 30 years (34.9 cases per 100,000 p-yrs and 43.1 cases per 100,000 p-yrs, respectively). Dur ing the surveillance period, annual rates increased in all age groups (data not shown) More than 10% of food-allergic indi viduals lled a prescription for an EAI within the 18 months prior to their food allergy diagnosis, and more than 28% of individuals with a diagnosis of food-allergy anaphylaxis lled a prescription for an EAI within the 18 months prior to being diag nosed with food-allergy anaphylaxis (Fig ure 4) ere were 26,085 incident cases of food allergy during the surveillance period; of these, 23.2% (6,054) lled a prescription for EAI within the 3 months following the diagnosis. ere were 4,475 incident cases of food-allergy anaphylaxis; of these, 58.4% (2,612) lled a prescription for EAI within the 3 months following the diagnosis. EDITORIAL COMMENT Few studies specically evaluate the incidence of food-allergy anaphylaxis, and comparison between studies is dicult given variable study design and popula tions. Still, comparison of incidence rates between military service members and the general U.S. population is informa tive. Given that food allergies and the risk for anaphylaxis are oen identied during childhood, and that anaphylaxis medically disqualies an individual from military service, the incidence of anaphylaxis in the military was expected to be lower than that in the general population. is expec tation was tempered somewhat by gener ous waiver approval rates among military applicants with a history of anaphylaxis, which ranged from 54% among Air Force applicants to 91% among Navy applicants between 2008 and 2013. 20 e current study found that the incidence of food-allergy anaphylaxis among active component ser vice members approximated that found in previous large, population-based studies performed in the U.S. 11 14 16 and was higher than that found in comparable studies per formed overseas. 15 17 18 Clearly, accession standards and the medical board process do not completely address the issue of ana phylaxis in the military. Military healthcare providers, including those providing care in operational environments, must be pre pared to manage at-risk and aected ser vice members. is is especially true given that the incidence of food-allergy anaphy laxis appears to be increasing. Epinephrine injection constitutes rstline treatment of anaphylaxis. U.S. stud ies of administrative claims data show that 46%% of patients being discharged from emergency departments following an episode of anaphylaxis lled a prescrip tion for EAI within 1 year. 5 21 Given that military service members undergo peri odic examinations that potentially identify EAI candidates, and the fact that there is no pre-authorization requirement or cost associated with lling a prescription for EAI, it was expected that active component service members would have a higher rate of EAI dispensing than the general popu lation. is expectation was bolstered by the ndings of a study of military bene ciaries (including dependents and active TABLE 2. 2007 2016 Sex 20 25 30 35 > 40
Page 26 ll rates among those who are prescribed an EAI. 23 Approximately 28% of service mem bers with food-allergy anaphylaxis lled prescriptions for an EAI within the 18 months prior to being diagnosed. is observation may reect recognition of the service members risk for anaphylaxis based on a previous, less severe food reac tion, or the existence of another allergy warranting an EAI prescription. More worrisome is the potential for this to reect a failure to identify at-risk individ uals and appropriately document the con dition in the members medical record as may be seen when avoidance of a medical board and potential separation from the military is desired. Current guidelines recommend that all patients experiencing food-allergy anaphylaxis be prescribed an EAI. Other patients for whom an EAI is indicated include patients with a history of a prior systemic allergic reaction; patients with food allergy and asthma; and patients with a known food allergy to peanut, tree nuts, sh, and crustacean shellsh (i.e., aller gens known to be associated with more fatal and near-fatal allergic reactions). 3 Given diculties associated with identifying food-allergic individuals who are at risk for anaphylaxis, as well as dif culties predicting the severity of future IgE-mediated reactions, guidelines also recommend that providers consider pre scribing an EAI to all patients with IgEmediated food reactions. 3 24 It is important to note that the current study did not dierentiate between foodallergic individuals who met the above cri teria from those who did not. As a result, it is dicult to interpret EAI ll rates among those diagnosed with food allergy. What is notable is that at least 23% of individuals with a documented history of food allergy were considered to be at risk for anaphy laxis and candidates for an EAI by their treating provider. Future eorts should ensure that med ical and emergency personnel are made aware of the notable number of individ uals who serve in the military who have experienced or at risk for food-allergy ana phylaxis. Healthcare professionals need to properly identify, document, and code for FIGURE 1. FIGURE 2. 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 component service members) in which 82% of individuals prescribed an EAI lled their prescriptions within 1 year. 22 e cur rent study found that only 58.4% lled their prescriptions for EAI within 3 months of incident anaphylaxis. It is unclear whether the 58.4% ll rate found in the current study is due to failure to prescribe, failure to ll, or the relatively short window used to evaluate prescription ll rates. Regardless of the reason, there is room for improve ment. Pharmacist-led interventions have been found to improve medication man agement and may play a role in improving
Page 27 anaphylaxis so that appropriate preven tion and treatment are made available. Although this study did not for mally address risk factors for anaphylaxis, it notes that the incidence of food-allergy anaphylaxis was higher among those FIGURE 3. FIGURE 4. 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 10. 7 28. 823. 258. 40 010. 020. 030. 0 40. 050. 060. 070. 0 Foo d a l l e r g y Foo d a lle r g y anaph y l a x i s % of cases with filled prescriptions % of cases with EAI prescriptions lled within 18 months prior to incident diagnosis % of cases with EAI prescriptions lled within 3 months on or after incident diagnosis aged 30 years, compared to other age groups; females compared to males; and non-Hispanic blacks, compared to other races/ethnicities. ese ndings are gen erally consistent with previous studies (Table 1) Other studies involving civilian populations have explored risk factors for severe anaphylaxis (e.g., asthma 12 13 25 and vitamin D deciency 26 ), biomarkers, 27 and cofactors that induce or exacerbate reac tions that might not otherwise occur (e.g., exercise, nonsteroidal anti-inamma tory drugs, and alcohol 1 ). Future studies aimed at identifying factors associated with severe, life-threatening anaphylaxis in the military could help stratify risk and further inform accession standards, tness for duty determinations, and prevention and treat ment eorts. is study has several limitations. Notably, not all cases of anaphylaxis come to medical attention and the true incidence of food-allergy anaphylaxis is likely under estimated here. In addition, this study relied on medically coded encounters that were not validated by chart review or a criteria-based approach to diagnosis; this may further contribute to underestima tion of the true incidence of food-allergy anaphylaxis. Of note, a study utilizing the National Electronic Injury Surveillance System found that 57% of patients present ing to an emergency department with a likely case of anaphylaxis did not receive a diagnosis of anaphylaxis. 9 Finally, it is not clear whether the increasing incidence of food-allergy anaphylaxis reported here reects an increase in the true incidence of anaphylaxis or increased awareness of the condition. With regard to food allergies, it is likely that some individuals with food allergies were missed due to the failure to report, diagnose, or document their condi tion. In addition, the ICD-9/ICD-10 codes used to identify individuals with food aller gies did not include nonspecic codes such as ICD-9: 693.1 (Dermatitis due to food taken internally), ICD-10: L27.2 (Der matitis due to ingested food), and ICD-9: 995.7 and ICD-10: T78.1* (Other adverse food reactions, not elsewhere classied); this further contributes to potential under estimation of the condition. With regard to EAI ll rates, signi cant information is lacking. Namely, pre scription rates were not available and thus could not be used as a comparison to ll rates. In addition, EAI prescriptions were not linked to a specic diagnosis or event and prescription lls could potentially be
Page 28 related to another diagnosis such as an allergy to bee stings. Finally, the reasons for ll failures, including the possibility that an EAI was not indicated or was already avail able to a patient, were not explored. e incidence of food-allergy ana phylaxis among active component service members approximates that found in the general population and increased steadily over the study period. Medical accession standards and the medical board process do not completely address the issue of food-allergy anaphylaxis in the military. Properly identifying and documenting atrisk individuals, and ensuring availability of EAI have the potential to mitigate the risk of anaphylaxis. Further identifying risk factors for severe anaphylaxis, biomarkers, and cofactors could inform accession and retention standards and prevent life-threat ening reactions. REFERENCES Ann Al J Allergy Clin J Allergy J Al Clin Exp Al Ann Allergy Medicine BMC Health Serv N Engl J Curr Opin Allergy
Page 29 CE/CME is activity oers continuing education (CE) and continuing medical education (CME) to qualied professionals, as well as a cer ticate of participation to those desiring documentation. For more information, go to www.health.mil/msmrce Key points e crude annual incidence rates of food-allergy anaphylaxis among active component service members increased over the course of the surveillance period; the rates among females were almost three times those of males, and this pattern was consistent over much of the surveillance period. Compared to their respective counterparts, the overall incidence of food-allergy anaphylaxis was highest among females, those aged 30 years, and non-Hispanic black service members. Of the total incident anaphylaxis cases during the surveillance period, 29% and 58% had lled a prescription for an epinephrine autoinjector within 18 months before or 3 months aer the incident diagnosis, respectively. Learning objectives 1. e reader will interpret data related to the incidence of anaphylaxis among active component service members. 2. e reader will explain how the incidence of food-allergy anaphylaxis among active component service members compares to that in the general population, and how the incidence has changed over time. 3. e reader will describe ways to prevent food-allergy anaphylaxis. Disclosures: MSMR sta authors, DHA J7, AnityCE/PESG, as well as the planners and reviewers of this activity have no nancial or non nancial interest to disclose.
Page 30 n 2013, the MSMR summarized cardio vascular-related deaths in U.S. military members overall. 1 is snapshot pro vides a summary of cardiovascular-related deaths occurring in service members while deployed. e surveillance popula tion included all individuals who served on active duty at any point between 1 October 2001 and 31 December 2012 as a member of the active, reserve, or guard component of the U.S. Army, Navy, Air Force, or Marine Corps. Cardiovascular-related deaths in active duty service members were ascer tained as previously described. 1 Deaths were included in this analysis if the date of death occurred during the surveillance period and between the start and end dates of a deployment identied from the Con tingency Tracking System from the Defense Manpower Data System. For each death identied, the presence of a cardiovascular risk factor was dened by the documenta tion of specic ICD-9 codes in any diagnos tic position of a hospitalization discharge record or an outpatient medical encounter prior to the start of the deployment during which the death occurred (Table 1) Between October 2001 and December 2012, there were a total of 62 deaths attrib uted to cardiovascular causes occurring dur ing deployment. Of these deaths, more than half occurred in reserve or guard members (n=35; 56.5%). e strongest demographic correlates of a cardiovascular-related death was age with the greatest number and per centage of deaths occurring in service members aged 45 years or older. e most frequently diagnosed cardiovascular risk factor was hypertension and approximately one in seven service members had more than one cardiovascular risk factor diag nosed prior to deployment (Table 2) e relatively few numbers of cardio vascular-related deaths occurring during deployment is likely attributable to multi ple factors. Military members who deploy are generally younger and healthier than their civilian counterparts and undergo comprehensive health assessment prior to deployment to identify potential deploy ment limiting health conditions. However, not all deploying service members undergo specic cardiovascular screening even in the presence of cardiovascular risk factors. 2 Signicantly, the deployment of forwarddeployed cardiologists with access to rstline cardiovascular diagnostic tools (e.g., echocardiography, stress testing, ambula tory electrocardiography) allows for expert evaluation of cardiac complaints in theater. is capability enables expert risk strati cation that provides an eective tool in discriminating life-threatening diagnoses from more benign conditions, and likely enhances the appropriate disposition of cardiac patients. 2-4 REFERENCES MSMR US Army Med Cardiology Mil Med Surveillance Snapshot: Cardiovascular-related Deaths During Deployment, U.S. Armed Forces, October 2001December 2012 Leslie L. Clark, PhD, MS TABLE 1. ICD-9 codes TABLE 2. 2012 ICD-9 codes % 62 Sex 60 2 0 20 6 25 7 30 5 35 9 40 14 > 45 21 34 20 2 6 10 16 37 60 6 10 8 13 1 2 27 44 35 56 49 79 6 10 5 8 2 3 13 21 3 5 0 0 15 24 18 29 4 6 9 15 15 24 11 18 5 8 1 2 1 2 9 15
Page 31 MSMR Welcomes Manuscript Submissions, Article Ideas Medical Surveillance Monthly Report (MSMR) welcomes manuscript submissions on evidence-based estimates of the inci dence, distribution, impact, or trends of illness and injuries among members of the U.S. Armed Forces and other beneciaries of the Military Health System. Information about manuscript submissions is available at www.health.mil/MSMRInstructions e MSMR also invites readers to submit topics for consideration as the basis for future MSMR reports. e MSMR edito rial sta will review suggested topics for feasibility and compatibility with the journals health surveillance goals. As is the case with most of the analyses and reports produced by Armed Forces Health Surveillance Branch (AFHSB) sta, studies that would take advantage of the healthcare and personnel data contained in the Defense Medical Surveillance System (DMSS) would be the most plausible types. For each promising topic, AFHSB sta members will design and carry out the data analysis, interpret the results, and write a manuscript to report on the study. is invitation represents a willingness to consider good ideas from anyone who shares the MSMR s objective to publish evidence-based reports on subjects relevant to the health, safety, and wellbeing of military service members and other beneciaries of the Military Health System. Please email your manuscript submissions, article ideas, and suggestions to the MSMR Editor at dha.ncr.health-surv.mbx. email@example.com
MEDICAL SURVEILLANCE MONTHLY REPORT MSMR in continuous publication since 1995, is produced by the Armed Forces Health Surveillance Branch (AFHSB). e MSMR provides evidence-based estimates of the incidence, distribution, impact, and trends of illness and injuries among U.S. military members and associated populations. Most reports in the MSMR are based on summaries of medical administrative data that are routinely provided to the AFHSB and integrated into the Defense Medical Surveillance System for health surveillance purposes. Archive: Past issues of the MSMR are available as downloadable PDF les at www. health.mil/MSMRArchives Online Subscriptions: Submit subscription requests at www.health.mil/MSMRSubscribe Editorial Inquiries : Call (301) 319-3240 or send email to: dha.ncr.health-surv.mbx. firstname.lastname@example.org Instructions for Authors: Information about article submissions is provided at www. health.mil/MSMRInstructions All material in the MSMR is in the public domain and may be used and reprinted without permission. Citation formats are available at www.health.mil/MSMR Opinions and assertions expressed in the MSMR should not be construed as reecting ocial views, policies, or positions of the Department of Defense or the United States Government. Follow us: www.facebook.com/AFHSBPAGE http://twitter.com/AFHSBPAGE ISSN 2158-0111 (print) ISSN 2152-8217 (online) Chief, Armed Forces Health Surveillance Branch COL Douglas A. Badzik, MD, MPH (USA) Editor Francis L. ODonnell, MD, MPH Contributing Editors Leslie L. Clark, PhD, MS Shauna Stahlman, PhD, MPH Writer/Editor Valerie F. Williams, MA, MS Managing/Production Editor Elizabeth J. Lohr, MA Data Analysis Michael Fan, PhD Gi-Taik Oh, MS Layout/Design Darrell Olson Editorial Oversight Col Dana J. Dane, DVM, MPH (USAF) CDR Shawn S. Clausen, MD, MPH (USN) Mark V. Rubertone, MD, MPH