The Military Injury Severity Score (mISS): A better predictor of combat mortality than Injury Severity Score (ISS).

BACKGROUND: The Military Injury Severity Score (mISS) was developed to better predict mortality in complex combat injuries but has yet to be validated. METHODS: US combat trauma data from Afghanistan and Iraq from January 1, 2003, to December 31, 2014, from the US Department of Defense Trauma Registry (DoDTR) were analyzed. Military ISS, a variation of the ISS, was calculated and compared with standard ISS scores.Receiver operating characteristic curve, area under the curve, and Hosmer-Lemeshow statistics were used to discriminate and calibrate between mISS and ISS. Wilcoxon-Mann-Whitney, t test and χ tests were used, and sensitivity and specificity calculated. Logistic regression was used to calculate the likelihood of mortality associated with levels of mISS and ISS overall. RESULTS: Thirty thousand three hundred sixty-four patients were analyzed. Most were male (96.8%). Median age was 24 years (interquartile range [IQR], 21-29 years). Battle injuries comprised 65.3%. Penetrating (39.5%) and blunt (54.2%) injury types and explosion (51%) and gunshot wound (15%) mechanisms predominated. Overall mortality was 6.0%.Median mISS and ISS were similar in survivors (5 [IQR, 2-10] vs. 5 [IQR, 2-10]) but different in nonsurvivors, 30 (IQR, 16-75) versus 24 (IQR, 9-23), respectively (p < 0.0001). Military ISS and ISS were discordant in 17.6% (n = 5,352), accounting for 56.2% (n = 1,016) of deaths. Among cases with discordant severity scores, the median difference between mISS and ISS was 9 (IQR, 7-16); range, 1 to 59. Military ISS and ISS shared 78% variability (R = 0.78).Area under the curve was higher in mISS than in ISS overall (0.82 vs. 0.79), for battle injury (0.79 vs. 0.76), non-battle injury (0.87 vs. 0.86), penetrating (0.81 vs. 0.77), blunt (0.77 vs. 0.75), explosion (0.81 vs. 0.78), and gunshot (0.79 vs. 0.73), all p < 0.0001. Higher mISS and ISS were associated with higher mortality. Compared with ISS, mISS had higher sensitivity (81.2 vs. 63.9) and slightly lower specificity (80.2 vs. 85.7). CONCLUSION: Military ISS predicts combat mortality better than does ISS. LEVEL OF EVIDENCE: Prognostic and epidemiologic study, level III.

Use of recombinant factor VIIa in US military casualties for a five-year period.

BACKGROUND: Two prospective randomized trauma trials have shown recombinant factor VIIa (rFVIIa) to be safe and to decrease transfusion requirements. rFVIIa is presently used in 22% of massively transfused civilian trauma patients. The US Military has used rFVIIa in combat trauma patients for five years, and two small studies of massively transfused patients described an association with improved outcomes. This study was undertaken to assess how deployed physicians are using rFVIIa and its impact on casualty outcomes. METHODS: US combat casualties (n = 2,050) receiving any blood transfusion from 2003 to 2009 were reviewed to compare patients receiving rFVIIa (n = 506) with those who did not (n = 1,544). Propensity-score matching (primary analysis) and multivariable logistic regression were used to compare outcomes. Differences were determined at p < 0.05. RESULTS: Twenty-five percent of patients received rFVIIa. Significant differences were noted between groups in indices of injury severity (Injury Severity Score, Abbreviated Injury Scale score, and Glasgow Coma Scale score), admission physiology (systolic blood pressure, diastolic blood pressure, heart rate, temperature, base deficit, hemoglobin, and international normalization ratio), and use of blood products, indicating that patients treated with rFVIIa were more severely injured, in shock, and coagulopathic. For propensity-score matching, factors associated with death were used: Injury Severity Score, Glasgow Coma Scale score, heart rate, systolic blood pressure, diastolic blood pressure, Hgb, and total packed red blood cell. A total of 266 patients per group were matched; 52% of the rFVIIa group. After pairing, there were no significant differences in any of the demographics, including incidence of massive transfusion (53% vs. 51%). There was no difference in the rate of complications (21% vs. 21%) or mortality (14% vs. 20%) for patients not treated or receiving rFVIIa, respectively. CONCLUSION: In military casualties, rFVIIa is used in the most severely injured patients based on physician selection rather than on guideline criteria. Use of rFVIIa is not associated with an improvement in survival or an increase in complications. The undetected bias of physician selection of patients for treatment with rFVIIa, likely, has an impact on case matching to achieve equivalence similar to that of randomized control studies. This inability to match populations, thus, prevents definitive interpretation of this study and others studies of similar design. This problem emphasizes the need to develop entry criteria to identify patients who could potentially benefit from use of rFVIIa and the need to subsequently perform efficacy studies.

Improved characterization of combat injury.

BACKGROUND: Combat injury patterns differ from civilian trauma in that the former are largely explosion-related, comprising multiple mechanistic and fragment injuries and high-kinetic-energy bullets. Further, unlike civilians, U.S. armed forces combatants are usually heavily protected with helmets and Kevlar body armor with ceramic plate inserts. Searchable databases providing actionable, statistically valid knowledge of body surface entry wounds and resulting organ injury severity are essential to understanding combat trauma. METHODS: Two tools were developed to address these unique aspects of combat injury: (1) the Surface Wound Mapping (SWM) database and Surface Wound Analysis Tool (SWAT) software that were developed to generate 3D density maps of point-of-surface wound entry and resultant anatomic injury severity; and (2) the Abbreviated Injury Scale (AIS) 2005-Military that was developed by a panel of military trauma surgeons to account for multiple injury etiology from explosions and other high-kinetic- energy weapons. Combined data from the Joint Theater Trauma Registry, Navy/Marine Combat Trauma Registry, and the Armed Forces Medical Examiner System Mortality Trauma Registry were coded in AIS 2005-Military, entered into the SWM database, and analyzed for entrance site and wounding path. RESULTS: When data on 1,151 patients, who had a total of 3,500 surface wounds and 12,889 injuries, were entered into SWM, surface wounds averaged 3.0 per casualty and injuries averaged 11.2 per casualty. Of the 3,500 surface wounds, 2,496 (71%) were entrance wounds with 6,631 (51%) associated internal injuries, with 2.2 entrance wounds and 5.8 associated injuries per casualty (some details cannot be given because of operational security). Crude deaths rates were calculated using Maximum AIS-Military. CONCLUSION: These new tools have been successfully implemented to describe combat injury, mortality, and distribution of wounds and associated injuries. AIS 2005-Military is a more precise assignment of severity to military injuries. SWM has brought data from all three combat registries together into one analyzable database. SWM and SWAT allow visualization of wounds and associated injuries by region on a 3D model of the body.

Prediction of mortality and of the need for massive transfusion in casualties arriving at combat support hospitals in Iraq.

BACKGROUND: Our purpose was to compare the Revised Trauma Score (RTS) with the new Field Triage Score (FTS) for prediction of mortality (MORT) and of need for massive transfusion (MASS, >or=10 units of packed cells or whole blood) in casualties arriving at combat support hospitals in Iraq. METHODS: Six hundred ninety-two cases were reviewed; 536 had complete data and were included. Total Glasgow Coma Scale score (GCS total) not GCS motor was used. Thus, a modification (FTS 07) of the FTS was calculated, using GCS <8 and systolic arterial pressure (SAP) <100 as cut-points, with range 0 to 2. Variables different by univariate analysis underwent logistic regression analysis (LRA) and areas under the curve for receiver operating characteristic curves (AUC) were calculated. By LRA, probability of an outcome is given by p = e(k)/(1 + e(k)). RESULTS: By LRA for MORT, k = 0.616 - 0.438 x RTS; AUC = 0.708. When used instead of RTS, FTS 07 provided k = -0.716 - 1.009 x FTS 07; AUC = 0.687 (NS). For MASS, k = 0.638 - 0.115 x RTS - 0.011 x DAP + 0.358 x SI, where DAP is diastolic arterial pressure and SI is shock index, i.e., heart rate or SAP; AUC = 0.638. When used instead of RTS, FTS 07 provided k = -0.740 - 0.376 x FTS 07- 0.011 x DAP; AUC = 0.618 (NS). CONCLUSIONS: RTS emerged as the best predictor of MORT, with FTS 07 a close surrogate. This indicates the effect of impaired mentation on MORT in these data. For prediction of MASS, RTS as well as the heart rate and blood pressure predominated. The advantage of FTS 07 (or original FTS) over RTS is the former's ease of computation.