injury. Variables incorporated into multivariable models included age, sex, Tile/Orthopedic Trauma Association grade, admission lactate, heart rate (HR), and systolic blood pressure (SBP). Addition of hematoma volume resulted in a significant improvement in model performance, with AUC for the composite outcome (AE, PP, or MT) increasing from 0.74 to 0.83 (p less then 0.001). Adjusted unit odds more than doubled for every additional 200 mL of hematoma volume. Increase in model AUC for mortality with incorporation of hematoma volume was not statistically significant (0.85 vs. 0.90, p = 0.12). CONCLUSION Hematoma volumes measured using a rapid automated deep learning algorithm improved prediction of need for AE, PP, or MT. Simultaneous automated measurement of multiple sources of bleeding at CT could augment outcome prediction in trauma patients. LEVEL OF EVIDENCE Diagnostic, level IV.BACKGROUND Neoplastic processes are among the known etiologies for acute appendicitis. While conservative treatment with antibiotics alone has been proposed as a treatment for uncomplicated appendicitis, the presence of tumors should be excluded when offering patients this option. The aim of this study was to assess the accuracy of computed tomography (CT) in detecting appendiceal tumors. METHOD Consecutive patients operated on for acute appendicitis between January 2007 and October 3, 2018, in our university hospital were included. Whenever appendiceal tumor was histopathologically confirmed, CT interpretations and surgical reports were carefully reviewed. All CT scans were reanalyzed by consultant body radiologists. Discrepancies between the preliminary and final radiological interpretations were noted. RESULTS A total of 5,224 patients underwent appendectomy, of whom 4,766 had histopathologically confirmed acute appendicitis. Eighty-four patients (median, 61 (13-89) years; 54% female) were diagnosed with appendiceal tumor. Fifty-two patients (62%) had uncomplicated appendicitis. Although incidence of tumors was associated with older age, tumors were found in all ages. selleck The share of tumors increased from 1.7% to 3.0%/year during the study. The most common tumors were neuroendocrine tumors (n = 33), low-grade appendiceal mucinous neoplasms (n = 14), and adenocarcinomas (n = 11). Sixty-one patients (73%) underwent preoperative CT. Computed tomography interpretation during on-call hours suspected tumor in only one case (3.4%) with invasive tumor, and in five cases (16%) with noninvasive tumor. CONCLUSION Appendiceal tumors are possible findings in appendix specimens, and most patients had uncomplicated acute appendicitis. In light of findings we conclude that CT cannot be used to exclude neoplastic etiology underlying acute appendicitis. LEVEL OF EVIDENCE Diagnostic, level IV.BACKGROUND As nonoperative management (NOM) of blunt splenic injury (BSI) increases, understanding risks, especially infectious complications, becomes more important. There are no national studies on BSI outcomes that track readmissions across hospitals. Prior studies demonstrate that infection is a major cause of readmission after trauma and that a significant proportion is readmitted to different hospitals. The purpose of this study was to compare nationwide outcomes of different treatment modalities for BSI including readmissions to different hospitals. METHODS The Nationwide Readmissions Database for 2010 to 2014 was queried for patients 18 years to 64 years old admitted nonelectively with a primary diagnosis of BSI. Organ space infection; a composite infectious incidence of surgical site infection (SSI), urinary tract infection, and pneumonia; and sepsis were identified in three groups NOM, splenic artery embolization (SAE), and operative management (OM). Rates of infection were quantified during index aeons should be aware of these risks and incorporate such knowledge into their practice accordingly. LEVEL OF EVIDENCE Epidemiological study, level IV.BACKGROUND The timing of coverage of an open wound is based on heavily on clinical gestalt. DoD’s Surgical Critical Care Initiative created a clinical decision support tool that predicts wound closure success using clinical and biomarker data. The military uses a regimented protocol consisting of serial washouts and debridements. While decisions around wound closure in civilian centers are subject to the same clinical parameters, preclosure wound management is, generally, much more variable. We hypothesized that the variability in management would affect local biomarker expression within these patients. METHODS We compared data from 116 wounds in 73 military patients (MP) to similar data from 88 wounds in 78 civilian patients (CP). We used Wilcoxon rank-sum tests to assess concentrations of 32 individual biomarkers taken from wound effluent. Along with differences in the debridement frequency, we focused on these local biomarkers in MP and CP at both the first washout and the washout performed just prior to attempted closure. RESULTS On average, CP waited longer from the time of injury to closure (21.9 days, vs. 11.6 days, p less then 0.0001) but had a similar number of washouts (3.86 vs. 3.44, p = 0.52). When comparing the wound effluent between the two populations, they had marked biochemical differences both when comparing the results at the first washout and at the time of closure. However, in a subset of civilian patients whose average number of days between washouts was never more than 72 hours, these differences ceased to be significant for most variables. CONCLUSION There were significant differences in the baseline biochemical makeup of wounds in the CP and MP. These differences could be eliminated if both were treated under similar wound care paradigms. Variations in therapy affect not only outcomes but also the actual biochemical makeup of wounds. LEVEL OF EVIDENCE Therapeutic, level IV.BACKGROUND On the morning of June 12, 2016, an armed assailant entered the Pulse Nightclub in Orlando, Florida, and initiated an assault that killed 49 people and injured 53. The regional Level I trauma center and two community hospitals responded to this mass casualty incident. A detailed analysis was performed to guide hospitals who strive to prepare for future similar events. METHODS A retrospective review of all victim charts and/or autopsy reports was performed to identify victim presentation patterns, injuries sustained, and surgical resources required. Patients were stratified into three groups survivors who received care at the regional Level I trauma center, survivors who received care at one of two local community hospitals, and decedents. RESULTS Of the 102 victims, 40 died at the scene and 9 died upon arrival to the Level I trauma center. The remaining 53 victims received definitive medical care and survived. Twenty-nine victims were admitted to the trauma center and five victims to a community hospital.