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Injury Severity Score (ISS) as a prospective predictive variable is limited, as it is scored post-discharge by registrars. We followed a phase 1 pilot investigation of the feasibility of prospective ISS estimation (eISS) by trauma surgeons within 1 day of admission with an investigation of the impact of a simple educational aid on the accuracy of these estimations. Eleven surgeons evaluated 178 patients in phase 2. With the educational aid, ISS concordance improved from 74.6% to 85.1% for non-severe (abstracted ISS, aISS <16) injuries and from 78.8% to 83.1% for severe (aISS ≥16) injuries; weighted k improved from 0.53 to 0.72. Abbreviated Injury Scale (AIS) concordance similarly improved in five of seven body regions. The ability to prospectively document ISS has important clinical and research implications. There remains opportunity to refine educational aides and harness the EHR to further improve prediction accuracy and facilitate adoption in standard clinical workflows., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Background: Septic patients who develop acute respiratory failure (ARF) requiring mechanical ventilation represent a heterogenous subgroup of critically ill patients with widely variable clinical characteristics. Identifying distinct phenotypes of these patients may reveal insights about the broader heterogeneity in the clinical course of sepsis, considering multi-organ dynamics. We aimed to derive novel phenotypes of sepsis-induced ARF using observational clinical data and investigate the generalizability of the derived phenotypes., Methods: We performed a multi-center retrospective study of ICU patients with sepsis who required mechanical ventilation for ≥ 24 h. Data from two different high-volume academic hospital centers were used, where all phenotypes were derived in MICU of Hospital-I (N = 3225). The derived phenotypes were validated in MICU of Hospital-II (N = 848), SICU of Hospital-I (N = 1112), and SICU of Hospital-II (N = 465). Clinical data from 24 h preceding intubation was used to derive distinct phenotypes using an explainable machine learning-based clustering model interpreted by clinical experts., Results: Four distinct ARF phenotypes were identified: A (severe multi-organ dysfunction (MOD) with a high likelihood of kidney injury and heart failure), B (severe hypoxemic respiratory failure [median P/F = 123]), C (mild hypoxia [median P/F = 240]), and D (severe MOD with a high likelihood of hepatic injury, coagulopathy, and lactic acidosis). Patients in each phenotype showed differences in clinical course and mortality rates despite similarities in demographics and admission co-morbidities. The phenotypes were reproduced in external validation utilizing the MICU of Hospital-II and SICUs from Hospital-I and -II. Kaplan-Meier analysis showed significant difference in 28-day mortality across the phenotypes (p < 0.01) and consistent across MICU and SICU of both Hospital-I and -II. The phenotypes demonstrated differences in treatment effects associated with high positive end-expiratory pressure (PEEP) strategy., Conclusion: The phenotypes demonstrated unique patterns of organ injury and differences in clinical outcomes, which may help inform future research and clinical trial design for tailored management strategies., (© 2024. The Author(s).)

Injury Severity Score (ISS) has limited utility as a prospective predictor of trauma outcomes as it is currently scored by abstractors post-discharge. This study aimed to determine accuracy of ISS estimation at time of admission. Attending trauma surgeons assessed the Abbreviated Injury Scale of each body region for patients admitted during their call, from which estimated ISS (eISS) was calculated. The eISS was considered concordant to abstracted ISS (aISS) if both were in the same category: mild (<9), moderate (9-15), severe (16-25), or critical (>25). Ten surgeons completed 132 surveys. Overall ISS concordance was 52.2%; 87.5%, 30.8%, 34.8%, and 61.7% for patients with mild, moderate, severe, and critical aISS, respectively; unweighted k = .36, weighted k = .69. This preliminarily supports attending trauma surgeons' ability to predict severity of injury in real time, which has important clinical and research implications., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Background: The Georgia Quality Improvement Program (GQIP) surgical collaborative participating hospitals have shown consistently poor performance in the post-operative sepsis category of National Surgical Quality Improvement Program data as compared with national benchmarks. We aimed to compare crude versus risk-adjusted post-operative sepsis rankings to determine high and low performers amongst GQIP hospitals. Patients and Methods: The cohort included intra-abdominal general surgery patients across 10 collaborative hospitals from 2015 to 2020. The American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) sepsis definition was used among all hospitals for case abstraction and NSQIP data were utilized to train and validate a multivariable risk-adjustment model with post-operative sepsis as the outcome. This model was used to rank GQIP hospitals by risk-adjusted post-operative sepsis rates. Rankings between crude and risk-adjusted post-operative sepsis rankings were compared ordinally and for changes in tertile. Results: The study included 20,314 patients with 595 cases of post-operative sepsis. Crude 30-day post-operative sepsis risk among hospitals ranged from 0.81 to 5.11. When applying the risk-adjustment model which included: age, American Society of Anesthesiology class, case complexity, pre-operative pneumonia/urinary tract infection/surgical site infection, admission status, and wound class, nine of 10 hospitals were re-ranked and four hospitals changed performance tertiles. Conclusions: Inter-collaborative risk-adjusted post-operative sepsis rankings are important to present. These metrics benchmark collaborating hospitals, which facilitates best practice exchange from high to low performers.

Introduction: Accurate identification of venous thromboembolism (VTE) is critical to develop replicable epidemiological studies and rigorous predictions models. Traditionally, VTE studies have relied on international classification of diseases (ICD) codes which are inaccurate - leading to misclassification bias. Here, we developed ClotCatcher, a novel deep learning model that uses natural language processing to detect VTE from radiology reports., Methods: Radiology reports to detect VTE were obtained from patients admitted to Emory University Hospital (EUH) and Grady Memorial Hospital (GMH). Data augmentation was performed using the Google PEGASUS paraphraser. This data was then used to fine-tune ClotCatcher, a novel deep learning model. ClotCatcher was validated on both the EUH dataset alone and GMH dataset alone., Results: The dataset contained 1358 studies from EUH and 915 studies from GMH (n = 2273). The dataset contained 1506 ultrasound studies with 528 (35.1%) studies positive for VTE, and 767 CT studies with 91 (11.9%) positive for VTE. When validated on the EUH dataset, ClotCatcher performed best (AUC = 0.980) when trained on both EUH and GMH dataset without paraphrasing. When validated on the GMH dataset, ClotCatcher performed best (AUC = 0.995) when trained on both EUH and GMH dataset with paraphrasing., Conclusion: ClotCatcher, a novel deep learning model with data augmentation rapidly and accurately adjudicated the presence of VTE from radiology reports. Applying ClotCatcher to large databases would allow for rapid and accurate adjudication of incident VTE. This would reduce misclassification bias and form the foundation for future studies to estimate individual risk for patient to develop incident VTE., (© 2023. The Author(s).)

Background: Thoracic injury can cause impairment of lung function leading to respiratory complications such as pneumonia (PNA). There is increasing evidence that central memory T cells of the adaptive immune system play a key role in pulmonary immunity. We sought to explore whether assessment of cell phenotypes using flow cytometry (FCM) could be used to identify pulmonary infection after thoracic trauma., Methods: We prospectively studied trauma patients with thoracic injuries who survived >48 hours at a Level 1 trauma center from 2014 to 2020. Clinical and FCM data from serum samples collected within 24 hours of admission were considered as potential variables. Random forest and logistic regression models were developed to estimate the risk of hospital-acquired and ventilator-associated PNA. Variables were selected using backwards elimination, and models were internally validated with leave-one-out., Results: Seventy patients with thoracic injuries were included (median age, 35 years [interquartile range (IQR), 25.25-51 years]; 62.9% [44 of 70] male, 61.4% [42 of 70] blunt trauma). The most common injuries included rib fractures (52 of 70 [74.3%]) and pulmonary contusions (26 of 70 [37%]). The incidence of PNA was 14 of 70 (20%). Median Injury Severity Score was similar for patients with and without PNA (30.5 [IQR, 22.6-39.3] vs. 26.5 [IQR, 21.6-33.3]). The final random forest model selected three variables (Acute Physiology and Chronic Health Evaluation score, highest pulse rate in first 24 hours, and frequency of CD4 + central memory cells) that identified PNA with an area under the curve of 0.93, sensitivity of 0.91, and specificity of 0.88. A logistic regression with the same features had an area under the curve of 0.86, sensitivity of 0.76, and specificity of 0.85., Conclusion: Clinical and FCM data have diagnostic utility in the early identification of patients at risk of nosocomial PNA following thoracic injury. Signs of physiologic stress and lower frequency of central memory cells appear to be associated with higher rates of PNA after thoracic trauma., Level of Evidence: Diagnostic Test/Criteria; Level IV., (Copyright © 2023 Written work prepared by employees of the Federal Government as part of their official duties is, under the U.S. Copyright Act, a "œwork of the United States Government"œ for which copyright protection under Title 17 of the United States Code is not available. As such, copyright does not extend to the contributions of employees of the Federal Government.)

Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Background: An emerging body of literature supports the role of individualized prognostic tools to guide the management of patients after trauma. The aim of this study was to develop advanced modeling tools from multidimensional data sources, including immunological analytes and clinical and administrative data, to predict outcomes in trauma patients., Methods: This was a prospective study of trauma patients at Level 1 centers from 2015 to 2019. Clinical, flow cytometry, and serum cytokine data were collected within 48 hours of admission. Sparse logistic regression models were developed, jointly selecting predictors and estimating the risk of ventilator-associated pneumonia, acute kidney injury, complicated disposition (death, rehabilitation, or nursing facility), and return to the operating room. Model parameters (regularization controlling model sparsity) and performance estimation were obtained via nested leave-one-out cross-validation., Results: A total of 179 patients were included. The incidences of ventilator-associated pneumonia, acute kidney injury, complicated disposition, and return to the operating room were 17.7%, 28.8%, 22.5%, and 12.3%, respectively. Regarding extensive resource use, 30.7% of patients had prolonged intensive care unit stay, 73.2% had prolonged length of stay, and 23.5% had need for prolonged ventilatory support. The models were developed and cross-validated for ventilator-associated pneumonia, acute kidney injury, complicated dispositions, and return to the operating room, yielding predictive areas under the curve from 0.70 to 0.91. Each model derived its optimal predictive value by combining clinical, administrative, and immunological analyte data., Conclusion: Clinical, immunological, and administrative data can be combined to predict post-traumatic outcomes and resource use. Multidimensional machine learning modeling can identify trauma patients with complicated clinical trajectories and high resource needs., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Introduction: The pathophysiology of the inflammatory response after major trauma is complex, and the magnitude correlates with severity of tissue injury and outcomes. Study of infection-mediated immune pathways has demonstrated that cellular microRNAs may modulate the inflammatory response. The authors hypothesize that the expression of microRNAs would correlate to complicated recoveries in polytrauma patients (PtPs)., Methods: Polytrauma patients enrolled in the prospective observational Tissue and Data Acquisition Protocol with Injury Severity Score of >15 were selected for this study. Polytrauma patients were divided into complicated recoveries and uncomplicated recovery groups. Polytrauma patients' blood samples were obtained at the time of admission (T0). Established biomarkers of systemic inflammation, including cytokines and chemokines, were measured using multiplexed Luminex-based methods, and novel microRNAs were measured in plasma samples using multiplex RNA hybridization., Results: Polytrauma patients (n = 180) had high Injury Severity Score (26 [20-34]) and complicated recovery rate of 33%. MicroRNAs were lower in PtPs at T0 compared with healthy controls, and bivariate analysis demonstrated that variations of microRNAs correlated with age, race, comorbidities, venous thromboembolism, pulmonary complications, complicated recovery, and mortality. Positive correlations were noted between microRNAs and interleukin 10, vascular endothelial growth factor, Acute Physiology and Chronic Health Evaluation, and Sequential Organ Failure Assessment scores. Multivariable Lasso regression analysis of predictors of complicated recovery based on microRNAs, cytokines, and chemokines revealed that miR-21-3p and monocyte chemoattractant protein-1 were predictive of complicated recovery with an area under the curve of 0.78., Conclusion: Systemic microRNAs were associated with poor outcomes in PtPs, and results are consistent with previously described trends in critically ill patients. These early biomarkers of inflammation might provide predictive utility in early complicated recovery diagnosis and prognosis. Because of their potential to regulate immune responses, microRNAs may provide therapeutic targets for immunomodulation., Level of Evidence: Diagnostic Tests/Criteria; Level II., (Copyright © 2022 Written work prepared by employees of the Federal Government as part of their official duties is, under the U.S. Copyright Act, a “work of the United States Government” for which copyright protection under Title 17 of the United States Code is not available. As such, copyright does not extend to the contributions of employees of the Federal Government.)

In health care, second victims are traumatized clinicians involved in unanticipated or untoward patient events. Programs that address second victim syndrome are sparse and its diagnosis often goes unrecognized. Consistently, literature has identified gaps in support resources, leading to compromised patient care and provider health. This project evaluates the need for second victim resources in trauma care providers at a tertiary public level 1 trauma hospital by electronically implementing a validated second victim survey over 5 weeks. Our results illustrate that second victim syndrome is prevalent among 57.1% of trauma care providers, of which 22.9% agree that second victim syndrome results in some form of undesirable work intentions.

Objectives: To evaluate early activation of latent viruses in polytrauma patients and consider prognostic value of viral micro-RNAs in these patients., Design: This was a subset analysis from a prospectively collected multicenter trauma database. Blood samples were obtained upon admission to the trauma bay (T0), and trauma metrics and recovery data were collected., Setting: Two civilian Level 1 Trauma Centers and one Military Treatment Facility., Patients: Adult polytrauma patients with Injury Severity Scores greater than or equal to 16 and available T0 plasma samples were included in this study. Patients with ICU admission greater than 14 days, mechanical ventilation greater than 7 days, or mortality within 28 days were considered to have a complicated recovery., Interventions: None., Measurements and Main Results: Polytrauma patients (n = 180) were identified, and complicated recovery was noted in 33%. Plasma samples from T0 underwent reverse transcriptase-quantitative polymerase chain reaction analysis for Kaposi's sarcoma-associated herpesvirus micro-RNAs (miR-K12&#95;10b and miRK-12-12) and Epstein-Barr virus-associated micro-RNA (miR-BHRF-1), as well as Luminex multiplex array analysis for established mediators of inflammation. Ninety-eight percent of polytrauma patients were found to have detectable Kaposi's sarcoma-associated herpesvirus and Epstein-Barr virus micro-RNAs at T0, whereas healthy controls demonstrated 0% and 100% detection rate for Kaposi's sarcoma-associated herpesvirus and Epstein-Barr virus, respectively. Univariate analysis revealed associations between viral micro-RNAs and polytrauma patients' age, race, and postinjury complications. Multivariate least absolute shrinkage and selection operator analysis of clinical variables and systemic biomarkers at T0 revealed that interleukin-10 was the strongest predictor of all viral micro-RNAs. Multivariate least absolute shrinkage and selection operator analysis of systemic biomarkers as predictors of complicated recovery at T0 demonstrated that miR-BHRF-1, miR-K12-12, monocyte chemoattractant protein-1, and hepatocyte growth factor were independent predictors of complicated recovery with a model complicated recovery prediction area under the curve of 0.81., Conclusions: Viral micro-RNAs were detected within hours of injury and correlated with poor outcomes in polytrauma patients. Our findings suggest that transcription of viral micro-RNAs occurs early in the response to trauma and may be associated with the biological processes involved in polytrauma-induced complicated recovery., Competing Interests: Dr. Schobel’s institution received funding from the Department of Defense Health Program (DOD DHP); he received support for article research from the DOD DHP. Drs. Anfossi, Shimizu, and Elster received support for article research from the National Institutes of Health (NIH). Drs. Lisboa, Davis, and Elster disclosed government work. Dr. Buchman’s institution received funding from the Uniformed Services University of the Health Sciences and/or the Henry M. Jackson Foundation, the Society of Critical Care Medicine, and Philips Corporation; he received support for article research from the Uniformed Services University of the Health Sciences; he disclosed that he is a Senior Advisor under an IPA tasked part-time to the Department of Health and Human Services/Office of the Assistant Secretary for Preparedness and Response/Biomedical Advanced Research and Development Authority/Division of Research, Innovation, and Ventures. Dr. Kirk’s institution received funding from the DOD. Dr. Calin is the Felix L. Haas Endowed Professor in Basic Science. Dr. Elster’s institution received funding from the DOD DHP – Joint Program Committee 6/Combat Casualty Care (USUHS HT9404-13-1-0032 and HU0001-15-2-0001), the NIH/the National Center for Advancing Translational Sciences grant UH3TR00943-01 through the NIH Common Fund, Office of Strategic Coordination, the National Cancer Institute grants 1R01 CA182905-01 and 1R01CA222007-01A1, the National Institute of General Medical Sciences 1R01GM122775-01 grant, a Team DOD (CA160445P1) grant, a Chronic Lymphocytic Leukemia Moonshot Flagship project, a CLL Global Research Foundation 2019 grant, a CLL Global Research Foundation 2020 grant, and donor support through Dr. Jaffer Ajani and the Estate of C. G. Johnson, Jr. The remaining authors have disclosed that they do not have any potential conflicts of interest.

Traumatic injuries to the mesenteric vessels are rare and often lethal. Visceral vessels, such as the superior mesenteric artery (SMA) and vein (SMV), supply blood to the small and large bowel by a rich system of collaterals. Because fewer than 100 such injuries have been described in the literature, they pose challenges in both diagnosis and management and can unfortunately result in high mortality rates. Prompt diagnosis, surgical intervention, and resuscitation can lead to improved outcomes. Here, we review the literature surrounding traumatic injuries of the SMA/SMV and discuss management strategies.

Objectives: Integrate a predictive model for massive transfusion protocol (MTP) activation and delivery in the electronic medical record (EMR) using prospectively gathered data; externally validate the model and assess the accuracy and precision of the model over time., Background: The Emory model for predicting MTP using only four input variables was chosen to be integrated into our hospital's EMR to provide a real time clinical decision support tool. The continuous variable output allows for periodic re-calibration of the model to optimize sensitivity and specificity., Methods: Prospectively collected data from level 1 and 2 trauma activations were used to input heart rate, systolic blood pressure, base excess (BE) and mechanism of injury into the EMR-integrated model for predicting MTP activation and delivery. MTP delivery was defined as: 6 units of packed red blood cells/6 hours (MTP1) or 10 units in 24 hours (MTP2). The probability of MTP was reported in the EMR. ROC and PR curves were constructed at 6, 12, and 20 months to assess the adequacy of the model., Results: Data from 1162 patients were included. Areas under ROC for MTP activation, MTP1 and MTP2 delivery at 6, 12, and 20 months were 0.800, 0.821, and 0.831; 0.796, 0.861, and 0.879; and 0.809, 0.875, and 0.905 (all P < 0.001). The areas under the PR curves also improved, reaching values at 20 months of 0.371, 0.339, and 0.355 for MTP activation, MTP1 delivery, and MTP2 delivery., Conclusions: A predictive model for MTP activation and delivery was integrated into our EMR using prospectively collected data to externally validate the model. The model's performance improved over time. The ability to choose the cut-points of the ROC and PR curves due to the continuous variable output of probability of MTP allows one to optimize sensitivity or specificity., Competing Interests: Disclosure: The authors declare that they have nothing to disclose., (Copyright © 2021 The Author(s). Published by Wolters Kluwer Health, Inc.)

Background: Improper or delayed activation of a massive transfusion protocol may have consequences to individuals and institutions. We designed a complex predictive algorithm that was packaged within a smartphone application. We hypothesized it would accurately assess the need for massive transfusion protocol activation and assist clinicians in that decision., Methods: We prospectively enrolled patients at an urban, level I trauma center. The application recorded the surgeon's initial opinion for activation and then prompted inputs for the model. The application provided a prediction and recorded the surgeon's final decision on activation., Results: Three hundred and twenty-one patients were enrolled (83% male; 59% penetrating; median Injury Severity Score 9; mean base deficit -4.11). Of 36 massive transfusion protocol activations, 26 had an app prediction of "high" or "moderate" probability. Of these, 4 (15%) patients received <10 u blood as a result of early hemorrhage control. Two hundred and eighty-five patients did not have massive transfusion protocol activated by the surgeon with 27 (9%) patients having "moderate" or "high" likelihood predicted by the application. Twenty-four of these did not require massive transfusion, and all patients had acidosis that unrelated to hemorrhagic shock. For 13 (50%) of the patients with "high" probability, the surgeon correctly altered their initial decision based on this information. The algorithm demonstrated an adjusted accuracy of 0.96 (95% confidence interval [0.93-0.98); P ≤ .001]), sensitivity = 0.99, specificity 0.72, positive predictive value 0.96, negative predictive value 0.99, and area under the receiver operating curve = 0.86., Conclusion: A smartphone-based clinical decision tools can aid surgeons in the decision to active massive transfusion protocol in real time, although it does not completely replace clinician judgment., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Visceral vascular injuries are relatively uncommon even in busy urban trauma centers. The inferior vena cava (IVC) is the most frequently injured visceral vein and can be a complex operative challenge. Despite advances in early volume resuscitation, improved transport times, prompt operative intervention, and hemorrhage control, mortality rates have remained largely unchanged. This article conducts an in-depth review of the literature surrounding IVC injuries and a detailed discussion of operative strategies and management as survivability is ultimately dependent on the grade of injury, location, and the presence of hemorrhagic shock.

Background: Flow cytometry (FCM) is a rapid diagnostic tool for monitoring immune cell function. We sought to determine if assessment of cell phenotypes using standardized FCM could be used to identify nosocomial infection after trauma., Methods: Prospective study of trauma patients at a Level I center from 2014 to 2018. Clinical and FCM data were collected within 24 hours of admission. Random forest (RF) models were developed to estimate the risk of severe sepsis (SS), organ space infection (OSI), and ventilator-associated pneumonia (VAP). Variables were selected using backward elimination and models were validated with leave-one-out., Results: One hundred and thirty-eight patients were included (median age, 30 years [23-44 years]; median Injury Severity Score, 20 (14-29); 76% (105/138) Black; 60% (83/138) gunshots). The incidence of SS was 8.7% (12/138), OSI 16.7% (23/138), and VAP 18% (25/138). The final RF SS model resulted in five variables (RBCs transfused in first 24 hours; absolute counts of CD56- CD16+ lymphocytes, CD4+ T cells, and CD56 bright natural killer [NK] cells; percentage of CD16+ CD56+ NK cells) that identified SS with an AUC of 0.89, sensitivity of 0.98, and specificity of 0.78. The final RF OSI model resulted in four variables (RBC in first 24 hours, shock index, absolute CD16+ CD56+ NK cell counts, percentage of CD56 bright NK cells) that identified OSI with an AUC of 0.76, sensitivity of 0.68, and specificity of 0.82. The RF VAP model resulted in six variables (Sequential [Sepsis-related] Organ Failure Assessment score: Injury Severity Score; CD4- CD8- T cell counts; percentages of CD16- CD56- NK cells, CD16- CD56+ NK cells, and CD19+ B lymphocytes) that identified VAP with AUC of 0.86, sensitivity of 0.86, and specificity of 0.83., Conclusions: Combined clinical and FCM data can assist with early identification of posttraumatic infections. The presence of NK cells supports the innate immune response that occurs during acute inflammation. Further research is needed to determine the functional role of these innate cell phenotypes and their value in predictive models immediately after injury., Level of Evidence: Prognostic, level III., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)

Background: The role of minimally invasive surgery in trauma has continued to evolve over the past 20 years. Diagnostic laparoscopy (DL) has become increasingly utilized for the diagnosis and management of both blunt and penetrating injuries., Objective: While the safety and feasibility of laparoscopy has been established for penetrating thoracoabdominal trauma, it remains a controversial tool for other injury patterns due to the concern for complications and missed injuries. We sought to examine the role of laparoscopy for the initial management of traumatic injuries at our urban Level 1 trauma center., Methods: All trauma patients who underwent DL for blunt or penetrating trauma between 2009 and 2018 were retrospectively reviewed. Demographic data, indications for DL, injuries identified, rate of conversion to open surgery, and outcomes were evaluated., Results: A total of 316 patients were included in the cohort. The mean age was 34.9 years old (± 13.7), mean GCS 14 (± 3), and median ISS 10 (4-18). A total of 110/316 patients (35%) sustained blunt injury and 206/316 patients (65%) sustained penetrating injury. Indications for DL included evaluation for peritoneal violation (152/316, 48%), free fluid without evidence of solid organ injury (52/316, 16%), evaluation of bowel injury (42/316, 13%), and evaluation for diaphragmatic injury (35/316, 11%). Of all DLs, 178/316 (56%) were negative for injury requiring intervention, which was 58% of blunt cases and 55% of penetrating cases. There were no missed injuries noted. Average hospital length of stay was significantly shorter for patients that underwent DL vs conversion to open exploration (2.2 days vs. 4.5 days, p < 0.05)., Conclusion: In this single institution, retrospective study, the high volume of cases appears to show that DL is a reliable tool for detecting injury and avoiding potential negative or non-therapeutic laparotomies. However, when injuries were present, the high rate of conversion to open exploration suggests that its utility for therapeutic intervention warrants further study.

Background: Post-traumatic acute kidney injury has occurred in every major military conflict since its initial description during World War II. To ensure the proper treatment of combat casualties, early detection is critical. This study therefore aimed to investigate combat-related post-traumatic acute kidney injury in recent military conflicts, used machine learning algorithms to identify clinical and biomarker variables associated with the development of post-traumatic acute kidney injury, and evaluated the effects of post-traumatic acute kidney injury on wound healing and nosocomial infection., Methods: We conducted a retrospective clinical cohort review of 73 critically injured US military service members who sustained major combat-related extremity wounds and had collected injury characteristics, assayed serum and tissue biopsy samples for the expression of protein and messenger ribonucleic acid biomarkers. Bivariate analyses and random forest recursive feature elimination classification algorithms were used to identify associated injury characteristics and biomarker variables., Results: The incidence of post-traumatic acute kidney injury was 20.5%. Of that, 86% recovered baseline renal function and only 2 (15%) of the acute kidney injury group required renal replacement therapy. Random forest recursive feature elimination algorithms were able to estimate post-traumatic acute kidney injury with the area under the curve of 0.93, sensitivity of 0.91, and specificity of 0.91. Post-traumatic acute kidney injury was associated with injury severity score, serum epidermal growth factor, and tissue activin A type receptor 1, matrix metallopeptidase 10, and X-C motif chemokine ligand 1 expression. Patients with post-traumatic acute kidney injury exhibited poor wound healing and increased incidence of nosocomial infections., Conclusion: The occurrence of acute kidney injury in combat casualties may be estimated using injury characteristics and serum and tissue biomarkers. External validations of these models are necessary to generalize for all trauma patients., (Published by Elsevier Inc.)

Mass casualty events (MCE) are an infrequent occurrence to most daily healthcare systems however these incidents are the causation for new hospital preparedness and the development of coordinated emergency services. The broad support and operational plans outside the hospital include emergency medical services, local law enforcement, government agencies, and city officials. Modern-day hospital disaster preparedness goals include scheduled training for healthcare personnel to ensure effective and accurate triage for a high-volume of injured patients. This MDT collaboration strengthens the emergency response to optimize the delivery of life-saving care during MCEs. This review identifies the clinical importance of the interdisciplinary team interactions and the lessons learned from past MCE experiences, strengthening healthcare system readiness for such critical incidents., Competing Interests: The authors report no conflicts of interest in this work., (© 2019 Melmer et al.)

Background: Identifying clinical and biomarker profiles of trauma patients may facilitate the creation of models that predict postoperative complications. We sought to determine the utility of modeling for predicting severe sepsis (SS) and organ space infections (OSI) following laparotomy for abdominal trauma., Methods: Clinical and molecular biomarker data were collected prospectively from patients undergoing exploratory laparotomy for abdominal trauma at a Level I trauma center between 2014 and 2017. Machine learning algorithms were used to develop models predicting SS and OSI. Random forest (RF) was performed, and features were selected using backward elimination. The SS model was trained on 117 records and validated using the leave-one-out method on the remaining 15 records. The OSI model was trained on 113 records and validated on the remaining 19. Models were assessed using areas under the curve., Results: One hundred thirty-two patients were included (median age, 30 years [23-42 years], 68.9% penetrating injury, median Injury Severity Score of 18 [10-27]). Of these, 10.6% (14 of 132) developed SS and 13.6% (18 of 132) developed OSI. The final RF model resulted in five variables for SS (Penetrating Abdominal Trauma Index, serum epidermal growth factor, monocyte chemoattractant protein-1, interleukin-6, and eotaxin) and four variables for OSI (Penetrating Abdominal Trauma Index, serum epidermal growth factor, monocyte chemoattractant protein-1, and interleukin-8). The RF models predicted SS and OSI with areas under the curve of 0.798 and 0.774, respectively., Conclusion: Random forests with RFE can help identify clinical and biomarker profiles predictive of SS and OSI after trauma laparotomy. Once validated, these models could be used as clinical decision support tools for earlier detection and treatment of infectious complications following injury., Level of Evidence: Prognostic, level III.

Background: Both the frequency and high complication rates associated with extremity wounds in recent military conflicts have highlighted the need for clinical decision support tools (CDST) to decrease time to wound closure and wound failure rates., Methods: Machine learning was used to estimate both successful wound closure (based on penultimate debridement biomarker data) and the necessary number of surgical debridements (based on presentation biomarkers) in 73 service members treated according to military guidelines based on clinical data and the local/systemic level of 32 cytokines. Models were trained to estimate successful closure including an additional 8 of 80 civilian patients with similar injury patterns. Previous analysis has demonstrated the potential to reduce the number of operative debridements by 2, with resulting decreases in ICU and hospital LOS, while decreasing the rate of wound failure., Results: Analysis showed similar cytokine responses when civilians followed a military-like treatment schedule with surgical debridements every 24 to 72 hours. A model estimating successful closure had AUC of 0.89. Model performance in civilians degraded when these had a debridement interval > 72 hours (73 of the 80 civilians). A separate model estimating the number of debridements required to achieve successful closure had a multiclass AUC of 0.81., Conclusion: CDSTs can be developed using biologically compatible civilian and military populations as cytokine response is highly influenced by surgical treatment. Our CDSTs may help identify who may require serial debridements versus early closure, and precisely when traumatic wounds should optimally be closed.

Background: Readiness costs are real expenses incurred by trauma centers to maintain essential infrastructure to provide emergent services on a 24/7 basis. Although the components for readiness are well described in the American College of Surgeons' Resources for Optimal Care of the Injured Patient, the cost associated with each component is not well defined. We hypothesized that meeting the requirements of the 2014 Resources for Optimal Care of the Injured Patient would result in significant costs for trauma centers., Methods: The state trauma commission in conjunction with trauma medical directors, program managers, and financial officers of each trauma center standardized definitions for each component of trauma center readiness cost and developed a survey tool for reporting. Readiness costs were grouped into four categories: administrative/program support staff, clinical medical staff, in-house operating room, and education/outreach. To verify consistent cost reporting, a financial auditor analyzed all data. Trauma center outliers were further evaluated to validate variances. All level I/level II trauma centers (n = 16) completed the survey on 2016 data., Results: Average annual readiness cost is US $10,078,506 for a level I trauma center and US $4,925,103 for level IIs. Clinical medical staff was the costliest component representing 55% of costs for level Is and 64% for level IIs. Although education/outreach is mandated, levels I and II trauma centers only spend approximately US $100,000 annually on this category (1%-2%), demonstrating a lack of resources., Conclusion: This study defines the cost associated with each component of readiness as defined in the Resources for Optimal Care of the Injured Patient manual. Average readiness cost for a level I trauma center is US $10,078,506 and US $4,925,103 for a level II. The significant cost of trauma center readiness highlights the need for additional trauma center funding to meet the requirements set forth by the American College of Surgeons., Level of Evidence: Economic and value-based evaluations, level III.

Background: The American College of Surgeons Needs Based Assessment of Trauma Systems (NBATS) tool was developed to help determine the optimal regional distribution of designated trauma centers (DTC). The objectives of our current study were to compare the current distribution of DTCs in Georgia with the recommended allocation as calculated by the NBATS tool and to see if the NBATS tool identified similar areas of need as defined by our previous analysis using the International Classification of Diseases, Ninth Revision, Clinical Modification Injury Severity Score (ICISS)., Methods: Population counts were acquired from US Census publications. Transportation times were estimated using digitized roadmaps and patient zip codes. The number of severely injured patients was obtained from the Georgia Discharge Data System for 2010 to 2014. Severely injured patients were identified using two measures: ICISS<0.85 and Injury Severity Score >15., Results: The Georgia trauma system includes 19 level I, II, or III adult DTCs. The NBATS guidelines recommend 21; however, the distribution differs from what exists in the state. The existing DTCs exactly matched the NBATS recommended number of level I, II, or III DTCs in 2 of 10 trauma service areas (TSAs), exceeded the number recommended in 3 of 10 TSAs, and was below the number recommended in 5 of 10 TSAs. Densely populated, or urban, areas tend to be associated with a higher number of existing centers compared with the NBATS recommendation. Other less densely populated TSAs are characterized by large rural expanses with a single urban core where a DTC is located. The identified areas of need were similar to the ones identified in the previous gap analysis of the state using the ICISS methodology., Discussion: The tool appears to underestimate the number of centers needed in extensive and densely populated areas, but recommends additional centers in geographically expansive rural areas. The tool signifies a preliminary step in assessing the need for state-wide inpatient trauma center services., Level of Evidence: Economic, level IV., Competing Interests: Competing interests: None declared.

Introduction: Morbidity from the treatment of extremity compartment syndrome is underappreciated. Closure technique effectiveness has yet to be definitively established., Methods: A randomized non-blinded prospective study was performed involving patients who underwent an extremity fasciotomy following trauma. Shoelace wounds were strapped with vessel loops under tension and VAC wounds were treated with a standard KCI VAC dressing. After randomization, patients returned to the OR every 96 h until primarily closed or skin grafted., Results: 21 patients were consented for randomization with 11 (52%) successfully closed at the first re-operation. After interim analysis the study was closed early with 5/5 (100%) of wounds treated with the shoelace technique closed primarily and only 1/9 (11%) of VAC wounds closed primarily (p = 0.003). Overall primary closure was achieved in 74% of patients., Conclusions: Aggressive attempts at wound closure lead to an increased early closure rate. For wounds that remain open after the first re-operation, a simple shoelace technique is more successful than a wound VAC for achieving same hospital stay skin closure., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Background: The complexity and severity of traumatic wounds in military and civilian trauma demands improved wound assessment, before, during, and after treatment. Here, we explore the potential of 3 charge-coupled device (3CCD) imaging values to distinguish between traumatic wounds that heal following closure and those that fail. Previous studies demonstrate that normalized 3CCD imaging values exhibit a high correlation with oxygen saturation and allow for comparison of values between diverse clinical settings, including utilizing different equipment and lighting., Methods: We screened 119 patients at Walter Reed National Military Medical Center and at Grady Memorial Hospital with at least one traumatic extremity wound of ≥ 75 cm2. We collected images of each wound during each débridement surgery for a total of 66 patients. An in-house written computer application selected a region of interest in the images, separated the pixel color values, calculated relative values, and normalized them. We followed patients until the enrolled wounds were surgically closed, quantifying the number of wounds that dehisced (defined as wound failure or infection requiring return to the operating room after closure) or healed., Results: Wound failure occurred in 20% (19 of 96) of traumatic wounds. Normalized intensity values for patients with wounds that healed successfully were, on average, significantly different from values for patients with wounds that failed (p ≤ 0.05). Simple thresholding models and partial least squares discriminant analysis models performed poorly. However, a hierarchical cluster analysis model created with 17 variables including 3CCD data, wound surface area, and time from injury predicts wound failure with 76.9% sensitivity, 76.5% specificity, 76.6% accuracy, and a diagnostic odds ratio of 10.8 (95% confidence interval: 2.6-45.9)., Conclusions: Imaging using 3CCD technology may provide a non-invasive and cost-effective method of aiding surgeons in deciding if wounds are ready for closure and could potentially decrease the number of required débridements and hospital days. The process may be automated to provide real-time feedback in the operating room and clinic. The low cost and small size of the cameras makes this technology attractive for austere and shipboard environments where space and weight are at a premium., Competing Interests: JAF is a paid consultant for the Solsidan Group LLC, Prognostix AB, Clementia Pharmaceuticals Inc. and receives research support as a Principal Investigator from Zimmer-Biomet Inc. This does not alter our adherence to PLOS ONE policies on sharing data and materials. No other authors have any conflicts of interests to declare.

Background: Despite increasing usage since their introduction, there exist no evidence-based guidelines on all-terrain vehicles (ATVs) and injury prevention. While the power and speed of these vehicles has increased over time, advancements in ATV safety have been rare., Methods: A priori questions about ATV injury pattern and the effect of helmet and safety equipment use and legislation mandating use were developed. A query of MEDLINE, PubMed, Cochrane Library, and Embase for all-terrain vehicle injury was performed. Letters to the editor, case reports, book chapters, and review articles were excluded. Grading of Recommendations Assessment, Development, and Evaluation methodology was used to perform a systematic review and create recommendations., Results: Twenty-eight studies were included. Helmet use reduced traumatic brain injury (TBI). However, studies examining whether legislation mandating helmet use reduced TBI had mixed results. When ATV safety legislation was enforced, overall injury rates and mortality decreased. However, enforcement varied widely and lack of enforcement led to decreased compliance with legislation and mixed results. There was not enough evidence to determine the effectiveness of non-helmet-protective equipment., Conclusion: Helmet use when riding an ATV reduced the rate of TBI. ATV safety legislation, when enforced, also reduced morbidity and mortality. Compliance with laws is often low, however, possibly due to poor enforcement. We recommend helmet use when riding on an ATV to reduce TBI. We conditionally recommend implementing ATV safety legislation as a means to reduce ATV injuries, noting that enforcement must go hand in hand with enactment to ensure compliance.

Precision medicine endeavors to leverage all available medical data in pursuit of individualized diagnostic and therapeutic plans to improve patient outcomes in a cost-effective manner. Its promise in the field of critical care remains incompletely realized. The Department of Defense has a vested interest in advancing precision medicine for those sent into harm's way and specifically seeks means of individualizing care in the context of complex and highly dynamic combat clinical decision environments. Building on legacy research efforts conducted during the Afghanistan and Iraq conflicts, the Uniformed Service University (USU) launched the Surgical Critical Care Initiative (SC2i) in 2013 to develop clinical- and biomarker-driven Clinical Decision Support Systems (CDSS), with the goals of improving both patient-specific outcomes and resource utilization for conditions with a high risk of morbidity or mortality. Despite technical and regulatory challenges, this military-civilian partnership is beginning to deliver on the promise of personalized care, organizing and analyzing sizable, real-time medical data sets to support complex clinical decision-making across critical and surgical care disciplines. We present the SC2i experience as a generalizable template for the national integration of federal and non-federal research databanks to foster critical and surgical care precision medicine.

This study was designed to compare the incidence of venous thromboembolism (VTE) in Georgia trauma centers with other national trauma centers participating in the Trauma Quality Improvement Program (TQIP). The use of chemoprophylaxis and characteristics of patients who developed VTE were also examined. We conducted a retrospective observational study of 325,703 trauma admissions to 245 trauma centers from 2013 to 2014. Patient demographics, rate of VTE, as well as the use, type, and timing of chemoprophylaxis were compared between patients admitted to Georgia and non-Georgia trauma centers. The rate of VTE in Georgia trauma centers was 1.9 per cent compared with 2.1 per cent in other national trauma centers. Overall, 49.6 per cent of Georgia patients and 45.5 per cent of patients in other trauma centers had documented chemoprophylaxis. Low molecular weight heparin was the most commonly used medication. Most patients who developed VTE did so despite receiving prophylaxis. The rate of VTE despite prophylaxis was 3.2 per cent in Georgia and 3.1 per cent in non-Georgia trauma centers. Mortality associated with VTE was higher in Georgia trauma centers compared with national TQIP benchmarks. The incidence of VTE and use of chemoprophylaxis within Georgia trauma centers were similar to national TQIP data. Interestingly, most patients who developed VTE in both populations received VTE prophylaxis. Further research is needed to develop best-practice guidelines for prevention, early detection, and treatment in high-risk populations.

Background: The biomarker profile of trauma patients may allow for the creation of models to assist bedside decision making and prediction of complications. We sought to determine the utility of modeling in the prediction of bacteremia and pneumonia in combat casualties., Methods: This is a prospective, observational trial of patients with complex wounds treated at Walter Reed National Military Medical Center (2007-2012). Tissue, serum, and wound effluent samples were collected during operative interventions until wound closure. Clinical, biomarker, and outcome data were used in machine learning algorithms to develop models predicting bacteremia or pneumonia. Modeling was performed on the first operative washout to maximize predictive benefit. Variable selection of dataset variables was performed and the best-fitting Bayesian belief network (BBN), using Bayesian information criterion (BIC), was selected for predictive modeling. Random forest was performed using variables from BBN step. Model performance was evaluated using area under the receiver operating characteristic curve (AUC) analysis., Results: Seventy-three patients (mean age 23, mean Injury Severity Score 25) were enrolled. Patients required a median of 3 (2-13) operations. The incidence of bacteremia and pneumonia was 22% and 12%, respectively. Best-fitting variable selected BBNs were maximum-minimum parents and children (MMPC) for both bacteremia (BIC-24948) and pneumonia (BIC-17886). Full variable and MMPC random forest models AUC were 0.721 and 0.834, respectively, for bacteremia and 0.809 and 0.856, respectively, for pneumonia., Conclusions: We identified a profile predictive of bacteremia and pneumonia in combat casualties. This has important clinical implications and should be validated in the civilian trauma population. This and similar tools will allow for increasing precision in the management of critically ill and injured patients., Level of Evidence: Prognostic, level III.

Trauma center readiness costs are incurred to maintain essential infrastructure and capacity to provide emergent services on a 24/7 basis. These costs are not captured by traditional hospital cost accounting, and no national consensus exists on appropriate definitions for each cost. Therefore, in 2010, stakeholders from all Level I and II trauma centers developed a survey tool standardizing and defining trauma center readiness costs. The survey tool underwent minor revisions to provide further clarity, and the survey was repeated in 2013. The purpose of this study was to provide a follow-up analysis of readiness costs for Georgia's Level I and Level II trauma centers. Using the American College of Surgeons Resources for Optimal Care of the Injured Patient guidelines, four readiness cost categories were identified: Administrative, Clinical Medical Staff, Operating Room, and Education/Outreach. Through conference calls, webinars and face-to-face meetings with financial officers, trauma medical directors, and program managers from all trauma centers, standardized definitions for reporting readiness costs within each category were developed. This resulted in a survey tool for centers to report their individual readiness costs for one year. The total readiness cost for all Level I trauma centers was $34,105,318 (avg $6,821,064) and all Level II trauma centers was $20,998,019 (avg $2,333,113). Methodology to standardize and define readiness costs for all trauma centers within the state was developed. Average costs for Level I and Level II trauma centers were identified. This model may be used to help other states define and standardize their trauma readiness costs.

As quality and outcomes have moved to the fore front of medicine in this era of healthcare reform, a state trauma system Performance Based Payments (PBP) program has been incorporated into trauma center readiness funding. The purpose of this study was to evaluate the impact of a PBP on trauma center revenue. From 2010 to 2016, a percentage of readiness costs funding to trauma centers was placed in a PBP and withheld until the PBP criteria were completed. To introduce the concept, only three performance criteria and 10 per cent of readiness costs funding were tied to PBP in 2010. The PBP has evolved over the last several years to now include specific criteria by level of designation with an increase to 50 per cent of readiness costs funding being tied to PBP criteria. Final PBP distribution to trauma centers was based on the number of performance criteria completed. During 2016, the PBP criteria for Level I and II trauma centers included participation in official state meetings/conference calls, required attendance to American College of Surgeons state chapter meetings, Trauma Quality Improvement Program, registry reports, and surgeon participation in Peer Review Committee and trauma alert response times. Over the seven-year study period, $36,261,469 was available for readiness funds with $11,534,512 eligible for the PBP. Only $636,383 (6%) was withheld from trauma centers. A performance-based program was successfully incorporated into trauma center readiness funding, supporting state performance measures without adversely affecting the trauma center revenue. Future PBP criteria may be aligned to designation standards and clinical quality performance metrics.

Background: High-energy missiles can cause cardiac injury regardless of entrance site. This study assesses the adequacy of the anatomic borders of the current "cardiac box" to predict cardiac injury., Methods: Retrospective autopsy review was performed to identify patients with penetrating torso gunshot wounds (GSWs) 2011 to 2013. Using a circumferential grid system around the thorax, logistic regression analysis was performed to detect differences in rates of cardiac injury from entrance/exit wounds in the "cardiac box" versus the same for entrance/exit wounds outside the box. Analysis was repeated to identify regions to compare risk of cardiac injury between the current cardiac box and other regions of the thorax., Results: Over the study period, 263 patients (89% men; mean age, 34 years; median injuries/person, 2) sustained 735 wounds (80% GSWs), and 239 patients with 620 GSWs were identified for study. Of these, 95 (34%) injured the heart. Of the 257 GSWs entering the cardiac box, 31% caused cardiac injury, whereas 21% GSWs outside the cardiac box (n = 67) penetrated the heart, suggesting that the current "cardiac box" is a poor predictor of cardiac injury relative to the thoracic non-"cardiac box" regions (relative risk [RR], 0.96; p = 0.82). The regions from the anterior to posterior midline of the left thorax provided the highest positive predictive value (41%) with high sensitivity (90%) while minimizing false-positives, making this region the most statistically significant discriminator of cardiac injury (RR, 2.9; p = 0.01)., Conclusion: For GSWs, the current cardiac box is inadequate to discriminate whether a GSW will cause a cardiac injury. As expected, entrance wounds nearest to the heart are the most likely to result in cardiac injury, but, from a clinical standpoint, it is best to think outside the "box" for GSWs to the thorax., Level of Evidence: Therapeutic/care management, level IV.

With a relative shortage of type AB plasma, many centers have converted to type A plasma for resuscitation of patients whose blood type is unknown. The goal of this study is to determine outcomes for trauma patients who received incompatible plasma transfusions as part of a massive transfusion protocol (MTP)., Methods: As part of an Eastern Association for the Surgery of Trauma multi-institutional trial, registry and blood bank data were collected from eight trauma centers for trauma patients (age, ≥ 15 years) receiving emergency release plasma transfusions as part of MTPs from January 2012 to August 2016. Incompatible type A plasma was defined as transfusion to patient blood type B or type AB., Results: Of the 1,536 patients identified, 92% received compatible plasma transfusions and 8% received incompatible type A plasma. Patient characteristics were similar except for greater penetrating injuries (48% vs 36%; p = 0.01) in the incompatible group. In the incompatible group, patients were transfused more plasma units at 4 hours (median, 9 vs. 5; p < 0.001) and overall for stay (11 vs. 9; p = 0.03). No hemolytic transfusion reactions were reported. Two transfusion-related acute lung injury events were reported in the compatible group. Between incompatible and compatible groups, there was no difference in the rates of acute respiratory distress syndrome (6% vs. 8%; p = 0.589), thromboembolic events (9% vs. 7%; p = 0.464), sepsis (6% vs. 8%; p = 0.589), or acute renal failure (8% vs. 8%, p = 0.860). Mortality at 6 (17% vs. 15%, p = 0.775) and 24 hours (25% vs. 23%, p = 0.544) and at 28 days or discharge (38% vs. 35%, p = 0.486) were similar between groups. Multivariate regression demonstrated that Injury Severity Score, older age and more red blood cell transfusion at 4 hours were independently associated with death at 28 days or discharge; Injury Severity Score and more red blood cell transfusion at 4 hours were predictors for morbidity. Incompatible transfusion was not an independent determinant of mortality or morbidity., Conclusion: Transfusion of type A plasma to patients with blood groups B and AB as part of a MTP does not appear to be associated with significant increases in morbidity or mortality., Level of Evidence: Therapeutic study, level IV.

Background: Despite the lethality of injuries to the heart, optimizing factors that impact mortality for victims that do survive to reach the hospital is critical., Methods: From 2003 to 2012, prehospital data, injury characteristics, and clinical patient factors were analyzed for victims with penetrating cardiac injuries (PCIs) at an urban, level I trauma center., Results: Over the 10-year study, 80 PCI patients survived to reach the hospital. Of the 21 factors analyzed, prehospital cardiopulmonary resuscitation (odds ratio [OR] = 30), scene time greater than 10 minutes (OR = 58), resuscitative thoracotomy (OR = 19), and massive left hemothorax (OR = 15) had the greatest impact on mortality. Cardiac tamponade physiology demonstrated a "protective" effect for survivors to the hospital (OR = .08)., Conclusions: Trauma surgeons can improve mortality after PCI by minimizing time to the operating room for early control of hemorrhage. In PCI patients, tamponade may provide a physiologic advantage (lower mortality) compared to exsanguination., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Improving diagnosis and treatment depends on clinical monitoring and computing. Clinical decision support systems (CDSS) have been in existence for over 50 years. While the literature points to positive impacts on quality and patient safety, outcomes, and the avoidance of medical errors, technical and regulatory challenges continue to retard their rate of integration into clinical care processes and thus delay the refinement of diagnoses towards personalized care. We conducted a systematic review of pertinent articles in the MEDLINE, US Department of Health and Human Services, Agency for Health Research and Quality, and US Food and Drug Administration databases, using a Boolean approach to combine terms germane to the discussion (clinical decision support, tools, systems, critical care, trauma, outcome, cost savings, NSQIP, APACHE, SOFA, ICU, and diagnostics). References were selected on the basis of both temporal and thematic relevance, and subsequently aggregated around four distinct themes: the uses of CDSS in the critical and surgical care settings, clinical insertion challenges, utilization leading to cost-savings, and regulatory concerns. Precision diagnosis is the accurate and timely explanation of each patient's health problem and further requires communication of that explanation to patients and surrogate decision-makers. Both accuracy and timeliness are essential to critical care, yet computed decision support systems (CDSS) are scarce. The limitation arises from the technical complexity associated with integrating and filtering large data sets from diverse sources. Provider mistrust and resistance coupled with the absence of clear guidance from regulatory bodies further retard acceptance of CDSS. While challenges to develop and deploy CDSS are substantial, the clinical, quality, and economic impacts warrant the effort, especially in disciplines requiring complex decision-making, such as critical and surgical care. Improving diagnosis in health care requires accumulation, validation and transformation of data into actionable information. The aggregate of those processes-CDSS-is currently primitive. Despite technical and regulatory challenges, the apparent clinical and economic utilities of CDSS must lead to greater engagement. These tools play the key role in realizing the vision of a more 'personalized medicine', one characterized by individualized precision diagnosis rather than population-based risk-stratification.

Background: Over the past decade, the American Association for the Surgery of Trauma Acute Care Surgery (ACS) fellowship program has matured to 20 verified programs. As part of an ongoing curricular evaluation, we queried the current practice patterns of the graduates of ACS fellowship programs regarding their view on their ACS training. We hypothesized that the majority of ACS fellowship graduates would be practicing ACS in academic Level I trauma centers and that fellowship training was pivotal in their career., Methods: Graduates of American Association for the Surgery of Trauma-certified ACS fellowships completed an online survey that included practice demographics, specific categories of cases delineated by the current ACS curriculum, and perceived impact of training., Results: Surveys were submitted by 56 of 77 graduates for a completion rate of 73%. The majority of respondents were male (68%) aged 40 years or younger (80%). All but four completed ACS fellowship training in last 5 years (93%), and 83% completed fellowship in the last 3 years. Regarding their current practice, broadly defined ACS predominated (96%) with 2% practicing only trauma surgery and 2% only general surgery. Practice settings were 64% urban, 29% suburban, and 7% rural locations, with 84% of graduates practicing in a hospital-based group. The practitioner's hospital was identified as university/university-affiliated in 53%, community in 38%, and military in 9%, with 91% identified as a teaching hospital; trauma designation was identified as Level I (55%), Level II (39%), and other (6%). The graduates' average current practice mix is 10% elective general surgery, 29% emergency general surgery, 32% trauma, 25% surgical critical care, and 4% other (burn, bariatric, vascular, and thoracic). Only 16% of graduates do not perform elective cases. Case specifics demonstrated 92% of graduates perform vascular cases, 88% perform thoracic cases, and 70% perform complex hepatobiliary. Practice elements that were satisfiers included (1) scope of practice, (2) case mix, (3) percentage emergency general surgery, (4) lifestyle, (5) case complexity (with 3 and 4 tied). Graduates agreed the ACS fellowship training prepared them well for practice and was worth the time invested (both 82%), increased their marketability and self-confidence (80%), and prepared them well for academics (71%) and administration (63%). Of those surveyed, 93% would encourage others to do an ACS fellowship., Conclusion: Although 93% of graduates practice in urban/suburban areas, there was a mixture of university, university-affiliated, and community institutions and an almost even division of Levels I and II designation. Graduates demonstrate ongoing use of their acquired advanced operative training, particularly in vascular and thoracic surgery. The majority of ACS fellowship graduates were practicing ACS and felt fellowship training was valuable in their career path and that they would recommend it to others.

Background: This study evaluates patterns of injuries and outcomes from penetrating cardiac injuries (PCIs) at Grady Memorial Hospital, an urban, Level I trauma center in Atlanta, Georgia, over 36 years., Methods: Patients sustaining PCIs were identified from the Trauma Registry of the American College of Surgeons and the Emory Department of Surgery database; data of patients who died prior to any therapy were excluded. Demographics and outcomes were compared over three time intervals: Period 1 (1975-1985; n = 113), Period 2 (1986-1996; n = 79), and Period 3 (2000-2010; n = 79)., Results: Two hundred seventy-one patients (86% were male; mean age, 33 years; initial base deficit = -11.3 mEq/L) sustained cardiac stab (SW, 60%) or gunshot wounds (GSW, 40%). Emergency department thoracotomy was performed in 67 (25%) of 271 patients. Overall mortality increased in the modern era (Period 1, 27%, vs. Period 2, 22%, vs. Period 3, 42%; p = 0.03) along with GSW mechanisms (Period 1, 32%, vs. Period 2, 33%, vs. Period 3, 57%; p = 0.001), GSW mortality (Period 1, 36%, vs. Period 2, 42%, vs. Period 3, 56%; p = 0.04), and multichamber injuries (Period 1, 12%, vs. Period 2, 10%, vs. Period 3, 34%; p< 0.001). In Period 3, GSWs (n = 45) resulted in multichamber injuries in 28 patients (62%) and multicavity injuries in 19 patients (42%). Surgeon-performed ultrasound accurately identified pericardial blood in 55 of 55 patients in Period 3., Conclusions: Increased frequency of GSWs in the past decade is associated with increased overall mortality, multichamber injuries, and multicavity injuries. Ultrasound is sensitive for detection of PCI., Level of Evidence: Therapeutic study, level IV; epidemioligc study, level III.

Background: Life-threatening conduction abnormalities after penetrating cardiac injuries (PCIs) are rare, and rapid identification and treatment of these arrhythmias are critical to survival. This study highlights diagnosis and management strategies for conduction abnormalities after PCI., Methods: Patients with life-threatening arrhythmias after PCI were identified at an urban, level I trauma center registry., Results: Seventy-one patients survived to reach the hospital after PCI. Of these, 3 (4%) survivors (male = 3, mean age 41.3, median injury severity score = 25) had critical conduction abnormalities after cardiorrhaphy. All patients had multichamber and atrioventricular nodal injury. After initial cardiorrhaphy and control of hemorrhage, all patients had sustained hypotension with bradycardia from complete heart block. Two patients had ventricular septal defects requiring repair. All 3 patients survived., Conclusions: Rapid recognition of injury to the cardiac conduction system after PCI as a source of sustained hypotension is essential to early restoration of cardiac function and survival., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Multiple stump closure techniques after distal pancreatectomy (DP) for trauma have been described, and all are associated with a significant fistula rate. With increasing emphasis on abbreviated laparotomy, stapled pancreatectomy has become more common. This study describes the outcomes of patients with different closure techniques of the pancreatic stump after resection following pancreatic trauma. Retrospective analysis of 50 trauma patients, who sustained grade III pancreatic injuries with subsequent DP and stapled stump closure, were conducted from 1995 to 2011. Demographic, operative, and outcome data were analyzed to characterize patients, and to directly compare closure techniques. After 12 patients were excluded because of early death (<72 hours), final analyses included 38 patients: 19 (50%) had stapled closure alone and 19 (50%) had stapling with adjunct, including additional closure with sutures, fibrin sealants, or a combination of sutures with fibrin sealants/omental coverage. Twenty-four patients (63%) had postoperative complications, most commonly pancreatic fistula (n = 11, 29%). There were no significant differences with regard to pancreatic fistula or other abdominal complications between closure groups, or were any factors associated with increased likelihood of complications. DP remains a morbid operation after trauma regardless of closure technique. Stapled closure alone is perhaps the method of choice in this setting due to the time constraints directly related to outcomes.

Background: Led by the American College of Surgeons Trauma Quality Improvement Program, performance improvement efforts have expanded to regional and national levels. The American College of Surgeons Trauma Quality Improvement Program recommends 5 audit filters to identify records with erroneous data, and the Georgia Committee on Trauma instituted standardized audit filter analysis in all Level I and II trauma centers in the state., Study Design: Audit filter reports were performed from July 2013 to September 2014. Records were reviewed to determine whether there was erroneous data abstraction. Percent yield was defined as number of errors divided by number of charts captured., Results: Twelve centers submitted complete datasets. During 15 months, 21,115 patient records were subjected to analysis. Audit filter captured 2,901 (14%) records and review yielded 549 (2.5%) records with erroneous data. Audit filter 1 had the highest number of records identified and audit filter 3 had the highest percent yield. Individual center error rates ranged from 0.4% to 5.2%. When comparing quarters 1 and 2 with quarters 4 and 5, there were 7 of 12 centers with substantial decreases in error rates. The most common missed complications were pneumonia, urinary tract infection, and acute renal failure. The most common missed comorbidities were hypertension, diabetes, and substance abuse., Conclusions: In Georgia, the prevalence of erroneous data in trauma registries varies among centers, leading to heterogeneity in data quality, and suggests that targeted educational opportunities exist at the institutional level. Standardized audit filter assessment improved data quality in the majority of participating centers., (Copyright © 2016 American College of Surgeons. Published by Elsevier Inc. All rights reserved.)

Background: Recent conflicts in Afghanistan and Iraq produced a substantial number of critically wounded service-members. We collected biomarker and clinical information from 73 patients who sustained 116 life-threatening combat wounds, and sought to determine if the data could be used to predict the likelihood of wound failure., Methods: From each patient, we collected clinical information, serum, wound effluent, and tissue prior to and at each surgical débridement. Inflammatory cytokines were quantified in both the serum and effluent, as were gene expression targets. The primary outcome was successful wound healing. Computer intensive methods were used to derive prognostic models that were internally validated using target shuffling and cross-validation methods. A second cohort of eighteen critically injured civilian patients was evaluated to determine if similar inflammatory responses were observed., Findings: The best-performing models enhanced clinical observation with biomarker data from the serum and wound effluent, an indicator that systemic inflammatory conditions contribute to local wound failure. A Random Forest model containing ten variables demonstrated the highest accuracy (AUC 0.79). Decision Curve Analysis indicated that the use of this model would improve clinical outcomes and reduce unnecessary surgical procedures. Civilian trauma patients demonstrated similar inflammatory responses and an equivalent wound failure rate, indicating that the model may be generalizable to civilian settings., Interpretation: Using advanced analytics, we successfully codified clinical and biomarker data from combat patients into a potentially generalizable decision support tool. Analysis of inflammatory data from critically ill patients with acute injury may inform decision-making to improve clinical outcomes and reduce healthcare costs., Funding: United States Department of Defense Health Programs.