The Association Between Tranexamic Acid and Seizures in Moderate or Severe Traumatic Brain Injury.

INTRODUCTION: Tranexamic acid (TXA) administered within 2 h of injury reduces mortality in traumatic brain injury (TBI) with intracranial hemorrhage. TXA also reduces the seizure threshold in a dose-dependent manner. We examined whether a 2-g bolus of prehospital TXA administered in moderate or severe TBI is associated with seizure activity within 72 h of injury. METHODS: Patients from the prehospital TXA for TBI trial with Glasgow Coma Scale < 13, blunt head injury, and time-of-seizure data were included in this analysis. The original trial randomized patients with suspected TBI to placebo, 1-g TXA bolus + 1-g 8-h TXA infusion, or 2-g TXA bolus within 2 h of injury. In this secondary analysis, multivariable logistic regression was performed to examine the association of treatment group with seizure incidence. The model controlled for age, Glasgow Coma Scale, Injury Severity Score, intracranial hemorrhage, Abbreviated Injury Scale-head, and home antiseizure medication use. RESULTS: Of the 786 patients who met the inclusion criteria, 19 had seizures within 72 h (five in placebo, two in 1-g bolus/1-g infusion, and 12 in 2-g bolus). The 2-g TXA bolus was not associated with increased seizures compared to placebo (odds ratio 0.41, 95% confidence interval 0.12-1.18, P = 0.12). Home antiseizure medication use was associated with increased seizures (odds ratio 15.95, 95% confidence interval 3.79-60.57, P < 0.001). CONCLUSIONS: A prehospital 2-g TXA bolus in moderate or severe TBI was not associated with increased seizure activity during the first 72 h after injury; however, limited power, limited use of continuous electroencephalography, and unavailable seizure prophylaxis data highlight the need for further study.

Digital twin mathematical models suggest individualized hemorrhagic shock resuscitation strategies.

BACKGROUND: Optimizing resuscitation to reduce inflammation and organ dysfunction following human trauma-associated hemorrhagic shock is a major clinical hurdle. This is limited by the short duration of pre-clinical studies and the sparsity of early data in the clinical setting. METHODS: We sought to bridge this gap by linking preclinical data in a porcine model with clinical data from patients from the Prospective, Observational, Multicenter, Major Trauma Transfusion (PROMMTT) study via a three-compartment ordinary differential equation model of inflammation and coagulation. RESULTS: The mathematical model accurately predicts physiologic, inflammatory, and laboratory measures in both the porcine model and patients, as well as the outcome and time of death in the PROMMTT cohort. Model simulation suggests that resuscitation with plasma and red blood cells outperformed resuscitation with crystalloid or plasma alone, and that earlier plasma resuscitation reduced injury severity and increased survival time. CONCLUSIONS: This workflow may serve as a translational bridge from pre-clinical to clinical studies in trauma-associated hemorrhagic shock and other complex disease settings.

Research to improve survival in patients with severe bleeding after major trauma presents many challenges. Here, we created a computer model to simulate the effects of severe bleeding. We refined this model using data from existing animal studies to ensure our simulations were accurate. We also used patient data to further refine the simulations to accurately predict which patients would live and which would not. We studied the effects of different treatment protocols on these simulated patients and show that treatment with plasma (the fluid portion of blood that helps form blood clots) and red blood cells jointly, gave better results than treatment with intravenous fluid or plasma alone. Early treatment with plasma reduced injury severity and increased survival time. This modelling approach may improve our ability to evaluate new treatments for trauma-associated bleeding and other acute conditions.

TXA does not affect levels of TBI-related biomarkers in blunt TBI with ICH: A secondary analysis of the prehospital TXA for TBI trial.

BACKGROUND: Brain specific biomarkers such as glial fibrillary acidic protein (GFAP), ubiquitin C-terminal hydrolase L1 (UCH-L1), and microtubule-associated protein-2 (MAP-2) have been identified as tools for diagnosis in traumatic brain injury (TBI). Tranexamic acid (TXA) has been shown to decrease mortality in patients with intracranial hemorrhage (ICH). The effect of TXA on these biomarkers is unknown. We investigated whether TXA affects levels of GFAP, UCH-L1, and MAP-2, and whether biomarker levels are associated with mortality in patients receiving TXA. METHODS: Patients enrolled in the prehospital TXA for TBI trial had GFAP, UCHL-1 and MAP-2 levels drawn at 0 hour and 24 hours postinjury (n = 422). Patients with ICH from blunt trauma with a GCS <13 and SBP >90 were randomized to placebo, 2 g TXA bolus, or 1 g bolus +1 g/8 hours TXA infusion. Associations of TXA and 24-hour biomarker change were assessed with multivariate linear regression. Association of biomarkers with 28-day mortality was assessed with multivariate logistic regression. All models were controlled for age, GCS, ISS, and AIS head. RESULTS: Administration of TXA was not associated with a change in biomarkers over 24 hours postinjury. Changes in biomarker levels were associated with AIS head and age. On admission, higher GFAP (odds ratio [OR], 1.75; confidence interval [CI], 1.31-2.38; p < 0.001) was associated with increased 28-day mortality. At 24 hours postinjury, higher levels of GFAP (OR, 2.09; CI, 1.37-3.30; p < 0.001 and UCHL-1 (OR, 2.98; CI, 1.77-5.25; p < 0.001) were associated with mortality. A change in UCH levels from 0 hour to 24 hours postinjury was also associated with increased mortality (OR, 1.68; CI, 1.15-2.49; p < 0.01). CONCLUSION: Administration of TXA does not impact change in GFAP, UCHL-1, or MAP-2 during the first 24 hours after blunt TBI with ICH. Higher levels of GFAP and UCH early after injury may help identify patients at high risk for 28-day mortality. LEVEL OF EVIDENCE: Therapeutic/Care Management; Level III.

Social Vulnerability and Firearm Violence: Geospatial Analysis of 5 US Cities.

BACKGROUND: Firearm violence is now endemic to certain US neighborhoods. Understanding factors that impact a neighborhood's susceptibility to firearm violence is crucial for prevention. Using a nationally standardized measure to characterize community-level firearm violence risk has not been broadly studied but could enhance prevention efforts. Thus, we sought to examine the association between firearm violence and the social, structural, and geospatial determinants of health, as defined by the Social Vulnerability Index (SVI). STUDY DESIGN: In this cross-sectional study, we merged 2018 SVI data on census tract with shooting incidents between 2015 and 2021 from Baltimore, Chicago, Los Angeles, New York City, and Philadelphia. We used negative binomial regression to associate the SVI with shooting incidents per 1,000 people in a census tract. Moran's I statistics and spatial lag models were used for geospatial analysis. RESULTS: We evaluated 71,296 shooting incidents across 4,415 census tracts. Fifty-five percent of shootings occurred in 9.4% of census tracts. In all cities combined, a decile rise in SVI resulted in a 37% increase in shooting incidents (p < 0.001). A similar relationship existed in each city: 30% increase in Baltimore (p < 0.001), 50% in Chicago (p < 0.001), 28% in Los Angeles (p < 0.001), 34% in New York City (p < 0.001), and 41% in Philadelphia (p < 0.001). Shootings were highly clustered within the most vulnerable neighborhoods. CONCLUSIONS: In 5 major US cities, firearm violence was concentrated in neighborhoods with high social vulnerability. A tool such as the SVI could be used to inform prevention efforts by directing resources to communities most in need and identifying factors on which to focus these programs and policies.

Early Prediction of Massive Transfusion for Patients With Traumatic Hemorrhage: Development of a Multivariable Machine Learning Model.

Objective: Develop a novel machine learning (ML) model to rapidly identify trauma patients with severe hemorrhage at risk of early mortality. Background: The critical administration threshold (CAT, 3 or more units of red blood cells in a 60-minute period) indicates severe hemorrhage and predicts mortality, whereas early identification of such patients improves survival. Methods: Patients from the PRospective, Observational, Multicenter, Major Trauma Transfusion and Pragmatic, Randomized Optimal Platelet, and Plasma Ratio studies were identified as either CAT+ or CAT-. Candidate variables were separated into 4 tiers based on the anticipated time of availability during the patient's assessment. ML models were created with the stepwise addition of variables and compared with the baseline performance of the assessment of blood consumption (ABC) score for CAT+ prediction using a cross-validated training set and a hold-out validation test set. Results: Of 1245 PRospective, Observational, Multicenter, Major Trauma Transfusion and 680 Pragmatic, Randomized Optimal Platelet and Plasma Ratio study patients, 1312 were included in this analysis, including 862 CAT+ and 450 CAT-. A CatBoost gradient-boosted decision tree model performed best. Using only variables available prehospital or on initial assessment (Tier 1), the ML model performed superior to the ABC score in predicting CAT+ patients [area under the receiver-operator curve (AUC = 0.71 vs 0.62)]. Model discrimination increased with the addition of Tier 2 (AUC = 0.75), Tier 3 (AUC = 0.77), and Tier 4 (AUC = 0.81) variables. Conclusions: A dynamic ML model reliably identified CAT+ trauma patients with data available within minutes of trauma center arrival, and the quality of the prediction improved as more patient-level data became available. Such an approach can optimize the accuracy and timeliness of massive transfusion protocol activation.

Tranexamic Acid, Mortality, and Intracranial Hemorrhage Type in Moderate or Severe Traumatic Brain Injury.

This cohort study examines the association of tranexamic acid administration with intracranial hemorrhage type, neurologic outcomes, and mortality in patients with traumatic brain injury.

A novel machine-learning tool to identify community risk for firearm violence: The Firearm Violence Vulnerability Index.

BACKGROUND: Firearm violence in the United States is a public health crisis, but accessing accurate firearm assault data to inform prevention strategies is a challenge. Vulnerability indices have been used in other fields to better characterize and identify at-risk populations during crises, but no tool currently exists to predict where rates of firearm violence are highest. We sought to develop and validate a novel machine-learning algorithm, the Firearm Violence Vulnerability Index (FVVI), to forecast community risk for shooting incidents, fill data gaps, and enhance prevention efforts. METHODS: Open-access 2015 to 2022 fatal and nonfatal shooting incident data from Baltimore, Boston, Chicago, Cincinnati, Los Angeles, New York City, Philadelphia, and Rochester were merged on census tract with 30 population characteristics derived from the 2020 American Community Survey. The data set was split into training (80%) and validation (20%) sets; Chicago data were withheld for an unseen test set. XGBoost, a decision tree-based machine-learning algorithm, was used to construct the FVVI model, which predicts shooting incident rates within urban census tracts. RESULTS: A total of 64,909 shooting incidents in 3,962 census tracts were used to build the model; 14,898 shooting incidents in 766 census tracts were in the test set. Historical third grade math scores and having a parent jailed during childhood were population characteristics exhibiting the greatest impact on FVVI's decision making. The model had strong predictive power in the test set, with a goodness of fit ( D2 ) of 0.77. CONCLUSION: The Firearm Violence Vulnerability Index accurately predicts firearm violence in urban communities at a granular geographic level based solely on population characteristics. The Firearm Violence Vulnerability Index can fill gaps in currently available firearm violence data while helping to geographically target and identify social or environmental areas of focus for prevention programs. Dissemination of this standardized risk tool could also enhance firearm violence research and resource allocation. LEVEL OF EVIDENCE: Prognostic and Epidemiological; Level IV.

Social Vulnerability Index is strongly associated with urban pediatric firearm violence: An analysis of five major US cities.

BACKGROUND: Firearm-related injury in children is a public health crisis. The Social Vulnerability Index (SVI) identifies communities at risk for adverse effects due to natural or human-caused crises. We sought to determine if SVI was associated with pediatric firearm-related injury and thus could assist in prevention planning. METHODS: The Centers for Disease Control and Prevention's 2018 SVI data were merged on census tract with 2015 to 2022 open-access shooting incident data in children 19 years or younger from Baltimore, Chicago, Los Angeles, New York City, and Philadelphia. Regression analyses were performed to uncover associations between firearm violence, SVI, SVI themes, and social factors at the census tract level. RESULTS: Of 11,654 shooting incidents involving children, 52% occurred in just 6.7% of census tracts, which were on average in the highest quartile of SVI. A decile increase in SVI was associated with a 45% increase in pediatric firearm-related injury in all cities combined (incidence rate ratio, 1.45; 95% confidence interval, 1.41-1.49; p < 0.001). A similar relationship was found in each city: 30% in Baltimore, 51% in Chicago, 29% in Los Angeles, 37% in New York City, and 35% in Philadelphia (all p < 0.001). Socioeconomic status and household composition were SVI themes positively associated with shootings in children, as well as the social factors below poverty, lacking a high school diploma, civilian with a disability, single-parent household, minority, and no vehicle access. Living in areas with multi-unit structures, populations 17 years or younger, and speaking English less than well were negatively associated. CONCLUSION: Geospatial disparities exist in pediatric firearm-related injury and are significantly associated with neighborhood vulnerability. We demonstrate a strong association between SVI and pediatric shooting incidents in multiple major US cities. Social Vulnerability Index can help identify social and structural factors, as well as geographic areas, to assist in developing meaningful and targeted intervention and prevention efforts. LEVEL OF EVIDENCE: Prognostic and Epidemiological; Level III.

Big data: More than big data sets.

The term big data has been popularized over the past decade and is often used to refer to data sets that are too large or complex to be analyzed by traditional means. Although the term has been utilized for some time in business and engineering, the concept of big data is relatively new to medicine. The reception from the medical community has been mixed; however, the widespread utilization of electronic health records in the United States, the creation of large clinical data sets and national registries that capture information on numerous vectors affecting healthcare delivery and patient outcomes, and the sequencing of the human genome are all opportunities to leverage big data. This review was inspired by a lively panel discussion on big data that took place at the 75th Central Surgical Association Annual Meeting. The authors' aim was to describe big data, the methodologies used to analyze big data, and their practical clinical application.

The impact of changes in radiographic sarcopenia on overall survival in older adults undergoing different treatment pathways for pancreatic cancer.

OBJECTIVE: Sarcopenia is associated with poor outcomes in patients undergoing surgery for pancreatic ductal adenocarcinoma (PDAC). However, few studies have assessed changes in sarcopenia during multimodality therapy or its effect on overall survival (OS). METHODS: Computed tomography (CT) total psoas area index (TPAI) and weighted average Hounsfield units (HU) were measured at each treatment interval in patients with resectable PDAC. Four cohorts were compared: 1. Neoadjuvant chemotherapy plus surgery plus adjuvant chemotherapy ("NSA"; n = 20); 2. surgery plus adjuvant chemotherapy ("SA"; n = 20); 3. neoadjuvant chemotherapy with intent to perform surgery ("Chemotherapy"; n = 24); and 4. treated with palliative intent ("Palliative"; n = 21). RESULTS: Fifty-nine deaths were identified. Median OS was 15.7 months (95% Confidence Interval (CI) 12.7-20.2). Patients who underwent surgery had a higher OS (p < 0.001), with the SA group having a longer OS than the NSA group. Cox regression models identified baseline TPAI (Hazard Ratio (HR) = 0.82; p = 0.04), but not psoas HU, as a significant predictor of OS. The mean decrease in TPAI following neoadjuvant chemotherapy was 0.6 cm2/m2 (p < 0.001; 95% CI -0.8--0.3) and the mean decrease in HU was 2.7 (p = 0.04, 95% CI -5.4--0.1). For patients who underwent surgery (NSA and SA cohorts), a decrease in TPAI was associated with worse OS (HR 0.52; p = 0.05). In contrast, decreased HU was associated with worse OS in patients who did not undergo surgery (HR 0.93; p = 0.01). CONCLUSIONS: In patients who received neoadjuvant chemotherapy, there was a significant decrease in TPAI and HU during treatment. Prospective studies are warranted to assess the impact of TPAI loss and HU changes on clinical outcomes to better individualize treatment pathways based on a patient's fitness.

Liver transplant offers a survival benefit over margin negative resection in patients with small unifocal hepatocellular carcinoma and preserved liver function.

BACKGROUND: Studies comparing orthotopic liver transplantation to margin negative resection for patients with small unifocal hepatocellular carcinoma have not controlled for degree of cirrhosis. METHODS: The National Cancer Database was used to identify patients with preserved liver function (Model for End-stage Liver Disease score ≤12) who underwent orthotopic liver transplantation or margin negative resection for American Joint Committee on Cancer stage I hepatocellular carcinoma lesions <3 cm between 2010 and 2013. Multivariable and Cox regression adjusting for age, demographics, comorbid disease burden, Model for End-stage Liver Disease score, tumor size, and operation were used to compare overall survival between cohorts. RESULTS: In the study, 241 (53%) patients underwent orthotopic liver transplantation. In addition, 219 (47%) underwent margin negative resection. On multivariable regression, patients having a Charlson comorbidity score ≥2 were more likely to undergo orthotopic liver transplantation, (odds ratio 1.94, P=.03). African American patients (odds ratio 0.44, P=.02), and patients of advanced age (odds ratio 0.92, P<.001) were more likely to undergo margin negative resection. Patients undergoing orthotopic liver transplantation had longer overall survival than those undergoing margin negative resection (median OS not reached versus 67.6 months, P<.001). Multivariable Cox regression identified surgical procedure as the only independent determinant of survival with margin negative resection conferring a nearly 3-fold increased risk of death (hazard ratio 2.86, P<.001). CONCLUSION: Orthotopic liver transplantation offers a survival advantage relative to margin negative resection for patients with small unifocal hepatocellular carcinoma and preserved liver function.

Can Comprehensive Imaging Analysis with Analytic Morphomics and Geriatric Assessment Predict Serious Complications in Patients Undergoing Pancreatic Surgery?

We aimed to determine whether comprehensive imaging analysis with analytic morphomics (AM) enhances or replaces geriatric assessment (GA) in risk-stratifying pancreatic surgery patients. One hundred thirty-four pancreatic surgery patients were identified from a prospective cohort. Sixty-three patients in the cohort had preoperative CT scans in addition to comprehensive geriatric assessments. CT scans were processed using AM. Associations with National Surgical Quality Improvement Program (NSQIP) serious complications were evaluated using univariate analysis and robust elastic net modeling to obtain AUROC curves by adding AM and GA measures to our previously defined clinical base risk model (age, body mass index, American Society of Anesthesiologists classification, and Charlson comorbidity index). NSQIP serious complications were associated with low psoas Hounsfield units (HUs) (p = 0.002), low-density (0 to 30 HU) psoas area (p = 0.01), visceral fat HU (p ≤ 0.001), visceral fat area (p = 0.009), subcutaneous fat HU (p = 0.023), and total body area (p = 0.012) on univariate analysis. Elastic net models incorporating the base model with geriatric assessment and psoas HU (AUC = 0.751), and AM alone (AUC = 0.739) have greater predictive value than the base model alone (AUC = 0.601). The model utilizing AM and GA in combination had the highest predictive value (AUC = 0.841). When combined, AM and GA improve prediction of NSQIP serious complications compared to either technique alone. The additive nature of these two modalities suggests they likely capture unique aspects of a patient's fitness for surgery.

Implementing a resident acute care surgery service: Improving resident education and patient care.

BACKGROUND: To simulate the duties and responsibilities of an attending surgeon and allow senior residents more intraoperative and perioperative autonomy, our program created a new resident acute care surgery consult service. METHODS: We structured resident acute care surgery as a new admitting and inpatient consult service managed by chief and senior residents with attending supervision. When appropriate, the chief resident served as a teaching assistant in the operation. Outcomes were recorded prospectively and reviewed at weekly quality improvement conferences. The following information was collected: (1) teaching assistant case logs for senior residents preimplentation (n = 10) and postimplementation (n = 5) of the resident acute care surgery service; (2) data on the proportion of each case performed independently by residents; (3) resident evaluations of the resident acute care surgery versus other general operative services; (4) consult time for the first 12 months of the service (June 2014 to June 2015). RESULTS: During the first year after implementation, the number of total teaching assistant cases logged among graduating chief residents increased from a mean of 13.4 ± 13.0 (range 4-44) for preresident acute care surgery residents to 30.8 ± 8.8 (range 27-36) for postresident acute care surgery residents (P < .01). Of 323 operative cases, the residents performed an average of 82% of the case independently. There was a significant increase in the satisfaction with the variety of cases (mean 5.08 vs 4.52, P < .01 on a 6-point Likert scale) and complexity of cases (mean 5.35 vs 4.94, P < .01) on service evaluations of resident acute care surgery (n = 27) in comparison with other general operative services (n = 127). In addition, creation of a 1-team consult service resulted in a more streamlined consult process with average consult time of 22 minutes for operative consults and 25 minutes for nonoperative consults (range 5-90 minutes). CONCLUSION: The implementation of a resident acute care surgery service has increased resident autonomy, teaching assistant cases, and satisfaction with operative case variety, as well as the efficiency of operative consultation at our institution.

A large-scale complex haploinsufficiency-based genetic interaction screen in Candida albicans: analysis of the RAM network during morphogenesis.

The morphogenetic transition between yeast and filamentous forms of the human fungal pathogen Candida albicans is regulated by a variety of signaling pathways. How these pathways interact to orchestrate morphogenesis, however, has not been as well characterized. To address this question and to identify genes that interact with the Regulation of Ace2 and Morphogenesis (RAM) pathway during filamentation, we report the first large-scale genetic interaction screen in C. albicans.Our strategy for this screen was based on the concept of complex haploinsufficiency (CHI). A heterozygous mutant of CBK1(cbk1Δ/CBK1), a key RAM pathway protein kinase, was subjected to transposon-mediated, insertional mutagenesis. The resulting double heterozygous mutants (6,528 independent strains) were screened for decreased filamentation on SpiderMedium (SM). From the 441 mutants showing altered filamentation, 139 transposon insertion sites were sequenced,yielding 41 unique CBK1-interacting genes. This gene set was enriched in transcriptional targets of Ace2 and, strikingly, the cAMP-dependent protein kinase A (PKA) pathway, suggesting an interaction between these two pathways. Further analysis indicates that the RAM and PKA pathways co-regulate a common set of genes during morphogenesis and that hyperactivation of the PKA pathway may compensate for loss of RAM pathway function. Our data also indicate that the PKA­regulated transcription factor Efg1 primarily localizes to yeast phase cells while the RAM­pathway regulated transcription factor Ace2 localizes to daughter nuclei of filamentous cells, suggesting that Efg1 and Ace2 regulate a common set of genes at separate stages of morphogenesis. Taken together, our observations indicate that CHI­based screening is a useful approach to genetic interaction analysis in C. albicans and support a model in which these two pathways regulate a common set of genes at different stages of filamentation.