Within the GRADE (Grading of Recommendations Assessment, Development and Evaluation) framework, we performed a systematic review and developed evidence-based recommendations to answer the following ...PICO (Population, Intervention, Comparator, Outcomes) question: should patients who present pulseless after critical injuries (with and without signs of life after penetrating thoracic, extrathoracic, or blunt injuries) undergo emergency department thoracotomy (EDT) (vs. resuscitation without EDT) to improve survival and neurologically intact survival?
All patients who underwent EDT were included while those involving either prehospital resuscitative thoracotomy or operating room thoracotomy were excluded. Quantitative synthesis via meta-analysis was not possible because no comparison or control group (i.e., survival or neurologically intact survival data for similar patients who did not undergo EDT) was available for the PICO questions of interest.
The 72 included studies provided 10,238 patients who underwent EDT. Patients presenting pulseless after penetrating thoracic injury had the most favorable EDT outcomes both with (survival, 182 21.3% of 853; neurologically intact survival, 53 11.7% of 454) and without (survival, 76 8.3% of 920; neurologically intact survival, 25 3.9% of 641) signs of life. In patients presenting pulseless after penetrating extrathoracic injury, EDT outcomes were more favorable with signs of life (survival, 25 15.6% of 160; neurologically intact survival, 14 16.5% of 85) than without (survival, 4 2.9% of 139; neurologically intact survival, 3 5.0% of 60). Outcomes after EDT in pulseless blunt injury patients were limited with signs of life (survival, 21 4.6% of 454; neurologically intact survival, 7 2.4% of 298) and dismal without signs of life (survival, 7 0.7% of 995; neurologically intact survival, 1 0.1% of 825).
We strongly recommend that patients who present pulseless with signs of life after penetrating thoracic injury undergo EDT. We conditionally recommend EDT for patients who present pulseless and have absent signs of life after penetrating thoracic injury, present or absent signs of life after penetrating extrathoracic injury, or present signs of life after blunt injury. Lastly, we conditionally recommend against EDT for pulseless patients without signs of life after blunt injury.
Systematic review/guideline, level III.
BACKGROUND: Recent data from military and civilian centers suggest that mortality is decreased in massive transfusion patients by increasing the transfusion ratio of plasma and platelet (PLT) ...products, and fibrinogen in relationship to red blood cell (RBC) products during damage control resuscitation and surgery. This study investigates the relationship of plasma:RBC, PLT:RBC, and cryoprecipitate:RBC transfusion ratios to mortality in massively transfused patients at a civilian Level 1 trauma center.
STUDY DESIGN AND METHODS: Demographic, laboratory, transfusion, and outcome data were collected prospectively from February 1, 2007, to January 31, 2009, and retrospectively from February 1, 2005, to January 31, 2007, on all injured patients who underwent massive transfusion (defined as ≥10 RBC products within 24 hr). Mortality was analyzed in relation to the plasma:RBC, PLT:RBC, and cryoprecipitate:RBC transfusion ratios using both univariate and multivariate analyses.
RESULTS: A total of 214 patients received massive transfusion secondary to traumatic injury. High versus low transfusion ratios were associated with improved 30‐day survival: plasma:RBC 59% versus 44%, p = 0.03; PLT:RBC 63% versus 33%, p < 0.01; and cryoprecipitate:RBC 66% versus 41%, p < 0.01. By multivariable stepwise logistic regression analysis, increased plasma:RBC (p = 0.02) and PLT:RBC (p = 0.02), and decreased age (p = 0.02), ISS (p < 0.01) and total RBCs (p = 0.03) were statistically associated with improved 30‐day survival.
CONCLUSIONS: In the civilian setting, plasma, PLT, and cryoprecipitate products significantly increased 30‐day survival in trauma patients. Future prospective randomized clinical trials are required to determine the optimal transfusion ratios.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Diagnostic Test/Criteria; Level IV.
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.
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.
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).
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.
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.
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.
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.
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.
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.
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