Journal of Emergencies, Trauma, and Shock最新文献

As traumatic brain injuries (TBIs) continue to rise annually, scientists are continuing to improve point-of-care (POC) testing, involved in TBI diagnosis. TBIs, having various levels of severity, are often misdiagnosed or overlooked, especially in acute mild TBI or concussion scenarios. At the POC, currently, medical professionals utilize neuroimaging, cognitive scales, and biomarker assays to diagnose concussions and other forms of TBI. However, many of these parameters hinder diagnostic value due to accessibility and time-sensitive restraints. After analyzing the profuse research surrounding time sensitive concussion biomarkers kinetics, in the National Institute of Health National Library of Medicine database, this review aims to compile all published research on concussion POC biomarkers, screened between 2022 and 2023. Commonly studied concussion POC biomarkers include ubiquitin C-terminal hydrolase L1, glial fibrillary acidic protein, visinin-like protein-1, S100 calcium-binding protein B, tau, and neurofilament light chain. Each neurologic biomarker has various implications and limitations when characterizing TBI. Novel biomarkers and multimodal paired concussion parameter models are continuously being evaluated for their respective diagnostic strengths and weaknesses.

Introduction: In clinical practice, it is common to see stroke and trauma simultaneously in the same patient. When such a patient presents to the emergency department (ED), rapid assessment must be done to adequately manage both conditions. As the assessment will cover a significant number of steps and tasks to be accomplished, it may prove challenging, especially for a novice practitioner. As a result, key diagnostic signs may be missed or overlooked. This may cause nondiagnosis, misdiagnosis, or delay in the handling of time-dependent diagnoses (e.g. thrombolytic therapy decision for stroke and recognition of early shock in trauma). Therefore, the need for a comprehensive approach to the management of the patient who has simultaneous acute stroke and trauma is needed.

Methods: We propose the Stroke-Trauma (STRAUMA) Code framework for use in the ED and by first-line healthcare staff. We used a trans-continental approach by testing our proposed STRAUMA framework at two centers: in the Department of Emergency Medicine at Singapore General Hospital in Singapore and in the Emergency Care Center at Sarasota Memorial Hospital in Sarasota, Florida, USA.

Results: Both teams agreed that the new proposed STRAUMA Code framework is systematic, structured, and organized thus making it easier to apply in the clinical setting.

Conclusion: A structured approach to manage the more complex cases presenting to the ED is useful so as not to miss important and often critical information and steps which will affect patient management as well as outcomes.

Introduction: Triage is a critical process in prioritizing patients based on acuity to ensure timely care. Patients arrive at the emergency department (ED) with complaints, not diagnoses. High-risk patients are identified based on history, vital signs, mechanism of injury in trauma, and clinical findings. Chief complaints in the ED may suggest acuity independent of other clinical parameters. The objective of this study was to identify high-risk chief complaints associated with intensive care unit (ICU) admission or mortality within 72 h of ED presentation. We also characterized the chief complaints by frequency and evaluated the accuracy of the All India Institute of Medical Sciences Triage Protocol (ATP) in conjunction with high-risk complaints for predicting mortality.

Methods: This prospective observational study was conducted at AIIMS, New Delhi, from March 2021 to October 2023, including 1225 patients. Inclusion criteria covered all patients older than 16 years presenting to the ED, excluding cardiac arrest cases, pregnancy-related complications, and individuals declared dead on arrival. Data were collected using predesigned proformas. Univariate and multivariate logistic regression analyses identified high-risk chief complaints.

Results: Of the 1754 patients screened, 1225 were included in the analysis. Thirty-four complaints were identified, with six deemed high risk. Specific complaints such as shortness of breath (odds ratio [OR] 43.691, 95% confidence interval [CI] 20.033-95.291, P = 0.001), altered mental status (OR: 6.243, 95% CI: 3.282-11.876, P < 0.001), hematemesis (OR: 3.88, 95% CI: 2.019-7.454, P < 0.001), fall from height (OR: 3.875, 95% CI: 1.874-8.014, P < 0.001), weakness of one side (OR: 3.159, 95% CI: 1.656-6.024, P < 0.001), and chest pain (OR: 1.784, 95% CI: 1.22-3.209, P = 0.043) were significantly associated with adverse outcomes (mortality or ICU admission) at 72 h, even after adjusting for age, gender, and comorbidities. Incorporating high-risk complaints into the ATP triage system increased predictive value (OR 3.12 vs. 7.14).

Conclusion: Our findings highlight specific chief complaints as valuable indicators for the early identification of patients at risk of 72-h mortality or ICU admission in the ED. Early identification of high-risk patients can enhance early resuscitation, timely referral to higher-level care, and improve patient outcomes.

Introduction: An initial systolic blood pressure (SBP1) of <110 mmHg has been shown to predict mortality. However, SBP1 may not reflect hemodynamic changes during initial resuscitation. We aimed to determine if the second recorded blood pressure (SBP2) could provide additional prognostic value.

Methods: An 8-year retrospective chart review was performed including patients who underwent trauma activations at a single institution. The initial systolic blood pressure (SBP 1) and second systolic blood pressure (SBP 2) were analyzed. Difference between the first and second systolic blood pressure (ΔSBP) was defined as SBP2 - SBP1. The primary outcome was inhospital mortality, and the secondary outcome was receipt of ≥2 units of blood in the first 4 h of admission. Univariable analysis and logistic regression analysis were performed to assess the relationship of SBP2 and ΔSBP with the study outcomes. Regression model fit was assessed by the likelihood ratio test and Akaike information criterion.

Results: Eight thousand seven hundred and ninety-eight patients were included with 12% and 13% presenting with SBP1 <110 mmHg and SBP2 <110 mmHg, respectively. Four hundred and six (5%) died and 327 (4%) received ≥2 units of blood in the first 4 h. The addition of ΔSBP to regression models improved model fit in explaining the primary and secondary outcomes. Subgroup analysis found that the addition of ΔSBP improved model fit for those with penetrating mechanism of injury and those with Injury Severity Score of ≥9, but not for those with blunt moderate or severe traumatic brain injury.

Conclusion: SBP2 offers additional prognostic value in predicting trauma outcomes. Incorporating subsequent hemodynamic data during resuscitation beyond the initial SBP in trauma databases should be considered.

Introduction: The objective of this study was to investigate the predictive value of thromboelastography (TEG) combined with conventional coagulation test parameters for the clinical outcome of patients with trauma-induced coagulopathy (TIC) and establish and evaluate a clinical nomogram for predicting the prognosis of TIC patients.

Methods: Clinical data of severe multiple trauma patients who underwent emergency treatment in the hospital from November 2018 to August 2021 were enrolled retrospectively. The prognosis was evaluated according to the length of hospital stay and the 30-day survival rate. Multivariable logistic regression model was used to evaluate the correlation between TEG parameters and clinical outcomes. A nomogram model was constructed and the receiver operating characteristic (ROC) curve was used to evaluate the predictive value.

Results: Univariate analysis indicated that there were significant differences in age, hypertension, temperature fluctuation (>3°C), transfusion, kinetics time (K), angle (α) value, maximal amplitude (MA), and international normalized ratio between the good and poor outcome group (P < 0.05). Multivariate logistic regression analysis showed that age, Glasgow Coma Scale scores, temperature fluctuation (>3°C), and MA parameters were independent risk factors for poor outcome, and we established the nomogram prediction model. According to ROC curve analysis, the area under the curve for MA parameter was 0.689 (95% confidence interval [CI]: 0.610-0.760), and the corresponding sensitivity and specificity were 44.12% and 91.87%, respectively. The area under the curve for temperature fluctuation (>3°C) was 0.697 (95% CI: 0.618-0.768), and the corresponding sensitivity and specificity were 60.00% and 79.67%, respectively.

Conclusion: TEG parameters combined with relevant clinical indicators can be used to evaluate the prognosis of TIC patients with severe multiple trauma. The establishment of correlation nomogram model was guiding significance for clinical evaluation of long-term prognosis of trauma patients.