The impact of high-frequency linear transducer on the accuracy of pelvic ultrasound in early pregnancy pelvic pain and bleeding.

INTRODUCTION: The primary concern of emergency physicians (EPs) in symptomatic patients in their early pregnancy is to rule out ectopic pregnancy by identifying a definite intrauterine pregnancy (IUP). Then an assessment of viability is required for the IUPs. Although transvaginal ultrasound (TVUS) stands as the best modality for these patients, it is not available in most emergency settings. This study aimed to investigate the effects of high-frequency linear transducers (HFLT) on the accuracy of point-of-care ultrasound (POCUS) for detection of IUP and the agreement between EPs and obstetricians for patients' diagnosis. METHOD: A convenience sample of pregnant patients who presented to the emergency department (ED) with vaginal bleeding and abdominopelvic pain was included. The characteristics of diagnostic tests of transabdominal POCUS performed by EPs were compared to TVUS. RESULTS: The study population was finalized as 143 patients. For the definite IUP, the diagnostic accuracy of POCUS was 93.0%, with a sensitivity of 89.0%, a specificity of 100%, compared to an accuracy of 97.9% for POCUS plus HFLT with a sensitivity of 96.7%, a specificity of 100%. For the identification of fetal cardiac activity (FCA), utilizing HFLT improved the diagnostic accuracy to 97.9% (from 94.4%) and sensitivity to 95.5% (from 88.1%). In addition, the agreement between the EPs and obstetricians concerning the classification of ED diagnosis was excellent (agreement: 96.5%, kappa: 0.943, p < 0.0001). CONCLUSION: POCUS plus HFLT performed by EPs in evaluating symptomatic patients in their first-trimester pregnancy improves the accuracy to a non-inferior level compared to TVUS performed by obstetricians. Hence, EPs can securely rely on POCUS to confirm IUP and FCA. However, they should be cautious about using it as a rule-out tool. Moreover, HFLT use could enhance the accuracy of POCUS in viability assessment as an alternative to TVUS.

Diagnostic Accuracy of Early Systolic Notching in Pulmonary Embolism.

OBJECTIVE: Recently, a cardiac sonography finding, early systolic notching (ESN), was reported with high sensitivity and specificity for the diagnosis of pulmonary embolism (PE) in a limited population. The aim of this study was to determine the diagnostic accuracy of ESN finding for PE in emergency department (ED) patients. METHOD: This prospective multicenter study was conducted in 4 academic EDs. All patients who underwent computed tomography angiography for suspected PE were included in the study. After inclusion, cardiac ultrasound including the right ventricular outflow tract Doppler signal was performed. The diagnostic tests of ESN finding were used for PE and its subgroups. RESULTS: In the study, 183 of 201 patients met the study criteria. Of all patients, 52.5% had PE (n = 96), and 19.7% (n = 36) had ESN finding. In all ED patients, the sensitivity of ESN for PE was 34% (95% CI 25-45), and the specificity was 97% (95% CI 90-99). In the subgroup analysis, the sensitivity of ESN for PE with high or intermediate-high risk was 69% (95% CI 49-85), and the specificity was 90% (95% CI 84-94). Inter-rater reliability for ESN finding between the cardiologist and emergency physician was strong with a kappa statistic of 0.87. CONCLUSION: The pulmonary Doppler flow of ESN was moderate to high specific but low sensitive for PE in all ED patients. In the subgroup analysis, this finding was moderate specific and low sensitive.

Effect of a cervical collar on optic nerve sheath diameter in trauma patients.

BACKGROUND: As advocated in advanced trauma life support and prehospital trauma life support protocols, cervical immobilization is applied until cervical spine injury is excluded. This study aimed to show the difference in optic nerve sheath diameter (ONSD) between patients with and without a cervical collar using computed tomography (CT). METHODS: This was a single-center, retrospective study examining trauma patients who presented to the emergency department between January 1, 2021, and December 31, 2021. The ONSD on brain CT of the trauma patients was measured and analyzed to determine whether there was a difference between the ONSD with and without the cervical collar. RESULTS: The study population consisted of 169 patients. On CT imaging of patients with (n=66) and without (n=103) cervical collars, the mean ONSD in the axial plane were 5.43 ± 0.50 mm and 5.04 ± 0.46 mm respectively for the right eye and 5.50 ± 0.52 mm and 5.11 ± 0.46 mm respectively for the left eye. The results revealed an association between the presence of a cervical collar and the mean ONSD, which was statistically significant (P<0.001) for both the right and left eyes. CONCLUSION: A cervical collar may be associated with increased ONSD. The effect of this increase in the ONSD on clinical outcomes needs to be investigated, and the actual need for cervical collar in the emergency department should be evaluated on a case-by-case basis.

The Diagnostic Accuracy of the Hounsfield Unit Value in Pulmonary Embolism.

Objective: Pulmonary embolism (PE) a vascular disease. Computed tomography pulmonary angiography (CTPA) is the radiological imaging technique used to diagnose PE. In this study, we aimed to demonstrate the diagnostic accuracy of Hounsfield Unit (HU) value for PE based on the hypothesis that acute thrombosis causes an increase in HU value on computed tomography (CT). Methods: This research was as a single-center, retrospective study. Patients presenting to the emergency department (ED) diagnosed with PE on CTPA were enrolled as the study group. In addition, patients admitted to the same emergency department who were not diagnosed with PE and had non-contrast CT scans were included as the control group. A receiver operating curve (ROC) was produced to the diagnostic accuracy of HU values in predicting PE. Results: The study population (N=74) consisted of a study group (N=46) and a control group (N=28). The sensitivity and specificity of HU value for predicting PE on thoracic CT were found 61.5% and 96.4% at a value of 54.8 (Area Under the Curve (AUC):0.690) for right main pulmonary artery; 65.0% and 96.4% at a value of 55.9 (AUC:0.736) for left main pulmonary artery; 44.4% and 96.4% at a value of 62.7 (AUC:0.615) for right interlobar artery; and 60.0% and 92.9% at a value of 56.7 (AUC:0.736) for left interlobar artery. Conclusion: HU values may exhibit high diagnostic specificity on CT, for thrombi up to the interlobar level. An HU value exceeding 54.8 up to the interlobar level may raise suspicion of the presence of PE.

February 6th, Kahramanmaras earthquakes and the disaster management algorithm of adult emergency medicine in Turkey: An experience review.

This compilation covers emergency medical management lessons from the February 6th Kahramanmaras earthquakes. The objective is to review relevant literature on emergency services patient management, focusing on Koenig's 1996 Simple Triage and Rapid Treatment (START) and Secondary Assessment of Victim Endpoint (SAVE) frameworks. Establishing a comprehensive seismic and mass casualty incident (MCI) protocol chain is the goal. The prehospital phase of seismic MCIs treats hypovolemia and gets patients to the nearest hospital. START-A plans to expedite emergency patient triage and pain management. The SAVE algorithm is crucial for the emergency patient secondary assessment. It advises using Glasgow Coma Scale, Mangled Extremity Severity Score, Burn Triage Score, and Safe Quake Score for admission, surgery, transfer, discharge, and outcomes. This compilation emphasizes the importance of using diagnostic tools like bedside blood gas analyzers and ultrasound devices during the assessment process, drawing from 6 February earthquake research. The findings create a solid framework for improving emergency medical response strategies, making them applicable in similar situations.

The Effect of Meteorological Factors on the COVID-19 Pandemic in Northeast Turkiye.

Introduction Although various studies have been conducted on the relationship between meteorological factors and coronavirus disease 2019 (COVID-19), this issue has not been sufficiently clarified. In particular, there are a limited number of studies on the course of COVID-19 in the warmer-humidity seasons. Methods Patients presenting to the emergency departments of health institutions and to clinics set aside for cases of suspected COVID-19 in the province of Rize between 1 June and 31 August 2021 and who met the case definition based on the Turkish COVID-19 epidemiological guideline were included in this retrospective study. The effect of meteorological factors on case numbers throughout the study was investigated. Results During the study period, 80,490 tests were performed on patients presenting to emergency departments and clinics dedicated to patients with suspected COVID-19. The total case number was 16,270, with a median daily number of 64 (range 43-328). The total number of deaths was 103, with a median daily figure of 1.00 (range 0.00-1.25). According to the Poisson distribution analysis, it is found that the number of cases tended to increase at temperatures between 20.8 and 27.2°C. Conclusion It is predicted that the number of COVID-19 cases will not decrease with the increase in temperature in temperate regions with high rainfall. Therefore, unlike influenza, there may not be seasonal variation in the prevalence of COVID-19. The requisite measures should be adopted in health systems and hospitals to manage increases in case numbers associated with changes in meteorological factors.

The role of repeated extended FAST in patients with stable blunt thoracoabdominal trauma.

BACKGROUND: Thoracic and abdominal computed tomography scans are widely used modalities for trauma patients in emergency department (ED). However, alternative diagnostic and follow-up tools are also needed, due to limitations such as high cost and exces-sive radiation exposure. This study aimed to investigate the utility of repeated extended focused abdominal sonography for trauma (rE-FAST) performed by the emergency physician in patients with stable blunt thoracoabdominal trauma. METHODS: This was a prospective, single-center diagnostic accuracy study. Patients with blunt thoracoabdominal trauma admitted to the ED were included in the study. The E-FAST was performed on the patients included in the study at the 0th h, the 3rd h, and the 6th h during their follow-up. Then, the diagnostic accuracy metrics of E-FAST and rE-FAST were calculated. RESULTS: The sensitivity and specificity of E-FAST in determining thoracoabdominal pathologies were found to be 75% and 98.7%, respectively. The sensitivity and specificity for specific pathologies were 66.7% and 100% for pneumothorax, 66.7% and 98.8% for hemothorax, and 66.7% and 100% for hemoperitoneum, respectively. The sensitivity and specificity of rE-FAST in determining thoracal and/or abdominal hemorrhage in stable patients were found to be 100% and 98.7%, respectively. CONCLUSION: E-FAST successfully rules in thoracoabdominal pathologies in patients with blunt trauma, with its high specificity. However, only a rE-FAST might be sensitive enough to exclude traumatic pathologies in these stable patients.

Predicting COVID-19 Outcomes: Machine Learning Predictions Across Diverse Datasets.

Background The COVID-19 infection has spread rapidly since its emergence and has affected a large part of the global population. With the increasing number of cases, researchers are trying to predict the prognosis of patients by using different data with artificial intelligence methods such as machine learning (ML). In this study, we aimed to predict mortality risk in COVID-19 patients using ML algorithms with different datasets. Methodology In this retrospective study, we evaluated the fever, oxygen saturation, laboratory results, thorax computed tomography (CT) findings, and comorbid diseases at admission to the hospital of 404 patients whose diagnosis was confirmed by the reverse transcription polymerase chain reaction test. Different datasets were created by combining the data. The Synthetic Minority Oversampling Technique was used to reduce the imbalance in the dataset. K-nearest neighbors, support vector machine, stochastic gradient descent, random forest, neural network, naive Bayes, logistic regression, gradient boosting, XGBoost, and AdaBoost models were used to create the ML algorithm, and the accuracy rates of mortality prediction were compared. Results When the dataset was created with CT parenchyma score, pulmonary artery and inferior vena cava diameters, and laboratory results, mortality was predicted with an accuracy of 98.4% with the gradient boosting model. Conclusions The study demonstrates that patient prognosis can be accurately predicted using simple measurements from thorax CT scans and laboratory findings.