Acute coronary syndrome (ACS) is a serious condition arising from an imbalance of supply and demand to meet myocardium's metabolic needs. Patients typically present with retrosternal chest pain radiating to neck and left arm. Electrocardiography (ECG) and laboratory tests are used indiagnosis. However in emergency departments, there are some difficulties for physicians to decide whether hospitalizing, following up or discharging the patient. The aim of the study is to diagnose ACS and helping the physician with his decisionto discharge or to hospitalizevia machine learning techniques such as support vector machine (SVM) by using patient data including age, sex, risk factors, and cardiac enzymes (CK-MB, Troponin I) of patients presenting to emergency department with chest pain. Clinical, laboratory, and imaging data of 228 patients presenting to emergency department with chest pain were reviewedand the performance of support vector machine. Four different methods (Support vector machine (SVM), Artificial neural network (ANN), Naïve Bayes and Logistic Regression) were tested and the results of SVM which has the highest accuracy is reported. Among 228 patients aged 19 to 91 years who were included in the study, 99 (43.4 %) were qualified as ACS, while 129 (56.5 %) had no ACS. The classification model using SVM attained a 99.13 % classification success. The present study showed a 99.13 % classification success for ACS diagnosis attained by Support Vector Machine. This study showed that machine learning techniques may help emergency department staff make decisions by rapidly producing relevant data.

Background This study aims to compare emergency trauma visits' severity, emergency surgical needs, and characteristics between the pandemic and pre-pandemic periods. Methods This retrospective observational study was conducted in a tertiary training and research hospital between 1 and 30 April 2020 (pandemic group) and compared with the previous year's same dates (pre-pandemic group). Trauma patients aged 18 and over were included in the study. Emergency Severity Index (ESI) levels, trauma surgery needs, and injury characteristics were compared. Results A total of 2097 patients (592 pandemic and 1505 pre-pandemic) were included. There was an approximately 60% reduction in total and daily visits. ESI levels 1 (0.2% vs. 1.4%) and 2 (0.8% vs. 1.9%) patients increased during pandemic period. Trauma surgery needs (1.6% vs. 2.2%), intensive care unit (ICU) admission (0.4% vs. 0.2%), and ward admission (6.3% vs. 7.9%) did not change during pandemic period. Conclusion Despite the decrease in the visit frequency of adult trauma patients during the pandemic period, the needs for trauma surgery, ICU, and ward admission did not change. Trauma teams should continue their duties during the pandemic period.

Background This study aimed to determine the effect of the COVID-19 outbreak on emergency department (ED) visits and emergency consultations according to the triage levels indicating the patients' urgency. Methods A cross-sectional retrospective study was performed in the ED of a tertiary training and research hospital between 1 April and 31 May 2020 in İstanbul, Turkey. The daily count of emergency visits and the count of the emergency consultations during the study period were recorded. The emergency visits and consultations in the same months of the previous year (1 April-31 May 2019) were included as a control group. Results Approximately 50% reduction in ED visits and a 30% reduction in emergency consultations were detected. A significant decrease was detected in all triage levels of visits and emergency consultations (p < 0.001). Within total ED visits, a significant increase was found in the red (4.32% vs. 4.74%) and yellow (21.66% vs. 33.16%) triage levels visit rates, while the green (74.01% vs. 62.1%) level was decreased. Within total emergency consultations, anesthesiology (0.83% vs. 1.56%) and cardiology (3.17% vs. 3.75%) consultation rates increased, neurology (2.22% vs. 1.15%), orthopedics (3.53% vs. 3.01%), and ophthalmology (2.89% vs. 1.57%) consultation rates decreased, internal medicine (2.45% vs. 2.49%), and general surgery (4.46% vs. 4.64%) consultation rates did not change. Conclusions During the COVID-19 pandemic, ED visits at all triage levels decreased. While the rate of critical patient visits increased, non-emergency patient visit rates decreased. The total count of consultations decreased, while the total consultation rates increased. The management of the COVID-19 pandemic will be easier by using or developing appropriate triage scores, as well as establishing good interdisciplinary coordination.