Objective: This study aimed to determine the clinical factors associated with positive brain magnetic resonance imaging (MRI) findings in patients presenting to the emergency department (ED) with acute altered mental status (AMS). Methods: Patients with acute AMS who presented to the ED were retrospectively analyzed from September 2019 to March 2020. Non-traumatic patients with abnormal alert, verbal, pain, unresponsive (AVPU) scale scores and exhibiting acute change in mental status were included in the study. We evaluated the clinical characteristics of patients with acute AMS according to the results of their brain MRI. A multivariable logistic regression model was used to determine the clinical factors associated with positive brain MRI findings. Results: During the study period, 138 patients underwent brain MRI in the ED, with 36 (26.1%) positive results. A majority of patients with positive brain MRI findings had underlying malignancies, cerebrovascular disease, higher serum total bicarbonate (TCO2) levels, TCO2≥22 mmol/L, lower blood urea nitrogen levels, abnormal findings on brain computed tomography and abnormal findings on neurologic examination. In the multivariable analysis, serum TCO2≥22 mmol/L (odds ratio [OR], 2.12; 95% confidence interval [CI], 1.09-4.12) and the presence of cranial nerve abnormalities (OR, 3.88; 95% CI, 1.55-9.68) and extremity abnormalities (OR, 2.76; 95% CI, 1.11-6.88) were significantly associated with positive brain MRI results. Conclusion Serum TCO2 level and the presence of cranial nerve and extremity abnormalities in the neurologic examinations were significantly associated with positive brain MRI results in patients with acute AMS.

Objective: We investigated the factors that affect the time from the onset of acute stroke symptoms to arrival at the emergency department (ED). Methods: Between July 2019 and February 2020, patients with acute stroke symptoms who visited a public hospital were evaluated by retrospective analysis using a prospective survey. The data for this study was gathered from baseline interviews with patients enrolled in stroke surveys. The primary outcome was time to arrival at the ED, evaluated as a binary variable with a value of 4.5 hours. Results: Overall, 205 patients were included in the final analysis. Among them, 47% (n=96) of patients with acute stroke symptoms arrived at the ED later than 4.5 hours from the time of onset of acute stroke symptoms. After multivariable logistic regression analyses, it was found that patients with higher National Institutes of Health Stroke Scale (NIHSS) scores, patients who did not live with their family members, and patients who were found by a passerby were associated with early ED arrival post onset of acute stroke symptoms. Among patients diagnosed with acute stroke, those with higher NIHSS scores or underlying malignant diseases were found to present earlier at the ED. Conclusion Approximately half of the patients (47%) with acute stroke symptoms presented to the ED within 4.5 hours. Higher NIHSS scores and the presence of underlying malignancy were identified as the key factors that were associated with an early presentation at the ED from the time of onset of acute stroke.

Objective: We investigated the effects of a quick Sequential Organ Failure Assessment (qSOFA)–negative result (qSOFA score <2 points) at triage on the compliance with sepsis bundles among patients with sepsis who presented to the emergency department (ED). Methods: Prospective sepsis registry data from 11 urban tertiary hospital EDs between October 2015 and April 2018 were retrospectively reviewed. Patients who met the Third International Consensus Definitions for Sepsis and Septic Shock criteria were included. Primary exposure was defined as a qSOFA score ≥2 points at ED triage. The primary outcome was defined as 3-hour bundle compliance, including lactate measurement, blood culture, broad-spectrum antibiotics administration, and 30 mL/kg crystalloid administration. Multivariate logistic regression analysis to predict 3-hour bundle compliance was performed. Results: Among the 2,250 patients enrolled in the registry, 2,087 fulfilled the sepsis criteria. Only 31.4% (656/2,087) of the sepsis patients had qSOFA scores ≥2 points at triage. Patients with qSOFA scores <2 points had lower lactate levels, lower SOFA scores, and a lower 28-day mortality rate. Rates of compliance with lactate measurement (adjusted odds ratio [aOR], 0.47; 95% confidence interval [CI], 0.29–0.75), antibiotics administration (aOR, 0.64; 95% CI, 0.52–0.78), and 30 mL/kg crystalloid administration (aOR, 0.62; 95% CI, 0.49–0.77) within 3 hours from triage were significantly lower in patients with qSOFA scores <2 points. However, the rate of compliance with blood culture within 3 hours from triage (aOR, 1.66; 95% CI, 1.33–2.08) was higher in patients with qSOFA scores <2 points. Conclusion A qSOFA-negative result at ED triage is associated with low compliance with lactate measurement, broad-spectrum antibiotics administration, and 30 mL/kg crystalloid administration within 3 hours in sepsis patients.

Background: We performed this study to establish a prediction model for 1-year neurological outcomes in out-of-hospital cardiac arrest (OHCA) patients who achieved return of spontaneous circulation (ROSC) immediately after ROSC using machine learning methods. Methods: We performed a retrospective analysis of an OHCA survivor registry. Patients aged ≥ 18 years were included. Study participants who had registered between March 31, 2013 and December 31, 2018 were divided into a develop dataset (80% of total) and an internal validation dataset (20% of total), and those who had registered between January 1, 2019 and December 31, 2019 were assigned to an external validation dataset. Four machine learning methods, including random forest, support vector machine, ElasticNet and extreme gradient boost, were implemented to establish prediction models with the develop dataset, and the ensemble technique was used to build the final prediction model. The prediction performance of the model in the internal validation and the external validation dataset was described with accuracy, area under the receiver-operating characteristic curve, area under the precision-recall curve, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Futhermore, we established multivariable logistic regression models with the develop set and compared prediction performance with the ensemble models. The primary outcome was an unfavorable 1-year neurological outcome. Results: A total of 1,207 patients were included in the study. Among them, 631, 139, and 153were assigned to the develop, the internal validation and the external validation datasets, respectively. Prediction performance metrics for the ensemble prediction model in the internal validation dataset were as follows: accuracy, 0.9620 (95% confidence interval [CI],0.9352–0.9889); area under receiver-operator characteristics curve, 0.9800 (95% CI, 0.9612– 0.9988); area under precision-recall curve, 0.9950 (95% CI, 0.9860–1.0000); sensitivity, 0.9594 (95% CI, 0.9245–0.9943); specificity, 0.9714 (95% CI, 0.9162–1.0000); PPV, 0.9916 (95% CI, 0.9752–1.0000); NPV, 0.8718 (95% CI, 0.7669–0.9767). Prediction performance metrics for the model in the external validation dataset were as follows: accuracy, 0.8509 (95% CI, 0.7825–0.9192); area under receiver-operator characteristics curve, 0.9301 (95% CI, 0.8845–0.9756); area under precision-recall curve, 0.9476 (95% CI, 0.9087–0.9867); sensitivity, 0.9595 (95% CI, 0.9145–1.0000); specificity, 0.6500 (95% CI, 0.5022–0.7978); PPV, 0.8353 (95% CI, 0.7564–0.9142); NPV, 0.8966 (95% CI, 0.7857–1.0000). All the prediction metrics were higher in the ensemble models, except NPVs in both the internal and the external validation datasets. Conclusion We established an ensemble prediction model for prediction of unfavorable 1-year neurological outcomes in OHCA survivors using four machine learning methods. The prediction performance of the ensemble model was higher than the multivariable logistic regression model, while its performance was slightly decreased in the external validation dataset.

Objective: The sensitivity of ultrasonography is poor in pregnant women with suspected appendicitis. Additional magnetic resonance imaging (MRI) is usually required, which can delay the diagnosis and surgical intervention. We hypothesized that the use of MRI as the first diagnostic tool could increase the detection rate and reduce the time for diagnosis. Therefore, we sought to investigate the diagnostic yield of ultrasonography vs. MRI and the emergency department length of stay (ED-LOS) of pregnant women with suspected appendicitis. Methods: This was a retrospective, observational study in the ED of a single tertiary teaching hospital from January 2010 to December 2017. Patients who underwent ultrasonography or MRI or both were enrolled. The primary outcome was the diagnostic yield of acute appendicitis and the ED-LOS. The secondary outcome was the proportion of complicated appendicitis cases. Results: A total of 145 pregnant women were enrolled (ultrasonography only, n=73; MRI only, n=26; both ultrasonography and MRI, n=46). The diagnostic yield was 23.5% (28/119) by ultrasonography and 79.2% (57/72) by MRI. The diagnostic yield of ultrasonography was significantly lower than that of MRI, especially in the second and third trimesters. The ED-LOS was significantly longer in the ultrasonography plus MRI group than that in the MRI-only group (9 hours vs. 6 hours, P=0.002). Conclusion In this study, MRI had a higher diagnostic yield than ultrasonography and can reduce the time to diagnosis. Thus, MRI should be considered as the first diagnostic tool for suspected acute appendicitis in pregnant women.

Background: We performed this study to establish a prediction model for 1-year neurological outcomes in out-of-hospital cardiac arrest (OHCA) patients who achieved return of spontaneous circulation (ROSC) immediately after ROSC using machine learning methods. Methods: We performed a retrospective analysis of an OHCA survivor registry. Patients aged ≥ 18 years were included. Study participants who had registered between March 31, 2013 and December 31, 2018 were divided into a develop dataset (80% of total) and an internal validation dataset (20% of total), and those who had registered between January 1, 2019 and December 31, 2019 were assigned to an external validation dataset. Four machine learning methods, including random forest, support vector machine, ElasticNet and extreme gradient boost, were implemented to establish prediction models with the develop dataset, and the ensemble technique was used to build the final prediction model. The prediction performance of the model in the internal validation and the external validation dataset was described with accuracy, area under the receiver-operating characteristic curve, area under the precision-recall curve, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Futhermore, we established multivariable logistic regression models with the develop set and compared prediction performance with the ensemble models. The primary outcome was an unfavorable 1-year neurological outcome. Results: A total of 1,207 patients were included in the study. Among them, 631, 139, and 153were assigned to the develop, the internal validation and the external validation datasets, respectively. Prediction performance metrics for the ensemble prediction model in the internal validation dataset were as follows: accuracy, 0.9620 (95% confidence interval [CI],0.9352–0.9889); area under receiver-operator characteristics curve, 0.9800 (95% CI, 0.9612– 0.9988); area under precision-recall curve, 0.9950 (95% CI, 0.9860–1.0000); sensitivity, 0.9594 (95% CI, 0.9245–0.9943); specificity, 0.9714 (95% CI, 0.9162–1.0000); PPV, 0.9916 (95% CI, 0.9752–1.0000); NPV, 0.8718 (95% CI, 0.7669–0.9767). Prediction performance metrics for the model in the external validation dataset were as follows: accuracy, 0.8509 (95% CI, 0.7825–0.9192); area under receiver-operator characteristics curve, 0.9301 (95% CI, 0.8845–0.9756); area under precision-recall curve, 0.9476 (95% CI, 0.9087–0.9867); sensitivity, 0.9595 (95% CI, 0.9145–1.0000); specificity, 0.6500 (95% CI, 0.5022–0.7978); PPV, 0.8353 (95% CI, 0.7564–0.9142); NPV, 0.8966 (95% CI, 0.7857–1.0000). All the prediction metrics were higher in the ensemble models, except NPVs in both the internal and the external validation datasets. Conclusion We established an ensemble prediction model for prediction of unfavorable 1-year neurological outcomes in OHCA survivors using four machine learning methods. The prediction performance of the ensemble model was higher than the multivariable logistic regression model, while its performance was slightly decreased in the external validation dataset.

Objective: The sensitivity of ultrasonography is poor in pregnant women with suspected appendicitis. Additional magnetic resonance imaging (MRI) is usually required, which can delay the diagnosis and surgical intervention. We hypothesized that the use of MRI as the first diagnostic tool could increase the detection rate and reduce the time for diagnosis. Therefore, we sought to investigate the diagnostic yield of ultrasonography vs. MRI and the emergency department length of stay (ED-LOS) of pregnant women with suspected appendicitis. Methods: This was a retrospective, observational study in the ED of a single tertiary teaching hospital from January 2010 to December 2017. Patients who underwent ultrasonography or MRI or both were enrolled. The primary outcome was the diagnostic yield of acute appendicitis and the ED-LOS. The secondary outcome was the proportion of complicated appendicitis cases. Results: A total of 145 pregnant women were enrolled (ultrasonography only, n=73; MRI only, n=26; both ultrasonography and MRI, n=46). The diagnostic yield was 23.5% (28/119) by ultrasonography and 79.2% (57/72) by MRI. The diagnostic yield of ultrasonography was significantly lower than that of MRI, especially in the second and third trimesters. The ED-LOS was significantly longer in the ultrasonography plus MRI group than that in the MRI-only group (9 hours vs. 6 hours, P=0.002). Conclusion In this study, MRI had a higher diagnostic yield than ultrasonography and can reduce the time to diagnosis. Thus, MRI should be considered as the first diagnostic tool for suspected acute appendicitis in pregnant women.

Objective: High-quality intensive care, including targeted temperature management (TTM) for patients with postcardiac arrest syndrome, is a key element for improving outcomes after out-of-hospital cardiac arrest (OHCA). We aimed to assess the status of postcardiac arrest syndrome care, including TTM and 6-month survival with neurologically favorable outcomes, after adult OHCA patients were treated with TTM, using data from the Korean Hypothermia Network prospective registry. Methods: We used the Korean Hypothermia Network prospective registry, a web-based multicenter registry that includes data from 22 participating hospitals throughout the Republic of Korea. Adult comatose OHCA survivors treated with TTM between October 2015 and December 2018 were included. The primary outcome was neurological outcome at 6 months. Results: Of the 1,354 registered OHCA survivors treated with TTM, 550 (40.6%) survived 6 months, and 413 (30.5%) had good neurological outcomes. We identified 839 (62.0%) patients with preClinsumed cardiac etiology. A total of 937 (69.2%) collapses were witnessed, shockable rhythms were demonstrated in 482 (35.6%) patients, and 421 (31.1%) patients arrived at the emergency department with prehospital return of spontaneous circulation. The most common target temperature was 33°C, and the most common target duration was 24 hours. Conclusion The survival and good neurologic outcome rates of this prospective registry show great improvements compared with those of an earlier registry. While the optimal target temperature and duration are still unknown, the most common target temperature was 33°C, and the most common target duration was 24 hours.

Objective: Practice guidelines for diverticulitis have been developed in countries where left-colon diverticulitis is dominant,but there is limited information on right-colon diverticulitis. This study examined the clinical characteristics and riskfactors of clinically severe right-colon diverticulitis. Methods: A retrospective chart review of patients diagnosed with diverticulitis in an emergency department in Koreabetween 2013 and 2017 was performed. Clinically severe diverticulitis was defined as any cause of death, intensive careunit admission, surgery, or invasive intervention due to diverticulitis, and admission for seven or more hospital days.Multivariable logistic regression was used to identify the risk factors for clinically severe diverticulitis. Results: This study analyzed 302 patients. Patients with older age (odds ratio [OR], 1.044; 95% confidence interval [CI],1.009-1.080; P=0.013), complications observed on computed tomography (CT) (OR, 6.906; 95% CI, 2.514-18.968;P<0.001), rebound tenderness on a physical examination (OR, 2.542; 95% CI, 1.041-6.218; P=0.041), high alkalinephosphatase (ALP) levels (OR, 1.014; 95% CI, 1.002-1.026; P=0.026), and high C-reactive protein (CRP) levels (OR,1.095; 95% CI, 1.017-1.178; P=0.013) were at higher risk of clinically severe diverticulitis. Conclusion Among patients diagnosed with right-colon diverticulitis in the emergency department, those of older age,distinct complications on CT, rebound tenderness on physical examination, high ALP, and high CRP levels are related toclinically severe disease.

Objective: Prior studies have explored the relationship between initial body temperature (BT) and mortality in patients with sepsis in the emergency department (ED). However, there has been no study on whether or not changes in BT are associated with prognosis in these patients. We hypothesize that BT measured upon ED arrival and septic shock registry enroll time are related to the prognosis of patients with septic shock. Methods: We conducted a prospective, observational, registry-based study. Each patient was assigned to 1 of 4 groups according to BT upon ED arrival and registry enrollment. Odds ratios for 28-day mortality according to the patient group were estimated using multivariable logistic regression. We also conducted logistic regression sensitivity analysis, except for patients whose time interval between arrival and enrollment was less than 1 hour. Results: A total of 2,138 patients with septic shock were included. The 28-day mortalities were 13.7%, 11.2%, 13.0%, and 25.8% in groups 1, 2, 3, and 4, respectively (P<0.001). After adjusting for age, sex, mean atrial pressure, respiratory rate, Sequential Organ Failure Assessment score, lactate concentration, comorbidity, and suspicious infection focus, the risk of mortality was significantly low in patients from group 1 (adjusted odds ratio [aOR], 0.433; 95% confidence interval [CI], 0.310-0.604) and group 2 (aOR, 0.540; 95% CI, 0.336-0.868) compared with group 4. In the sensitivity analysis, group based on BT measured upon ED arrival and registry enrollment also remained an independent predictor of mortality. Conclusion Afebrile status upon ED arrival and registry enrollment were strongly associated with higher 28-day mortality in patients with septic shock.