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Objective@#The purpose of this study was to identify if there was a perception of difficulty in using emergency department (ED) services during the coronavirus disease 2019 (COVID-19) pandemic and the contributing factors to this situation through a cross-sectional public survey in a metropolitan city. @*Methods@#In November 2020, face-to-face interviews based on a structured questionnaire were conducted with 1,000 citizens. A multivariable logistic regression analysis was performed to identify the factors affecting the perception of difficulty in using the ED. @*Results@#Of the respondents, 65.2% (58.9% male and 71.3% female) perceived difficulty in using ED services during the pandemic. By age, 69.8% of those who had this perception were under the age of 40 years ; 63.2% were 40-64 years old, and 61.1% were over the age of 65. Of the total number of respondents, 24.8% and 13.8% said they would hesitate to visit ED for chest pain and neurological symptoms, respectively. As a result of multivariate analysis, the significant contributing factors were age under 40 years old, female gender, fear of in-hospital COVID-19 contagion, emergency medical technician (EMT) referral to the ED, and prior experience with the emergency medical service (EMS) dispatch center. @*Conclusion@#A significant percentage of respondents perceived that it was difficult to use ED services during the COVID19 pandemic, even when experiencing chest pain and neurological symptoms, which require urgent treatment. Younger age, women, and fear of nosocomial COVID-19 contagion appear to have aggravated this situation. Conversely, prior experience with the EMS dispatch center and visits to the EMT-recommended ED facilitated ED utilization.
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Objective@#This study aimed at analyzing the clinical characteristics of patients visiting the emergency department (ED) and pre-triage clinic during the coronavirus disease 2019 (COVID-19) pandemic era in Daegu, South Korea. @*Methods@#We conducted a retrospective observational study by using the medical records of patients who visited the ED and pre-triage clinic from February 22 to March 31, 2020 and comparing them with the corresponding period in 2019. @*Results@#The number of patients visiting the ED per day decreased from 122 (115-138) to 77 (66-93). The percentage of patients with respiratory infection increased from 6.6% to 15.4% (P<0.001). The length of the ED stay increased from 269 (150-562) to 559 (293-941) minutes, especially in patients with fever (P<0.001). The rate of injured and less urgent patients decreased from 24.7 to 13.2 and 53.4% to 50.2%, respectively (P<0.001). Sixty-one-point nine percent of patients visiting the ED were triaged and discharged at the pre-triage clinic without entering the ED. @*Conclusion@#In the COVID-19 pandemic era, there was an increase in the proportion of patients with fever and respiratory symptoms and a decrease in the proportion of injured patients. At the pre-triage clinic, a significant number of patients with suspected COVID-19 or less urgent conditions were treated and discharged without their having to enter the ED.
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Purpose@#A high anion gap (AG) is known to be a significant risk factor for serious acid-base imbalances and death in acute poisoning cases. The strong ion difference (SID), or strong ion gap (SIG), has recently been used to predict in-hospital mortality or acute kidney injury (AKI) in patients with systemic inflammatory response syndrome. This study presents a comprehensive acidbase analysis in order to identify the predictive value of the SIG for disease severity in severe poisoning. @*Methods@#A cross-sectional observational study was conducted on acute poisoning patients treated in the emergency intensive care unit (ICU) between December 2015 and November 2020. Initial serum electrolytes, base deficit (BD), AG, SIG, and laboratory parameters were concurrently measured upon hospital arrival and were subsequently used along with Stewart’s approach to acid-base analysis to predict AKI development and in-hospital death. The area under the receiver operating characteristic curve (AUC) and logistic regression analysis were used as statistical tests. @*Results@#Overall, 343 patients who were treated in the intensive care unit were enrolled. The initial levels of lactate, AG, and BD were significantly higher in the AKI group (n=62). Both effective SID [SIDe] (20.3 vs. 26.4 mEq/L, p<0.001) and SIG (20.2 vs. 16.5 mEq/L, p<0.001) were significantly higher in the AKI group; however, the AUC of serum SIDe was 0.842 (95% confidence interval [CI]=0.799-0.879). Serum SIDe had a higher predictive capacity for AKI than initial creatinine (AUC=0.796, 95% CI=0.749-0.837), BD (AUC=0.761, 95% CI=0.712-0.805), and AG (AUC=0.660, 95% CI=0.607-0.711). Multivariate logistic regression analyses revealed that diabetes, lactic acidosis, high SIG, and low SIDe were significant risk factors for in-hospital mortality. @*Conclusion@#Initial SIDe and SIG were identified as useful predictors of AKI and in-hospital mortality in intoxicated patients who were critically ill. Further research is necessary to evaluate the physiological nature of the toxicant or unmeasured anions in such patients.
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Epidural hematoma with Brown-Sequard syndrome caused by an epidural injection is a rarely found condition in the emergency department (ED). We report an unusual case of Brown-Sequard syndrome in a 55-year-old man who presented at the ED with right-sided weakness and contralateral loss of pain and temperature sensation after a cervical epidural injection for shoulder pain. Cervicla spine magnetic resonance imaging showed an epidural hematoma from C4 to C6. After admission, his right hemiparesis and contralateral sensory loss improved within eight days, and surgical decompression was not required. Diagnosing spinal lesions in the ED is challenging, especially in patients with acute neurological signs requiring immediate evaluation for stroke. In this case, definite hemiparesis and some contralateral sensory loss were noted. Therefore, a potential spinal lesion was suspected rather than a stroke. This case emphasized the importance of conducting a focused neurological examination after history taking.
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Objective@#Trauma death is one of the most preventable deaths by various efforts in the healthcare sector. The establishment of a regional trauma center will aid in efforts to reduce mortality. On the other hand, the effects of trauma centers on pediatric trauma in Korea are not fully understood. This study compared the clinical outcomes of severe pediatric trauma patients before and after the regional trauma center was set into action. @*Methods@#A cross-sectional, retrospective analysis was performed on the medical records in a single regional emergency and trauma center from November 2014 to October 2016 and from January 2017 to December 2018. The general demographic information, injury details, and clinical outcome data were collected. The cases were divided into two groups, the before and after groups, and comparisons were made. @*Results@#Seventy-three patients were included in the study. Thirty-seven patients were in the before group, and 36 were in the after group. The mortality (21.6% to 5.6%, P=0.04) and interhospital transfer rate (27.0% to 8.3%, P=0.03) were lower in after group than in the before group. On the other hand, the time to receive a transfusion, operation, and intensive care unit (ICU) admission did not differ significantly. The lengths of the emergency department, ICU, and hospital stay were also similar in the two groups. @*Conclusion@#For severe pediatric trauma patients, the mortality and transfer rates decreased after implementing the trauma center. On the other hand, the implementation itself was not identified as a major factor, and the time required to receive a definite treatment or length of stay did not change significantly.
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Objective@#This study compared the prognostic performance of the following five injury severity scores: the Geriatric Trauma Outcome Score (GTOS), the Injury Severity Score (ISS), the New Injury Severity Score (NISS), the Revised Trauma Score (RTS), and the Trauma and Injury Severity Score (TRISS) for in-hospital mortality in severe geriatric trauma patients. @*Methods@#A retrospective, cross-sectional, observational study was conducted using a database of severe geriatric trauma patients (age ≥65 years and ISS ≥16) who presented to a single regional trauma center between November 2016 and October 2018. We compared the baseline characteristics between the survivor and mortality groups and the predictive ability of the five scoring systems. @*Results@#A total of 402 patients were included in the analysis; the in-hospital mortality rate was 25.6% (n=103). The TRISS had the highest area under the curve of 0.953 (95% confidence interval [CI], 0.927-0.971); followed by RTS, 0.777 (95% CI, 0.733-0.817); NISS, 0.733 (95% CI, 0.687-0.776); ISS, 0.660 (95% CI, 0.612-0.707); and GTOS, 0.660 (95% CI, 0.611-0.706) in severe geriatric trauma. The TRISS also had the highest area under the curve of 0.961 (0.919-0.985) among the injury severity scoring systems in polytrauma. The predictive ability of TRISS was significantly higher than the other four scores with respect to overall trauma and polytrauma (P<0.001). @*Conclusion@#The TRISS showed the highest prognostic performance for predicting in-hospital mortality among all the injury severity scoring systems in severe geriatric trauma.
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Background@#There is currently a lack of evidence-based postresuscitation or postmortem guidelines for patients with out-of-hospital cardiac arrest (OHCA) in the setting of an emerging infectious disease. This study aimed to develop and validate a multimodal screening tool that aids in predicting the disease confirmation in emergency situations and patients with OHCA during a coronavirus disease 2019 (COVID-19) outbreak. @*Materials and Methods@#We conducted a retrospective, multicenter observational study of adult patients with OHCA in Daegu, Korea. To identify the potential predictors that could be used in screening tools in the emergency department, we applied logistic regression to data collected from March 1 to March 14. The prediction performance of the screening variables was then assessed and validated on the data of patients with OHCA who were treated between February 19 and March 31, 2020. General patient characteristics and hematological findings of the COVID-19-negative and COVID-19-positive groups were compared. We also evaluated confirmation test criteria as predictors for COVID-19 positivity in patients with OHCA. @*Results@#Advanced age, body temperature, and abnormal chest X-ray (CXR) revealed significant predictive ability in the derivation cohort. Of the 184 adult patients with OHCA identified in the validation cohort, 80 patients were included in the analysis. Notably, 9 patients were positive and 71 were negative on the COVID-19 reverse transcription polymerase chain reaction test. Five patients (55.6%) in the COVID-19-positive group had a fever before OHCA, and 12 (16.9%) of the COVID-19-negative group had a fever before OHCA (P = 0.018).Eight patients (88.9%) in the COVID-19-positive group had a CXR indicating pneumonic infiltration. Of the criteria for predicting COVID-19, fever or an abnormal CXR had a sensitivity of 100% (95% confidence interval [CI]: 65.4 – 100) and a specificity of 22.5% (95% CI: 13.5 – 34.0). @*Conclusion@#The screening tools that combined fever or abnormal CXR had a good discriminatory ability for COVID-19 infection in adult patients with OHCA. Therefore, during the COVID-19 outbreak period, it is recommended to suspect COVID-19 infection and perform COVID-19 test if patients present with a history of fever or show abnormal findings in postmortem CXR
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Objective@#This study compared the prognostic performance of the following five injury severity scores: the Geriatric Trauma Outcome Score (GTOS), the Injury Severity Score (ISS), the New Injury Severity Score (NISS), the Revised Trauma Score (RTS), and the Trauma and Injury Severity Score (TRISS) for in-hospital mortality in severe geriatric trauma patients. @*Methods@#A retrospective, cross-sectional, observational study was conducted using a database of severe geriatric trauma patients (age ≥65 years and ISS ≥16) who presented to a single regional trauma center between November 2016 and October 2018. We compared the baseline characteristics between the survivor and mortality groups and the predictive ability of the five scoring systems. @*Results@#A total of 402 patients were included in the analysis; the in-hospital mortality rate was 25.6% (n=103). The TRISS had the highest area under the curve of 0.953 (95% confidence interval [CI], 0.927-0.971); followed by RTS, 0.777 (95% CI, 0.733-0.817); NISS, 0.733 (95% CI, 0.687-0.776); ISS, 0.660 (95% CI, 0.612-0.707); and GTOS, 0.660 (95% CI, 0.611-0.706) in severe geriatric trauma. The TRISS also had the highest area under the curve of 0.961 (0.919-0.985) among the injury severity scoring systems in polytrauma. The predictive ability of TRISS was significantly higher than the other four scores with respect to overall trauma and polytrauma (P<0.001). @*Conclusion@#The TRISS showed the highest prognostic performance for predicting in-hospital mortality among all the injury severity scoring systems in severe geriatric trauma.
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Background@#There is currently a lack of evidence-based postresuscitation or postmortem guidelines for patients with out-of-hospital cardiac arrest (OHCA) in the setting of an emerging infectious disease. This study aimed to develop and validate a multimodal screening tool that aids in predicting the disease confirmation in emergency situations and patients with OHCA during a coronavirus disease 2019 (COVID-19) outbreak. @*Materials and Methods@#We conducted a retrospective, multicenter observational study of adult patients with OHCA in Daegu, Korea. To identify the potential predictors that could be used in screening tools in the emergency department, we applied logistic regression to data collected from March 1 to March 14. The prediction performance of the screening variables was then assessed and validated on the data of patients with OHCA who were treated between February 19 and March 31, 2020. General patient characteristics and hematological findings of the COVID-19-negative and COVID-19-positive groups were compared. We also evaluated confirmation test criteria as predictors for COVID-19 positivity in patients with OHCA. @*Results@#Advanced age, body temperature, and abnormal chest X-ray (CXR) revealed significant predictive ability in the derivation cohort. Of the 184 adult patients with OHCA identified in the validation cohort, 80 patients were included in the analysis. Notably, 9 patients were positive and 71 were negative on the COVID-19 reverse transcription polymerase chain reaction test. Five patients (55.6%) in the COVID-19-positive group had a fever before OHCA, and 12 (16.9%) of the COVID-19-negative group had a fever before OHCA (P = 0.018).Eight patients (88.9%) in the COVID-19-positive group had a CXR indicating pneumonic infiltration. Of the criteria for predicting COVID-19, fever or an abnormal CXR had a sensitivity of 100% (95% confidence interval [CI]: 65.4 – 100) and a specificity of 22.5% (95% CI: 13.5 – 34.0). @*Conclusion@#The screening tools that combined fever or abnormal CXR had a good discriminatory ability for COVID-19 infection in adult patients with OHCA. Therefore, during the COVID-19 outbreak period, it is recommended to suspect COVID-19 infection and perform COVID-19 test if patients present with a history of fever or show abnormal findings in postmortem CXR
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PURPOSE@#Osmolar gap (OG) has been used for decades to screen for toxic alcohol levels. However, its reliability may vary due to several reasons. We validated the estimated ethanol concentration formula for patients with suspected poisoning and who visited the emergency department. We examined discrepancies in the ethanol level and patient characteristics by applying this formula when it was used to screen for intoxication due to toxic levels of alcohol.@*METHODS@#We retrospectively reviewed 153 emergency department cases to determine the measured levels of toxic ethanol ingestion and we calculated alcohol ingestion using a formula based on serum osmolality. Those patients who were subjected to simultaneous measurements of osmolality, sodium, urea, glucose, and ethanol were included in this study. Patients with exposure to other toxic alcohols (methanol, ethylene glycol, or isopropanol) or poisons that affect osmolality were excluded. OG (the measured-calculated serum osmolality) was used to determine the calculated ethanol concentration.@*RESULTS@#Among the 153 included cases, 114 had normal OGs (OG≤14 mOsm/kg), and 39 cases had elevated OGs (OG>14). The mean difference between the measured and estimated (calculated ethanol using OG) ethanol concentration was −9.8 mg/dL. The 95% limits of agreement were −121.1 and 101.5 mg/dL, and the correlation coefficient R was 0.7037. For the four subgroups stratified by comorbidities and poisoning, the correlation coefficients R were 0.692, 0.588, 0.835, and 0.412, respectively, and the mean differences in measurement between the measured and calculated ethanol levels were −2.4 mg/dL, −48.8 mg/dL, 9.4 mg/dL, and −4.7 mg/dL, respectively. The equation plots had wide limits of agreement.@*CONCLUSION@#We found that there were some discrepancies between OGs and the calculated ethanol concentrations. Addition of a correction factor for unmeasured osmoles to the equation of the calculated serum osmolality would help mitigate these discrepancies.