Early identification of suspected serious infection among patients afebrile at initial presentation using neural network models and natural language processing: A development and external validation study in the emergency department.

OBJECTIVE: To develop and externally validate models based on neural networks and natural language processing (NLP) to identify suspected serious infections in emergency department (ED) patients afebrile at initial presentation. METHODS: This retrospective study included adults who visited the ED afebrile at initial presentation. We developed four models based on artificial neural networks to identify suspected serious infection. Patient demographics, vital signs, laboratory test results and information extracted from initial ED physician notes using term frequency-inverse document frequency were used as model variables. Models were trained and internally validated with data from one hospital and externally validated using data from a different hospital. Model discrimination was evaluated using area under the receiver operating characteristic curve (AUC) and 95% confidence intervals (CIs). RESULTS: The training, internal validation, and external validation datasets comprised 150,699, 37,675, and 85,098 patients, respectively. The AUCs (95% CIs) for Models 1 (demographics + vital signs), 2 (demographics + vital signs + initial ED physician note), 3 (demographics + vital signs + laboratory tests), and 4 (demographics + vital signs + laboratory tests + initial ED physician note) in the internal validation dataset were 0.789 (0.782-0.796), 0.867 (0.862-0.872), 0.881 (0.876-0.887), and 0.911 (0.906-0.915), respectively. In the external validation dataset, the AUCs (95% CIs) of Models 1, 2, 3, and 4 were 0.824 (0.817-0.830), 0.895 (0.890-0.899), 0.879 (0.873-0.884), and 0.913 (0.909-0.917), respectively. Model 1 can be utilized immediately after ED triage, Model 2 can be utilized after the initial physician notes are recorded (median time from ED triage: 28 min), and Models 3 and 4 can be utilized after the initial laboratory tests are reported (median time from ED triage: 68 min). CONCLUSIONS: We developed and validated models to identify suspected serious infection in the ED. Extracted information from initial ED physician notes using NLP contributed to increased model performance, permitting identification of suspected serious infection at early stages of ED visits.

Effect of first epinephrine administration time on cerebral perfusion pressure and cortical cerebral blood flow in a porcine cardiac arrest model.

OBJECTIVE: The optimal time for epinephrine administration and its effects on cerebral blood flow (CBF) and microcirculation remain controversial. This study aimed to assess the effect of the first administration of epinephrine on cerebral perfusion pressure (CePP) and cortical CBF in porcine cardiac arrest model. METHODS: After 4 min of untreated ventricular fibrillation, eight of 24 swine were randomly assigned to the early, intermediate, and late groups. In each group, epinephrine was administered intravenously at 5, 10, and 15 min after cardiac arrest induction. CePP was calculated as the difference between the mean arterial pressure and intracranial pressure. Cortical CBF was measured using a laser Doppler flow probe. The outcomes were CePP and cortical CBF measured continuously during cardiopulmonary resuscitation (CPR). Mean CePP and cortical CBF were compared using analysis of variance and a linear mixed model. RESULTS: The mean CePP was significantly different between the groups at 6-11 min after cardiac arrest induction. The mean CePP in the early group was significantly higher than that in the intermediate group at 8-10 min and that in the late group at 6-9 min and 10-11 min. The mean cortical CBF was significantly different between the groups at 9-11 min. The mean cortical CBF was significantly higher in the early group than in the intermediate and late group at 9-10 min. CONCLUSION: Early administration of epinephrine was associated with improved CePP and cortical CBF compared to intermediate or late administration during the early period of CPR.

Prediction of Increased Intracranial Pressure in Traumatic Brain Injury Using Quantitative Electroencephalogram in a Porcine Experimental Model.

Continuous and non-invasive measurement of intracranial pressure (ICP) in traumatic brain injury (TBI) is important to recognize increased ICP (IICP), which can reduce treatment delays. The purpose of this study was to develop an electroencephalogram (EEG)-based prediction model for IICP in a porcine TBI model. Thirty swine were anaesthetized and underwent IICP by inflating a Foley catheter in the intracranial space. Single-channel EEG data were collected every 6 min in 10 mmHg increments in the ICP from baseline to 50 mmHg. We developed EEG-based models to predict the IICP (equal or over 25 mmHg) using four algorithms: logistic regression (LR), naive Bayes (NB), support vector machine (SVM), and random forest (RF). We assessed the performance of each model based on the accuracy, sensitivity, specificity, and AUC values. The accuracy of each prediction model for IICP was 0.773 for SVM, 0.749 for NB, 0.746 for RF, and 0.706 for LR. The AUC of each model was 0.860 for SVM, 0.824 for NB, 0.802 for RF, and 0.748 for LR. We developed a machine learning prediction model for IICP using single-channel EEG signals in a swine TBI experimental model. The SVM model showed good predictive power with the highest AUC value.

Extracorporeal cardiopulmonary resuscitation location, coronary angiography and survival in out-of-hospital cardiac arrest.

INTRODUCTION: The best location for safe and timely implementation of extracorporeal cardiopulmonary resuscitation (ECPR) is currently uncertain. We aimed to evaluate the association between the location of ECPR and survival outcomes in out-of-hospital cardiac arrest (OHCA) patients. We also evaluated whether the effects of ECPR location on survival differed between patients who underwent coronary angiography (CAG) and those who did not. METHODS: We used data collected between 2013 and 2020 from a nationwide OHCA database. Adult OHCA patients with presumed cardiac etiology who underwent ECPR were included in the study. The primary outcome was survival to discharge. The main exposure was the ECPR location (emergency department [ED] or cardiac catheterization laboratory [Cath lab]). We compared primary outcomes of ECPR between the ED and Cath lab using multivariable logistic regression. The interaction between ECPR location and CAG was also evaluated. RESULTS: Of 564 ECPR patients, 448 (79.4%) and 116 (20.6%) underwent ECPR in the ED and Cath lab, respectively. CAG was observed in 52.5% and 72.4% of the patients in the ED and Cath lab groups, respectively. There were no significant differences in survival to discharge between the ED and Cath lab groups (14.1% vs. 12.9%, p = 0.75, adjusted odds ratio [AOR] [95% confidence interval] 1.87 [0.85-4.11]). AOR of interaction analysis (95% CI) for survival to discharge of the ED group was 2.34 (1.02-5.40) in patients with CAG and 0.28 (0.04-1.84) in patients without CAG (p for interaction was 0.04). CONCLUSION: In adult OHCA patients who underwent ECPR and CAG, ECPR in the ED shortened time to ECMO pump-on time and increased survival to discharge compared to ECPR in the Cath lab.

Trend in Disability-Adjusted Life Years (DALYs) for Injuries in Korea: 2004-2012.

BACKGROUND: Injury is a major public health problem and accounts for 10% of the global burden of disease. This study intends to present the temporal trend in the injury burden in Korea and to compare the burden size by injury mechanism and age group. METHODS: This study was a nationwide population-based observational study. We used two data sets, the death certificates statistics and the Korean National Hospital Discharge Survey data (2004-2012). We calculated age-standardized disability-adjusted life year (DALY) from years of life lost (YLL) and years lived with disability (YLD) and trend analysis. RESULTS: The DALYs of road injury decreased (P = 0.002), falls did not exhibit a trend (P = 0.108), and self-harm increased overall (P = 0.045). In the road injury, the YLLs decreased across all 4 age groups (0-14, 15-49, 50-79, ≥ 80) and the YLDs decreased in the 0-14-year-old group. In total, the DALYs of road injuries decreased in the 0-14-year-old group. In the fall injury, although the YLLs decreased in the over 80-year-old group, the YLDs increased in the 50-79-year-old group and the over 80-year-old group. The burden of self-harm injury was high in the age group 15 years and over, especially in the 15-49-year-old group. CONCLUSION: The leading causes of the injury burden were road injuries, falls, and self-harm. The burden of road injury and self-harm have recently shown a gradual decreasing tendency. On the other hands, that of fall injuries are continually high in the age group over 50 years of age.