Modified Cardiovascular Sequential Organ Failure Assessment Score in Sepsis: External Validation in Intensive Care Unit Patients.

BACKGROUND: There is a need to update the cardiovascular (CV) Sequential Organ Failure Assessment (SOFA) score to reflect the current practice in sepsis. We previously proposed the modified CV SOFA score from data on blood pressure, norepinephrine equivalent dose, and lactate as gathered from emergency departments. In this study, we externally validated the modified CV SOFA score in multicenter intensive care unit (ICU) patients. METHODS: A multicenter retrospective observational study was conducted on ICU patients at six hospitals in Korea. We included adult patients with sepsis who were admitted to ICUs. We compared the prognostic performance of the modified CV/total SOFA score and the original CV/total SOFA score in predicting 28-day mortality. Discrimination and calibration were evaluated using the area under the receiver operating characteristic curve (AUROC) and the calibration curve, respectively. RESULTS: We analyzed 1,015 ICU patients with sepsis. In overall patients, the 28-day mortality rate was 31.2%. The predictive validity of the modified CV SOFA (AUROC, 0.712; 95% confidence interval [CI], 0.677-0.746; P < 0.001) was significantly higher than that of the original CV SOFA (AUROC, 0.644; 95% CI, 0.611-0.677). The predictive validity of modified total SOFA score for 28-day mortality was significantly higher than that of the original total SOFA (AUROC, 0.747 vs. 0.730; 95% CI, 0.715-0.779; P = 0.002). The calibration curve of the original CV SOFA for 28-day mortality showed poor calibration. In contrast, the calibration curve of the modified CV SOFA for 28-day mortality showed good calibration. CONCLUSION: In patients with sepsis in the ICU, the modified SOFA score performed better than the original SOFA score in predicting 28-day mortality.

Developing neural network models for early detection of cardiac arrest in emergency department.

BACKGROUND: Automated surveillance for cardiac arrests would be useful in overcrowded emergency departments. The purpose of this study is to develop and test artificial neural network (ANN) classifiers for early detection of patients at risk of cardiac arrest in emergency departments. METHODS: This is a single-center electronic health record (EHR)-based study. The primary outcome was the development of cardiac arrest within 24 h after prediction. Three ANN models were trained: multilayer perceptron (MLP), long-short-term memory (LSTM), and hybrid. These were compared to other classifiers including the modified early warning score (MEWS), logistic regression, and random forest. We used AUROC, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for the comparison. RESULTS: During the study period, there were a total of 374,605 ED visits and 2,910,321 patient status updates. The ANN models (MLP, LSTM, and hybrid) achieved higher AUROC (AUROC: 0.929, 0.933, and 0.936; 95% confidential interval: 0.926-0.932, 0.930-0.936, and 0.933-0.939, respectively) compared to the non-ANN models, and the hybrid model exhibited the best performance. The ANN classifiers displayed higher performance in most of the test characteristics when the threshold levels of the classifiers were fixed to display the same positive result as those at the three MEWS thresholds (score ≥ 3, ≥4, and ≥5), and when compared with each other. CONCLUSIONS: The ANN improves upon MEWS and conventional machine learning algorithms for the prediction of cardiac arrests in emergency departments. The hybrid ANN model utilizing both baseline and sequence information achieved the best performance.

Characterization of Fecal Peritonitis-Induced Sepsis in a Porcine Model.

BACKGROUND: Although there are well-established small-animal sepsis models, the longitudinal assessment of hemodynamic variables, laboratory values, and blood culture in a single living sepsis model is limited. Therefore, we aimed to comprehensively characterize fecal peritonitis-induced sepsis in a porcine model. MATERIALS AND METHODS: Autologous feces (1 g/kg) was administered into the peritoneum of 11 male pigs (49 ± 8 kg). The pigs were monitored up to 12 h with full fluid and vasopressor support to maintain the mean arterial pressure at >65 mm Hg. Longitudinal blood culture and laboratory values were obtained at defined time intervals. The cytokine levels in plasma were analyzed. Furthermore, a clinical registry of sepsis patients at a single emergency department was used to compare the Sepsis-related Organ Failure Assessment scores with those of the porcine model. RESULTS: The hyperdynamic phase of increasing cardiac output with decreasing systemic vascular resistance was maintained until 2 h, followed by the reverse (hypodynamic phase). With the escalating requirement for fluid and vasopressor, the lactate level progressively increased while the platelet count, urine output, and serum albumin level consistently decreased. Bacteremia developed 7 h (median) after the administration of feces, and Escherichia coli was the most common pathogen. The pattern of Sepsis-related Organ Failure Assessment scores with prominent cardiovascular failure was comparable to clinical data. CONCLUSIONS: We implemented a porcine fecal peritonitis-induced sepsis model that demonstrates culture-proven bacteremia and multiple organ failure, particularly cardiovascular system failure. This model could facilitate the development of technologies for the early diagnosis of bacterial pathogens in blood.

Efficacy of Non-Enhanced Brain Computed Tomography in Patients Presenting to the Emergency Department with Headache after COVID-19 Vaccination.

Headaches are a common side effect of vaccination against the severe acute respiratory syndrome, coronavirus 2; however, it is usually not necessary to seek emergency medical attention or undergo brain imaging such as non-enhanced brain computed tomography (CT) for routine evaluation of vaccine-related headaches. This study aimed to demonstrate that brain CT is of no clinical benefit to patients presenting to the emergency department (ED) with post-coronavirus disease 2019 (COVID-19) vaccination headaches. This retrospective, single-center observational study used electronic medical record (EMR) data of patients who received the COVID-19 vaccination during the first year of the vaccination program. In total, 914 patients were analyzed, of whom 435 underwent CT (CT group, n = 435; no CT group, n = 475). More female patients visited the ED, and there was no significant sex difference between the CT and no-CT groups. The type of vaccine affected the clinical decision to perform brain CT, but the number of doses did not. The CT rate was relatively high for patients who had received the ChAdOx1 nCoV-19 (Oxford-AstraZeneca) and Johnson and Johnson Janssen (Jansen) vaccines (p = 0.004). Focal neurological deficits were present in all cases of abnormalities on non-enhanced brain CT in patients complaining of headaches. Two out of the 435 patients had abnormal brain CT findings (glioblastoma and Rathke's pouch cyst) at 35 and 32 days after vaccination, respectively. Non-enhanced brain CT should be performed cautiously in patients visiting the ED for post-vaccination headaches only.

MONITORING OF PULMONARY EDEMA USING ULTRASOUND RADIOFREQUENCY SIGNAL.

ABSTRACT: Objectives: Excessive accumulation of extravascular lung water impairs respiratory gas exchange and results in respiratory distress. Real-time radiofrequency signals of ultrasound can continuously and quantitatively monitor excessive lung water. This study aims to evaluate the availability of continuous real-time quantitative pulmonary edema monitoring using ultrasound radiofrequency signals and compare it with Pa o2 (partial pressure of arterial oxygen)/F io2 (fraction of inspired oxygen) (PF) ratio, conventional lung ultrasound, and the Hounsfield unit of chest computed tomography. Methods: Male Yorkshire pigs (40.5 ± 0.5 kg) were anesthetized and mechanically ventilated. A balanced crystalloid was administered to induce hydrostatic pulmonary edema. Three different infusion rates of 2, 4, and 6 mL/kg per minute were tested to determine the infusion rate for the appropriate swine model. The chest computed tomography and ultrasonography with radiofrequency signals were taken every 5 min during the full inspiration. The ultrasonography scans with radiofrequency signals were measured at the intercostal space where the line crossing the two armpits and the right anterior axillary line intersected. Results: The infusion rate of fluid for the pulmonary edema model was determined to be 6 mL/kg per minute, and a total of four pigs were tested at an injection rate of 6 mL/kg. The adjusted R2 values of regression analysis between the radiofrequency signal and computer tomography Hounsfield score were 0.990, 0.993, 0.988, and 0.993 (all P values <0.05). All radiofrequency signal changes preceded changes in PF ratio or lung ultrasound changes. The area under the receiver operating characteristic curve of the radiofrequency signal for predicting PF ratio <300 was 0.88 (95% confidence interval, 0.82-0.93). Conclusion: We evaluated ultrasound radiofrequency signals to assess pulmonary edema in a swine model that can worsen gradually and showed that quantitative ultrasound radiofrequency signal analysis could assess pulmonary edema and its progression before PF ratio or lung ultrasound changes.

Impact of the COVID-19 pandemic on emergency department utilization patterns in South Korea: A retrospective observational study.

ABSTRACT: The purpose of analyzing changes in the use of emergency departments (EDs) was to better understand how to use ED resources efficiently during infectious disease outbreaks.Our study was a retrospective observational study. We analyzed the patterns of visits of adult and pediatric patients to separate EDs during 2020 coronavirus disease 2019 (COVID-19) outbreak to know the changes in the ED utilization. We collected the patient's demographics and time of visit, patients' acuity level at triage, cause of visit, transportation used, disposition, symptom to visit time, length of stay, and top 10 most common complaints. We compared pediatric and adult EDs before and after COVID-19.The total number of patients who visited the EDs was 197,152 over 3 years. During the COVID-19 outbreak in 2020, the number of visits decreased significantly, especially the number of pediatric patients. The number of ED visits decreased in correlation with a surge in the number of confirmed COVID patients. The proportion of severe cases in pediatric emergency department (PED) visits increased, but there was no difference in adult emergency department. The number of hospitalized PED patients increased, and the number of hospitalized adult emergency department patients decreased. However, both types of ED patients increased in intensive care unit hospitalizations, proportion of deaths, and use of ambulances. The proportion of trauma patients in the PED increased significantly (P  < .001). The time from symptom onset to ED visit time was reduced for patients. The ED length of stay increased in adults, and decreased for pediatric patients.COVID-19 brought about many changes to ED utilization. A greater reduction in ED utilization occurred in pediatric patients compared to adult patients. Our study showed changes in the number and characteristics of patients visiting the ED during the COVID-19 period compared to 2018 and 2019.

A Unique Case of Inferior Vena Cava Aneurysm Complicated with Pulmonary Embolism and Cerebral Infarction.

Inferior vena cava (IVC) aneurysms rarely occur. They are commonly detected incidentally since they present with mild or no symptoms. This was the first study to report a fatal case of a saccular IVC aneurysm with pulmonary embolism and cerebral infarction. The patient developed cardiac arrest five minutes after arriving at the emergency department, and spontaneous circulation was restored after two minutes of cardiopulmonary resuscitation. Computed tomography scans of the brain, chest, and abdomen-pelvis were obtained. The patient was diagnosed with a saccular aneurysm of the IVC measuring 8 × 11 cm, massive embolism of both pulmonary arteries, and cerebral infarction. An electroencephalogram, taken on the third day of hospitalization, suggested brain death, and the patient died on the eleventh day of hospitalization. This case report highlights that an IVC aneurysm with pulmonary embolism can be associated with paradoxical emboli-induced cerebral infarction, which is fatal.

Machine learning for prediction of septic shock at initial triage in emergency department.

BACKGROUND: We hypothesized utilizing machine learning (ML) algorithms for screening septic shock in ED would provide better accuracy than qSOFA or MEWS. METHODS: The study population was adult (≥20 years) patients visiting ED for suspected infection. Target event was septic shock within 24 h after arrival. Demographics, vital signs, level of consciousness, chief complaints (CC) and initial blood test results were used as predictors. CC were embedded into 16-dimensional vector space using singular value decomposition. Six base learners including support vector machine, gradient-boosting machine, random forest, multivariate adaptive regression splines and least absolute shrinkage and selection operator and ridge regression and their ensembles were tested. We also trained and tested MLP networks with various setting. RESULTS: A total of 49,560 patients were included and 4817 (9.7%) had septic shock within 24 h. All ML classifiers significantly outperformed qSOFA score, MEWS and their age-sex adjusted versions with their AUROC ranging from 0.883 to 0.929. The ensembles of the base classifiers showed the best performance and addition of CC embedding was associated with statistically significant increases in performance. CONCLUSIONS: ML classifiers significantly outperforms clinical scores in screening septic shock at ED triage.