Prediction of high-risk emergency department revisits from a machine-learning algorithm: a proof-of-concept study.

BACKGROUND: High-risk emergency department (ED) revisit is considered an important quality indicator that may reflect an increase in complications and medical burden. However, because of its multidimensional and highly complex nature, this factor has not been comprehensively investigated. This study aimed to predict high-risk ED revisit with a machine-learning (ML) approach. METHODS: This 3-year retrospective cohort study assessed adult patients between January 2019 and December 2021 from National Taiwan University Hospital Hsin-Chu Branch with high-risk ED revisit, defined as hospital or intensive care unit admission after ED return within 72 hours. A total of 150 features were preliminarily screened, and 79 were used in the prediction model. Deep learning, random forest, extreme gradient boosting (XGBoost) and stacked ensemble algorithm were used. The stacked ensemble model combined multiple ML models and performed model stacking as a meta-level algorithm. Confusion matrix, accuracy, sensitivity, specificity and area under the receiver operating characteristic curve (AUROC) were used to evaluate performance. RESULTS: Analysis was performed for 6282 eligible adult patients: 5025 (80.0%) in the training set and 1257 (20.0%) in the testing set. High-risk ED revisit occurred for 971 (19.3%) of training set patients vs 252 (20.1%) in the testing set. Leading predictors of high-risk ED revisit were age, systolic blood pressure and heart rate. The stacked ensemble model showed more favourable prediction performance (AUROC 0.82) than the other models: deep learning (0.69), random forest (0.78) and XGBoost (0.79). Also, the stacked ensemble model achieved favourable accuracy and specificity. CONCLUSION: The stacked ensemble algorithm exhibited better prediction performance in which the predictions were generated from different ML algorithms to optimally maximise the final set of results. Patients with older age and abnormal systolic blood pressure and heart rate at the index ED visit were vulnerable to high-risk ED revisit. Further studies should be conducted to externally validate the model.

A feasibility study of a handmade ultrasound-guided phantom for paracentesis.

BACKGROUND: Simulation-based training is effective for ultrasound (US)-guided procedures. However, commercially developed simulators are costly. This study aims to evaluate the feasibility of a hand-made phantom for US-guided paracentesis. METHODS: We described the recipe to prepare an agar phantom. We collected the US performance data of 50 novices, including 22 postgraduate-year (PGY) residents and 28 undergraduate-year (UGY) students, who used the phantom for training, as well as 12 emergency residents with prior US-guided experience. We obtained the feedback after using the phantom with the Likert 5-point scale. The data were presented with medians and interquartile ranges (IQRs) and analyzed by the Wilcoxon rank sum test. RESULTS: While emergency residents demonstrated superior performance compared to trainees, all trainees exhibited acceptable proficiency (global rating of ≥ 3, 50/50 vs. 12/12, p = 1.000) and comparable needle steadiness [5 (5) vs. 5 (5), p = 0.223]. No significant difference in performance was observed between PGYs [5 (4-5)] and UGYs [5 (4-5), p = 0.825]. No significant differences were observed in terms of image stimulation, puncture texture, needle visualization, drainage simulation, and endurance of the phantom between emergency residents and trainees. However, experienced residents rated puncture texture and draining fluid as "neutral" (3/5 on the Likert scale). The cost of the paracentesis phantom is US$16.00 for at least 30 simulations, reducing it to US$6.00 without a container. CONCLUSIONS: The paracentesis phantom proves to be a practical and cost-effective training tool. It enables novices to acquire paracentesis skills, enhances their US proficiency, and boosts their confidence. Nevertheless, further investigation is needed to assess its long-term impact on clinical performance in real patients. TRIAL REGISTRATION: NCT04792203 at the ClinicalTrials.gov.

Risk stratification of patients with chest pain who have an unscheduled revisit to the emergency department.

AIMS: Acute cardiovascular (CV) emergencies are critical conditions that require urgent attention in the emergency department (ED). Failure to make a timely diagnosis may result in unscheduled ED revisits and severe outcomes. Therefore, this study aimed to investigate the risk factors associated with potentially missed acute CV emergencies. METHODS AND RESULTS: This retrospective study enrolled adult patients who presented with chest pain and returned to the ED within 72 h. Demographic information, pre-existing medical conditions, chief complaints, triage level and vital signs, electrocardiography (ECG) reports, and laboratory data were collected from medical charts by independent physicians. The primary outcome was the diagnosis of acute CV diseases, including ACS, pulmonary embolism, unstable arrhythmia, acute decompensated heart failure, and aortic dissection. Multivariable logistic regression was used to analyze the association between variables and acute CV emergencies. A total of 453 eligible patients were included, with 60 (13.2%) patients diagnosed as acute CV emergencies at the ED revisit. Risk factors for acute CV emergencies included male gender (adjusted odds ratio [aOR] = 2.71, 95% confidence interval [CI] = 1.17-6.25), abnormal ECG rhythm (aOR = 10.33, 95% CI = 4.68-22.83), and abnormal changes in high sensitivity Troponin-T (hs-cTnT) during sequential follow-up (aOR = 6.52, 95% CI = 2.19-19.45). CONCLUSIONS: Male gender, abnormal ECG rhythm, and a significant increase in sequential follow-up hs-cTnT levels were identified as significant risk factors for acute CV emergencies. ED physicians should recognize these high-risk patients with chest pain to prevent misdiagnosis and potential severe complications.

A simplified scoring model for predicting bacteremia in the unscheduled emergency department revisits: The SADFUL score.

BACKGROUND: Bacteremia is a severe complication of infectious disease. Patients with a high bacteremia risk in the emergency department (ED) but misidentified would lead to the unscheduled revisits. This study aimed to develop a simplified scoring model to predict bacteremia in patients with unscheduled ED revisits. METHODS: Adult patients with unscheduled ED revisits within 72 h with a final diagnosis of infectious disease were retrospectively included. The development cohort included patients visiting the ED from January 1, 2019 to December 31, 2021. Internal validation was performed in patients visiting the ED from January 1, 2022 to March 31, 2022. Variables including demographics, pre-comorbidities, triage levels, vital signs, chief complaints, and laboratory data in the index visit were analyzed. Bacteremia was the primary outcome determined by blood culture in either index visits or revisits. RESULTS: The SADFUL score for predicting bacteremia comprised the following predictors: "S"egmented neutrophil percentage (+3 points), "A"ge > 55 years (+1 point), "D"iabetes mellitus (+1 point), "F"ever (+2 points), "U"pper respiratory tract symptoms (-2 points), and "L"eukopenia (2 points). The area under receiver operating characteristic curve with 95% confidence interval in the development (1802 patients, 190 [11%] with bacteremia) and the validation cohort (134 patients, 17 [13%] with bacteremia) were 0.78 (0.74-0.81) and 0.79 (0.71-0.88), respectively. CONCLUSIONS: The SADFUL score is a simplified useful tool for predicting bacteremia in patients with unscheduled ED revisits. The scoring model could help ED physicians decrease misidentification of patients at a high risk for bacteremia and potential complications.

Intravenous antibiotics at the index emergency department visit as an independent risk factor for hospital admission at the return visit within 72 hours.

INTRODUCTION: Although infection was the most common symptom in patients returning to the ED, whether intravenous antibiotic administration at the index visit could serve as an indicator of patients with infectious diseases at high risk for hospital admission after returning to the ED within a short period of time remains unclear. The study aimed to investigate the potential risk factors for hospital admission in patients returning to the ED within 72 hours with a final diagnosis of infectious diseases. MATERIAL AND METHODS: This retrospective cohort study analyzed return visits to the ED from January to December 2019. Adult patients aged >20 years who had a return visit to the ED within 72 hours with an infectious disease were included herein. In total, 715 eligible patients were classified into the intravenous antibiotics and non-intravenous antibiotics group (reference group). The outcome studied was hospital admission to general ward and intensive care unit (ICU) at the return visits. RESULTS: Patients receiving intravenous antibiotics at index visits had significantly higher risk-approximately two times-for hospital admission at the return visits than those did not (adjusted odds ratio = 2.47, 95% CI = 1.34-4.57, p = 0.004). For every 10 years increase in age, the likelihood for hospital admission increased by 38%. Other factors included abnormal respiratory rate and high C-reactive protein levels. CONCLUSIONS: Intravenous antibiotic administration at the index visit was an independent risk factor for hospital admission at return visits in patients with an infection disease. Physicians should consider carefully before discharging patients receiving intravenous antibiotics.