Medical students as disaster volunteers: A strategy for improving emergency department surge response in times of crisis

Disasters resulting in mass casualty incidents can rapidly overwhelm the Emergency Department (ED). To address critical manpower needs in the ED’s disaster response, medical student involvement has been advocated. Duke-National University of Singapore Medical School is in proximity to Singapore General Hospital and represents an untapped manpower resource. With appropriate training and integration into ED disaster workflows, medical students can be leveraged upon as qualified manpower. This review provides a snapshot of the conceptualization and setting up of the Disaster Volunteer Corps – a programme where medical students were recruited to receive regular training and assessment from emergency physicians on disaster response principles to fulfil specific roles during a crisis, while working as part of a team under supervision. We discuss overall strategy and benefits to stakeholders, emphasizing the close symbiotic relationship between academia and healthcare services.

Heart rate n-variability (HRnV) measures for prediction of mortality in sepsis patients presenting at the emergency department

Sepsis is a potentially life-threatening condition that requires prompt recognition and treatment. Recently, heart rate variability (HRV), a measure of the cardiac autonomic regulation derived from short electrocardiogram tracings, has been found to correlate with sepsis mortality. This paper presents using novel heart rate n-variability (HRnV) measures for sepsis mortality risk prediction and comparing against current mortality prediction scores. This study was a retrospective cohort study on patients presenting to the emergency department of a tertiary hospital in Singapore between September 2014 to April 2017. Patients were included if they were above 21 years old and were suspected of having sepsis by their attending physician. The primary outcome was 30-day in-hospital mortality. Stepwise multivariable logistic regression model was built to predict the outcome, and the results based on 10-fold cross-validation were presented using receiver operating curve analysis. The final predictive model comprised 21 variables, including four vital signs, two HRV parameters, and 15 HRnV parameters. The area under the curve of the model was 0.77 (95% confidence interval 0.70–0.84), outperforming several established clinical scores. The HRnV measures may have the potential to allow for a rapid, objective, and accurate means of patient risk stratification for sepsis severity and mortality. Our exploration of the use of wealthy inherent information obtained from novel HRnV measures could also create a new perspective for data scientists to develop innovative approaches for ECG analysis and risk monitoring.

ST-segment elevation myocardial infarction with non-chest pain presentation at the Emergency Department: Insights from the Singapore Myocardial Infarction Registry

ST-segment elevation myocardial infarction (STEMI) often presents acutely at the Emergency Department (ED). Although chest pain is a classical symptom, a significant proportion of patients do not present with chest pain. The impact of a non-chest pain (NCP) presentation on ED processes-of-care and outcomes is not fully understood. We utilised a national registry to characterise predictors, processes-of-care, and outcomes of NCP STEMI presentations. Retrospective data for all STEMI cases occurring between 2010 and 2012 were analysed from the Singapore Myocardial Infarction Registry. Cases of inpatient onset, inter-facility transfers, and out-of-hospital cardiac arrests were excluded. Univariable analysis of demographic, clinical, processes-of-care, and outcome variables was conducted. Multivariable logistic regression ascertained independent predictors of a NCP presentation and 28-day mortality. Of 4667 STEMI cases, 12.9% presented without chest pain. Patients with NCP presentation were older (median, years = 74 vs. 58; p < 0.001), more likely to be female (39.1% vs. 15.7%; p < 0.001), of the Chinese race (72.5% vs. 62.7%; p < 0.001), and with diabetes (48.6% vs. 36.7%; p < 0.001). These patients were more likely to present with syncope (6.0% vs. 1.9%; p < 0.001) or epigastric pain (10.6% vs. 4.9%; p < 0.001). Patients with NCP presentation were less likely to receive percutaneous coronary intervention (27.0% vs. 75.6%; p < 0.001), had longer door-to-balloon time (median, minutes = 83 vs. 63; p < 0.001), and experienced greater mortality at 28 days (31.2% vs. 4.5%; p < 0.001). On multivariable logistic regression, independent predictors of a NCP presentation included age (adjusted odds ratio [aOR] = 1.05, 95% confidence interval [CI] 1.04-1.07), diabetes (aOR = 1.76, 95% CI 1.40-2.19), BMI (aOR = 0.93, 95% CI 0.91-0.96), and dyslipidemia (aOR = 0.73, 95% CI 0.58-0.91). Absence of chest pain was an independent predictor for 28-day mortality (aOR = 3.46, 95% CI 2.64-4.52). Patients who presented with a NCP STEMI had a distinct clinical profile and experienced poorer outcomes. Routine triage ECG could be considered for patients with high-risk factors and non-classical symptoms.

Validation of the mortality in emergency department sepsis (MEDS) score in a Singaporean cohort

The emergency department (ED) serves as the first point of hospital contact for most septic patients. Early mortality risk stratification using a quick and accurate triage tool would have great value in guiding management. The mortality in emergency department sepsis (MEDS) score was developed to risk stratify patients presenting to the ED with suspected sepsis, and its performance in the literature has been promising. We report in this study the first utilization of the MEDS score in a Singaporean cohort.In this retrospective observational cohort study, adult patients presenting to the ED with suspected sepsis and fulfilling systemic inflammatory response syndrome (SIRS) criteria were recruited. Primary outcome was 30-day in-hospital mortality (IHM) and secondary outcome was 72-hour mortality. MEDS, acute physiology and chronic health evaluation II (APACHE II), and sequential organ failure assessment (SOFA) scores were compared for prediction of primary and secondary outcomes. Receiver operating characteristic (ROC) analysis was conducted to compare predictive performance.Of the 249 patients included in the study, 46 patients (18.5%) met 30-day IHM. MEDS score achieved an area under the ROC curve (AUC) of 0.87 (95% confidence interval [CI], 0.82-0.93), outperforming the APACHE II score (0.77, 95% CI 0.69-0.85) and SOFA score (0.78, 95% CI 0.71-0.85). On secondary analysis, MEDS score was superior to both APACHE II and SOFA scores in predicting 72-hour mortality, with AUC of 0.88 (95% CI 0.82-0.95), 0.81 (95% CI 0.72-0.89), and 0.79 (95% CI 0.71-0.87), respectively. In predicting 30-day IHM, MEDS score ≥12, APACHE II score ≥23, and SOFA score ≥5 performed at sensitivities of 76.1%, 67.4%, and 76.1%, and specificities of 83.3%, 73.9%, and 65.0%, respectively.The MEDS score performed well in its ability for mortality risk stratification in a Singaporean ED cohort.

Combining Heart Rate Variability with Disease Severity Score Variables for Mortality Risk Stratification in Septic Patients Presenting at the Emergency Department

The emergency department (ED) serves as the first point of hospital contact for many septic patients, where risk-stratification would be invaluable. We devised a combination model incorporating demographic, clinical, and heart rate variability (HRV) parameters, alongside individual variables of the Sequential Organ Failure Assessment (SOFA), Acute Physiology and Chronic Health Evaluation II (APACHE II), and Mortality in Emergency Department Sepsis (MEDS) scores for mortality risk-stratification. ED patients fulfilling systemic inflammatory response syndrome criteria were recruited. National Early Warning Score (NEWS), Modified Early Warning Score (MEWS), quick SOFA (qSOFA), SOFA, APACHE II, and MEDS scores were calculated. For the prediction of 30-day in-hospital mortality, combination model performed with an area under the receiver operating characteristic curve of 0.91 (95% confidence interval (CI): 0.88–0.95), outperforming NEWS (0.70, 95% CI: 0.63–0.77), MEWS (0.61, 95% CI 0.53–0.69), qSOFA (0.70, 95% CI 0.63–0.77), SOFA (0.74, 95% CI: 0.67–0.80), APACHE II (0.76, 95% CI: 0.69–0.82), and MEDS scores (0.86, 95% CI: 0.81–0.90). The combination model had an optimal sensitivity and specificity of 91.4% (95% CI: 81.6–96.5%) and 77.9% (95% CI: 72.6–82.4%), respectively. A combination model incorporating clinical, HRV, and disease severity score variables showed superior predictive ability for the mortality risk-stratification of septic patients presenting at the ED.