Development and Assessment of an Interpretable Machine Learning Triage Tool for Estimating Mortality After Emergency Admissions.

Importance: Triage in the emergency department (ED) is a complex clinical judgment based on the tacit understanding of the patient's likelihood of survival, availability of medical resources, and local practices. Although a scoring tool could be valuable in risk stratification, currently available scores have demonstrated limitations. Objectives: To develop an interpretable machine learning tool based on a parsimonious list of variables available at ED triage; provide a simple, early, and accurate estimate of patients' risk of death; and evaluate the tool's predictive accuracy compared with several established clinical scores. Design, Setting, and Participants: This single-site, retrospective cohort study assessed all ED patients between January 1, 2009, and December 31, 2016, who were subsequently admitted to a tertiary hospital in Singapore. The Score for Emergency Risk Prediction (SERP) tool was derived using a machine learning framework. To estimate mortality outcomes after emergency admissions, SERP was compared with several triage systems, including Patient Acuity Category Scale, Modified Early Warning Score, National Early Warning Score, Cardiac Arrest Risk Triage, Rapid Acute Physiology Score, and Rapid Emergency Medicine Score. The initial analyses were completed in October 2020, and additional analyses were conducted in May 2021. Main Outcomes and Measures: Three SERP scores, namely SERP-2d, SERP-7d, and SERP-30d, were developed using the primary outcomes of interest of 2-, 7-, and 30-day mortality, respectively. Secondary outcomes included 3-day mortality and inpatient mortality. The SERP's predictive power was measured using the area under the curve in the receiver operating characteristic analysis. Results: The study included 224 666 ED episodes in the model training cohort (mean [SD] patient age, 63.60 [16.90] years; 113 426 [50.5%] female), 56 167 episodes in the validation cohort (mean [SD] patient age, 63.58 [16.87] years; 28 427 [50.6%] female), and 42 676 episodes in the testing cohort (mean [SD] patient age, 64.85 [16.80] years; 21 556 [50.5%] female). The mortality rates in the training cohort were 0.8% at 2 days, 2.2% at 7 days, and 5.9% at 30 days. In the testing cohort, the areas under the curve of SERP-30d were 0.821 (95% CI, 0.796-0.847) for 2-day mortality, 0.826 (95% CI, 0.811-0.841) for 7-day mortality, and 0.823 (95% CI, 0.814-0.832) for 30-day mortality and outperformed several benchmark scores. Conclusions and Relevance: In this retrospective cohort study, SERP had better prediction performance than existing triage scores while maintaining easy implementation and ease of ascertainment in the ED. It has the potential to be widely applied and validated in different circumstances and health care settings.

Modulation of mRNA Translation and Cell Viability by Influenza A Virus Derived Nonstructural Protein 1.

Translation of in vitro transcribed messenger RNA (mRNA) is known to be compromised by cell's innate immune responses. Herein we show that when mRNA encoding nonstructural protein 1 (NS1), an immune evasion gene derived from influenza A virus, is co-delivered with mRNA encoding green fluorescent protein (GFP), higher GFP expression can be observed in four different interferon competent cell types within 6 h, indicating NS1's wide host range property and rapid counter response to the cells' innate immune response. Enhanced mRNA translation correlates with reduced interferon production in all tested cell types and substituting a small portion of luciferase mRNA with NS1 mRNA enhances luciferase production compared to the same dose composing of only luciferase mRNA although in a cell type specific manner. Toxicity caused by transfection of unmodified mRNA is mitigated with the delivery of NS1 mRNA and is observed only in NS1 without cleavage and polyadenylation specificity factor 30 kda (CPSF30) inhibition function. Conversely, delivery of mRNA encoding NS1 with CPSF30 inhibition function aggravated toxicity. Overall, we demonstrate that NS1 enhanced mRNA transfection through active evasion of innate immune responses and modulated cellular viability during mRNA transfection.