Development of the PREDS Score to Predict In-Hospital Mortality of Patients with Ebola Virus Disease under Advanced Supportive Care: Results from the EVISTA Cohort in the Democratic Republic of the Congo

Background As mortality remains high for patients with Ebola virus disease (EVD) despite new treatment options, the ability to level up the provided supportive care and to predict the risk of death is of major importance. This analysis of the EVISTA cohort aims to describe advanced supportive care provided to EVD patients in the Democratic Republic of the Congo (DRC) and to develop a simple risk score for predicting in-hospital death, called PREDS. Methods In this prospective cohort (NCT04815175), patients were recruited during the 10(th) EVD outbreak in the DRC across three Ebola Treatment Centers (ETCs). Demographic, clinical, biological, virological and treatment data were collected. We evaluated factors known to affect the risk of in-hospital death and applied univariate and multivariate Cox proportional-hazards analyses to derive the risk score in a training dataset. We validated the score in an internal-validation dataset, applying C-statistics as a measure of discrimination. Findings Between August 1(st) 2018 and December 31(th) 2019, 711 patients were enrolled in the study. Regarding supportive care, patients received vasopressive drug (n = 111), blood transfusion (n = 101), oxygen therapy (n = 250) and cardio-pulmonary ultrasound (n = 15). Overall, 323 (45%) patients died before day 28. Six independent prognostic factors were identified (ALT, creatinine, modified NEWS2 score, viral load, age and symptom duration). The final score range from 0 to 13 points, with a good concordance (C = 86.24%) and calibration with the Hosmer-Lemeshow test (p = 0.12). Interpretation The implementation of advanced supportive care is possible for EVD patients in emergency settings. PREDS is a simple, accurate tool that could help in orienting early advanced care for at-risk patients after external validation. Copyright (c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)