ABSTRACT
OBJECTIVE: Investigate the predictive value of NEWS2, NEWS-C, and COVID-19 Severity Index for predicting intensive care unit (ICU) transfer in the next 24h. DESIGN: Retrospective multicenter study. SETTING: Two third-level hospitals in Argentina. PATIENTS: All adult patients with confirmed COVID-19, admitted on general wards, excluding patients with non-intubated orders. INTERVENTIONS: Patients were divided between those who were admitted to ICU and non-admitted. We calculated the three scores for each day of hospitalization. VARIABLES: We evaluate the calibration and discrimination of the three scores for the outcome ICU admission within 24, 48h, and at hospital admission. RESULTS: We evaluate 13,768 days of hospitalizations on general medical wards of 1318 patients. Among these, 126 (9.5%) were transferred to ICU. The AUROC of NEWS2 was 0.73 (95%CI 0.68-0.78) 24h before ICU admission, and 0.52 (95%CI 0.47-0.57) at hospital admission. The AUROC of NEWS-C was 0.73 (95%CI 0.68-0.78) and 0.52 (95%CI 0.47-0.57) respectively, and the AUROC of COVID-19 Severity Index was 0.80 (95%CI 0.77-0.84) and 0.61 (95%CI 0.58-0.66) respectively. COVID-19 Severity Index presented better calibration than NEWS2 and NEWS-C. CONCLUSION: COVID-19 Severity index has better calibration and discrimination than NEWS2 and NEWS-C to predict ICU transfer during hospitalization.
ABSTRACT
Objective Investigate the predictive value of NEWS2, NEWS-C, and COVID-19 Severity Index for predicting intensive care unit (ICU) transfer in the next 24 h. Design Retrospective multicenter study. Setting Two third-level hospitals in Argentina. Patients All adult patients with confirmed COVID-19, admitted on general wards, excluding patients with non-intubated orders. Interventions Patients were divided between those who were admitted to ICU and non-admitted. We calculated the three scores for each day of hospitalization. Variables We evaluate the calibration and discrimination of the three scores for the outcome ICU admission within 24, 48 h, and at hospital admission. Results We evaluate 13,768 days of hospitalizations on general medical wards of 1318 patients. Among these, 126 (9.5%) were transferred to ICU. The AUROC of NEWS2 was 0.73 (95%CI 0.68–0.78) 24 h before ICU admission, and 0.52 (95%CI 0.47–0.57) at hospital admission. The AUROC of NEWS-C was 0.73 (95%CI 0.68–0.78) and 0.52 (95%CI 0.47–0.57) respectively, and the AUROC of COVID-19 Severity Index was 0.80 (95%CI 0.77–0.84) and 0.61 (95%CI 0.58–0.66) respectively. COVID-19 Severity Index presented better calibration than NEWS2 and NEWS-C. Conclusion COVID-19 Severity index has better calibration and discrimination than NEWS2 and NEWS-C to predict ICU transfer during hospitalization.
ABSTRACT
Pandemics pose a major challenge for public health preparedness, requiring a coordinated inter- national response and the development of solid containment plans. Early and accurate identification of high-risk patients in the course of the current COVID-19 pandemic is vital for planning and making proper use of available resources. The purpose of this study was to identify the key variables that account for worse outcomes to create a predictive model that could be used effectively for triage. Through literature review, 44 variables that could be linked to an unfavorable course of COVID-19 disease were obtained, including clinical, laboratory, and X-ray variables. These were used for a 2-round modified Delphi processing with 14 experts to select a final list of variables with the greatest predictive power for the construction of a scoring system, leading to the creation of a new scoring system: the COVID-19 Severity Index. The analysis of the area under the curve for the COVID-19 Severity Index was 0.94 to predict the need for ICU admission in the following 24 hours against 0.80 for NEWS-2. Additionally, the digital medical record of the Hospital Italiano de Buenos Aires was electronically set for an automatic calculation and constant update of the COVID-19 Severity Index. Specifically designed for the current COVID-19 pandemic, COVID-19 Severity Index could be used as a reliable tool for strategic planning, organization, and administration of resources by easily identifying hospitalized patients with a greater need of intensive care.