A NOVEL EVIDENCE-BASED PREDICTOR TOOL FOR HOSPITALIZATION AND LENGTH OF STAY: INSIGHTS FROM PATIENTS WITH COVID-19 IN NEW YORK CITY

TOPIC: Chest Infections TYPE: Original Investigations PURPOSE: Coronavirus disease 2019 (COVID-19) has infected more than 150 million people worldwide. Predictive models for key outcomes can optimize resource utilization and patient outcome as outbreaks continue. We aimed to design and internally validate a web-based calculator predictive of hospitalization and length of stay (LOS) in a large cohort of COVID-19 positive patients presenting to the Emergency Department (ED) in a New York City health system. METHODS: The study cohort consisted of consecutive adult (>18 years) patients presenting to the ED of one of the Mount Sinai Health System hospitals between March, 2020 and April, 2020 who were diagnosed with COVID-19. Logistic regression was utilized to construct predictive models for hospitalization and prolonged (>3 days) LOS. Discrimination was evaluated using area under the receiver operating curve (AUC). Internal validation with bootstrapping was performed, and a web-based calculator was implemented. RESULTS: From 5859 patients, 65% were hospitalized. Independent predictors of hospitalization included older age (OR=6.29;95% CI [1.83-2.63], >65 vs. 18-44), male sex (OR=1.35 [1.17-1.55]), chronic obstructive pulmonary disease (OR=1.74;[1.00-3.03]), hypertension (OR=1.39;[1.13-1.70]), diabetes (OR=1.45;[1.16-1.81]), chronic kidney disease (OR=1.69;[1.23-2.32]), elevated maximum temperature (OR=4.98;[4.28-5.79]), and low minimum oxygen saturation (OR=13.40;[10.59-16.96]). The mean LOS was 7.3 days (SD=5.3 days;median=6 days;IQR=6 days). Predictors of extended LOS included older age (OR=1.03 [1.02-1.04], per year), chronic kidney disease (OR=1.91 [1.35-2.71]), elevated maximum temperature (OR=2.91 [2.40-3.53]), and low minimum percent oxygen saturation (OR=3.89 [3.16-4.79]). AUCs of 0.881 and 0.770 were achieved for hospitalization and LOS, respectively. Elevated levels of CRP, creatinine, and ferritin were key determinants of hospitalization and LOS (p<0.05). A calculator was made available under the following URL: https://covid19-outcome-prediction.shinyapps.io/COVID19_Hospitalization_Calculator/ CONCLUSIONS: This study yielded internally validated models with good discrimination that predict both the need for hospitalization in COVID-19 patients presenting to the ED, and the risk of prolonged hospitalization among admitted patients. Older age, chronic kidney disease, fever, and oxygen desaturation predicted the need of hospitalization and extended LOS. Additional predictors for hospitalization included male gender, chronic obstructive pulmonary disease, hypertension, and diabetes. CLINICAL IMPLICATIONS: We developed a practical tool predicting hospitalization risk in patients presenting to the ED diagnosed with COVID-19. This tool can be used to optimize resource allocation, help guide quality of care, and assist in designing future studies on the triage and management of patients with COVID-19. DISCLOSURES: No relevant relationships by Jeeyune Bahk, source=Web Response No relevant relationships by Maan El Halabi, source=Web Response No relevant relationships by James Feghali, source=Web Response No relevant relationships by Kam Sing Ho, source=Web Response No relevant relationships by Judy Huang, source=Web Response No relevant relationships by Joseph Mathew, source=Web Response no disclosure on file for Bharat Narasimhan;No relevant relationships by Georgina Osorio, source=Web Response No relevant relationships by David Steiger, source=Web Response No relevant relationships by Paulino Tallon de Lara, source=Admin input No relevant relationships by Juan Wisnivesky, source=Web Response