Simple risk scores to predict hospitalization or death in outpatients with COVID-19 including the Omicron variant (preprint)

ABSTRACT

Importance Outpatient physicians need guidance to support their clinical decisions regarding management of patients with COVID-19, specifically whether to hospitalize a patient or if managed as an outpatient, how closely to follow them. Objective To develop and prospectively validate a clinical prediction rule to predict the likelihood of hospitalization for outpatients with COVID-19 that does not require laboratory testing or imaging, including during the current Omicron wave. Design Derivation and temporal validation of a clinical prediction rule, and prospective validation of two externally derived clinical prediction rules. Setting Primary and urgent care clinics in a Pennsylvania health system. Participants Patients 12 years and older presenting to outpatient clinics who had a positive polymerase chain reaction test for COVID-19. Main outcomes and measures Classification accuracy (percentage in each risk group hospitalized) and area under the receiver operating characteristic curve (AUC). Results Overall, 4.0% of outpatients in the early derivation cohort (5843 patients presenting before 3/1/21), 4.2% in the late validation cohort (3806 patients presenting 3/1/21 to 9/30/21), and 1.9% in an Omicron cohort were ultimately hospitalized. We developed and temporally validated four simple risk scores. The base score included age, dyspnea, and the presence of a comorbidity, with the other scores adding fever, respiratory rate and/or oxygen saturation. All had very good overall accuracy (AUC 0.85-0.87) and classified at least half of patients into a low risk with a < 1% likelihood of hospitalization. Hospitalization rates in the Omicron cohort were 0.22%, 1.3% and 8.7% for the base score. Two externally derived risk scores identified more low risk patients, but with a higher overall risk of hospitalization than our novel risk scores. Conclusions and relevance A simple risk score applicable to outpatient and telehealth settings can classify over half of COVID-19 outpatients into a very low risk group with a 0.22% hospitalization risk in the Omicron cohort. The Lehigh Outpatient COVID Hospitalization (LOCH) risk score is available online as a free app https//ebell-projects.shinyapps.io/LehighRiskScore/ . Key points Question Is it possible to predict the eventual likelihood of hospitalization for outpatients with COVID-19 using simple non-laboratory based risk scores? Findings We created and temporally validated in the same population 4 risk scores with 3 to 5 predictors that do not require laboratory testing. Groups with low (0.34% to 0.89%), moderate (4.0% to 6.2%), and high-risk (19.2% to 25.2%) of hospitalization were identified. The risk scores were also accurate in an Omicron dominant cohort with hospitalization rates of 0.22% to 0.43% in the low-risk groups, 1.3% to 1.7% in the moderate risk groups, and 8.7% to 15.3% in the high risk groups. Meaning Simple risk scores can help support decisions about hospitalization in the outpatient setting.