Identification on Admission of COVID-19 Patients at Risk of Subsequent Rapid Clinical Deterioration

Beals, J.; Barnes, J.; Durand, D.; Rimar, J.; Donohue, T.; Hoq, M.; Belk, K.; Amin, A.; Rothman, M.

Introduction: Recent localized surges in COVID-19 cases have resulted in the hospitals serving those areas being overwhelmed. In such cases, the ability to rapidly and objectively determine a patient's acuity and predict near-term care needs is a major challenge. At issue is the clinician's ability to correctly identify patients at risk for subsequent rapid clinical deterioration. Data-driven tools that can support such determinations in real-time may be a valuable adjunct to clinician judgement during COVID-19 surges. Objective: To assess the effectiveness of the Rothman Index (RI) predictive model in distinguishing the risk of subsequent deterioration or elevated care needs among hospitalized COVID-19 patients at the time of hospital admission. Methods: We evaluated the initial RI score on admission to predict COVID-19 patient risk for 216 COVID-19 patients discharged from March 21st to June 7th, 2020 at Sinai LifeBridge Hospital and 1,453 COVID-19 patients discharged from any of Yale New Haven Health System's Yale New Haven, Bridgeport, and Greenwich hospitals from April 1st to April 28th, 2020. In-hospital mortality as a function of age and RI on admission for COVID-19 and non-COVID-19 patients were compared. AUC values using each COVID-19 patient's initial RI on admission to predict in-hospital mortality, mechanical ventilation, and ICU utilization were computed, as were precision and recall for mortality prediction at specific RI thresholds. Results: The RI computed at the time of admission provides a high degree of objective discrimination to differentiate the COVID-19 population into high and low risk populations at the outset of hospitalization. The high risk segment based on initial RI constitutes 20-30% of the COVID-19 positive population with mortality rates from 40-50%. The low risk segment based on initial RI constitutes 40%-55% of the population with mortality rates ranging from 1%-8%. Of note is that COVID-19 patients who present with heightened but generally unremarkable acuity can be identified early as having considerably elevated risk for subsequent physiological deterioration. Conclusion: COVID-19 patients exhibit elevated mortality rates compared to non-COVID-19 medical service patients and may be subject to rapid deterioration following hospital admission. A lack of predictive indicators for identifying patients at high risk of subsequent deterioration or death can pose a challenge to clinicians. The RI has excellent performance characteristics when stratifying risk among COVID-19 patients at the time of admission. The RI can assist clinicians in real-time with a high degree of objective discrimination by segmenting the COVID-19 population into high and low risk populations. This supports rapid and optimal patient bed assignment and resource allocation.