Facilitating Safe Discharge Through Predicting Disease Progression in Moderate Coronavirus Disease 2019 (COVID-19): A Prospective Cohort Study to Develop and Validate a Clinical Prediction Model in Resource-Limited Settings

Abstract

Background In locations where few people have received COVID-19 vaccines, health systems remain vulnerable to surges in SARS-CoV-2 infections. Tools to identify patients suitable for community-based management are urgently needed. Methods We prospectively recruited adults presenting to two hospitals in India with moderate symptoms of laboratory-confirmed COVID-19 in order to develop and validate a clinical prediction model to rule-out progression to supplemental oxygen requirement. The primary outcome was defined as any of the following: SpO2 < 94%; respiratory rate > 30 bpm; SpO2/FiO2 < 400; or death. We specified a priori that each model would contain three clinical parameters (age, sex and SpO2) and one of seven shortlisted biochemical biomarkers measurable using commercially-available rapid tests (CRP, D-dimer, IL-6, NLR, PCT, sTREM-1 or suPAR), to ensure the models would be suitable for resource-limited settings. We evaluated discrimination, calibration and clinical utility of the models in a held-out temporal external validation cohort. Results 426 participants were recruited, of whom 89 (21.0%) met the primary outcome. 257 participants comprised the development cohort and 166 comprised the validation cohort. The three models containing NLR, suPAR or IL-6 demonstrated promising discrimination (c-statistics: 0.72 to 0.74) and calibration (calibration slopes: 1.01 to 1.05) in the validation cohort, and provided greater utility than a model containing the clinical parameters alone. Conclusions We present three clinical prediction models that could help clinicians identify patients with moderate COVID-19 suitable for community-based management. The models are readily implementable and of particular relevance for locations with limited resources.

Host Biomarkers Reflect Prognosis in Patients Presenting With Moderate Coronavirus Disease 2019: A Prospective Cohort Study

“…In a previous analysis, we developed and validated 3 readily implementable clinical prediction models for supplemental oxygen requirement in patients presenting with moderate COVID-19 [ 9 ]. The models combined 3 simple clinical predictors with a host biomarker for which commercial point-of-care tests are available.…”

Circulating suPAR associates with severity and in‐hospital progression of COVID‐19

“…A recent study funded by Médecins Sans Frontières (MSF) evaluated a clinical prediction model including age, sex, peripheral oxygen saturation, and suPAR to assist with the assessment of patients with COVID‐19, categorized by the WHO‐CPS, in high‐patient‐throughput resource‐limited settings. 28 The primary outcome was development of oxygen requirement within 14 days of enrolment, and the authors found suPAR and interleukin‐6 to be the best predictors for need of oxygen. The combination of prehospital MSF model with the in‐hospital SALGA model may prove the best strategy to decompress overstretched healthcare systems and reduce healthcare costs by supporting clinicians to identify which patients with COVID‐19 will deteriorate throughout the continuum of the disease.…”