Chandna, Arjun; Mahajan, Raman; Gautam, Priyanka; Mwandigha, Lazaro; Gunasekaran, Karthik; Bhusan, Divendu; Cheung, Arthur TL; Day, Nicholas; Dittrich, Sabine; Dondorp, Arjen; +29 more... Geevar, Tulasi; Ghattamaneni, Srinivasa R; Hussain, Samreen; Jimenez, Carolina; Karthikeyan, Rohini; Kumar, Sanjeev; Kumar, Shiril; Kumar, Vikash; Kundu, Debasree; Lakshmanan, Ankita; Manesh, Abi; Menggred, Chonticha; Moorthy, Mahesh; Osborn, Jennifer; Richard-Greenblatt, Melissa; Sharma, Sadhana; Singh, Veena K; Singh, Vikash K; Suri, Javvad; Suzuki, Shuichi; Tubprasert, Jaruwan; Turner, Paul; Villanueva, Annavi MG; Waithira, Naomi; Kumar, Pragya; Varghese, George M; Koshiaris, Constantinos; Lubell, Yoel; Burza, Sakib; (2022) 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. Clinical infectious diseases : an official publication of the Infectious Diseases Society of America, 75 (1). e368-e379. ISSN 1058-4838 DOI: https://doi.org/10.1093/cid/ciac224
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Abstract
BACKGROUND: In locations where few people have received coronavirus disease 2019 (COVID-19) vaccines, health systems remain vulnerable to surges in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. Tools to identify patients suitable for community-based management are urgently needed. METHODS: We prospectively recruited adults presenting to 2 hospitals in India with moderate symptoms of laboratory-confirmed COVID-19 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 1 of 7 shortlisted biochemical biomarkers measurable using commercially available rapid tests (C-reactive protein [CRP], D-dimer, interleukin 6 [IL-6], neutrophil-to-lymphocyte ratio [NLR], procalcitonin [PCT], soluble triggering receptor expressed on myeloid cell-1 [sTREM-1], or soluble urokinase plasminogen activator receptor [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: In total, 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 3 models containing NLR, suPAR, or IL-6 demonstrated promising discrimination (c-statistics: 0.72-0.74) and calibration (calibration slopes: 1.01-1.05) in the validation cohort and provided greater utility than a model containing the clinical parameters alone. CONCLUSIONS: We present 3 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.
Item Type | Article |
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Faculty and Department | Faculty of Infectious and Tropical Diseases > Department of Infection Biology |
PubMed ID | 35323932 |
Elements ID | 213595 |
Official URL | http://dx.doi.org/10.1093/cid/ciac224 |
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Filename: Chandna-etal-2022-Facilitating-safe-discharge-through-predicting-disease-progression-in-moderate-coronavirus-disease-2019-covid-19.pdf
Licence: Creative Commons: Attribution 4.0
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