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

Arjun Chandna, Raman Mahajan, Priyanka Gautam, Lazaro Mwandigha, Karthik Gunasekaran, Divendu Bhusan, Arthur T. L. Cheung, Nicholas Day, Sabine Dittrich, Arjen Dondorp, Tulasi Geevar, Srinivasa R. Ghattamaneni, Samreen Hussain, Carolina Jimenez, Rohini Karthikeyan, Sanjeev Kumar, Shiril Kumar, Vikash Kumar, Debasree Kundu, Ankita LakshmananAbi Manesh, Chonticha Menggred, Mahesh Moorthy, Jennifer Osborn, Melissa Richard-Greenblatt, Sadhana Sharma, Veena K. Singh, Vikash K. Singh, Javvad Suri, Shuichi Suzuki, Jaruwan Tubprasert, Paul Turner, Annavi M. G. Villanueva, Naomi Waithira, Pragya Kumar, George M. Varghese, Constantinos Koshiaris, Yoel Lubell, Sakib Burza

Research output: Contribution to journalArticleAcademicpeer-review

2 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)e368-e379
JournalClinical Infectious Diseases
Volume75
Issue number1
DOIs
Publication statusPublished - 1 Jul 2022

Keywords

  • COVID-19
  • LMIC
  • low- and middle-income country
  • prognostic model
  • triage

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