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

Author:

Chandna Arjun12,Mahajan Raman3,Gautam Priyanka4,Mwandigha Lazaro5,Gunasekaran Karthik6,Bhusan Divendu7,Cheung Arthur T L28,Day Nicholas28,Dittrich Sabine29,Dondorp Arjen28,Geevar Tulasi10,Ghattamaneni Srinivasa R3,Hussain Samreen3,Jimenez Carolina3,Karthikeyan Rohini4,Kumar Sanjeev11,Kumar Shiril12,Kumar Vikash3,Kundu Debasree4,Lakshmanan Ankita3,Manesh Abi4,Menggred Chonticha8,Moorthy Mahesh13,Osborn Jennifer9,Richard-Greenblatt Melissa14,Sharma Sadhana15,Singh Veena K16,Singh Vikash K3,Suri Javvad3,Suzuki Shuichi17,Tubprasert Jaruwan8,Turner Paul12,Villanueva Annavi M G17,Waithira Naomi28,Kumar Pragya18,Varghese George M4,Koshiaris Constantinos5,Lubell Yoel28,Burza Sakib319

Affiliation:

1. Cambodia Oxford Medical Research Unit, Angkor Hospital for Children , Siem Reap , Cambodia

2. Centre for Tropical Medicine & Global Health, University of Oxford , Oxford , United Kingdom

3. Médecins Sans Frontières , New Delhi , India

4. Department of Infectious Diseases, Christian Medical College , Vellore , India

5. Nuffield Department of Primary Care Health Sciences, University of Oxford , Oxford , United Kingdom

6. Department of Medicine, Christian Medical College , Vellore , India

7. Department of Internal Medicine, All India Institute of Medical Sciences , Patna , India

8. Mahidol Oxford Tropical Medicine Research Unit, Mahidol University , Bangkok , Thailand

9. Foundation for Innovative Diagnostics , Geneva , Switzerland

10. Department of Transfusion Medicine & Immunohaematology, Christian Medical College , Vellore , India

11. Department of Cardiothoracic & Vascular Surgery, All India Institute of Medical Sciences , Patna , India

12. Department of Virology, Rajendra Memorial Research Institute of Medical Sciences , Patna , India

13. Department of Clinical Virology, Christian Medical College , Vellore , India

14. Perelman School of Medicine, University of Pennsylvania , Philadelphia, Pennsylvania , USA

15. Department of Biochemistry, All India Institute of Medical Sciences , Patna , India

16. Department of Burns & Plastic Surgery, All India Institute of Medical Sciences , Patna , India

17. School of Tropical Medicine & Global Health, Nagasaki University , Nagasaki , Japan

18. Department of Community & Family Medicine, All India Institute of Medical Sciences , Patna , India and

19. Department of Clinical Research, London School of Hygiene & Tropical Medicine , London , United Kingdom

Abstract

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.

Funder

Wellcome Trust

Publisher

Oxford University Press (OUP)

Subject

Infectious Diseases,Microbiology (medical)

Reference44 articles.

1. The potential impact of COVID-19 in refugee camps in Bangladesh and beyond: a modeling study;Truelove;PLoS Med,2020

2. Fragility and challenges of health systems in pandemic: early lessons from India’s second wave of coronavirus disease 2019 (COVID-19);Malik;Glob Health J,2022

3. Collapse of the public health system and the emergence of new variants during the second wave of the COVID-19 pandemic in Brazil;Silva;One Health,2021

4. Pragmatic recommendations for the management of acute respiratory failure and mechanical ventilation in patients with COVID-19 in low- and middle-income countries;Serpa Neto;Am J Trop Med Hyg,2021

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