Your browser doesn't support javascript.
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.
Chandna, Arjun; Mahajan, Raman; Gautam, Priyanka; Mwandigha, Lazaro; Gunasekaran, Karthik; Bhusan, Divendu; Cheung, Arthur T L; Day, Nicholas; Dittrich, Sabine; Dondorp, Arjen; 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 M G; Waithira, Naomi; Kumar, Pragya; Varghese, George M; Koshiaris, Constantinos; Lubell, Yoel; Burza, Sakib.
  • Chandna A; Cambodia Oxford Medical Research Unit, Angkor Hospital for Children, Siem Reap, Cambodia.
  • Mahajan R; Centre for Tropical Medicine & Global Health, University of Oxford, Oxford, United Kingdom.
  • Gautam P; Médecins Sans Frontières, New Delhi, India.
  • Mwandigha L; Department of Infectious Diseases, Christian Medical College, Vellore, India.
  • Gunasekaran K; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom.
  • Bhusan D; Department of Medicine, Christian Medical College, Vellore, India.
  • Cheung ATL; Department of Internal Medicine, All India Institute of Medical Sciences, Patna, India.
  • Day N; Centre for Tropical Medicine & Global Health, University of Oxford, Oxford, United Kingdom.
  • Dittrich S; Mahidol Oxford Tropical Medicine Research Unit, Mahidol University, Bangkok, Thailand.
  • Dondorp A; Centre for Tropical Medicine & Global Health, University of Oxford, Oxford, United Kingdom.
  • Geevar T; Mahidol Oxford Tropical Medicine Research Unit, Mahidol University, Bangkok, Thailand.
  • Ghattamaneni SR; Centre for Tropical Medicine & Global Health, University of Oxford, Oxford, United Kingdom.
  • Hussain S; Foundation for Innovative Diagnostics, Geneva, Switzerland.
  • Jimenez C; Centre for Tropical Medicine & Global Health, University of Oxford, Oxford, United Kingdom.
  • Karthikeyan R; Mahidol Oxford Tropical Medicine Research Unit, Mahidol University, Bangkok, Thailand.
  • Kumar S; Department of Transfusion Medicine & Immunohaematology, Christian Medical College, Vellore, India.
  • Kumar S; Médecins Sans Frontières, New Delhi, India.
  • Kumar V; Médecins Sans Frontières, New Delhi, India.
  • Kundu D; Médecins Sans Frontières, New Delhi, India.
  • Lakshmanan A; Department of Infectious Diseases, Christian Medical College, Vellore, India.
  • Manesh A; Department of Cardiothoracic & Vascular Surgery, All India Institute of Medical Sciences, Patna, India.
  • Menggred C; Department of Virology, Rajendra Memorial Research Institute of Medical Sciences, Patna, India.
  • Moorthy M; Médecins Sans Frontières, New Delhi, India.
  • Osborn J; Department of Infectious Diseases, Christian Medical College, Vellore, India.
  • Richard-Greenblatt M; Médecins Sans Frontières, New Delhi, India.
  • Sharma S; Department of Infectious Diseases, Christian Medical College, Vellore, India.
  • Singh VK; Mahidol Oxford Tropical Medicine Research Unit, Mahidol University, Bangkok, Thailand.
  • Singh VK; Department of Clinical Virology, Christian Medical College, Vellore, India.
  • Suri J; Foundation for Innovative Diagnostics, Geneva, Switzerland.
  • Suzuki S; Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
  • Tubprasert J; Department of Biochemistry, All India Institute of Medical Sciences, Patna, India.
  • Turner P; Department of Burns & Plastic Surgery, All India Institute of Medical Sciences, Patna, India.
  • Villanueva AMG; Médecins Sans Frontières, New Delhi, India.
  • Waithira N; Médecins Sans Frontières, New Delhi, India.
  • Kumar P; School of Tropical Medicine & Global Health, Nagasaki University, Nagasaki, Japan.
  • Varghese GM; Mahidol Oxford Tropical Medicine Research Unit, Mahidol University, Bangkok, Thailand.
  • Koshiaris C; Cambodia Oxford Medical Research Unit, Angkor Hospital for Children, Siem Reap, Cambodia.
  • Lubell Y; Centre for Tropical Medicine & Global Health, University of Oxford, Oxford, United Kingdom.
  • Burza S; School of Tropical Medicine & Global Health, Nagasaki University, Nagasaki, Japan.
Clin Infect Dis ; 75(1): e368-e379, 2022 08 24.
Article in English | MEDLINE | ID: covidwho-1886381
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.
Subject(s)
Keywords

Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Cohort study / Diagnostic study / Experimental Studies / Observational study / Prognostic study Topics: Vaccines Limits: Adult / Humans Language: English Journal: Clin Infect Dis Journal subject: Communicable Diseases Year: 2022 Document Type: Article Affiliation country: Cid

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Cohort study / Diagnostic study / Experimental Studies / Observational study / Prognostic study Topics: Vaccines Limits: Adult / Humans Language: English Journal: Clin Infect Dis Journal subject: Communicable Diseases Year: 2022 Document Type: Article Affiliation country: Cid