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
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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.
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SciScore for 10.1101/2021.12.02.21267170: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics IRB: Ethical approval was given by the AIIMS, Patna Ethics Committee; CMC Ethics Committee; Oxford Tropical Research Ethics Committee; and MSF Ethical Review Board. Sex as a biological variable not detected. Randomization not detected. Blinding The site study teams were unaware of which baseline variables had been preselected as candidate predictors when determining outcome status. Power Analysis not detected. Table 2: Resources
Antibodies Sentences Resources SARS-CoV-2 IgG and IgM antibodies were measured using the SCoV-2 Detect ELISA (InBios, WA) IgMsuggested: NoneResults from OddPub: Thank you for sharing your data.
Results from LimitationRecognizer: We detected the following sentences addressing …SciScore for 10.1101/2021.12.02.21267170: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics IRB: Ethical approval was given by the AIIMS, Patna Ethics Committee; CMC Ethics Committee; Oxford Tropical Research Ethics Committee; and MSF Ethical Review Board. Sex as a biological variable not detected. Randomization not detected. Blinding The site study teams were unaware of which baseline variables had been preselected as candidate predictors when determining outcome status. Power Analysis not detected. Table 2: Resources
Antibodies Sentences Resources SARS-CoV-2 IgG and IgM antibodies were measured using the SCoV-2 Detect ELISA (InBios, WA) IgMsuggested: NoneResults from OddPub: Thank you for sharing your data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:We addressed the limitations identified in other COVID-19 prognostic models by following the TRIPOD guidelines,18 and using a prospectively collected dataset with minimal loss-to-follow-up and missing data.8 Nevertheless, the small validation cohort (determined by the natural history of the pandemic in India) limits our ability to draw strong conclusions. Although the same models appeared superior in the different analyses we performed, further external validation is required before they can be recommended for use; the PRIORITISE study continues to recruit in Brazil and we have published our full model to encourage independent validation. No vaccinated individuals were included in the study. The models may require recalibration for use in vaccinated populations with lower baseline risk of progression to severe COVID-19. However, it is important to note that only 15/54 African countries met the WHO target of vaccinating 10% of their population by the end of September 2021.40 An estimated 55-70% vaccination coverage is required to achieve herd immunity for a vaccine with 90% efficacy.41 Unfortunately, the timelines for adequate vaccination coverage in many LMICs are likely to be long. The models were developed and validated within the Indian healthcare context. Whilst the two sites are over 2,000 kilometres apart, data from another continent would be important to assess generalisability. Although there are no licensed treatments for moderate COVID-19 available in LMIC contexts,...
Results from TrialIdentifier: We found the following clinical trial numbers in your paper:
Identifier Status Title NCT04441372 Recruiting Prognostication of Oxygen Requirement in Non-severe SARS-CoV… Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
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