Prognostication of Oxygen Requirement in Non-severe SARS-CoV-2 Infection

Background At the time of writing the novel betacoronavirus SARS-CoV-2 has infected more than 11 million individuals and killed more than 500,000. The most recent epidemiological surveillance curve shows that the number of new infections continues to rise, with over 230,000 new cases reported in the last 24 hours. Whilst the absolute number of deaths attributable to COVID-19 is substantial, effectively managing high patient volumes is also a major challenge facing health systems, particularly in under-resourced settings. With an estimated case-fatality rate amongst symptomatic patients of between 1-2%, it is vitally important that health workers are able to accurately identify the majority of patients at low risk for progression to severe disease. These patients can be safely discharged away from the health facility ensuring the available resources are allocated to patients most likely to benefit. If low-risk patients cannot be readily identified, there is a real risk that health facilities in these regions will be overrun, with consequent substantial avoidable mortality. COVID-19 has already started to hit extremely vulnerable populations in refugee camps and conflict areas. In Bangladesh, cases within the Rohingya refugee megacamps have already been reported, and local transmission is ongoing. Such contexts already suffer from a lack of medical facilities and even a moderate number of COVID-19 cases will overburden existing, and proposed, capacity. Having the ability to prognosticate the need for supplemental oxygen (the main treatment available in these settings) through measurement of parameters available at the time of arrival at a healthcare facility would strengthen the capability to identify those patients presenting with moderate symptoms that can be safely discharged away from the facility. Based on recent estimates, only 20% of all symptomatic patients with COVID-19 develop a requirement for supplemental oxygen. Although existing prognostic scores have yielded disappointing results in patients with SARS-CoV-2 infection a number of demographic, clinical and laboratory parameters are associated with a more severe disease course and worse patient outcomes. However, to our knowledge, few studies have examined the performance of prognostic markers in patients who do not require supplemental oxygen at presentation. Only one of these studies included outpatient or ambulatory care settings and none were conducted in resource-limited settings. Hence, whether measurement of these parameters can inform the decision to safely discharge a patient away from a health facility is as yet unclear. Main research question In adults presenting to care with non-severe COVID-19, can subsequent need for oxygen be predicted from parameters measured at the time of arrival at a healthcare facility? This study will evaluate several clinical and biochemical biomarkers that have been identified as possible predictors of deterioration in patients with COVID-19. The primary objective is to develop a prognostic tool combining up to four markers (including a maximum of two biochemical markers) with a high negative predictive value (NPV) for subsequent supplemental oxygen requirement (WHO Grade ≥ 5). Clinical biomarkers will be limited to simple clinico-demographic variables (for example, age, sex and duration of symptoms) in order to ensure the tool remains as simple as possible. Biochemical biomarkers for which point-of-care (POC) and/or near-patient tests are either already commercially available or in late-stage development have been prioritised, in order to maximise the chance of translation on to the field within a time period that is useful for the current global pandemic response. The requirement for supplemental oxygen has been selected as the primary outcome: it is a relatively objective endpoint (based either on the measurement of peripheral oxygen saturation \[sO2 ≤ 93%\] or a respiratory rate \> 30 breaths per minute or a clinical decision to give supplemental oxygen) and from a practical perspective is the main evidence-based therapeutic intervention available in such settings, but in very limited supply in the majority of low- and middle-income countries (LMICs). We have identified near-patient tests for one of the priority biochemical biomarkers that have not yet been field-evaluated in LMICs (suPAR). We will evaluate the performance of this test under field conditions. We have selected this test for evaluation because unlike the other potential markers for which near-patient tests also exist, there is a relative paucity of field experience in tropical settings. As all biochemical markers will be measured using a validated multi-analyte quantitative immunoassay (using the Ella platform), this study will provide an opportunity to evaluate the field performance of these tests. If either of the markers is found to be useful prognosticators for patients with non-severe SARS-CoV-2 infection, this may facilitate a more rapid translation of the results of this study into practice. Assumptions, limitations, and generalisability The main assumption that underlies this work is that a validated, rapid, low-cost antigen-based test for SARS-CoV-2 will become available in the near future. There is reason to believe that this will be the case.Availability of such a test would allow the prognostic tool developed in this study to be applied to the appropriate patient population at the point of arrival at a health facility. Whilst the absence of such a test would undoubtedly limit the utility of the tool, it is likely that when local incidence of patients presenting with confirmed SARS-CoV-2 infection exceeds a threshold, use of the tool could be justified based upon a clinical case definition alone. Furthermore, in order to mitigate this risk, we plan to use the data collected in this study (specifically the baseline and outcome data collected from participants who are subsequently confirmed to be SARS-CoV-2 negative by RT-PCR) to inform exploratory simulation analyses, with the aim of customizing of the tool for use in different prevalence settings, thereby extending utility to different phases of the pandemic. An additional limitation of this study is that due to its single-site nature we will not be able to explore whether the performance of the prognostic markers is impacted by different host populations, or perform an external geographic validation of the prognostic model. To mitigate this risk we have designed a pragmatic study that could be implemented in other sites. We are actively exploring options for conducting the study at other sites if sufficient additional funding can be identified. We will inform and seek approval from all relevant regulatory bodies (international and local) prior to the inclusion of any additional study sites.