An adaptive randomized controlled trial of non-invasive respiratory strategies in acute respiratory failure patients with COVID-19

BackgroundBoth continuous positive airway pressure (CPAP) and high-flow nasal oxygenation (HFNO) have been recommended for acute respiratory failure in COVID-19. However, uncertainty exists regarding effectiveness and safety. MethodsIn the Recovery-Respiratory Support multi-center, three-arm, open-label, adaptive, randomized controlled trial, adult hospitalized patients with acute respiratory failure due to COVID-19, deemed suitable for treatment escalation, were randomly assigned to receive CPAP, HFNO, or conventional oxygen therapy. Comparisons were made between each intervention and conventional oxygen therapy. The primary outcome was a composite of tracheal intubation or mortality within 30-days. ResultsOver 13-months, 1272 participants were randomized and included in the analysis (380 (29.9%) CPAP; 417 (32.8%) HFNO; 475 (37.3%) conventional oxygen therapy). The need for tracheal intubation or mortality within 30-days was lower in the CPAP group (CPAP 137 of 377 participants (36.3%) vs conventional oxygen therapy 158 of 356 participants (44.4%); unadjusted odds ratio 0.72; 95% CI 0.53 to 0.96, P=0.03). There was no difference between HFNO and conventional oxygen therapy (HFNO 184 of 414 participants (44.4%) vs conventional oxygen therapy 166 of 368 participants (45.1%); unadjusted odds ratio 0.97; 95% CI 0.73 to 1.29, P=0.85). ConclusionsCPAP, compared with conventional oxygen therapy, reduced the composite outcome of intubation or death within 30 days of randomisation in hospitalized adults with acute respiratory failure due to COVID-19. There was no effect observed, compared with conventional oxygen therapy, with the use of HFNO. (Funded by the UK National Institute for Health Research; ISRCTN 16912075).

Development and validation of blood-based prognostic biomarkers for severity of COVID disease outcome using EpiSwitch 3D genomic regulatory immuno-genetic profiling.

The COVID-19 pandemic has raised several global public health challenges to which the international medical community have responded. Diagnostic testing and the development of vaccines against the SARS-CoV-2 virus have made remarkable progress to date. As the population is now faced with the complex lifestyle and medical decisions that come with living in a pandemic, a forward-looking understanding of how a COVID-19 diagnosis may affect the health of an individual represents a pressing need. Previously we used whole genome microarray to identify 200 3D genomic marker leads that could predict mild or severe COVID-19 disease outcomes from blood samples in a multinational cohort of COVID-19 patients. Here, we focus on the development and validation of a qPCR assay to accurately predict severe COVID-19 disease requiring intensive care unit (ICU) support and/or mechanical ventilation. From 200 original biomarker leads we established a classification model containing six markers. The markers were qualified and validated on 38 COVID-19 patients from an independent cohort. Overall, the six-marker model obtained a positive predictive value of 93% and balanced accuracy of 88% across 116 patients for the prognosis of COVID-19 severity requiring ICU care/ventilation support. The six-marker signature identifies individuals at the highest risk of developing severe complications in COVID-19 with high predictive accuracy and can assist in patient prognosis and clinical management decisions.

Relevance of prediction scores derived from the SARS-CoV-2 first wave, in the UK COVID-19 second wave, for early discharge, severity and mortality: a PREDICT COVID UK prospective observational cohort study

ObjectiveProspectively validate two prognostic scores, pre-hospitalisation (SOARS) and hospitalised mortality prediction (4C Mortality Score), derived from the coronavirus disease 2019 (COVID-19) first wave, in the evolving second wave with prevalent B.1.1.7 and parent D614 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants, in two large United Kingdom (UK) cohorts. DesignProspective observational cohort study of SOARS and 4C Mortality Score in PREDICT (single site) and multi-site ISARIC (International Severe Acute Respiratory and Emerging Infections Consortium) cohorts. SettingProtocol-based data collection in UK COVID-19 second wave, between October 2020 and January 2021, from PREDICT and ISARIC cohorts. Participants1383 from single site PREDICT cohort and 20,595 from multi-site ISARIC cohort. Main outcome measuresRelevance of SOARS and 4C Mortality Score derived from the COVID-19 first wave, determining in-hospital mortality and safe discharge in the UK COVID-19 second wave. ResultsData from 1383 patients (median age 67y, IQR 52-82; mortality 24.7%) in the PREDICT and 20,595 patients from the ISARIC (mortality 19.4%) cohorts showed both SOARS and 4C Mortality Score remained relevant despite the B.1.1.7 variant and treatment advances. SOARS had AUC of 0.8 and 0.74, while 4C Mortality Score had an AUC of 0.83 and 0.91 for hospital mortality, in the PREDICT and ISARIC cohorts respectively, therefore effective in evaluating both safe discharge and in-hospital mortality. 19.3% (231/1195, PREDICT cohort) and 16.7% (2550/14992, ISARIC cohort) with a SOARS of 0-1 were potential candidates for home discharge to a virtual hospital (VH) model. SOARS score implementation resulted in low re-admission rates, 11.8% (27/229), and low mortality, 0.9% (2/229), in the VH pathway. Use is still suboptimal to prevent admission, as 8.1% in the PREDICT cohort and 9.5% in the ISARIC cohort were admitted despite SOARS score of 0-1. ConclusionSOARS and 4C Mortality Score remains valid, providing accurate prognostication despite evolving viral subtype and treatment advances, which have altered mortality. Both scores are easily implemented within urgent care pathways with a scope for admission avoidance. They remain safe and relevant to their purpose, transforming complex clinical presentations into tangible numbers, aiding objective decision making. Trial registrationNHS HRA registration and REC approval (20/HRA/2344, IRAS ID 283888).

Increased prevalence and clinical impact of hypocalcaemia in severe COVID-19 distinguishes it from other forms of infective pneumonia

BackgroundHypocalcaemia has been reported in the context of acute COVID-19, where it has been associated with an increased risk of hospitalisation and disease severity. Calcium is an important intracellular messenger that controls diverse cellular processes. Two other clinically important coronaviruses, SARS-CoV-1 and Middle East respiratory syndrome (MERS)-CoV, can use calcium ions to enter and replicate within host cells. Calcium may therefore be important in the pathophysiology of COVID-19 infection. We sought to investigate whether calcium derangement was a specific feature of COVID-19 that distinguishes it from other infective pneumonias, and its association with disease severity. MethodsWe conducted a single centre retrospective study of albumin-corrected serum calcium on adult patients with COVID-19 who presented between March 1st and May 16th 2020. The primary outcome was maximal level of care based on the World Health Organization Clinical Progression Scale for COVID-19. Cases with community acquired pneumonia (CAP) and viral pneumonia (VP) were identified through a clinical database over three intervals (January to February 2018, January to February 2019 and September to December 2019). ResultsWe analysed data from 506 patients with COVID-19, 95 patients with CAP and 152 patients with VP. Hypocalcaemia (serum calcium <2.2mmol/L) was a specific and common clinical finding in patients with COVID-19 that was not present in other respiratory infections. Calcium levels were significantly lower in those with severe disease. Ordinal regression of risk estimates for categorised care levels showed that baseline hypocalcaemia was incrementally associated with odds ratio of 2.33 for higher level of care, superior to other variables that have previously been shown to predict worse COVID-19 outcome. Serial calcium levels showed improvement by day 7-9 of admission, only in in survivors of COVID-19. ConclusionHypocalcaemia may independently predict not only more severe but more progressive disease and warrants detailed prognostic investigation. The fact that decreased serum calcium is observed at the time of clinical presentation in COVID-19, but not other infective pneumonias, suggests that its early derangement is pathophysiological and may influence the deleterious evolution of this disease. If calcium is ultimately shown to be critical to the entry and replication of SARS-CoV-2 in host cells, unravelling how this mechanism could be therapeutically targeted deserves more intensive examination. Trial registration HRA20/HRA/2344.

3D genomic capture of regulatory immuno-genetic profiles in COVID-19 patients for prognosis of severe COVID disease outcome

Human infection with the SARS-CoV-2 virus leads to coronavirus disease (COVID-19). A striking characteristic of COVID-19 infection in humans is the highly variable host response and the diverse clinical outcomes, ranging from clinically asymptomatic to severe immune reactions leading to hospitalization and death. Here we used a 3D genomic approach to analyse blood samples at the time of COVID diagnosis, from a global cohort of 80 COVID-19 patients, with different degrees of clinical disease outcomes. Using 3D whole genome EpiSwitch(R) arrays to generate over 1 million data points per patient, we identified a distinct and measurable set of differences in genomic organization at immune-related loci that demonstrated prognostic power at baseline to stratify patients with mild forms of illness and those with severe forms that required hospitalization and intensive care unit (ICU) support. Further analysis revealed both well established and new COVID-related dysregulated pathways and loci, including innate and adaptive immunity; ACE2; olfactory, G{beta}{psi}, Ca2+ and nitric oxide (NO) signalling; prostaglandin E2 (PGE2), the acute inflammatory cytokine CCL3, and the T-cell derived chemotactic cytokine CCL5. We identified potential therapeutic agents for mitigation of severe disease outcome, with several already being tested independently, including mTOR inhibitors (rapamycin and tacrolimus) and general immunosuppressants (dexamethasone and hydrocortisone). Machine learning algorithms based on established EpiSwitch(R) methodology further identified a subset of 3D genomic changes that could be used as prognostic molecular biomarker leads for the development of a COVID-19 disease severity test.

Evaluation of the ROX index in SARS-CoV-2 Acute Respiratory failure treated with both High-Flow Nasal Oxygen (HFNO) and Continuous Positive Airway Pressure (CPAP)

BackgroundNon-invasive respiratory support including high-flow nasal oxygen (HFNO), and continuous positive airway pressure (CPAP) have been used to provide therapy in selected SARS-CoV-2 patients with acute respiratory failure (ARF). The value of the ROX index, a validated benchmark for outcomes in HFNO is unknown in CPAP. ObjectiveCan the ROX, a validated benchmark in HFNO be used for measuring treatment outcomes of CPAP in SARS-COV-2 ARF? Study Design and MethodsA non-randomised prospective protocol driven observational non-intensive care unit study in 130 SARS-COV-2 patients with ARF treated with non-invasive therapy from March 2020 to January 2021. The primary end point was failure of therapy (death or escalation). Secondary outcomes included time to failure including invasive mechanical ventilation (IMV) or death, the effect of escalation to CPAP from HFNO and the utility of ROX in ARF. ResultsHFNO was better than CPAP in treating SARS-COV-2 ARF: 17/35 (48.5%) with successful HFNO therapy versus 24/95 (25.2%) with CPAP. The ROX index was more sensitive to outcomes with CPAP compared to HFNO and distinguished treatment failure early at 1, 4, 6, 12, and 24 hours with the highest sensitivity at 24 hours (ROX-24h). The AUC for the ROX-24h was 0.77 for HFNO (P<0.0001), and 0.84 for CPAP (P<0.0001). The ROX-24h cut-points predicted failure with HFNO when < 3.9 (PPV 71%, NPV 75%) and CPAP < 4.3 (PPV 75%, NPV 91%). For success, ROX-24h cut-points of 7.6 for HFNO (PPV 85%, NPV 48%) and 6.1 for CPAP (PPV 88%, NPV 62%) were observed. Escalation from HFNO to CPAP was mostly not successful. ConclusionARF in SARS-COV-2 can be successfully managed by non-invasive support. The ROX index, validated for HFNO, provides a timely, low resource measure for both HFNO and CPAP avoiding delayed intubation. Trial registrationStudy approved by NHS HRAREC (20/HRA/2344;ethics 283888) KEY MESSAGEO_ST_ABSWhat is the key question?C_ST_ABSCan the ROX, a validated benchmark in high-flow nasal oxygen (HFNO) be used for measuring treatment outcomes of continuous positive airway pressure (CPAP) in SARS-COV-2 ARF? What is the bottom line?The ROX index, validated for HFNO, provides a timely, low resource measure for both HFNO and CPAP support avoiding delayed intubation. Why read on?The present study compares the efficacy of HFNO and CPAP, two common globally used modalities of treatment for SARS-CoV-2 and notes the superior utility of the ROX-24h in CPAP to predict outcome, enabling timely escalation decisions.

Accuracy of Rapid Point-of-Care Antibody Test in patients with suspected or confirmed COVID-19

ObjectivesTo assess the real-world diagnostic accuracy of the Livzon point-of-care rapid test for antibodies to SARS-COV-2 DesignProspective cohort study SettingDistrict general hospital in England Participants173 Patients and 224 hospital staff with a history of COVID-19 symptoms, and who underwent PCR and/or reference antibody testing for COVID-19. InterventionsThe Livzon point-of-care (POC) lateral flow immunoassay rapid antibody test (IgM and IgG) was conducted at least 7 days after onset of symptoms and compared to the composite reference standard of PCR for SARS-COV-2 plus reference laboratory testing for antibodies to SARS-COV-2. The SARS-CoV-2 RT-PCR was tested using the available molecular technology during the study time (PHE laboratories, GeneXpert(R) system Xpert, Xpress SARS-CoV-2 and Source bioscience laboratory). All molecular platforms/assays were PHE/NHSE approved. The reference antibody test was the Elecsys Anti-SARS-CoV-2 assay (Roche diagnostics GmBH). Main outcome measuresSensitivity and specificity of the rapid antibody test ResultsThe reference antibody test was positive in 190/268 (70.9%) of participants with a history of symptoms suggestive of COVID-19; in the majority (n=312) the POC test was taken 35 days or more after onset of symptoms. The POC antibody test had an overall sensitivity of 90.1% (292/328, 95% CI 86.3 - 93.1) and specificity of 100% (68/68, 95% CI 94.7 - 100) for confirming prior SARS-CoV-2 infection when compared to the composite reference standard. Sensitivity was 97.8% (89/92, 95% CI 92.3% to 99.7%) in participants who had been admitted to hospital and 84.4% (124/147, 95% CI 77.5% to 89.8%) in those with milder illness who had never been seen in hospital. ConclusionsThe Livzon point-of-care antibody test had comparable sensitivity and specificity to the reference laboratory antibody test, so could be used in clinical settings to support decision-making about patients presenting with more than 10 days of symptoms of COVID-19. What is already known on this topic- Presence of IgG and IgM antibodies to SARS-COV-2 indicates that the person was infected at least 7 days previously and is usually no longer infectious. - Rapid point-of-care tests for antibodies to SARS-COV-2 are widely available, cheap and easy to use - Preliminary evaluations suggested that rapid antibody tests may have insufficient accuracy to be useful for testing individual patients. What this study adds- The rapid point-of-care test for antibodies to SARS-COV-2 was 90.1% sensitive and 100% specific compared to reference standards for prior infection with COVID-19. - This is comparable to reference antibody tests - The point-of-care test evaluated in this study could be used to support clinical decision-making in real time, for patients presenting with symptoms of possible COVID-19 with at least 10 days of symptoms.

Predictors of adverse outcome in patients with suspected COVID-19 managed in a virtual hospital setting: a cohort study

ObjectiveIdentify predictors of adverse outcome in a Virtual Hospital (VH) setting for COVID 19. DesignReal-world prospective observational study. SettingVirtual hospital remote assessment service in West Hertfordshire NHS Trust, UK. ParticipantsPatients with suspected COVID-19 illness enrolled directly from the community (post-accident and emergency (A&E) or medical intake assessment) or post-inpatient admission. Main outcome measureDeath or (re-)admission to inpatient hospital care over 28 days. Results900 patients with a clinical diagnosis of COVID-19 (455 referred from A&E or medical intake and 445 post-inpatient) were included in the analysis. 76 (8.4%) of these experienced an adverse outcome (15 deaths in admitted patients, 3 deaths in patients not admitted, and 58 additional inpatient admissions). Predictors of adverse outcome were increase in age (OR 1.04 [95%CI: 1.02, 1.06] per year of age), history of cancer (OR 2.87 [95%CI: 1.41, 5.82]), history of mental health problems (OR 1.76 [95%CI: 1.02, 3.04]), severely impaired renal function (OR for eGFR <30 = 9.09 [95%CI: 2.01, 41.09]) and having a positive SARS-CoV-2 PCR result (OR 2.0 [95% CI: 1.11, 3.60]). ConclusionsThese predictors may help direct intensity of monitoring for patients with suspected or confirmed COVID-19 who are being remotely monitored by primary or secondary care services. Further research is needed to identify the reasons for increased risk of adverse outcome associated with cancer and mental health problems. ARTICLE SUMMARYO_ST_ABSStrengths and limitations of this studyC_ST_ABSO_LIThe study uses anonymised data from all patients registered for the virtual hospital between 17/03/20 and 17/05/20, and therefore selection bias is not an issue. C_LIO_LIAt the time of this study, this was the only service providing remote follow-up for patients with suspected COVID-19 in the area, and therefore our findings are likely to be relevant to primary care patients receiving remote follow-up. C_LIO_LIWe were able to collect reliable data on a wide range of clinical and demographic features, and reliably follow all patients for the primary outcome for at least two weeks following their discharge from the VH. C_LIO_LIWe were not able to extract detailed symptom or clinical examination data, and there were significant amounts of missing data for some variables. C_LIO_LIOur study is likely underpowered to detect all predictors, especially in the analysis of our two sub-groups C_LI

Early prognostication of COVID-19 to guide hospitalisation versus outpatient monitoring using a point-of-test risk prediction score

IntroductionRisk factors of adverse outcomes in COVID-19 are defined but stratification of mortality using non-laboratory measured scores, particularly at the time of pre-hospital SARS-CoV-2 testing, is lacking. MethodsMultivariate regression with bootstrapping was used to identify independent mortality predictors in a derivation cohort of COVID-19 patients. Predictions were externally validated in a large random sample of the ISARIC cohort (N=14,231) and a smaller cohort from Aintree (N=290). Results983 patients (median age 70, IQR 53-83; in-hospital mortality 29.9%) were recruited over an 11-week study period. Through sequential modelling, a 5-predictor score termed SOARS (SpO2, Obesity, Age, Respiratory rate, Stroke history) was developed to correlate COVID-19 severity across low, moderate and high strata of mortality risk. The score discriminated well for in-hospital death, with area under the receiver operating characteristic values of 0.82, 0.80 and 0.74 in the derivation, Aintree and ISARIC validation cohorts respectively. Its predictive accuracy (calibration) in both external cohorts was consistently higher in patients with milder disease (SOARS 0-1), the same individuals who could be identified for safe outpatient monitoring. Prediction of a non-fatal outcome in this group was accompanied by high score sensitivity (99.2%) and negative predictive value (95.9%). ConclusionThe SOARS score uses constitutive and readily assessed individual characteristics to predict the risk of COVID-19 death. Deployment of the score could potentially inform clinical triage in pre-admission settings where expedient and reliable decision-making is key. The resurgence of SARS-CoV-2 transmission provides an opportunity to further validate and update its performance.