Early identification of high-risk individuals for combination monoclonal antibody therapy is feasible by SARS-CoV-2 anti-spike antibody specific lateral flow assay

BackgroundCombination monoclonal antibody therapy has recently been approved for prevention and treatment of severe COVID-19 infection in the UK. Available data suggests benefit is limited to those yet to mount an effective immune response from natural infection or vaccination, but concern exists around ability to make timely assessment of immune status of community-based patients.MethodsHealthcare workers were invited to undergo paired laboratory-based and rapid point-of- care (POC) lateral flow anti-spike antibody testing. Three commercial POC tests were selected to represent currently available testing methods: a split IgM/IgG anti-spike antibody test, an anti-receptor binding domain total antibody test and an anti-spike neutralisation assay. Qualitative POC colourmetric band intensities were independently scored and correlated with quantitative IgG neutralising antibody titres (Abbott Architect SARS-CoV-2 IgG Quant II chemiluminescent microparticle immunoassay [CMIA]). CMIA titres were correlated with the World Health Organisation international reference standard for neutralising antibody. Negative controls were carried out using 2018 pre-pandemic sera and post-pandemic individuals with negative CMIA results (target population).Results190 individuals (median 40 years, IQR 29-49;76.2% female) underwent paired testing, with a further 40 pre-pandemic sera tested. Assays demonstrated high performance characteristics: split IgM/IgG assay sensitivity 96.2% (95%CI 92.4.5–98.5), specificity 100.0% (95%CI 91.8–100.0);anti-receptor binding domain total antibody assay sensitivity 100.0% (95%CI 95.5–100.0), specificity 100.0% (95%CI 69.2–100.0). The neutralising antibody assay had a specificity of 97.0% (95%CI 84.2–99.9%) and strongly correlated with neutralising antibody titre (p<0.001). Probability for matched paired results was significant (McNemar’s p<0.001) while band intensity correlated strongly with neutralising titres (p<0.0001). Positive and negative predictive values for total antibody and neutralising assays were both >99%.ConclusionsPOC assays were found to be reliable predictors of both antibody status and broadly of neutralising antibody titre. Anti-S POC assays have potential to act as suitable alternatives for rapid identification of community patient immune status at presentation.

Early identification of high-risk individuals for monoclonal antibody therapy and prophylaxis is feasible by SARS-CoV-2 anti-spike antibody specific lateral flow assay.

Monoclonal antibody therapy has been approved for prophylaxis and treatment of severe COVID-19 infection. Greatest benefit appears limited to those yet to mount an effective immune response from natural infection or vaccination, but concern exists around ability to make timely assessment of immune status of community-based patients where laboratory-based serodiagnostics predominate. Participants were invited to undergo paired laboratory-based (Abbott Architect SARS-CoV-2 IgG Quant II chemiluminescent microparticle immunoassay) and lateral flow assays (LFA; a split SARS-CoV-2 IgM/IgG and total antibody test) able to detect SARS-CoV-2 anti-spike antibodies. LFA band strength was compared with CMIA titer by log-linear regression. Two hundred individuals (median age 43.5 years, IQR 30-59; 60.5% female) underwent testing, with a further 100 control sera tested. Both LFA band strengths correlated strongly with CMIA antibody titers (P < 0.001). LFAs have the potential to assist in early identification of seronegative patients who may demonstrate the greatest benefit from monoclonal antibody treatment.

Assessing a novel, lab-free, point-of-care test for SARS-CoV-2 (CovidNudge): a diagnostic accuracy study.

BACKGROUND: Access to rapid diagnosis is key to the control and management of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Laboratory RT-PCR testing is the current standard of care but usually requires a centralised laboratory and significant infrastructure. We describe our diagnostic accuracy assessment of a novel, rapid point-of-care real time RT-PCR CovidNudge test, which requires no laboratory handling or sample pre-processing. METHODS: Between April and May, 2020, we obtained two nasopharyngeal swab samples from individuals in three hospitals in London and Oxford (UK). Samples were collected from three groups: self-referred health-care workers with suspected COVID-19; patients attending emergency departments with suspected COVID-19; and hospital inpatient admissions with or without suspected COVID-19. For the CovidNudge test, nasopharyngeal swabs were inserted directly into a cartridge which contains all reagents and components required for RT-PCR reactions, including multiple technical replicates of seven SARS-CoV-2 gene targets (rdrp1, rdrp2, e-gene, n-gene, n1, n2 and n3) and human ribonuclease P (RNaseP) as sample adequacy control. Swab samples were tested in parallel using the CovidNudge platform, and with standard laboratory RT-PCR using swabs in viral transport medium for processing in a central laboratory. The primary analysis was to compare the sensitivity and specificity of the point-of-care CovidNudge test with laboratory-based testing. FINDINGS: We obtained 386 paired samples: 280 (73%) from self-referred health-care workers, 15 (4%) from patients in the emergency department, and 91 (23%) hospital inpatient admissions. Of the 386 paired samples, 67 tested positive on the CovidNudge point-of-care platform and 71 with standard laboratory RT-PCR. The overall sensitivity of the point-of-care test compared with laboratory-based testing was 94% (95% CI 86-98) with an overall specificity of 100% (99-100). The sensitivity of the test varied by group (self-referred healthcare workers 94% [95% CI 85-98]; patients in the emergency department 100% [48-100]; and hospital inpatient admissions 100% [29-100]). Specificity was consistent between groups (self-referred health-care workers 100% [95% CI 98-100]; patients in the emergency department 100% [69-100]; and hospital inpatient admissions 100% [96-100]). Point of care testing performance was similar during a period of high background prevalence of laboratory positive tests (25% [95% 20-31] in April, 2020) and low prevalence (3% [95% 1-9] in inpatient screening). Amplification of viral nucleocapsid (n1, n2, and n3) and envelope protein gene (e-gene) were most sensitive for detection of spiked SARS-CoV-2 RNA. INTERPRETATION: The CovidNudge platform was a sensitive, specific, and rapid point of care test for the presence of SARS-CoV-2 without laboratory handling or sample pre-processing. The device, which has been implemented in UK hospitals since May, 2020, could enable rapid decisions for clinical care and testing programmes. FUNDING: National Institute of Health Research (NIHR) Imperial Biomedical Research Centre, NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance at Oxford University in partnership with Public Health England, NIHR Biomedical Research Centre Oxford, and DnaNudge.

Pooled sputum to optimise the efficiency and utility of rapid, point-of-care molecular SARS-CoV-2 testing.

BACKGROUND: As SARS-CoV-2 testing expands, particularly to widespread asymptomatic testing, high sensitivity point-of-care PCR platforms may optimise potential benefits from pooling multiple patients' samples. METHOD: We tested patients and asymptomatic citizens for SARS-CoV-2, exploring the efficiency and utility of CovidNudge (i) for detection in individuals' sputum (compared to nasopharyngeal swabs), (ii) for detection in pooled sputum samples, and (iii) by modelling roll out scenarios for pooled sputum testing. RESULTS: Across 295 paired samples, we find no difference (p = 0.1236) in signal strength for sputum (mean amplified replicates (MAR) 25.2, standard deviation (SD) 14.2, range 0-60) compared to nasopharyngeal swabs (MAR 27.8, SD 12.4, range 6-56). At 10-sample pool size we find some drop in absolute strength of signal (individual sputum MAR 42.1, SD 11.8, range 13-60 vs. pooled sputum MAR 25.3, SD 14.6, range 1-54; p < 0.0001), but only marginal drop in sensitivity (51/53,96%). We determine a limit of detection of 250 copies/ml for an individual test, rising only four-fold to 1000copies/ml for a 10-sample pool. We find optimal pooled testing efficiency to be a 12-3-1-sample model, yet as prevalence increases, pool size should decrease; at 5% prevalence to maintain a 75% probability of negative first test, 5-sample pools are optimal. CONCLUSION: We describe for the first time the use of sequentially dipped sputum samples for rapid pooled point of care SARS-CoV-2 PCR testing. The potential to screen asymptomatic cohorts rapidly, at the point-of-care, with PCR, offers the potential to quickly identify and isolate positive individuals within a population "bubble".

Association between SARS-CoV-2 exposure and antibody status among healthcare workers in two London hospitals: a cross-sectional study.

BACKGROUND: Patient-facing (frontline) health-care workers (HCWs) are at high risk of repeated exposure to SARS-CoV-2. AIM: We sought to determine the association between levels of frontline exposure and likelihood of SARS-CoV-2 seropositivity amongst HCW. METHODS: A cross-sectional study was undertaken using purposefully collected data from HCWs at two hospitals in London, United Kingdom (UK) over eight weeks in May-June 2020. Information on sociodemographic, clinical and occupational characteristics was collected using an anonymised questionnaire. Serology was performed using split SARS-CoV-2 IgM/IgG lateral flow immunoassays. Exposure risk was categorised into five pre-defined ordered grades. Multivariable logistic regression was used to examine the association between being frontline and SARS-CoV-2 seropositivity after controlling for other risks of infection. FINDINGS: 615 HCWs participated in the study. 250/615 (40.7%) were SARS-CoV-2 IgM and/or IgG positive. After controlling for other exposures, there was non-significant evidence of a modest association between being a frontline HCW (any level) and SARS-CoV-2 seropositivity compared to non-frontline status (OR 1.39, 95% CI 0.84-2.30, P=0.200). There was 15% increase in the odds of SARS-CoV-2 seropositivity for each step along the frontline exposure gradient (OR 1.15, 95% CI 1.00-1.32, P=0.043). CONCLUSION: We found a high SARS-CoV-2 IgM/IgG seropositivity with modest evidence for a dose-response association between increasing levels of frontline exposure risk and seropositivity. Even in well-resourced hospital settings, appropriate use of personal protective equipment, in addition to other transmission-based precautions for inpatient care of SARS-CoV-2 patients could reduce the risk of hospital-acquired SARS-CoV-2 infection among frontline HCW.

Real-world evaluation of COVID-19 lateral flow device (LFD) mass-testing in healthcare workers at a London hospital; a prospective cohort analysis.

OBJECTIVES: Real-world evaluation of the performance of the Innova lateral flow immunoassay antigen device (LFD) for regular COVID-19 testing of hospital workers. METHODS: This prospective cohort analysis took place at a London NHS Trust. 5076 secondary care healthcare staff participated in LFD testing from 18 November 2020 to21 January 2021. Staff members submitted results and symptoms via an online portal twice weekly. Individuals with positive LFD results were invited for confirmatory SARS CoV-2 PCR testing. The positive predictive value (PPV) of the LFD was measured. Secondary outcome measures included time from LFD result to PCR test and staff symptom profiles. RESULTS: 284/5076 individuals reported a valid positive LFD result, and a paired PCR result was obtained in 259/284 (91.2%). 244 were PCR positive yielding a PPV of 94.21% (244/259, 95% CI 90.73% to 96.43%). 204/259 (78.8%) staff members had the PCR within 36 hours of the LFD test. Symptom profiles were confirmed for 132/244 staff members (54.1%) with positive PCR results (true positives) and 13/15 (86.6%) with negative PCR results (false positives). 91/132 true positives (68.9%) were symptomatic at the time of LFD testing: 65/91 (71.4%) had symptoms meeting the PHE case definition of COVID-19, whilst 26/91 (28.6%) had atypical symptoms. 18/41 (43.9%) staff members who were asymptomatic at the time of positive LFD developed symptoms in the subsequent four days. 9/13 (76.9%) false positives were asymptomatic, 1/13 (7.7%) had atypical symptoms and 3/13 (23.1%) had symptoms matching the PHE case definition. CONCLUSIONS: The PPV of the Innova LFD is high when used amongst hospital staff during periods of high prevalence of COVID-19, yet we find frequent use by symptomatic staff rather than as a purely asymptomatic screening tool. LFD testing does allow earlier isolation of infected workers and facilitates detection of individuals whose symptoms do not qualify for PCR testing.

Clinical Utility and Functionality of an Artificial Intelligence-Based App to Predict Mortality in COVID-19: Mixed Methods Analysis.

BACKGROUND: The artificial neural network (ANN) is an increasingly important tool in the context of solving complex medical classification problems. However, one of the principal challenges in leveraging artificial intelligence technology in the health care setting has been the relative inability to translate models into clinician workflow. OBJECTIVE: Here we demonstrate the development of a COVID-19 outcome prediction app that utilizes an ANN and assesses its usability in the clinical setting. METHODS: Usability assessment was conducted using the app, followed by a semistructured end-user interview. Usability was specified by effectiveness, efficiency, and satisfaction measures. These data were reported with descriptive statistics. The end-user interview data were analyzed using the thematic framework method, which allowed for the development of themes from the interview narratives. In total, 31 National Health Service physicians at a West London teaching hospital, including foundation physicians, senior house officers, registrars, and consultants, were included in this study. RESULTS: All participants were able to complete the assessment, with a mean time to complete separate patient vignettes of 59.35 (SD 10.35) seconds. The mean system usability scale score was 91.94 (SD 8.54), which corresponds to a qualitative rating of "excellent." The clinicians found the app intuitive and easy to use, with the majority describing its predictions as a useful adjunct to their clinical practice. The main concern was related to the use of the app in isolation rather than in conjunction with other clinical parameters. However, most clinicians speculated that the app could positively reinforce or validate their clinical decision-making. CONCLUSIONS: Translating artificial intelligence technologies into the clinical setting remains an important but challenging task. We demonstrate the effectiveness, efficiency, and system usability of a web-based app designed to predict the outcomes of patients with COVID-19 from an ANN.

3 Clinical implications of the differential antibody response in mild-moderate SARS-CoV-2: a prospective multi-centre cross-sectional study

IntroductionSerological testing can augment delayed case identification programmes for Severe Acute Respiratory Syndrome coronoravirus-2 (SARS-CoV-2). Immunoassays employ anti-nucleocapsid (anti-NP;the majority) or potentially neutralising anti-spike (including anti-receptor binding domain;anti-RBD) antibody targets, yet correlation between assays and variability arising from disease symptomatology remains unclear. We explore these possibly differential immune responses across the disease spectrum.MethodsA multicentre prospective study was undertaken via a SARS-CoV-2 delayed case identification programme (08 May-11 July 2020). Matched samples were tested for anti-NP and anti-RBD (utilising an ‘inhouse’ double-antigen bridged assay), reactivity expressed as test/cut-off binding ratios (BR) and results compared. A multivariate linear regression model analysed age, sex, symptomatology, PCR positivity, anti-NP, and anti-RBD BRs. Participants were followed up for possible reinfection.Results902 individuals underwent matched testing;109 were SARS-CoV-2 PCR swab positive. Anti-NP, anti-RBD immunoassay agreement was 87.5% (95% CI 85.3–89.6), with BRs strongly correlated (R=0.75). PCR confirmed cases were more frequently identified by anti-RBD (sensitivity 108/109, 99.1%, 95% CI 95.0–100.0) than anti-NP (102/109, 93.6%, 95% CI 87.2–97.4). Anti-RBD identified an additional 83/325 (25.5%) cases in those seronegative for anti-NP. Presence of anti-NP (p<0.0001), fever (p=0.005), or anosmia (p=0.002) were all significantly associated with an increased anti-RBD BR. Age was associated with reduced anti-RBD BR (p=0.052). Three cases with evidence of seroconversion (anti-RBD seropositive) presented with subsequent reactive PCR results, two of which coincided with first time onset of Public Heath England SARS-CoV-2 symptoms.ConclusionsSARS-CoV-2 anti-RBD shows significant correlation with anti-NP for absolute seroconversion, and BRs. Higher BRs are seen in symptomatic individuals with significantly higher levels seen in those with fever and anosmia. The degree of discordant results (12.5%) limits the use of anti-NP as a stand-alone for delayed case finding programmes. Similarly, this discordance limits the utility of non-neutralising anti-NP assays in place of potentially neutralising anti-RBD to infer possible immunity.** this abstract presentation was awarded an Honourable Mention

The pilot, proof of concept REMOTE-COVID trial: remote monitoring use in suspected cases of COVID-19 (SARS-CoV 2).

BACKGROUND: SARS-CoV-2 has ever-increasing attributed deaths. Vital sign trends are routinely used to monitor patients with changes in these parameters preceding an adverse event. Wearable sensors can measure vital signs continuously and remotely, outside of hospital facilities, recognising early clinical deterioration. We aim to determine the feasibility & acceptability of remote monitoring systems for quarantined individuals in a hotel suspected of COVID-19. METHODS: A pilot, proof-of-concept, feasibility trial was conducted in engineered hotels near London airports (May-June 2020). Individuals arriving to London with mild suspected COVID-19 symptoms requiring quarantine, as recommended by Public Health England, or healthcare professionals with COVID-19 symptoms unable to isolate at home were eligible. The SensiumVitals™ patch, measuring temperature, heart & respiratory rates, was applied on arrival for the duration of their stay. Alerts were generated when pre-established thresholds were breeched; trained nursing staff could consequently intervene. RESULTS: Fourteen individuals (M = 7, F = 7) were recruited; the mean age was 34.9 (SD 11) years. Mean length of stay was 3 (SD 1.8) days. In total, 10 vital alerts were generated across 4 participants, resulting in telephone contact, reassurance, or adjustment of the sensor. No individuals required hospitalisation or virtual general practitioner review. DISCUSSION: This proof-of-concept trial demonstrated the feasibility of a rapidly implemented model of healthcare delivery through remote monitoring during a pandemic at a hotel, acting as an extension to a healthcare trust. Benefits included reduced viral exposure to healthcare staff, with recognition of clinical deterioration through ambulatory, continuous, remote monitoring using a discrete wearable sensor. CONCLUSION: Remote monitoring systems can be applied to hotels to deliver healthcare safely in individuals suspected of COVID-19. Further work is required to evaluate this model on a larger scale. TRIAL REGISTRATION: Clinical trials registration information: ClinicalTrials.gov Identifier: NCT04337489 (07/04/2020).

Design of the pilot, proof of concept REMOTE-COVID trial: remote monitoring use in suspected cases of COVID-19 (SARS-CoV-2).

BACKGROUND: The outbreak of SARS-CoV-2 (coronavirus, COVID-19), declared a pandemic by the World Health Organization (WHO), is a global health problem with ever-increasing attributed deaths. Vital sign trends are routinely used to monitor patients with changes in these parameters often preceding an adverse event. Wearable sensors can measure vital signs continuously (e.g. heart rate, respiratory rate, temperature) remotely and can be utilised to recognise early clinical deterioration. METHODS: We describe the protocol for a pilot, proof-of-concept, observational study to be conducted in an engineered hotel near London airports, UK. The study is set to continue for the duration of the pandemic. Individuals arriving to London with mild symptoms suggestive of COVID-19 or returning from high-risk areas requiring quarantine, as recommended by the Public Health England, or healthcare professionals with symptoms suggestive of COVID-19 unable to isolate at home will be eligible for a wearable patch to be applied for the duration of their stay. Notifications will be generated should deterioration be detected through the sensor and displayed on a central monitoring hub viewed by nursing staff, allowing for trend deterioration to be noted. The primary objective is to determine the feasibility of remote monitoring systems in detecting clinical deterioration for quarantined individuals in a hotel. DISCUSSION: This trial should prove the feasibility of a rapidly implemented model of healthcare delivery through remote monitoring during a global pandemic at a hotel, acting as an extension to a healthcare trust. Potential benefits would include reducing infection risk of COVID-19 to healthcare staff, with earlier recognition of clinical deterioration through ambulatory, continuous, remote monitoring using a discrete wearable sensor. We hope our results can power future, robust randomised trials. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04337489 .

Increase in COVID-19 inpatient survival following detection of Thromboembolic and Cytokine storm risk from the point of admission to hospital by a near real time Traffic-light System (TraCe-Tic)

Introduction Our goal was to evaluate if traffic-light driven personalized care for COVID-19 was associated with improved survival in acute hospital settings. Methods Discharge outcomes were evaluated before and after prospective implementation of a real-time dashboard with feedback to ward-based clinicians. Thromboembolism categories were "medium-risk"(D-dimer &gt;1000 ng/mL or CRP &gt;200 mg/L);"high-risk"(D-dimer &gt;3000 ng/mL or CRP &gt;250 mg/L) or "suspected"(D-dimer &gt;5000 ng/mL). Cytokine storm risk was categorized by ferritin. Results 939/1039 COVID-19 positive patients (median age 67 years, 563/939 (60%) male) completed hospital encounters to death or discharge by 21st May 2020. Thromboembolism flag criteria were reached by 568/939 (60.5%), including 238/275 (86.6%) of the patients who died, and 330/664 (49.7%) of the patients who survived to discharge, p &lt;0.0001. Cytokine storm flag criteria were reached by 212 (22.6%) of admissions, including 80/275 (29.1%) of the patients who died, and 132/664 (19.9%) of the patients who survived, p &lt;0.0001. The maximum thromboembolism flag discriminated completed encounter mortality (no flag: 37/371 [9.97%] died;medium-risk: 68/239 [28.5%];high-risk: 105/205 [51.2%];and suspected thromboembolism: 65/124 [52.4%], p &lt;0.0001). Flag criteria were reached by 535 consecutive COVID-19 positive patients whose hospital encounter completed before traffic-light introduction: 173/535 (32.3% [95% confidence intervals 28.0, 36.0]) died. For the 200 consecutive admissions after implementation of real-time traffic light flags, 46/200 (23.0% [95% confidence intervals 17.1, 28.9]) died, p = 0.013. Adjusted for age and sex, the probability of death was 0.33 (95% confidence intervals 0.30, 0.37) before traffic light implementation, 0.22 (0.17, 0.27) after implementation, p &lt;0.001. In subgroup analyses, older patients, males, and patients with hypertension (p &#8804;0.01), and/or diabetes (p = 0.05) derived the greatest benefit from admission under the traffic light system. Conclusion Personalized early interventions were associated with a 33% reduction in early mortality. We suggest benefit predominantly resulted from early triggers to review/enhance anticoagulation management, without exposing lower-risk patients to potential risks of full anticoagulation therapy.

Comparison of deep learning with regression analysis in creating predictive models for SARS-CoV-2 outcomes.

BACKGROUND: Accurately predicting patient outcomes in Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) could aid patient management and allocation of healthcare resources. There are a variety of methods which can be used to develop prognostic models, ranging from logistic regression and survival analysis to more complex machine learning algorithms and deep learning. Despite several models having been created for SARS-CoV-2, most of these have been found to be highly susceptible to bias. We aimed to develop and compare two separate predictive models for death during admission with SARS-CoV-2. METHOD: Between March 1 and April 24, 2020, 398 patients were identified with laboratory confirmed SARS-CoV-2 in a London teaching hospital. Data from electronic health records were extracted and used to create two predictive models using: (1) a Cox regression model and (2) an artificial neural network (ANN). Model performance profiles were assessed by validation, discrimination, and calibration. RESULTS: Both the Cox regression and ANN models achieved high accuracy (83.8%, 95% confidence interval (CI) 73.8-91.1 and 90.0%, 95% CI 81.2-95.6, respectively). The area under the receiver operator curve (AUROC) for the ANN (92.6%, 95% CI 91.1-94.1) was significantly greater than that of the Cox regression model (86.9%, 95% CI 85.7-88.2), p = 0.0136. Both models achieved acceptable calibration with Brier scores of 0.13 and 0.11 for the Cox model and ANN, respectively. CONCLUSION: We demonstrate an ANN which is non-inferior to a Cox regression model but with potential for further development such that it can learn as new data becomes available. Deep learning techniques are particularly suited to complex datasets with non-linear solutions, which make them appropriate for use in conditions with a paucity of prior knowledge. Accurate prognostic models for SARS-CoV-2 can provide benefits at the patient, departmental and organisational level.

Investigating the association between ethnicity and health outcomes in SARS-CoV-2 in a London secondary care population.

BACKGROUND: Black, Asian and minority ethnic (BAME) populations are emerging as a vulnerable group in the severe acute respiratory syndrome coronavirus disease (SARS-CoV-2) pandemic. We investigated the relationship between ethnicity and health outcomes in SARS-CoV-2. METHODS AND FINDINGS: We conducted a retrospective, observational analysis of SARS-CoV-2 patients across two London teaching hospitals during March 1 -April 30, 2020. Routinely collected clinical data were extracted and analysed for 645 patients who met the study inclusion criteria. Within this hospitalised cohort, the BAME population were younger relative to the white population (61.70 years, 95% CI 59.70-63.73 versus 69.3 years, 95% CI 67.17-71.43, p<0.001). When adjusted for age, sex and comorbidity, ethnicity was not a predictor for ICU admission. The mean age at death was lower in the BAME population compared to the white population (71.44 years, 95% CI 69.90-72.90 versus, 77.40 years, 95% CI 76.1-78.70 respectively, p<0.001). When adjusted for age, sex and comorbidities, Asian patients had higher odds of death (OR 1.99: 95% CI 1.22-3.25, p<0.006). CONCLUSIONS: BAME patients were more likely to be admitted younger, and to die at a younger age with SARS-CoV-2. Within the BAME cohort, Asian patients were more likely to die but despite this, there was no difference in rates of admission to ICU. The reasons for these disparities are not fully understood and need to be addressed. Investigating ethnicity as a clinical risk factor remains a high public health priority. Studies that consider ethnicity as part of the wider socio-cultural determinant of health are urgently needed.

Increase in COVID-19 inpatient survival following detection of Thromboembolic and Cytokine storm risk from the point of admission to hospital by a near real time Traffic-light System (TraCe-Tic).

INTRODUCTION: Our goal was to evaluate if traffic-light driven personalized care for COVID-19 was associated with improved survival in acute hospital settings. METHODS: Discharge outcomes were evaluated before and after prospective implementation of a real-time dashboard with feedback to ward-based clinicians. Thromboembolism categories were "medium-risk" (D-dimer >1000ng/mL or CRP >200mg/L); "high-risk" (D-dimer >3000ng/mL or CRP >250mg/L) or "suspected" (D-dimer >5000ng/mL). Cytokine storm risk was categorized by ferritin. RESULTS: 939/1039 COVID-19 positive patients (median age 67 years, 563/939 (60%) male) completed hospital encounters to death or discharge by 21st May 2020. Thromboembolism flag criteria were reached by 568/939 (60.5%), including 238/275 (86.6%) of the patients who died, and 330/664 (49.7%) of the patients who survived to discharge, p<0.0001. Cytokine storm flag criteria were reached by 212 (22.6%) of admissions, including 80/275 (29.1%) of the patients who died, and 132/664 (19.9%) of the patients who survived, p<0.0001. The maximum thromboembolism flag discriminated completed encounter mortality (no flag: 37/371 [9.97%] died; medium-risk: 68/239 [28.5%]; high-risk: 105/205 [51.2%]; and suspected thromboembolism: 65/124 [52.4%], p<0.0001). Flag criteria were reached by 535 consecutive COVID-19 positive patients whose hospital encounter completed before traffic-light introduction: 173/535 (32.3% [95% confidence intervals 28.0, 36.0]) died. For the 200 consecutive admissions after implementation of real-time traffic light flags, 46/200 (23.0% [95% confidence intervals 17.1, 28.9]) died, p=0.013. Adjusted for age and sex, the probability of death was 0.33 (95% confidence intervals 0.30, 0.37) before traffic light implementation, 0.22 (0.17, 0.27) after implementation, p<0.001. In subgroup analyses, older patients, males, and patients with hypertension (p≤0.01), and/or diabetes (p=0.05) derived the greatest benefit from admission under the traffic light system. CONCLUSION: Personalized early interventions were associated with a 33% reduction in early mortality. We suggest benefit predominantly resulted from early triggers to review/enhance anticoagulation management, without exposing lower-risk patients to potential risks of full anticoagulation therapy.

Point-of-care serological assays for delayed SARS-CoV-2 case identification among health-care workers in the UK: a prospective multicentre cohort study.

BACKGROUND: Health-care workers constitute a high-risk population for acquisition of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Capacity for acute diagnosis via PCR testing was limited for individuals with mild to moderate SARS-CoV-2 infection in the early phase of the COVID-19 pandemic and a substantial proportion of health-care workers with suspected infection were not tested. We aimed to investigate the performance of point-of-care and laboratory serology assays and their utility in late case identification, and to estimate SARS-CoV-2 seroprevalence. METHODS: We did a prospective multicentre cohort study between April 8 and June 12, 2020, in two phases. Symptomatic health-care workers with mild to moderate symptoms were eligible to participate 14 days after onset of COVID-19 symptoms, as per the Public Health England (PHE) case definition. Health-care workers were recruited to the asymptomatic cohort if they had not developed PHE-defined COVID-19 symptoms since Dec 1, 2019. In phase 1, two point-of-care lateral flow serological assays, the Onsite CTK Biotech COVID-19 split IgG/IgM Rapid Test (CTK Bitotech, Poway, CA, USA) and the Encode SARS-CoV-2 split IgM/IgG One Step Rapid Test Device (Zhuhai Encode Medical Engineering, Zhuhai, China), were evaluated for performance against a laboratory immunoassay (EDI Novel Coronavirus COVID-19 IgG ELISA kit [Epitope Diagnostics, San Diego, CA, USA]) in 300 samples from health-care workers and 100 pre-COVID-19 negative control samples. In phase 2 (n=6440), serosurveillance was done among 1299 (93·4%) of 1391 health-care workers reporting symptoms, and in a subset of asymptomatic health-care workers (405 [8·0%] of 5049). FINDINGS: There was variation in test performance between the lateral flow serological assays; however, the Encode assay displayed reasonable IgG sensitivity (127 of 136; 93·4% [95% CI 87·8-96·9]) and specificity (99 of 100; 99·0% [94·6-100·0]) among PCR-proven cases and good agreement (282 of 300; 94·0% [91·3-96·7]) with the laboratory immunoassay. By contrast, the Onsite assay had reduced sensitivity (120 of 136; 88·2% [95% CI 81·6-93·1]) and specificity (94 of 100; 94·0% [87·4-97·8]) and agreement (254 of 300; 84·7% [80·6-88·7]). Five (7%) of 70 PCR-positive cases were negative across all assays. Late changes in lateral flow serological assay bands were recorded in 74 (9·3%) of 800 cassettes (35 [8·8%] of 400 Encode assays; 39 [9·8%] of 400 Onsite assays), but only seven (all Onsite assays) of these changes were concordant with the laboratory immunoassay. In phase 2, seroprevalence among the workforce was estimated to be 10·6% (95% CI 7·6-13·6) in asymptomatic health-care workers and 44·7% (42·0-47·4) in symptomatic health-care workers. Seroprevalence across the entire workforce was estimated at 18·0% (95% CI 17·0-18·9). INTERPRETATION: Although a good positive predictive value was observed with both lateral flow serological assays and ELISA, this agreement only occurred if the pre-test probability was modified by a strict clinical case definition. Late development of lateral flow serological assay bands would preclude postal strategies and potentially home testing. Identification of false-negative results among health-care workers across all assays suggest caution in interpretation of IgG results at this stage; for now, testing is perhaps best delivered in a clinical setting, supported by government advice about physical distancing. FUNDING: None.