SARS-CoV-2 N-Antigen Quantification in Respiratory Tract, Plasma and Urine: Kinetics and Association with RT-qPCR Results.

Qualitative SARS-CoV-2 antigen assays based on immunochromatography are useful for mass diagnosis of COVID-19, even though their sensitivity is poor in comparison with RT-PCR assays. In addition, quantitative assays could improve antigenic test performance and allow testing with different specimens. Using quantitative assays, we tested 26 patients for viral RNA and N-antigen in respiratory samples, plasma and urine. This allowed us to compare the kinetics between the three compartments and to compare RNA and antigen concentrations in each. Our results showed the presence of N-antigen in respiratory (15/15, 100%), plasma (26/59, 44%) and urine (14/54, 28.9%) samples, whereas RNA was only detected in respiratory (15/15, 100%) and plasma (12/60, 20%) samples. We detected N-antigen in urine and plasma samples until the day 9 and day 13 post-inclusion, respectively. The antigen concentration was found to correlate with RNA levels in respiratory (p < 0.001) and plasma samples (p < 0.001). Finally, urinary antigen levels correlated with plasma levels (p < 0.001). Urine N-antigen detection could be part of the strategy for the late diagnosis and prognostic evaluation of COVID-19, given the ease and painlessness of sampling and the duration of antigen excretion in this biological compartment.

Remdesivir in combination with dexamethasone for patients hospitalized with COVID-19: A retrospective multicenter study.

BACKGROUND: Dexamethasone is standard of care for the treatment of patients with COVID-19 requiring oxygen. The objective is to assess the clinical benefit of adding remdesivir to dexamethasone. PATIENTS AND METHODS: A retrospective cohort study of hospitalized patients with COVID-19 pneumonia requesting low-flow oxygen who received dexamethasone. Patients admitted to infectious diseases wards also received remdesivir. Primary outcome was duration of hospitalization after oxygen initiation. Secondary outcomes were in-hospital death, and death and/or transfer to the intensive care unit. To handle potential confounding by indication bias, outcome comparison was performed on propensity score-matched populations. Propensity score was estimated by a multivariable logistic model including prognostic covariates; then 1:1 matching was performed without replacement, using the nearest neighbor algorithm with a caliper of 0.10 fold the standard deviation of the propensity score as the maximal distance. Balance after matching was checked on standardized mean differences. RESULTS: From August 15th 2020, to February 28th, 2021, 325 patients were included, 101 of whom received remdesivir. At admission median time from symptoms onset was 7 days, median age: 68 years, male sex; 61%, >1 comorbidity: 58.5%. Overall 180 patients matched on propensity score were analyzed, 90 each received remdesivir plus dexamethasone or dexamethasone alone. Median duration of hospitalization was 9 (IQR: 7-13) and 9 (IQR: 5-18) days with and without remdesivir, respectively (p = 0.37). In-hospital death rates and rates of transfer to the intensive care unit or death were 8.9 and 17.8% (HR: 0.46, 95% CI: 0.21-1.02, p = 0.06) and 20.0 and 35.6% with and without remdesivir, respectively (HR: 0.45, 95% CI: 0.23-0.89, p = 0.015). CONCLUSION: In hospitalized patients with COVID-19 pneumonia receiving low-flow oxygen and dexamethasone, the addition of remdesivir was not associated with shorter hospitalization or lower in-hospital mortality but may have reduced the combined outcome of death and transfer to the intensive care unit.

Clinical Outcomes of Hospitalized COVID-19 Patients Treated with Remdesivir-NEAT ID 909REM Study

Background There are few real-world data on the use of remdesivir (RDV) looking at timing of initiation in relation to symptom onset and severity of presenting disease. Methods We conducted multi-country retrospective study of clinical practice and use of RDV in COVID-19 patients. De-identified medical records data were entered into an e-CRF. Primary endpoints were all-cause mortality at day 28 and hospitalization duration. We assessed time from symptom onset to RDV start and re-admission. We included adults with PCR-confirmed symptomatic COVID-19 who were hospitalized after Aug 31, 2020 and received at least 1 dose of RDV. Descriptive analyses were conducted. Kaplan-Meier methods were used to calculate the mortality rate, LogRank test to compare groups defined by severity of disease. Competing risk regression with discharge and death as competing events was used to estimate duration of hospitalization, and Gray’s test to compare the groups. Results 448 patients in 5 countries (12 sites) were included. Demographics are summarized (table) by 3 disease severity groups at baseline: no supplemental oxygen (NSO), low flow oxygen ≤6 L/min (LFO), and high-flow oxygen > 6L/min (HFO). No demographic differences were found between groups except for the higher percentage of cancer/chemotherapy patients in NSO group. Corticosteroids use was HFO 73.6%, LFO 62.7%, NSO 58.0%. Mortality rate was significantly lower in NSO, and LFO groups compared with HFO (6.2%, 10.2%, 23.6%, respectively;Fig1). Median duration of hospitalization was 9 (95%CI 8-10), 9 (8-9), 13 (10-15) days, respectively (Fig2). Median time from first symptom to RDV start was 7 days in all 3 groups. Patients started RDV on day 1 of hospitalization in HFO and LFO and day 2 on NSO groups. And received a 5 day course (median). Readmission within 28-days of discharge was < 5% and similar across all 3 groups. Table 1. Patients baseline characteristics and primary and secondary outcomes Figure 1. Kaplan-Meier estimates of mortality Figure 2. Competing-risks regression of discharge from hospital Conclusion In this real-world cohort of COVID-19 positive hospitalized patients, RDV use was consistent across countries. RDV was started within a median of 7 days from symptom within 2 days of admission and given for a median of 5 days. Higher mortality rate and duration of hospitalization was seen in the HFO group and similar rates seen in the LFO and NSO groups. Readmission was consistently low across all 3 groups. Disclosures François Raffi, MD, PhD, Gilead Sciences (Consultant, Scientific Research Study Investigator, Advisor or Review Panel member)Janssen (Consultant)MSD (Consultant, Scientific Research Study Investigator, Advisor or Review Panel member)Roche (Consultant)Theratechnologies (Advisor or Review Panel member)ViiV (Consultant, Scientific Research Study Investigator, Advisor or Review Panel member) Nadir Arber, MD, MSc, MHA, Check cap (Consultant)Coved cd 24 (Board Member)Israel Innovation Authority (Research Grant or Support)Nucleix (Advisor or Review Panel member)Zion Pharmaceuticals (Advisor or Review Panel member) Casper Rokx, MD PhD, Gilead Sciences (Grant/Research Support, Advisor or Review Panel member, Research Grant or Support)Merck (Grant/Research Support, Research Grant or Support)ViiV (Grant/Research Support, Advisor or Review Panel member, Research Grant or Support) Ameet Bakhai, MBBS, MD, FRCP, FESC, Bayer AG (Consultant, Grant/Research Support, Scientific Research Study Investigator, Advisor or Review Panel member, Research Grant or Support, Speaker's Bureau, Independent Contractor)Boehringer Ingelheim (Consultant, Grant/Research Support, Scientific Research Study Investigator, Advisor or Review Panel member, Research Grant or Support, Speaker's Bureau, Independent Contractor)Bristol-Myers Squibb (Consultant, Grant/Research Support, Scientific Research Study Investigator, Advisor or Review Panel member, Research Grant or Support, Speaker's Bureau, Independent Contractor)Daiichi-Sankyo Europe (Consultant, Grant/Research Support, Scientific Research Study Investigator, Advisor or Review Panel member, Research Grant or Support, Speaker's Bureau, Independent Contractor)Gilead Sciences (Grant/Research Support, Scientific Research Study Investigator)Janssen (Consultant, Grant/Research Support, Scientific Research Study Investigator, Advisor or Review Panel member, Research Grant or Support, Speaker's Bureau, Independent Contractor)Johnson & Johnson (Consultant, Grant/Research Support, Scientific Research Study Investigator, Advisor or Review Panel member, Research Grant or Support, Speaker's Bureau, Independent Contractor)MSD (Consultant, Grant/Research Support, Scientific Research Study Investigator, Advisor or Review Panel member, Research Grant or Support, Speaker's Bureau, Independent Contractor)Novartis (Consultant, Grant/Research Support, Scientific Research Study Investigator, Advisor or Review Panel member, Research Grant or Support, Speaker's Bureau, Independent Contractor)Pfizer (Consultant, Grant/Research Support, Scientific Research Study Investigator, Advisor or Review Panel member, Research Grant or Support, Speaker's Bureau, Independent Contractor)Roche (Consultant, Grant/Research Support, Scientific Research Study Investigator, Advisor or Review Panel member, Research Grant or Support, Speaker's Bureau, Independent Contractor)Sanofi (Consultant, Grant/Research Support, Scientific Research Study Investigator, Advisor or Review Panel member, Research Grant or Support, Speaker's Bureau, Independent Contractor) Alex Soriano, MD, Angelini (Speaker's Bureau)Gilead Sciences (Research Grant or Support, Speaker's Bureau)Menarini (Speaker's Bureau)MSD (Research Grant or Support, Speaker's Bureau)Pfizer (Research Grant or Support, Speaker's Bureau)Shionogi (Speaker's Bureau) Carlos Lumbreras, MD, PhD, Gilead Sciences (Grant/Research Support)MSD (Consultant) Vicente Estrada, MD, PhD, Gilead Sciences (Consultant, Grant/Research Support)Janssen (Advisor or Review Panel member)MSD (Consultant, Grant/Research Support)Theratechnologies (Consultant)ViiV (Consultant) Adrian Curran, MD, PhD, Gilead Sciences (Advisor or Review Panel member, Research Grant or Support)Janssen (Advisor or Review Panel member, Research Grant or Support)MSD (Advisor or Review Panel member, Research Grant or Support)ViiV (Advisor or Review Panel member, Research Grant or Support) Essy Mozaffari, PharmD, MPH, MBA, Gilead Sciences (Employee, Shareholder) Richard Haubrich, MD, Gilead Sciences (Employee, Shareholder) Paul Hodgkins, PhD, MSc, Gilead Sciences (Employee, Shareholder) Anton Pozniak, MD, FRCP, Gilead Sciences (Grant/Research Support, Scientific Research Study Investigator, Advisor or Review Panel member, Research Grant or Support)Janssen (Grant/Research Support, Research Grant or Support)Merck (Advisor or Review Panel member)Theratec (Grant/Research Support, Advisor or Review Panel member, Research Grant or Support)ViiV (Grant/Research Support, Scientific Research Study Investigator, Advisor or Review Panel member, Research Grant or Support)

Profiles and outcomes in patients with COVID-19 admitted to wards of a French oncohematological hospital: A clustering approach.

OBJECTIVES: Although some prognostic factors for COVID-19 were consistently identified across the studies, differences were found for other factors that could be due to the characteristics of the study populations and the variables incorporated into the statistical model. We aimed to a priori identify specific patient profiles and then assess their association with the outcomes in COVID-19 patients with respiratory symptoms admitted specifically to hospital wards. METHODS: We conducted a retrospective single-center study from February 2020 to April 2020. A non-supervised cluster analysis was first used to detect patient profiles based on characteristics at admission of 220 consecutive patients admitted to our institution. Then, we assessed the prognostic value using Cox regression analyses to predict survival. RESULTS: Three clusters were identified, with 47 patients in cluster 1, 87 in cluster 2, and 86 in cluster 3; the presentation of the patients differed among the clusters. Cluster 1 mostly included sexagenarian patients with active malignancies who were admitted early after the onset of COVID-19. Cluster 2 included the oldest patients, who were generally overweight and had hypertension and renal insufficiency, while cluster 3 included the youngest patients, who had gastrointestinal symptoms and delayed admission. Sixty-day survival rates were 74.3%, 50.6% and 96.5% in clusters 1, 2, and 3, respectively. This was confirmed by the multivariable Cox analyses that showed the prognostic value of these patterns. CONCLUSION: The cluster approach seems appropriate and pragmatic for the early identification of patient profiles that could help physicians segregate patients according to their prognosis.