ABSTRACT
Background Retrospective observational studies suggest that interleukin-6 (IL-6), C-reactive protein (CRP), lactate dehydrogenase (LDH), ferritin, lymphocytes, monocytes, neutrophils, D-dimer, and platelets are associated with disease progression, treatment outcomes, or both, in patients with COVID-19 pneumonia. We explored these candidate prognostic and predictive biomarkers with efficacy outcomes after treatment with tocilizumab, an anti-IL-6 receptor antibody using data from the COVACTA trial for patients hospitalised with severe COVID-19 pneumonia. Methods Candidate biomarkers were measured in 295 patients in the tocilizumab arm and 142 patients in the placebo arm. Efficacy outcomes assessed were clinical status on a seven-category ordinal scale (1, discharge; 7, death), mortality, time to hospital discharge, and mechanical ventilation (if not receiving it at randomisation) through day 28. Prognostic and predictive biomarkers were evaluated continuously with proportional odds, binomial or Fine-Gray models, and additional sensitivity analyses. Findings Modelling in the placebo arm showed all candidate biomarkers except LDH and D-dimer were strongly prognostic for day 28 clinical outcomes of mortality, mechanical ventilation, clinical status, and time to hospital discharge. Modelling in the tocilizumab arm showed a predictive value of ferritin for day 28 clinical outcomes of mortality (predictive interaction p=0.03), mechanical ventilation (predictive interaction p=0.01), and clinical status (predictive interaction p=0.02) compared with placebo. Interpretation Multiple biomarkers prognostic for clinical outcomes were confirmed in COVACTA. Ferritin was identified as a predictive biomarker for the effects of tocilizumab in the COVACTA patient population; high ferritin levels were associated with better clinical outcomes for tocilizumab compared with placebo at day 28.
Subject(s)
COVID-19 , PneumoniaABSTRACT
IntroductionThe COVID-19 pandemic has been characterised by significant in-hospital virus transmission and deaths among healthcare workers. Sources of in-hospital transmission are not fully understood, with special precautions currently reserved for procedures previously shown to generate aerosols (particles <5 microns). Pleural procedures are not currently considered AGPs, reflecting a lack of data in this area. MethodsAn underwater seal chest drain bottle (R54500, Rocket Medical UK) was set up inside a 60-litre plastic box and connected via an airtight conduit to a medical air supply. A multichannel particle counter (TSI Aerotrak 9310 Aerosol Monitor) was placed inside the box, allowing measurement of particle count/cubic foot (pc/ft3) within six channel sizes: 0.3-0.5, 0.5-1, 1-3, 3-5, 5-10 and >10 microns. Stabilised particle counts at 1, 3 and 5 L/min were compared by Wilcoxon signed rank test; p-values were Bonferroni-adjusted. Measurements were repeated with a simple anti-viral filter, designed using repurposed materials by the study team, attached to the drain bottle. The pressure within the bottle was measured to assess any effect of the filter on bottle function. ResultsAerosol emissions increased with increasing air flow, with the largest increase observed in smaller particles (0.3-3 microns). Concentration of the smallest particles (0.3-0.5 microns) increased from background levels by 700, 1400 and 2500 pc/ft3 at 1, 3 and 5 L/min, respectively. However, dispersion of particles of all sizes was effectively prevented by use of the viral filter at all flow rates. Use of the filter was associated with a maximum pressure rise of 0.3 cm H2O after 24hours of flow at 5 L/min, suggesting minimal impact on drain function. ConclusionA bubbling chest drain is a source of aerosolised particles, but emission can be prevented using a simple anti-viral filter. These data should be considered when designing measures to reduce in-hospital spread of SARS-CoV-2.