Development and validation of COVID-19 Radiological Risk Score (COVID-RRS): a multivariable radiological score to estimate the in-hospital mortality risk in COVID-19 patients.

OBJECTIVE: To develop and validate in-hospital mortality risk score comprising radiological aberrances in chest computed tomography (CT) performed on admission. PATIENTS AND METHODS: Single-center, longitudinal cohort study in adult patients admitted with Coronavirus Disease 2019 (COVID-19) to our ward. Patients were followed-up during hospitalization until discharge or death. Eligibility criteria for the study comprised positive real-time reverse transcription-polymerase chain reaction test (RT-PCR) for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and ground-glass opacities in chest CT. In-hospital death was the outcome of interest. Radiological, laboratory, and clinical data were analyzed. Radiological determinants of mortality were used as variables in multivariate logistic regression analysis, and results were used to build a radiological risk score. RESULTS: 371 patients were enrolled in development and validation cohorts (181 and 190 respectively), with a total of 47 non-survivors. Univariate analysis data determined 12 predictive factors (nine risk and three protective). In multivariate analysis, we developed COVID-RRS (COVID-19 Radiological Risk Score) - a radiological score predicting in-hospital COVID-19 mortality risk comprising estimated lung involvement percentage, pleural effusion, and domination of consolidation-type changes in chest CT. Our score was superior in the prediction of COVID-19 mortality to the percentage of lung involvement alone, Chest Computed Tomography Severity Score (CTSS), and Total Severity Score (TSS) in both groups with AUC of 0.910 and 0.902, respectively (p <0.001). CONCLUSIONS: Additional imaging features independently contribute to COVID-19 mortality risk. Our model comprising lung involvement estimation, pleural effusion, and domination of consolidations performed significantly better than scores based on the extent of the changes alone. COVID-RRS is a simple, reliable, and ready-to-use tool for clinical practice.

CLINICAL RESPONSE PREDICTORS of TOCILIZUMAB THERAPY in PATIENTS with SEVERE COVID-19

Background: Aberrant immune response is hallmark of severe COVID-19, irrespectively from viral replication. Immunomodulatory therapies such as interleukin-6 (IL-6) receptor inhibitors were proven to be benefcial in reducing in-hospital mor-tality1. Yet, it remains unclear which patients can beneft most from such therapy. Objectives: To identify predictors of clinical response to tocilizumab (TCZ) added to dexamethasone in patients hospitalized with severe COVID-19. Methods: We prospectively assessed clinical and laboratory details of 120 patients hospitalized due to severe COVID-19 treated with TCZ (two doses of 8 mg/kg 24h apart) in our ward between 1st Feb 2021 and 31st Dec 2021. Severe COVID-19 was defned as SpO2 <94% on room air with ground glass opacities in chest computed tomography (CT). Clinical response was defned as respiratory improvement on day 5 after TCZ infusion compared to day of treatment initiation, no further deterioration and survival. Decision of adding TCZ to dexamethasone as emergency therapy was made collectively by rheumatologists experienced in COVID-19 treatment. Laboratory and clinical parameters from hospital admission day and from TCZ institution day were analyzed. Statistical analysis was conducted with PQStat v.1.8.2 and predictors were identifed in univariate logistic regression. Results: We identifed 86 (71.7%) clinical responders and 34 (28.3%) non-re-sponders. 20 (58.8%) of the second group needed ICU admission, 18 (52.9%) died on ICU and 2 patients (5.9%) died on the ward. Responders were signif-cantly younger (mean age 56.1 vs. 63.5 years, p=0.006), had lesser comorbidity burden (median Charleson Comorbidity Index 2 vs. 3, p=0.005), lower median lung involvement (50 vs. 70%, p<0.001), higher median baseline PaO2/FiO2 index (203 vs. 106, p<0.001) and less of them needed high-fow oxygen therapy on TCZ initiation day (12.7% vs 32.4%, p=0.025). Identifed predictors of clinical response are shown in Table 1. Conclusion: Administration of TCZ early in severe disease, with moderate IL-6 concentration and low organ damage indices is most benefcial in patients with severe COVID-19, especially in younger patients without respiratory and cardiac comorbidities.

A PHASE III, RANDOMISED, DOUBLE-BLIND, ACTIVE-CONTROLLED CLINICAL TRIAL to COMPARE BAT1806/BIIB800, A PROPOSED TOCILIZUMAB BIOSIMILAR, with TOCILIZUMAB REFERENCE PRODUCT in SUBJECTS with MODERATE to SEVERE RHEUMATOID ARTHRITIS with AN INADEQUATE RESPONSE to METHOTREXATE THERAPY

Background: BAT1806/BIIB800 is a proposed biosimilar to reference tocili-zumab (TCZ). A Phase III randomised, double-blind, active-controlled clinical trial was conducted as part of a biosimilar development programme. Objectives: To evaluate the efficacy, pharmacokinetics (PK), safety and immu-nogenicity of BAT1806/BIIB800 in comparison with EU-sourced TCZ in subjects with moderate to severe rheumatoid arthritis with inadequate response to meth-otrexate (MTX). Methods: The study was conducted at 55 centres in China and Europe, between June 2018 and January 2021. Eligible subjects were randomised in a 2:1:1 ratio to one of three treatment groups: (1) BAT1806/BIIB800 up to Week 48, (2) TCZ up to Week 48, or (3) TCZ up to Week 24, followed by BAT1806/BIIB800 from Week 24 to Week 48, administered intravenously every 4 weeks at a dose of 8mg/kg. The primary endpoint was the proportion of subjects achieving an ACR20 response at timepoints pre-specifed to meet the requirements of different Regulatory Agencies: Week 12, for EMA;Week 24, for FDA and NMPA. Equivalence margins applied to differences in ACR20 response rates in the BAT1806/BIIB800 and TCZ treatment groups were pre-specifed as follows: +/-14.5% for EMA (95% confdence interval (CI));-12.0%,15% for FDA (90% CI);+/-13.6% for NMPA (95% CI). Secondary endpoints included pharmacokinetics, safety and immunogenicity. The ICH E9(R1) estimands framework including intercurrent events (related or unrelated to the COVID19 pandemic) was implemented for the ACR20 evaluation. A logistic regression model including 'region' (China and Eastern Europe) and 'previous biologic or targeted synthetic DMARD use' (Yes/No) as captured in Interactive Web Response System as stratifcation factors was utilised to assess equivalence for the primary endpoint. The difference in response rates was estimated and corresponding confdence intervals were derived to assess equivalence for the primary endpoint. This presents results up to Week 24. Results: In total, 621 subjects were randomised to receive BAT1806/BIIB800 (N=312), TCZ (N=155), or TCZ followed by BAT1806/BIIB800 (N=154). The groups were comparable in terms of baseline demographics and disease characteristics, including age, gender, disease activity and disease duration. The estimated proportions of subjects achieving an ACR20 response in the BAT1806/BIIB800 vs. the TCZ groups, respectively, were 68.97% vs. 64.82% at Week 12 and 69.89% vs. 67.94% at Week 24. The estimated difference between ACR response rates was 4.15% (95% CI-3.63, 11.93) at week 12, and 1.94% (90% CI-4.04, 7.92;95% CI-5.18, 9.07) at Week 24. The CIs for the estimated differences between the treatment groups were within the pre-defned equivalence margins (Figure 1). The treatment groups were comparable in terms of serum trough levels, incidence of TEAEs and ADA/NAb positivity (Table 1). Conclusion: BAT1806/BIIB800 has demonstrated equivalent efficacy at Week 12 and Week 24 and a similar PK, safety and immunogenicity profile as reference tocilizumab up to Week 24.

E-learning Practice at Medical Universities in Poland in the Perspective of the SARS-CoV-2 Pandemic

The epidemiological situation resulting from the SARS-CoV-2 pandemic caused the Polish universities to fully switch to distance education in March 2020. Medical e-learning has not yet been broadly implemented into the education process. Therefore, examples of successful e-learning implementations or the organization of the process of medical e-learning offer a valuable source of knowledge today, which is needed immediately. The article presents e-learning practices at the Polish medical universities during the SARS-CoV-2 epidemic during the period from March to September 2020, covering seven universities in Poland that offer medical and health studies. The organization and implementation of e-learning classes is presented, including knowledge evaluation practices, providing example decisions issued by university rectors, on which the teaching process was based. A detailed presentation of the schools' organizational units or workgroups that played an important role in the process of coordination of measures supporting e-education is also included. The article also presents a description of the software applications, utilities, and services used at the schools in the course of the process of online education. Below are some examples of specific such implementations in selected university courses. © 2020 Piotr K. Leszczyński et al., published by Sciendo.