Background: The COVID-19 pandemic continues to escalate. There is urgent need to stratify patients. Understanding risk of deterioration will assist in admission and discharge decisions, and help selection for clinical studies to indicate where risk of therapy-related complications is justified. Methods: An observational cohort of patients acutely admitted to two London hospitals with COVID-19 and positive SARS-CoV-2 swab results was assessed. Demographic details, clinical data, comorbidities, blood parameters and chest radiograph severity scores were collected from electronic health records. Endpoints assessed were critical care admission and death. A risk score was developed to predict outcomes. Findings: Analyses included 1,157 patients. Older age, male sex, comorbidities, respiratory rate, oxygenation, radiographic severity, higher neutrophils, higher CRP and lower albumin at presentation predicted critical care admission and mortality. Non-white ethnicity predicted critical care admission but not death. Social deprivation was not predictive of outcome. A risk score was developed incorporating twelve characteristics: age > 40, male, non-white ethnicity, oxygen saturations < 93%, radiological severity score > 3, neutrophil count > 8.0 x10 9 /L, CRP > 40 mg/L, albumin < 34 g/L, creatinine > 100 μmol/L, diabetes mellitus, hypertension and chronic lung disease. Risk scores of 4 or higher corresponded to a 28-day cumulative incidence of critical care admission or death of 40.7% (95% CI: 37.1 to 44.4), versus 12.4% (95% CI: 8.2 to 16.7) for scores less than 4. Interpretation: Our study identified predictors of critical care admission and death in people admitted to hospital with COVID-19. These predictors were incorporated into a risk score that will inform clinical care and stratify patients for clinical trials.

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As efficacy and safety data emerge, differences between JAK inhibitor subclasses are appearing. JAK1 selective drugs, upadacitinib and filgotinib, have broadly come with the same overarching safety recommendations as other immunosuppressive drugs for RA: caution is needed regarding infection risk; monitoring for laboratory abnormalities, including lipids and muscle enzymes, is indicated. A distinguishing feature of JAK inhibitors is a risk for zoster reactivation. Numerically, overall rates of serious infection are similar among JAK inhibitor classes. There are currently no signals for diverticular perforation. VTE incidence rates were similar across comparator groups for the JAK1 selective agents. These observations are not yet conclusive evidence for different safety profiles between JAK1 selective agents and other JAK inhibitors. Differences in study population, design, and concomitant steroid use are examples of potential confounders. It is too early to draw conclusions on long-term outcomes such as malignancy and cardiovascular risk. Post-marketing pharmacovigilance studies will be essential.

Objectives : Multiple RCTs of interkeukin-6 (IL-6) inhibitors in COVID-19 have been published, with conflicting conclusions. We performed a meta-analysis to assess the impact of IL-6 inhibition on mortality from COVID-19, utilising meta-regression to explore differences in study results. Methods : Systematic database searches were performed to identify RCTs comparing IL-6 inhibitors (tocilizumab and sarilumab) to placebo or standard of care in adults with COVID-19. Meta-analysis was used to estimate the relative risk of mortality at 28 days between arms, expressed as a risk ratio. Within-study mortality rates were compared, and meta-regression was used to investigate treatment effect modification. Results : Data from nine RCTs were included. The combined mortality rate across studies was 19% (95% CI: 18, 20%), ranging from 2% to 31%. The overall risk ratio for 28-day mortality was 0.90 (95% CI: 0.81, 0.99), in favour of benefit for IL-6 inhibition over placebo or standard of care, with low treatment effect heterogeneity: I 2 0% (95% CI: 0, 53%). Meta-regression showed no evidence of treatment effect modification by patient characteristics. Trial-specific mortality rates were explained by known patient-level predictors of COVID-19 outcome (male sex, CRP, hypertension), and country-level COVID-19 incidence. Conclusions : IL-6 inhibition is associated with clinically meaningful improvements in outcomes for patients admitted with COVID-19. Long-term benefits of IL-6 inhibition, its effectiveness across healthcare systems, and implications for differing standards of care are currently unknown.

Objective To evaluate whether polypharmacy is associated with treatment response and serious adverse events (SAEs) in patients with RA using data from the British Society for Rheumatology Biologics Register (BSRBR-RA). Methods The BSRBR-RA is a prospective observational cohort study of biologic therapy starters and a DMARD comparator arm. A logistic regression model was used to calculate the odds of a EULAR ‘good response’ after 12 months of biologic therapy by medication count. Cox proportional hazards models were used to identify risk of SAEs. The utility of the models were compared with the Rheumatic Disease Comorbidity Index using Receiver Operator Characteristic and Harrell’s C statistic. Results The analysis included 22 005 patients, of which 83% were initiated on biologics. Each additional medication reduced the odds of a EULAR good response by 8% [odds ratios 0.92 (95% CI 0.91, 0.93) P < 0.001] and 3% in the adjusted model [adjusted odds ratios 0.97 (95% CI 0.95, 0.98) P < 0.001]. The Receiver Operator Characteristic demonstrated significantly greater areas under the curve with the polypharmacy model than the Rheumatic Disease Comorbidity Index. There were 12 547 SAEs reported in 7286 patients. Each additional medication equated to a 13% increased risk of an SAE [hazard ratio 1.13 (95% CI 1.12, 1.13) P < 0.001] and 6% in the adjusted model [adjusted hazard ratio 1.06 (95% CI 1.05, 1.07) P < 0.001]. Predictive values for SAEs were comparable between the polypharmacy and Rheumatic Disease Comorbidity Index model. Conclusion Polypharmacy is a simple but valuable predictor of clinical outcomes in patients with RA. This study supports medication count as a valid measure for use in epidemiologic analyses.