The factors associated with increased risk of hospitalisation in people with diabetes following SARS-CoV- 2 infection: A national replication study

Aim: People with type 1 or type 2 diabetes have a higher hospital admission rate following Covid-19 infection. This study aims to determine the degree to which the results of a previous study in Greater Manchester (GM) could be replicated in national-level data for England. Method(s): We focussed on the univariable regression analysis, which shows the association between admission and Covid-19 infection in people with diabetes. Modelling was conducted using logistic regression on data from the Covid-IMPACT database. Odds ratios were compared descriptively with the previous study. Result(s): In people with type 2 diabetes, factors associated with an increased risk of hospitalisation similar to the previous study were: older age, male sex, higher social deprivation, higher body mass index (BMI), higher cholesterol, lower eGFR, taking an ACE-inhibitor/ ARB, not taking metformin, and having asthma or hypertension. Patients with COPD, and those taking aspirin or clopidogrel also had increased risk, but the national data showed a greater risk (GM COPD odds ratio 1.89 [1.63-2.19] vs national 2.34 [2.28-2.40] / aspirin 1.49 [1.34-1.66] vs 1.66 [1.63-1.70] / clopidogrel 1.71 [1.47-1.98] vs 1.99 [1.94-2.04]). Similar results were observed in patients with type 1 diabetes. However, due to the increase in sample size, many factors which were previously not statistically significant have become significant, such as in type 2 diabetes BMI, low HDL-cholesterol. Conclusion(s): We have successfully replicated the methods, results and conclusions of our previous study in relation to factors associated with increased risk of hospital admission in diabetes individuals. Regional databases are suitable for large cohort studies, and in this instance produced similar results to a national database, validating our previous findings.

Trends for Opioid Prescriptions and the Impact of the Covid-19 Pandemic among Patients with Rheumatic and Musculoskeletal Diseases between 2006 and 2021

Background/Aims Rheumatic and musculoskeletal diseases (RMDs) are some of the most common indications for prescribed opioids. It is unclear how opioid prescribing has changed in the UK for RMDs, especially during the COVID-19 pandemic with limited healthcare access and cancelled elective-surgical interventions, which could impact prescribing in either direction. We aimed to investigate trends in opioid prescribing in RMDs and assess the impact of the pandemic in the UK. Methods Adult patients with rheumatoid arthritis (RA), psoriatic arthritis (PsA), axial spondyloarthritis (AxSpA), systemic lupus erythematosus (SLE), osteoarthritis (OA) and fibromyalgia with opioid prescriptions between 01/Jan/2006-31/Aug/2021 without prior cancer in the UK Clinical Practice Research Datalink (CPRD) were included. We calculated ageand gender-standardised yearly rates of people with opioid prescriptions between 2006-2021, and identified change points in trends by checking whether the rate of change of standardised rates crossed zero. For people with opioid prescriptions, monthly measures of mean morphine milligram equivalents (MME)/day were calculated between 2006-2021. To assess the impact of the pandemic, we fitted regression models to the monthly number of people with opioid prescriptions between Jan/2015-Aug/2021. The time coefficient reflects the trend pre-pandemic and the interaction term coefficient represents the change in the trend during the pandemic. Results We included 1,313,519 patients: 36,932 with RA, 12,649 with PsA, 6,811 with AxSpA, 6,423 with SLE, 1,255,999 with OA, and 66,944 with fibromyalgia. People with opioid prescriptions increased from 2006 to 2018 for OA, to 2019 for RA, AxSpA and SLE, to 2020 for PsA, and to 2021 for fibromyalgia, and all plateaued/decreased afterwards. OA patients on opioids increased from 466.8/10,000 persons in 2006 to a peak of 703.0 in 2018, followed by a decline to 575.3 in 2021. From 2006 to 2021, there was a 4.5-fold increase in fibromyalgia opioid users (17.7 vs.78.5/10,000 persons). In this period, MME/day increased for all RMDs, with the highest for fibromyalgia (>=35). During COVID-19 lockdowns, RA, PsA and fibromyalgia showed significant changes in the trend of people with opioid prescriptions. With a decreasing trend for RA (-0.001,95%CI=-0.002,-0.001) and a decreasing-to-flat curve for PsA (0.0010,95%CI=0.0006,0.0015) prepandemic until Feb/2020, the trends changed by -0.005 (95%CI=-0.008,-0.002) for RA and -0.003 (95%CI=-0.006,-0.0003) for PsA, leading to steeper decreasing trends during the pandemic (Mar/2020-Aug/2021). Fibromyalgia, conversely, had an increasing trend (0.009,95%CI=0.008,0.009) pre-pandemic, and this trend started decreasing by -0.009 (95%CI=-0.011,-0.006) during the pandemic. Conclusion The plateauing/decreasing trend of people with opioid prescriptions in RMDs after 2018 may reflect the efforts to tackle the rising opioid prescribing in UK primary care. Of all RMDs, fibromyalgia patients had the highest MME/day throughout the study period. COVID-19 lockdowns contribute to fewer people on opioids for most RMDs, reassuring there was no sudden increase in opioid prescribing during the pandemic.

Risk of death in people with type 2 diabetes following SARS-CoV- 2 infection: A population level analysis of potential risk factors

Introduction: In this study we set out to determine the relative likelihood of death following covid-19 infection in people with type 2 diabetes when compared to those without type 2 diabetes. Methods: Analysis of digital health record data was performed relating to people living in the Greater Manchester conurbation (population 2.82 million) who had a recorded diagnosis of type 2 diabetes and subsequent covid-19 confirmed infection. Each individual with type 2 diabetes (n = 13,807) was matched with three covid-19 infected non-diabetes controls (n = 39583). Results: For type 2 diabetes individuals, their mortality rate after a covid-19 positive test was 7.7% vs 6.0% in matched controls;the relative risk (RR) of death was 1.28. From univariate analysis performed within type 2 diabetes individuals, likelihood of death following covid-19 recorded infection was lower in people taking metformin, sodium glucose cotransporter-inhibitor 2(SGLT-2i) or glucagon-like peptide-1( GLP-1) agonist. A lower estimated glomerular filtration rate (eGFR) was associated with a higher mortality rate, as was hypertension history. Likelihood of death following covid-19 infection was also higher in those people with diagnosis of COPD/severe enduring mental illness, and in people taking aspirin/ clopidogrel/insulin. Smoking in people with type 2 diabetes significantly increased mortality rate. In combined analysis of type 2 diabetes patients/controls, multiple regression modelling indicated that factors independently relating to higher likelihood of death (accounting for 26% of variance) were: type 2 diabetes/age/ malegender/social deprivation (higher Townsend index). Conclusion: Following confirmed infection with covid- 19 a number of factors are associated with mortality in type 2 diabetes individuals. Prescription of metformin, SGLT-2is or GLP-1 agonists + non-smoking status associated with reduced risk of death for people with type 2 diabetes. Age/male sex/social disadvantage associated with an increased risk of death.