PSYCHOLOGICAL DISTRESS OVER 12 MONTHS POST-DIAGNOSIS IN A NATIONAL EARLY INFLAMMATORY ARTHRITIS COHORT

BackgroundIn inflammatory arthritis patients, the concomitant decline of their mental wellbeing is an increasing concern[1,2]. It is important to not only describe the trajectory of psychological distress in early disease stages, but also understand which clinical outcome measures are most associated with these changes.ObjectivesUsing data from the National Early Inflammatory Arthritis Audit (NEIAA), we assessed trends in psychological wellbeing over 12 months after initial diagnosis and mapped these against clinical outcomes to identify significant associations.MethodsNEIAA collects data from patients referred with suspected early inflammatory arthritis in rheumatology services in England and Wales. We used data provided by 20,472 patients eligible for follow-up (diagnosis of inflammatory arthritis) between May 1st, 2018, and April 1st, 2022. Data items included baseline demographics e.g., age and gender, and clinical variables e.g., rheumatic disease comorbidity index (RDCI), DAS28, and patient reported outcomes.Psychological distress was measured by the sum score of Patient Health Questionnaire Anxiety and Depression Screener (PHQ4ADS). Using mixed effects regression models, we analysed the co-variability of PHQ4ADS with demographic factors and clinical outcomes over 12 months. Time was included as a dummy-coded covariant.ResultsThe analysis included 36% of patients (7,378 out of 20,472) who completed the baseline patient outcome survey. In this cohort, PHQ4ADS scores decreased from a baseline average of 4.7 (CI: [4.6, 4.8]) to 2.62 (CI: [2.5, 2.8]) at 12 months post-diagnosis. The proportion of patients screening positive decreased from 50.0% (CI: [48.9, 51.1]) at baseline to 23.8% (CI: [21.8, 25.9]) at 12 months.At baseline, psychological distress correlated significantly with age, gender, ethnicity, RDCI, prior depression diagnosis, and baseline DAS28 (Figure 1). No significant correlations were found between psychological distress and working diagnosis, seropositivity, or the assessment being recorded after the start of the COVID-19 pandemic. Younger ages were nonlinearly associated with higher distress levels (coefficient per decade: -0.006;p<0.001;CI: [-0.009, -0.003]) (Figure 1a). Distress levels in females were higher than that of males (coefficient: 0.5;p<0.001;CI: [0.4, 0.7]) (Figure 1b). White patients reported lower PHQ4ADS scores compared to non-white patients (coefficient: -0.7;p<0.001;CI: [-1.0, -0.4]) (Figure 1c). Higher distress levels were also associated with higher RDCI (coefficient: 0.2;p<0.001;CI: [0.1, 0.3]) and prior diagnosis of depression (coefficient: 1.8;p<0.001;CI: [1.5, 2.2]) (Figure 1d, 1e). Furthermore, higher baseline DAS28 scores correlated with more severe psychological distress (coefficient: 0.8;p<0.001;CI: [0.7, 0.8]) (Figure 1f).By 12-months, psychological distress decreased significantly overall, which correlated significantly with ethnicity (coefficient: 0.8;p=0.005;CI: [0.3, 1.4]) and baseline DAS28 (coefficient: -0.5;p<0.001;CI: [-0.6, -0.4]). Compared to white patients, the reduction was significantly greater for non-white patients, but the level of distress was no longer different at 12 months (Figure 1c). While those with higher baseline DAS28 showed a greater reduction in psychological distress, the distress levels remained higher at 12 months (Figure 1f).Figure 1.Changes in psychological distress correlated with age, gender, ethnicity, RDCI, prior depression diagnosis, and baseline DAS28.[Figure omitted. See PDF]ConclusionIn this early inflammatory arthritis cohort, mental health burden was high. Age, gender, ethnicity, RDCI, prior depression diagnosis and baseline DAS28 significantly correlated with psychological distress at baseline. Supporting mental health should be a focus of clinical care for this population and it may be beneficial to use an approach that is culturally valid for non-white patients and accounts for multimorbidity.References[1]Euesden, J, et al. Psychosomatic medicine 79.6 (2017): 638.[2]Lwin, MN, et al. Rheumatology and therapy 7.3 (2020): 457-471.AcknowledgementsThe authors would like to thank the Healthcare Quality Improvement Partnership (HQIP) as the commisioner of NEIAA, British Society for Rheumatology as the audit providers, Net Solving as the audit platform developers, and the Wellcome Trust (ST12406) for funding to support L.Z..Disclosure of InterestsLucy Zhao: None declared, James Galloway Speakers bureau: Has received honoraria from AbbVie Celgene, Chugai, Gillead, Janssen, Eli Lilly, Pfizer, Roche, and UCB, Jo Ledingham: None declared, Sarah Gallagher: None declared, Neena Garnavos: None declared, Paul Amlani-Hatcher: None declared, Nicky Wilson: None declared, Lewis Carpenter Consultant of: Statistical consultancy for Pfizer, Kirsty Bannister: None declared, Sam Norton Speakers bureau: Has received honoraria from Janssen and Pfizer.

Incidence and Management of Inflammatory Arthritis in England before and during the Covid- 19 Pandemic: A Population-Level Cohort Study Using Opensafely

Background/Aims The impact of the pandemic on the incidence and management of inflammatory arthritis (IA) is not understood. Routinely-captured data in secure platforms, such as OpenSAFELY, offer unique opportunities to understand how IA was impacted upon by the pandemic. Our objective was to use OpenSAFELY to assess the effects of the pandemic on diagnostic incidence and care delivery for IA in England, and replicate key metrics from the National Early Inflammatory Arthritis Audit. Methods With the approval of NHS England, we used primary care and hospital data for 17 million adults registered with general practices using TPP health record software, to explore the following outcomes between 1 April 2019 and 31 March 2022: 1) incidence of IA diagnoses (rheumatoid arthritis, psoriatic arthritis, axial spondyloarthritis, undifferentiated IA) recorded in primary care;2) time to first rheumatology assessment;3) time to first prescription of a conventional synthetic DMARD (csDMARD) in primary care, and choice of first csDMARD. Results From 17,683,500 adults (representing 40% of the English population), there were 31,280 incident IA diagnoses recorded between April 2019 and March 2022. New IA diagnoses decreased by 39.7% in the early months of the pandemic. Overall, a 20.3% decrease in IA diagnoses was seen in the year commencing April 2020, relative to the preceding year (5.1 vs. 6.4 diagnoses per 10,000 adults, respectively). Further decreases coincided with rising COVID-19 numbers, before returning to pre-pandemic levels by the end of the study period. No rebound increase in IA incidence was observed as of April 2022. The median time from referral to first rheumatology assessment was shorter during the pandemic (18 days;IQR 8-35 days) than before (21 days;9-41 days). The proportion of patients prescribed csDMARDs in primary care was comparable to before the pandemic;however, fewer people were prescribed methotrexate or leflunomide, and more were prescribed sulfasalazine or hydroxychloroquine. Conclusion IA diagnoses decreased markedly during the early phase of the pandemic;however, the impact on rheumatology assessment times and DMARD prescribing was less marked than might have been anticipated. This study demonstrates the feasibility of using routinelycaptured, near real-time data in the secure OpenSAFELY platform to benchmark care quality on a national scale, without the need for manual data collection.

COVID-19 ADMISSIONS and MORTALITY in PATIENTS with EARLY INFLAMMATORY ARTHRITIS: RESULTS from A NATIONAL COHORT

Background: There has been a major concern about the impact of COVID-19 in patients with infammatory arthritis during the pandemic, with recommendations from governments for patients to shield. Objectives: Our aim was to describe the risk factors for COVID-19 hospitalisation and mortality amongst patients recruited to the National Early Infammatory Arthritis Audit (NEIAA) in England. Methods: An observational cohort study design was used. The population included adults in England with new diagnoses of infammatory arthritis between May 2018 and March 2021 who enrolled in NEIAA. The outcomes were hospitalisation due to COVID-19 (primary admission reason or nosocomial acquisition) and death due to COVID-19 (COVID-19 stated on a death certifcate), identifed via linkage with secondary care records. Hazard ratios were calculated using Cox proportional hazards models, with adjustment for patient factors (age, gender, smoking status, and comorbidity) and disease factors (seropositivity, 28-joint disease activity score, patient-reported disability (HAQ), and functional impact (MSK-HQ)) recorded at baseline. Individuals were considered at risk from the date of diagnosis or February 2020 (whichever was later) and censored at a COVID-19 event, death or May 2021 (whichever was sooner). Results: 14,127 patients were included. The mean age was 57 years;62% were female;19% were current smokers, while 29% were ex-smokers. The frequency of comorbidities at baseline were: hypertension (19%), diabetes mellitus (9%), and lung disease (9%). Overall, 20% had two or more comorbidities. Rheumatoid factor or CCP antibodies were positive in 56%. At presentation, mean scores for DAS28 were 4.6 (+/-1.5), 1. 1 (+/-0.7) for HAQ, and 25 (+/-11) for MSK-HQ. Initial DMARD therapy was known for 13,682/14,127 patients: methotrexate was the most common (54%), followed by hydroxychloroquine (23%), and sulfasalazine (11%). There were 143 COVID-19 hospital admissions and 47 deaths, corresponding to incidence rates per 100 person-years for hospitalisation: 0.94 [95% CI: 0.79-1.10] and death: 0.31 [95% CI: 0.23-0.41]. Increasing age, male gender, diabetes, hypertension, lung disease and smoking status all predicted COVID-19 hospitalisation and death. Higher baseline DAS28 predicted COVID-19 hospitalisation (HR 1.24 [95% CI: 1.10-1.39]) and mortality (HR 1.33 [95% CI: 1.09-1.63]). Higher HAQ predicted both COVID-19 hospitalisation and death. Seropositivity was not a signifcant predictor of any COVID-19 event, nor was MSK-HQ. In unadjusted models, corticosteroids associated with COVID-19 death (HR 2.29 [95% CI: 1.02-5.13], and sulfasalazine monotherapy associated with COVID-19 hospitalisation (HR 1.93 [95% CI: 1.04-3.56]. In adjusted models, associations for corticoster-oids and sulfasalazine were no longer signifcant. Only age, smoking status, and comorbidities independently predicted COVID-19 events. Conclusion: The burden of COVID-19 amongst early arthritis patients was substantial during the pandemic, with concerns about the use of csDMARDs and corticosteroids.1,2 Patient characteristics and rheumatoid disease severity at diagnosis appear to be the more important predictors of COVID-19 events than initial treatment strategy. An important limitation is that we have not looked at treatment changes over time, and must acknowledge that many patients, especially those recruited in 2019, may have changed therapy prior to the pandemic.

IMPACT of COVID-19 on the PRESCRIPTION of BIOLOGIC DMARDS: A POPULATION-LEVEL STUDY in ENGLAND

Background: There has been considerable uncertainty about the impact of biologic DMARDs (bDMARDs) on COVID-19 morbidity and vaccine efficacy, which may have influenced prescribing during the pandemic. Objectives: To assess trends in the prescription of three commonly used bDMARDs with different modes of action-adalimumab (ADA), rituximab (RTX) and tocilizumab (TOC)-in England before and during the COVID-19 pandemic. Methods: The National Health Service (NHS) Secondary Care Medicines dataset was utilised to analyse temporal trends in bDMARD prescriptions issued by all NHS hospital pharmacies in England. Monthly averages of prescriptions issued for ADA, RTX and TOC for combined indications, standardised using WHO Defned Daily Doses (DDD), were described from January 2019 to November 2021. Interrupted time-series analyses (ITSA) were used to estimate the effect of the pandemic on prescription trends for ADA, RTX and TOC;Newey-West standard errors with lags were used to account for autocorrelation between observation periods in these models. Results: Temporal trends in ADA, RTX and TOC prescriptions are shown in Figure 1. A 46% decrease in RTX prescriptions was observed between March and April 2020, from 1,338,300 DDD to 718,900 DDD, respectively, coinciding with the worsening COVID-19 pandemic in England. RTX prescriptions increased after May 2020, refected in the positive prescription trend observed in ITSA models (Table 1);however, RTX prescriptions remained below pre-pandemic levels, before decreasing again between November 2020 and February 2021. This coincided with increasing COVID-19 case numbers in England. For ADA, the pre-pandemic trend of increasing prescriptions continued during the pandemic, with no differences in prescription trends seen in ITSA models (Table 1). A 22% decrease in ADA prescriptions was observed between September and October 2020, from 2,037,800 DDD to 1,587,500 DDD, respectively, before rebounding to above pre-pandemic levels. Prescriptions for TOC increased during the pandemic, driven primarily by a 76% increase in prescriptions between December 2020 and January 2021, from 241,800 DDD to 425,000 DDD, respectively. Conclusion: Prescriptions for RTX in England halved during the early COVID-19 pandemic, and remain below pre-pandemic levels as of November 2021. This likely refects concerns about RTX use and increased COVID-19 mortality and reduced vaccine efficacy.1,2 In contrast, prescriptions for ADA have continued to increase during the pandemic, while prescriptions for TOC surged in December 2020, coinciding with the more widespread use of TOC for the treatment of severe COVID-19.

The impact of methotrexate and targeted immunosuppression on cellular and humoral immune responses to COVID-19 vaccine BNT162b2: a cohort study

Individuals on immunosuppression were excluded from COVID-19 vaccine trials. We evaluated immune responses to COVID-19 vaccine BNT162b2 (Pfizer-BioNTech) in people taking methotrexate and biologics. Given the roll out of extended interval vaccination programmes to maximise population coverage, we present findings following the first dose. We recruited individuals with psoriasis (n=84) established on methotrexate or biologic monotherapy (TNF, IL-17 or IL-23 inhibitors) and healthy controls (n=17). Immunogenicity was evaluated pre and post (day 28) vaccine. Seroconversion rates were lower in patients taking immunosuppression (78%, 95%CI 67-87%) compared to controls (100%, 95%CI 79-100%), with the lowest rate in those on methotrexate (50%, 95%CI 26-74%). Neutralising activity to wild-type SARS-CoV-2 was lower in patients receiving methotrexate (median ID50 152, IQR 47-257) compared to controls (median ID50 316, IQR 212-481, p<0.01), but preserved in those receiving biologics (median ID50 280, IQR 137-428). Neutralising titres against B.1.1.7 were comparably low in all participants. Spike-specific T cell responses (including IFNγ, IL-2, IL-21) were induced in all groups, and were equivalent among individuals receiving methotrexate, biologics and controls. Functional humoral immunity to a single dose of BNT162b2 is impaired by methotrexate but not by biologics, while cellular responses are unaffected. Seroconversion alone may not adequately reflect vaccine immunogenicity in individuals with immune-mediated disease receiving immunosuppression. Real-world pharmacovigilance studies will determine whether these findings translate to clinical effectiveness.

The relationship between symptoms and functional physiological outcomes in survivors of severe COVID-19 pneumonia

P136 Table 1Results of correlation analysis Correlation analysis 4MGS 1STSreps SpO2% desaturation Results r p-value r p-value r p-value Pre-COVID mMRC dyspnoea score 0(0–1) -0.267** <0.001 -0.285** <0.001 -0.108 0.094 Post-COVID mMRC dyspnoea score 1(0–2) -0.442** <0.001 -0.457** <0.001 -0.143* 0.025 NRS breathlessness 3(0–5) -0.287** <0.001 -0.406** <0.001 -0.490 0.445 NRS fatigue 3(0–5) -0.315** <0.001 -0.379** <0.001 -0.190* 0.003 NRS cough 0(0–2) -0.660 0.292 -0.153* 0.017 0.083 0.194 NRS pain 1(0–4) -0.278** <0.001 -0.346** <0.001 -0.188* 0.003 NRS sleep difficulty 2(0–5) -0.246** <0.001 -0.386** <0.001 -0.122 0.057 Data are presented as median (interquartile range) or frequency (proportion%;95% confidence interval). SpO2% desaturation = SpO2% desaturation from baseline during 1 minute sit to stand test;1STSreps = repetitions per minute during 1 minute sit to stand test;4MGS = 4 metre gait speed;mMRC = modified Medical Research Council;NRS = 0 – 10 numerical rating scale;r = Spearman correlation coefficient. *indicates statistical significance at 0.05 level. **indicates statistical significance at 0.001 level.ConclusionRespiratory symptoms were not strong predictors of 4-metre gait speed and 1-minute sit-to-stand test performance. These data highlight the importance of face-to-face testing to objectively assess functional limitation in patients recovering from severe COVID pneumonia.

Clinical, functional and psychological characteristics of survivors of severe COVID-19 pneumonia: a comparison of outcomes from the first and second waves

P135 Table 1Patient demographics, self-reported scores and functional test results by wave 1st wave 2nd wave p-value Demographics n=167 n=141 Age 59±13 58±12 0.564 Female 60 (35.93;28.94–43.40) 62 (43.97;35.97–52.22) 0.15 BMI (kg/m2) 30.5 (26.6–35.2) 32.1 (28.5–37.9) 0.009 ** BAME 115 (69.7;62.39–76.32) 72 (59.5;50.62–67.94) 0.073 Number of comorbidities 2 (1–3) 2 (1–3) 0.144 Patients Receiving Drugs Dexamethasone 11 (6.63;3.57–11.17) 138 (97.87;94.43–99.40) <0.001 *** Remdesivir 18 (10.84;6.79–16.24) 81 (57.45;49.20–65.39) <0.001 *** Other Immunomodulator 2 (1.20;0.25–3.81) 31 (21.99;15.76–29.35) <0.001 *** Questionnaire Scores n=164 n=132 NRS Breathlessness 2 (0–5) 3 (0–5) 0.153 ≥4 56 (34.78;27.75–42.36) 52 (37.14;29.47–45.34) 0.67 NRS Cough 0 (0–2) 0 (0–3) 0.439 ≥4 17 (10.56;6.52–16.00) 18 (13.64;8.59–20.26) 0.419 NRS Fatigue 3 (0–5) 3 (0–5) 0.867 ≥4 65 (40.63;33.24–48.35) 48 (36.92;28.99–45.43) 0.52 NRS Pain 0 (0–5) 1 (0–3) 0.682 ≥4 44 (27.50;21.03–34.78) 30 (23.08;16.48–30.86) 0.39 NRS Sleep disturbance 2 (0–5) 2 (0–5) 0.558 ≥4 52 (32.50;25.61–40.02) 49 (37.40;29.47–45.89) 0.382 Pre-COVID-19 mMRC 1 (0–2) 1 (1–2) 0.478 Post-COVID-19 mMRC 0 (0–1) 0 (0–1) 0.329 Post-COVID-19 mMRC ≥2 66 (40.99;33.61–48.70) 49 (38.58;30.45–47.23) 0.678 PCFS 2 (0–3) 1 (0–2) 0.055 PCFS ≥2 80 (50.00;42.31–57.69) 51 (42.15;33.62–51.05) 0.191 PHQ-9 ≥10 32 (20.38;14.66–27.19) 29 (23.02;16.33–30.92) 0.592 GAD-7 ≥10 34 (21.38;15.56–28.24) 16 (12.80;7.81- 19.49) 0.059 TSQ ≥6 43 (27.56;21.01–34.94) 27 (22.31;15.60–30.33) 0.319 Functional Tests n=160 n=139 4MGS <0.8 (ms-1) 67 (42.41;34.89–50.19) 47 (35.07;27.38–43.40) 0.201 1STS repetitions 18 (12–23) 17 (12–21) 0.460 <2.5 percentile 96 (60.00;52.29–67.36) 108 (77.70;70.25–84.00) 0.011 * Desaturation ≥4% 52 (34.67;27.40–4 .52) 42 (32.31;24.73–40.67) 0.677 Parametric data are presented as mean ± standard deviation, non-parametric data are presented as median (interquartile range) or frequency (proportion;95% confidence interval). Statistical significance indicated by * (p<0.05), ** (p<0.01), *** (p<0.001). BMI = Body mass index, BAME = Black, Asian or minority ethnic, NRS = Numerical rating scale (0–10), mMRC = modified Medical Research Council for dyspnoea (0–4), PCFS = Post-COVID-19 functional status scale (0–4), PHQ-9 = Patient health questionnaire 9 (0–27), GAD-7 = General Anxiety Disorder-7 scale (0–21), TSQ = Trauma screening questionnaire (0–10), 4MGS = 4-metre gait speed, 1STS = 1-minute sit-to-stand.ConclusionDespite shorter admission duration, and less frequent IMV, the burden of symptoms and functional limitation experienced post-hospitalisation for severe COVID-19 pneumonia was at least as severe during Wave 2 as in Wave 1. Identification of contributing factors and impact on post-COVID rehabilitation outcomes requires further study.

The impact of COVID-19 lockdown on clinicalcare, self-management, and mental health inpatients with inflammatory arthritis

Background/AimsCOVID-19 lockdown affected access to clinical care for manyvulnerable patients, including those with inflammatory arthritis (IA). Italso had the potential to alter self-management behaviours. Thesechanges could in turn impact mental health, especially given that IApatients are already at higher risk of mental health disorders. Thus, theaims of this study were to determine how IA care and self-management were affected by lockdown and assess the impact of thesechanges on disease outcomes and mental health.MethodsOnline questionnaires were completed by 338 participants betweenJune and July 2020. The questionnaires assessed demographics, IAcondition, IA self-management, COVID-19 clinical information, qualityof life, and mental health. Visual analogue scale (VAS) scores forpatient global assessment (PGA) of disease activity, pain, fatigue, andemotional distress were completed relating to the previous week andretrospectively for pre-lockdown (March) and early-lockdown (April).Improvement/worsening in each VAS was considered as a change of10 points or more from pre-lockdown to the current rating. Linearregressions were conducted to determine factors associated withworse outcomes, controlling for potential confounders including selfreported pre-lockdown status.ResultsMean VAS scores worsened during lockdown for all outcomemeasures, with over half reporting a more than 10-point worsening(Table 1). Changes to clinical care affected 87% of patients. The mostcommonly affected services were hospital outpatient appointments(77%), GP appointments (59%), and blood tests (53%). Changes toclinical care were significantly associated with worse PGA (b = 8.95, p=0.01), pain (b = 7.13, p=0.05), fatigue (b = 17.01, p<0.00) andemotional distress (b = 12.78, p<0.01). Regarding self-management, 64% of patients reported changes to diet while 51% reduced physicalactivity. Change in diet was not significantly associated with any of theoutcomes, whereas physical activity was associated with PGA (b=-2.42, p<0.01), pain (b=-2.43, p<0.01), fatigue (b=-2.5, p < 0.01), andemotional distress (b=-2.41, p<0.01).ConclusionMost patients (87%) had at least one area of clinical care affected bythe lockdown. These changes in IA clinical care were associated withworse disease outcomes across all measures and greater emotionaldistress. In self-management, reduced physical activity was associated with worse outcomes in all physical and mental healthmeasures.

Early experience and outcomes of telephoneand video consultations in rheumatology during firstwave of COVID-19

Background/AimsInflammatory arthritis (IA) patients have been identified as being atgreater risk of severe illness from COVID-19. It is likely that lockdownrestrictions enforced by the UK government in response to the COVID-19 pandemic, and subsequent changes made to healthcare provisions, could impact patients' abilities to effectively manage theircondition. The aim of this study was to qualitatively explore the impact of COVID-19 and lockdown on self-management behaviours andhealthcare provision in people with IA.MethodsSemi-structured interviews were conducted with 21 patients with IAfrom across the UK (as part of a larger longitudinal survey studyexploring the impact of COVID-19 on health-related quality of life forpeople with IA). Participants who gave consent for contact, followingthe completion of the baseline survey study, were approached to takepart in the qualitative interviews. The interview schedule wasdeveloped with a Patient Research Partner and consisted of eightmain questions to explore participants' experiences of the COVID-19pandemic, including the impact of COVID-19 on their self-management behaviours and access to healthcare services. The interviewswere conducted via telephone and were recorded and transcribedbefore being analysed using inductive thematic analysis.ResultsParticipants were aged between 24-72 (mean age 50.0, SD 15.6) andwere mostly female (71%) and White British (86%). Four main themeswere identified: impact of COVID-19 on medication adherence, impactof COVID-19 on physical activity, impact of COVID-19 on diet, andimpact of COVID-19 on healthcare access. Subthemes focused onpositive and negative changes made to these areas, as well asbehaviours which remained consistent. Some participants expressedthat the lockdown period had enabled them to increase their physicalactivity, improve their diet and maintain their usual medicationregimen, whilst others noted that lockdown had had a negativeimpact on their self-management behaviours. For example, somepatients decided to discontinue their medication during the pandemicdue to concerns that it would make them more susceptible to severeconsequences from COVID-19. In relation to healthcare provision, themost commonly reported change was the introduction of telephoneappointments to replace face-to-face consultations. Several patientsfound the telephone appointments ineffective, especially if theirdisease was relatively uncontrolled. Nevertheless, participants understood why a remote approach had been implemented during thepandemic.ConclusionCOVID-19 has had an impact on patients' abilities to manage their IA.Healthcare professionals need to recognise the impact of COVID-19on patient self-management and healthcare provision to ensure thatadequate understanding and support is available to patients who mayhave inadequate disease control as a result.