Clinical practice guideline-inconsistent management of fever and neutropenia in pediatric oncology: A Children's Oncology Group study

BACKGROUND

The primary objective was to measure the proportion of episodes where care delivery was inconsistent with selected recommendations of a clinical practice guideline (CPG) on fever and neutropenia (FN) management. The influence of site size on CPG-inconsistent care delivery, and association between patient outcomes and CPG-inconsistent care were described.

METHODS

This retrospective, multicenter study included patients less than 21 years old with cancer who were at high risk of poor FN outcomes and were previously enrolled to a Children's Oncology Group (COG) study at participating National Cancer Institute Community Oncology Research Program (NCORP) institutions from January 2014 through December 2015. Patients were randomly selected for chart review by participating sites from a COG-generated list. Care delivered in each episode was adjudicated (CPG-consistent or CPG-inconsistent) against each of five selected recommendations.

RESULTS

A total of 107 patients from 22 sites, representing 157 FN episodes, were included. The most common CPG-inconsistent care delivered was omission of pulmonary computerized tomography in patients with persistent FN (60.3%). Of 74 episodes where assessment of four (episodes without persistent FN) or five (episodes with persistent FN) recommendations was possible, CPG-inconsistent care was delivered with respect to at least one recommendation in 63 (85%) episodes. Site size was not associated with CPG-inconsistent care delivery. No statistically significant association between CPG-inconsistent care and fever recurrence was observed.

CONCLUSIONS

In this cohort of pediatric patients at high risk of poor FN outcomes, CPG-inconsistent care was common. Opportunities to optimize resource stewardship by boosting supportive care CPG implementation are highlighted.

1172 APPLYING THE NATIONAL STANDARDS OF PERIOPERATIVE CARE OF OLDER PEOPLE UNDERGOING EMERGENCY LAPAROTOMY (NELA)

Introduction

There are well documented in-equalities for outcomes for surgical intervention associated with Age and Frailty including emergency laparotomy. NELA data has shown over half of such patients are over 65 years old about one fifth are over 80. These patients having significantly higher mortality, longer hospital stays and it has also shown frailty to be an independent marker of poor outcomes. Through application of key standards these outcomes have improved however input from “consultant geriatrician-led MDT” remains stubbornly low nationally.

Aims

To improve local Trust performance in meeting the NELA standard: “Peri-operative assessment by a member of the Geriatrician-Led MDT for frail (CFS 5+) patients 65 or older” to >80% (Green: ≥80%, Amber: 50 – 79% Red: <50%) of estimated 100 patients per year.

Methods

1. Proactive case finding with general surgical teams; 2. Engagement with Emergency Surgical Committee and NELA leads; 3. Improved our own electronic referral system; 4. Assist in development of electronic booking system with emergency laparotomy cases

Results

We showed a significant improved in meeting the NELA standard from the red zone (Mean: 33% range 5% to 35%) into the amber with a of mean 60% (quartile range 52% to 78%) but still remains below our target with significant quarterly variation seen. All referrals and assessment remain post-intervention.

Limitations in measures:

Conclusions

Following a number of change ideas and despite challenging COVID related staffing issues we showed that a combination of key stakeholder engagement, proactive case-finding and improved referral processes we have improved Geriatrician input in frail patients undergoing emergency laparotomy. We suspect due to the non-systematic assessment of frailty that we may be missing some patients and or seeing late in care pathway.

Editorial - Community Dental Health opens its archive of papers to all

Readers will have noticed the ways we have been modernising Community Dental Health this year. In March we dispensed with hard copies of the journal, publishing it only online. This change was in line with our subscribers' reading behaviours and minimised our environmental impact by reducing the carbon footprints of printing, of using paper and of postage. Subscribers can now also access papers as soon as they are accepted, ahead of publication. Our newly commissioned reviews digest key topics in dental public health to help busy readers keep up with emerging knowledge. In addition, our move to prioritise systematic reviews, by accelerating peer review and fast-tracking publication ensures subscribers' confidence that they are reading the most up to date evidence in our discipline.

How well do polygenic risk scores identify men at high risk for prostate cancer? Systematic review and meta-analysis

OBJECTIVES

Genome-wide association studies have revealed over 200 genetic susceptibility loci for prostate cancer (PCa). By combining them, polygenic risk scores (PRS) can be generated to predict risk of PCa. We summarize the published evidence and conduct meta-analyses of PRS as a predictor of PCa risk in Caucasian men.

PATIENTS AND METHODS

Data were extracted from 59 studies, with 16 studies including 17 separate analyses used in the main meta-analysis with a total of 20,786 cases and 69,106 controls identified through a systematic search of ten databases. Random effects meta-analysis was used to obtain pooled estimates of area under the receiver-operating characteristic curve (AUC). Meta-regression was used to assess the impact of number of single-nucleotide polymorphisms (SNPs) incorporated in PRS on AUC. Heterogeneity is expressed as I² scores. Publication bias was evaluated using funnel plots and Egger tests.

RESULTS

The ability of PRS to identify men with PCa was modest (pooled AUC 0.63, 95% CI 0.62-0.64) with moderate consistency (I² 64%). Combining PRS with clinical variables increased the pooled AUC to 0.74 (0.68-0.81). Meta-regression showed only negligible increase in AUC for adding incremental SNPs. Despite moderate heterogeneity, publication bias was not evident.

CONCLUSION

Typically, PRS accuracy is comparable to PSA or family history with a pooled AUC value 0.63 indicating mediocre performance for PRS alone.

POS0941 LONG-TERM CLINICAL OUTCOMES OF CERTOLIZUMAB PEGOL TREATMENT IN PATIENTS WITH ACTIVE NON‑RADIOGRAPHIC AXIAL SPONDYLOARTHRITIS STRATIFIED BY BASELINE MRI AND C-REACTIVE PROTEIN STATUS

Background

Certolizumab pegol (CZP) has demonstrated clinical efficacy in patients with active non-radiographic axial spondyloarthritis (nr-axSpA) and objective signs of inflammation during the 52-week (wk) placebo (PBO)-controlled period and 104 wk open-label (OL) safety follow-up extension (SFE) of the C-axSpAnd study.1 There is, however, a paucity of data on the long-term efficacy of biologics in nr-axSpA according to patients’ baseline MRI and C-reactive protein (CRP) status.

Objectives

This post hoc analysis from C-axSpAnd aimed to evaluate whether patients’ baseline MRI and CRP status impacted long-term (3-year) clinical responses to CZP.

Methods

C-axSpAnd (NCT02552212) was a 3-year, phase 3, multicentre study. Adults (N=317) with nr-axSpA fulfilling the Assessment of SpondyloArthritis international Society (ASAS) classification criteria and objective signs of inflammation (CRP ≥ upper limit of normal (10 mg/L) [CRP+] and/or evidence of sacroiliitis on MRI [MRI+])2 were randomised 1:1 to PBO or CZP (400 mg at Wks 0, 2 and 4, then 200 mg every 2 wks [Q2W]) for 52 wks.3 Those enrolled into the SFE received OL CZP (200 mg Q2W) for an additional 104 wks.

Ankylosing Spondylitis Disease Activity Score (ASDAS) and Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) alongside the percentage of patients achieving ASDAS major improvement (ASDAS-MI, C-axSpAnd primary outcome) and ASAS 40% response (ASAS40) at Wks 52 and 156 were assessed according to prespecified subgroups based on MRI/CRP status (MRI+/CRP+, MRI−/CRP+, MRI+/CRP−). All data are reported as observed case.

Results

243/317 (76.7%) patients entered the SFE, 120 from the group initially randomised to CZP (36 MRI+/CRP+, 32 MRI−/CRP+ and 52 MRI+/CRP−) and 123 from the initial PBO group (30 MRI+/CRP+, 34 MRI−/CRP+ and 59 MRI+/CRP−; 75/123 had switched to OL treatment in the 52 wk double-blind phase). 206/243 completed the SFE; 102/120 (85.0%) from the group initially randomised to CZP, 104/123 (84.6%) from the initial PBO group.

Among CZP-randomised patients, mean ASDAS was similar between timepoints (MRI+/CRP+: 1.6 at Wk 52 vs 1.6 at Wk 156; MRI−/CRP+: 2.1 vs 2.2; MRI+/CRP−: 1.7 vs 1.6), the percentage achieving ASDAS-MI was lower at Wk 156 compared to Wk 52 across all subgroups (Figure 1 A). Patients initially randomised to PBO showed improvements in mean ASDAS over time (MRI+/CRP+: 2.1 Wk 52 vs 1.8 Wk 156; MRI−/CRP+: 2.2 vs 1.9; MRI+/CRP−: 2.0 vs 1.7) and a sustained proportion of patients achieved ASDAS-MI.

Similar results were shown for BASDAI, with mean scores for CZP-randomised patients sustained from Wk 52 to Wk 156 across all subgroups (Figure 1 B). Mean BASDAI decreased (indicative of clinical improvements) from Wk 52 to Wk 156 in patients initially randomised to PBO, at which point the values aligned with those reported for the CZP-randomised group.

In CZP-randomised patients, ASAS40 responses were sustained at Wk 156 compared to Wk 52. An increased percentage of patients achieved ASAS40 in all MRI/CRP subgroups initially randomised to PBO at Wk 156 compared to Wk 52 (Figure 1 C).

Conclusion

In this analysis of patients with nr-axSpA and objective signs of inflammation, long-term clinical outcomes achieved after 1 year were generally sustained at 3 years across MRI+/CRP+, MRI−/CRP+ and MRI+/CRP− subgroups; ASDAS-MI was numerically highest in the MRI+/CRP+ subgroup.

References

[1]van der Heijde D. Arthritis Rheumatol 2021;73 (suppl 10);

[2]Lambert RG. Ann Rheum Dis 2016;75(11):1958–63;

[3]Deodhar A. Arthritis Rheumatol 2019;71(7):1101–11.

Acknowledgements

This study was funded by UCB Pharma. Editorial services were provided by Costello Medical and funded by UCB Pharma.

Disclosure of Interests

Philip Robinson Consultant of: Personal fees from AbbVie, Atom Biosciences, Eli Lilly, Gilead, Janssen, Novartis, Roche, Pfizer and UCB Pharma, Grant/research support from: Grant funding from Janssen, Novartis and UCB Pharma; meeting attendance support from Bristol Myers Squibb, Lilly, Pfizer and Roche, Walter P Maksymowych Consultant of: Honoraria/consulting fees from AbbVie, Boehringer Ingelheim, Celgene, Eli Lilly, Galapagos, Janssen, Novartis, Pfizer and UCB Pharma, Grant/research support from: Research grants from AbbVie and Pfizer; educational grants from AbbVie, Janssen, Novartis and Pfizer; Chief Medical Officer for CARE Arthritis Limited., Lianne S. Gensler Speakers bureau: Speaker for AbbVie, Eli Lilly, Novartis and UCB Pharma, Consultant of: Consulting fees from AbbVie, Celgene, Eli Lilly, Janssen, Novartis and UCB Pharma, Martin Rudwaleit Speakers bureau: Speaker for AbbVie, Eli Lilly, Novartis and UCB Pharma, Consultant of: Consulting fees from AbbVie, Celgene, Eli Lilly, Janssen, Novartis and UCB Pharma, Bengt Hoepken Shareholder of: Stockholder of UCB Pharma, Employee of: Employee of UCB Pharma, Lars Bauer Shareholder of: Stockholder of UCB Pharma, Employee of: Employee of UCB Pharma, Thomas Kumke Shareholder of: Stockholder of UCB Pharma, Employee of: Employee of UCB Pharma, Mindy Kim Shareholder of: Stockholder of UCB Pharma, Employee of: Employee of UCB Pharma, Atul Deodhar Speakers bureau: Speaker for Janssen, Novartis and Pfizer, Consultant of: Consulting fees from AbbVie, Amgen, Aurinia, Bristol Myers Squibb, Celgene, Eli Lilly, GSK, Janssen, MoonLake, Novartis, Pfizer and UCB Pharma, Grant/research support from: Research grants from AbbVie, Eli Lilly, GSK, Novartis, Pfizer and UCB Pharma

POS1208 EQUITY CONSIDERATIONS IN COVID-19 VACCINATION STUDIES OF INDIVIDUALS WITH AUTOIMMUNE INFLAMMATORY RHEUMATIC DISEASES

Background

Individuals with autoimmune inflammatory rheumatic diseases (AIRDs) have an increased baseline risk of severe COVID-19 infection. Intersection of inequity factors may result in more severe adverse effects through influencing opportunities for health. We sought to examine the extent to which populations experiencing inequities were considered in studies of COVID-19 vaccination in individuals with AIRDs.

Objectives

The objective of this study is to assess how health equity is considered in studies of COVID-19 vaccination studies in individuals with AIRDs.

Methods

All studies (N=19) from an ongoing Cochrane living systematic review on the effects of COVID-19 vaccination in people with AIRDs were included. We identified inequity factors using the PROGRESS-Plus framework which stands for Place of residence, Race/ethnicity, Occupation, Gender/sex, Religion, Education, Socioeconomic status, and Social capital. Age, multimorbidity, and health literacy were also assessed as “Plus” factors. We applied the framework to assess equity considerations in relation to differences in COVID-19 baseline risk, description of participant characteristics, controlling for confounding factors, subgroup analysis and applicability of study findings.

Results:

Figure 1.

All nineteen studies are cohort studies that followed individuals with AIRDs after COVID-19 vaccination. Two articles (11%) described differences in baseline risk for COVID-19 across age. All nineteen studies described participant age and sex, with race/ethnicity and multimorbidity described in four (21%) and occupation in one (5%). Seven studies (37%) controlled for age and/or sex as confounding factors. Eleven studies (58%) conducted subgroup analysis across at least one PROGRESS-Plus factor, most commonly age. Eight studies (42%) discussed at least one PROGRESS-Plus factor in interpreting the applicability of results, most commonly age (32%), then race/ethnicity and multimorbidity (11%).

Conclusion

It is unknown whether COVID-19 vaccine studies on individuals with AIRDs are applicable to populations experiencing inequities, as key inequity factors beyond age and sex have little to no reporting or analysis. Future COVID-19 vaccine studies should report social characteristics of participants consistently, facilitating informed decisions about the applicability of study results to the population of interest.

References

[1]Whittle SL, Hazlewood GS, Robinson P, Johnston RV, Leder K, Glennon V, Avery JC, Grobler L, Buchbinder R. COVID-19 vaccination for people with autoimmune inflammatory rheumatic diseases on immunomodulatory therapies. Cochrane Database of Systematic Reviews 2021, Issue 6. Art. No.: CD014991. DOI: 10.1002/14651858.CD014991. Accessed 31 January 2022.

[2]O’Neill J, Tabish H, Welch V, Petticrew M, Pottie K, Clarke M, Evans T, Pardo Pardo J, Waters E, White H, Tugwell P. Applying an equity lens to interventions: using PROGRESS ensures consideration of socially stratifying factors to illuminate inequities in health. J Clin Epidemiol. 2014 Jan;67(1):56-64. doi: 10.1016/j.jclinepi.2013.08.005. Epub 2013 Nov 1. PMID: 24189091.

Disclosure of Interests

Harry Wang: None declared, Omar Dewidar: None declared, Samuel Whittle: None declared, Elizabeth Ghogomu: None declared, Glen Hazlewood: None declared, Lawrence Mbuagbaw Consultant of: Design, analysis and report for Janssen, Bayer and AstraZeneca, Jordi Pardo Pardo: None declared, Philip Robinson Speakers bureau: Pfizer, Lilly, Abbvie, UCB, GSK, Novartis, Paid instructor for: Lilly, Consultant of: Abbvie, Lilly, Janssen, Kukdong, Atom Biosciences, Grant/research support from: Janssen, Pfizer, UCB and Novartis, Rachelle Buchbinder: None declared, Vivian Welch: None declared

OP0252 FACTORS ASSOCIATED WITH SEVERE COVID-19 OUTCOMES IN PATIENTS WITH IDIOPATHIC INFLAMMATORY MYOPATHY: RESULTS FROM THE COVID-19 GLOBAL RHEUMATOLOGY ALLIANCE PHYSICIAN-REPORTED REGISTRY

Background

There is a paucity of data in the literature about the outcome of patients with idiopathic inflammatory myopathy (IIM) who have been infected with SARS-CoV-2.

Objectives

To investigate factors associated with severe COVID-19 outcomes in patients with IIM.

Methods

Data on demographics, number of comorbidities, region, COVID-19 time period, physician-reported disease activity, anti-rheumatic medication exposure at the clinical onset of COVID-19, and COVID-19 outcomes of IIM patients were obtained from the voluntary COVID-19 Global Rheumatology Alliance physician-reported registry of adults with rheumatic disease (from 17 March 2020 to 27 August 2021). An ordinal COVID-19 severity scale was used as primary outcome of interest, with each outcome category being mutually exclusive from the other:a) no hospitalization, b) hospitalization (and no death), or c) death. Odds ratios (OR) were estimated using multivariable ordinal logistic regression. In ordinal logistic regression, the effect size of a categorical predictor can be interpreted as the odds of being one level higher on the ordinal COVID-19 severity scale than the reference category.

Results

Complete hospitalization and death outcome data was available in 348 IIM cases. Mean age was 53 years, and 223 (64.1%) were female. Overall, 167/348 (48.0%) people were not hospitalized, 136/348 (39.1%) were hospitalized (and did not die), and 45/348 (12.9%) died. Older age (OR=1.59 per decade of life, 95%CI 1.32-1.93), male sex (OR=1.63, 95%CI 1.004-2.64; versus female), high disease activity (OR=4.05, 95%CI 1.29-12.76; versus remission), presence of two or more comorbidities (OR=2.39, 95%CI 1.22-4.68; versus none), prednisolone-equivalent dose >7.5 mg/day (OR=2.37, 95%CI 1.27-4.44; versus no glucocorticoid intake), and exposure to rituximab (OR=2.60, 95%CI 1.23-5.47; versus csDMARDs only) were associated with worse COVID-19 outcomes (Table 1).

Table 1.

Multivariable logistic regression analysis of factors associated with the ordinal COVID-19 severity outcomes. AZA, azathioprine; CI, confidence interval; combo, combination; CSA, ciclosporin; CYC, cyclophosphamide; DMARD, disease-modifying anti-rheumatic drug; b/tsDMARD, biologic/targeted synthetic DMARD, csDMARD, conventional synthetic DMARD; HCQ, hydroxychloroquine; IVIg, intravenous immunoglobulin; LEF, leflunomide; MMF, mycophenolate mofetil; mono, monotherapy; MTX, methotrexate; OR, odds ratio; Ref, reference; RTX, rituximab; SSZ, sulfasalazine; TAC, tacrolimus.

VariableOR (95%CI)P-valueVariableOR (95%CI)P-valueAge (per decade)1.59 (1.32-1.93)<0.001ComorbiditiesMale sex1.63 (1.004-2.64)0.048NoneRefNAPrednisolone-equivalent doseOne1.46 (0.79-2.72)0.228NoneRefNATwo or more2.39 (1.22-4.68)0.011>0 to 7.5mg/day1.10 (0.57-2.11)0.779Physician-reported disease activity>7.5mg/day2.37 (1.27-4.44)0.007RemissionRefNAIVIg0.41 (0.15-1.16)0.093Low/moderate1.23 (0.67-2.28)0.504DMARDsHigh4.05 (1.29-12.76)0.018csDMARD only (mono or combi - HCQ, MTX, LEF, SSZ)RefNARegionNo DMARD1.84 (0.90-3.75)0.094EuropeRefNAb/tsDMARD mono or combi (except RTX)1.60 (0.49-5.26)0.435North America0.89 (0.49-1.61)0.694CSA/CYC/TAC mono or combi (except RTX or b/tsDMARDs)1.55 (0.52-4.58)0.429Other4.25 (2.21-8.16)<0.001AZA mono1.70 (0.69-4.19)0.249Time periodMMF mono1.22 (0.53-2.82)0.634Before 15 June 2020RefNAAZA/MMF combi (except RTX or b/tsDMARDs)0.71 (0.25-2.00)0.51716 June - 30 September 20200.58 (0.26-1.27)0.171RTX mono or combi2.60 (1.23-5.47)0.012After 1 October 20200.58 (0.35-0.95)0.032

Conclusion

These are the first global registry data on the impact of COVID-19 on IIM patients. Older age, male gender, higher comorbidity burden, higher disease activity, higher glucocorticoid intake and rituximab exposure were associated with worse outcomes. These findings will inform risk stratification and management decisions for IIM patients.

References

None

Disclosure of Interests

Su-Ann Yeoh: None declared, Milena Gianfrancesco: None declared, Saskia Lawson-Tovey: None declared, Kimme Hyrich Speakers bureau: AbbVie unrelated to this work, Grant/research support from: Pfizer, BMS, both unrelated to this work, Anja Strangfeld Speakers bureau: AbbVie, Celltrion, MSD, Janssen, Lilly, Roche, BMS, Pfizer, all unrelated to this work, Laure Gossec Consultant of: AbbVie, Amgen, BMS, Galapagos, Gilead, GSK, Janssen, Lilly, Novartis, Pfizer, Samsung Bioepis, Sanofi-Aventis, UCB, all unrelated to this work, Grant/research support from: Amgen, Galapagos, Lilly, Pfizer, Sandoz, all unrelated to this work, Loreto Carmona: None declared, Elsa Mateus Consultant of: Boehringer Ingelheim Portugal, not related to this work, Martin Schaefer: None declared, Christophe Richez Speakers bureau: Abbvie, Amgen, Astra Zeneca, Biogen, BMS, Celltrion, Eli Lilly, Galapagos, GSK, MSD, Novartis, and Pfizer, all unrelated to this abstract, Consultant of: Abbvie, Amgen, Astra Zeneca, Biogen, BMS, Celltrion, Eli Lilly, Galapagos, GSK, MSD, Novartis, and Pfizer, all unrelated to this abstract, Eric Hachulla Speakers bureau: Johnson & Johnson, GlaxoSmithKline, Roche-Chugai, all unrelated to this work, Consultant of: Bayer, Boehringer Ingelheim, GlaxoSmithKline, Johnson & Johnson, Roche-Chugai, Sanofi-Genzyme, all unrelated to this work, Grant/research support from: CSL Behring, GlaxoSmithKline, Johnson & Johnson, Roche-Chugai, Sanofi-Genzyme, all unrelated to this work, Marie Holmqvist: None declared, Carlo Alberto Scirè Grant/research support from: AbbVie, Lilly, both unrelated to this work, Rebecca Hasseli: None declared, Arundathi Jayatilleke: None declared, Tiffany Hsu: None declared, Kristin D’Silva: None declared, Victor Pimentel-Quiroz: None declared, Monica Vasquez del Mercado: None declared, Samuel Katsuyuki Shinjo: None declared, Edgard Reis Neto: None declared, Laurindo Rocha Jr: None declared, Ana Carolina de Oliveira e Silva Montandon Speakers bureau: GSK, not related to this work, Paula Jordan: None declared, Emily Sirotich: None declared, Jonathan Hausmann Speakers bureau: Novartis, Biogen, Pfizer, not related to this work, Consultant of: Novartis, Biogen, Pfizer, not related to this work, Jean Liew Grant/research support from: Pfizer research grant, completed in 2021, not related to this work, Lindsay Jacobsohn: None declared, Monique Gore-Massy Speakers bureau: Aurinia Pharmaceuticals, Boehringer Ingelheim, Bristol-Myers Squibb, not related to this work, Consultant of: Aurinia Pharmaceuticals, Boehringer Ingelheim, Bristol-Myers Squibb, not related to this work, Paul Sufka: None declared, Rebecca Grainger Speakers bureau: AbbVie, Janssen, Novartis, Pfizer and Cornerstones, all unrelated to this work, Consultant of: AbbVie, Novartis, both unrelated to this work, Suleman Bhana Shareholder of: Pfizer, Inc, Speakers bureau: AbbVie, Horizon, Novartis, and Pfizer, all unrelated to this work, Consultant of: AbbVie, Horizon, Novartis, and Pfizer, all unrelated to this work, Employee of: Pfizer, Inc, Zachary Wallace: None declared, Philip Robinson Speakers bureau: Abbvie, Janssen, Roche, GSK, Novartis, Lilly, UCB, all unrelated to this work, Paid instructor for: Lilly, unrelated to this work, Consultant of: GSK, Kukdong, Atom Biosciences, UCB, all unrelated to this work, Grant/research support from: Janssen, Pfizer, UCB and Novartis, all unrelated to this work, Jinoos Yazdany Consultant of: Aurinia, Astra Zeneca, Pfizer, all unrelated to this work, Grant/research support from: Astra Zeneca, Gilead, BMS Foundation, all unrelated to this work, Pedro Machado Speakers bureau: Abbvie, BMS, Celgene, Eli Lilly, Galapagos, Janssen, MSD, Novartis, Orphazyme, Pfizer, Roche and UCB, all unrelated to this work., Consultant of: Abbvie, BMS, Celgene, Eli Lilly, Galapagos, Janssen, MSD, Novartis, Orphazyme, Pfizer, Roche and UCB, all unrelated to this work.

POS1222 FOLIC ACID AND METHOTREXATE USE AND THEIR ASSOCIATION WITH COVID-19 DIAGNOSIS AND MORTALITY: AN ANALYSIS FROM THE UK BIOBANK

Background

Folate metabolism is implicated in SARS-CoV-2 infectivity (Ref).

Objectives

To determine if methotrexate (an antifolate) or folic acid prescription were associated with a lowered and increased risk, respectively, for COVID-19 diagnosis or mortality in a large population-based cohort (UK Biobank).

Methods

Data from 380,380 UK Biobank participants with general practice prescription data were used. Criteria for COVID-19 diagnosis were 1) a positive SARS-CoV-2 test and / or 2) ICD-10 code for confirmed COVID-19 (U07.1) or probable COVID-19 (U07.2) in hospital records, or death records. This definition identified 26,003 individuals diagnosed with COVID-19 of whom 820 were known to have died from COVID-19. Logistic regression statistical models were adjusted for age group (4 categories), sex, ethnicity, Townsend deprivation index, BMI, smoking status, presence of rheumatoid arthritis, sickle cell disease, use of anticonvulsants, statins and iron supplements.

Results

Compared with people prescribed neither folic acid nor methotrexate, people prescribed folic acid supplementation had increased risk of diagnosis of COVID-19 (OR 1.51 [1.42; 1.61]). The prescription of methotrexate with or without folic acid was not associated with COVID-19 diagnosis (P≥0.18). Compared with people prescribed neither folic acid nor methotrexate, people prescribed folic acid supplementation had an increased risk of death after a diagnosis of COVID-19 (OR 2.64 [2.15; 3.24]) in a fully adjusted model. The prescription of methotrexate in combination with folic acid was not associated with an increased risk for death after a diagnosis of COVID-19 (1.07 [0.57; 1.98]). (Table 1)

Table 1.

COVID-19 diagnosis and associated death in people prescribed methotrexate and / or folic acid in the UKBB, compared to people not prescribed methotrexate or folic acid. Model 1 adjusted for age group, sex, ethnicity, Townsend deprivation index, BMI, smoking status Model 2 is model 1 plus adjustment by the presence of rheumatoid arthritis, sickle cell disease, use of statins, anticonvulsants and iron supplementation.

UnadjustedModel 1Model 2OR[95% CI]POR[95% CI]POR[95% CI]PNeither Folic acid nor Methotrexate1.0-1.0-1.0-COVID-19 diagnosisFolic acid only1.58[1.49; 1.68]<0.0011.60[1.50; 1.70]<0.0011.51[1.42; 1.61]<0.001Methotrexate and Folic acid1.09[0.96; 1.23]0.181.15[1.02; 1.30]0.0211.09[0.96; 1.23]0.18COVID-19 associated deathFolic acid only5.14 [4.23; 6.24]<0.0012.91 [2.38; 3.55]<0.0012.64[2.15; 3.24]<0.001Methotrexate and folic acid1.47 [0.81; 2.67]0.211.26 [0.70; 2.30]0.441.07 [0.57; 1.98]0.84

Conclusion

We report increased risk for COVID-19 diagnosis and COVID-19-related death for people prescribed folic acid supplementation. The prescription and use of supplemental folic acid may confer risk of infection with the SARS-CoV-2 virus as well as the risk of death resulting from COVID-19. Our results also suggest that methotrexate might attenuate an increased risk for COVID-19 diagnosis and death conferred by folic acid.

References

[1]Zhang Y, Guo R, Kim SH, et al. SARS-CoV-2 hijacks folate and one-carbon metabolism for viral replication. Nature Communications 2021;12(1):1676. doi: 10.1038/s41467-021-21903-z

Disclosure of Interests

Ruth Topless: None declared, Ralph Green: None declared, Sarah Morgan: None declared, Philip Robinson Consultant of: Abbvie, Atom Biosciences, Eli Lilly, Gilead, Janssen, Novartis, UCB, Roche, Pfizer, Grant/research support from: Janssen, Novartis, Pfizer and UCB Pharma, Tony Merriman: None declared, Angelo Gaffo Consultant of: SOBI, Selecta

OP0249 CHARACTERISTICS ASSOCIATED WITH POOR COVID-19 OUTCOMES IN PEOPLE WITH PSORIASIS AND SPONDYLOARTHRITIS: DATA FROM THE COVID-19 PsoProtect AND GLOBAL RHEUMATOLOGY ALLIANCE PHYSICIAN-REPORTED REGISTRIES

Background

Some factors associated with severe COVID-19 outcomes have been identified in patients with psoriasis (PsO) and inflammatory/autoimmune rheumatic diseases, namely older age, male sex, comorbidity burden, higher disease activity, and certain medications such as rituximab. However, information about specificities of patients with PsO, psoriatic arthritis (PsA) and axial spondyloarthritis (axSpA), including disease modifying anti-rheumatic drugs (DMARDs) specifically licensed for these conditions, such as IL-17 inhibitors (IL-17i), IL-23/IL-12 + 23 inhibitors (IL-23/IL-12 + 23i), and apremilast, is lacking.

Objectives

To determine characteristics associated with severe COVID-19 outcomes in people with PsO, PsA and axSpA.

Methods

This study was a pooled analysis of data from two physician-reported registries: the Psoriasis Patient Registry for Outcomes, Therapy and Epidemiology of COVID-19 Infection (PsoProtect), comprising patients with PsO/PsA, and the COVID-19 Global Rheumatology Alliance (GRA) registry, comprising patients with PsA/axSpA. Data from the beginning of the pandemic up to 25 October, 2021 were included. An ordinal severity outcome was defined as: 1) not hospitalised, 2) hospitalised without death, and 3) death. A multivariable ordinal logistic regression model was constructed to assess the relationship between COVID-19 severity and demographic characteristics (age, sex, time period of infection), comorbidities (hypertension, other cardiovascular disease [CVD], chronic obstructive lung disease [COPD], asthma, other chronic lung disease, chronic kidney disease, cancer, smoking, obesity, diabetes mellitus [DM]), rheumatic/skin disease (PsO, PsA, axSpA), physician-reported disease activity, and medication exposure (methotrexate, leflunomide, sulfasalazine, TNFi, IL17i, IL-23/IL-12 + 23i, Janus kinase inhibitors (JAKi), apremilast, glucocorticoids [GC] and NSAIDs). Age-adjustment was performed employing four-knot restricted cubic splines. Country-adjustment was performed using random effects.

Results

A total of 5008 individuals with PsO (n=921), PsA (n=2263) and axSpA (n=1824) were included. Mean age was 50 years (SD 13.5) and 51.8% were male. Hospitalisation (without death) was observed in 14.6% of cases and 1.8% died. In the multivariable model, the following variables were associated with severe COVID-19 outcomes: older age (Figure 1), male sex (OR 1.53, 95%CI 1.29-1.82), CVD (hypertension alone: 1.26, 1.02-1.56; other CVD alone: 1.89, 1.22-2.94; vs no hypertension and no other CVD), COPD or asthma (1.75, 1.32-2.32), other lung disease (2.56, 1.66-3.97), chronic kidney disease (2.32, 1.50-3.59), obesity and DM (obesity alone: 1.36, 1.07-1.71; DM alone: 1.85, 1.39-2.47; obesity and DM: 1.89, 1.34-2.67; vs no obesity and no DM), higher disease activity and GC intake (remission/low disease activity and GC intake: 1.96, 1.36-2.82; moderate/severe disease activity and no GC intake: 1.35, 1.05-1.72; moderate/severe disease activity and GC intake 2.30, 1.41-3.74; vs remission/low disease activity and no GC intake). Conversely, the following variables were associated with less severe COVID-19 outcomes: time period after 15 June 2020 (16 June 2020-31 December 2020: 0.42, 0.34-0.51; 1 January 2021 onwards: 0.52, 0.41-0.67; vs time period until 15 June 2020), a diagnosis of PsO (without arthritis) (0.49, 0.37-0.65; vs PsA), and exposure to TNFi (0.58, 0.45-0.75; vs no DMARDs), IL17i (0.63, 0.45-0.88; vs no DMARDs), IL-23/IL-12 + 23i (0.68, 0.46-0.997; vs no DMARDs) and NSAIDs (0.77, 0.60-0.98; vs no NSAIDs).

Conclusion

More severe COVID-19 outcomes in PsO, PsA and axSpA are largely driven by demographic factors (age, sex), comorbidities, and active disease. None of the DMARDs typically used in PsO, PsA and axSpA, were associated with severe COVID-19 outcomes, including IL-17i, IL-23/IL-12 + 23i, JAKi and apremilast.

Acknowledgements

We thank all the contributors to the COVID-19 PsoProtect, GRA and EULAR Registries.

Disclosure of Interests

None declared

557 Becoming Virtual: Lessons Learned from Moving Wessex Core Surgical Training Deanery Teaching On-Line

Aim

Surgical training has been significantly impacted by COVID-19. Social distancing requirements mandated a change in face-to-face teaching with many deaneries adopting ‘virtual' sessions. Surgical training does not immediately lend itself to e-learning owing to its hands-on nature. We describe our experiences in developing a virtual teaching program for Core Surgical Trainees within the Wessex Deanery. We provide tips, tricks, and pitfalls for educators to establish or improve similar programs.

Method

From June 2020 monthly, in-person teaching was replaced with virtual sessions. Quantitative and qualitative feedback directed improvements in the program. In addition to knowledge-based lectures we integrated on-line learning tools (LapPass) and utilised surgical videos to ensure continued development of surgical skills. Mock MRCS and ST3 interviews were conducted remotely using ‘break-out rooms. Where face-to-face teaching was essential (Boot Camp, Field Camp) safety was ensured with reduced numbers (split sessions), social distancing and appropriate PPE.

Results

All trainees strongly agreed (67%) or agreed (33%) that virtual teaching works well. There were no significant differences in feedback scores compared with face-to-face teaching. Attendance increased by 42%. Interactivity was maintained with ‘cameras on, mics off', polling apps and chat box function. Advantages include uploading webinars for future review, ability for educators to present from multiple locations, increased availability and breadth of speakers and reduced burden on clinical commitments.

Conclusions

The COVID-19 pandemic has dictated an evolution of surgical teaching. Virtual teaching has many advantages over face-to-face and should continue to play a part in postgraduate medical education, even after social distancing restrictions are lifted.

225 The Management of Acute Cholecystitis in a District General setting: An Audit of Practice

Aim

The benefits of laparoscopic cholecystectomy during index admission with acute cholecystitis (AC) are multiple. As such, current NICE guidelines dictate that adults with AC undergo laparoscopic cholecystectomy within 1 week of diagnosis. However, significant variation exists with regards to the management of such patients. Here we present the results of an audit of practice at a UK district general hospital and suggest that this standard can be achieved regardless of hospital.

Method

Electronic database search at Salisbury District Hospital over a period of 12 months to identify all patients with a coded diagnosis of AC. Electronic Discharge System (EDS) was consulted to assess whether patients underwent laparoscopic cholecystectomy within 7 days of diagnosis. Notes were reviewed for all patients who failed to meet this target to ascertain reasons why.

Results

Of the 336 patients coded as AC 8 were excluded due to incorrect coding leaving 328. 285 patients (87%) underwent laparoscopic cholecystectomy within 7 days. Of the 43 that did not, 31 (65%) had clinically justified reasons for delay. 285/297 (96%) patients met the NICE standard.

Conclusions

At Salisbury District Hospital 87% patients presenting with AC underwent laparoscopic cholecystectomy within 7 days. Common reasons for failure included: Awaiting further investigation (i.e., ERCP / MRCP), unfit for operative management, patient choice. Excluding justifiable reasons 96% of patients met NICE standards. Poor documentation was the most common cause for failure. Subsequent education and re-audit showed significant improvement. This audit exemplifies that NICE standards for the management of AC can be achieved in a district general setting.

POS1147 COSTS AND FACTORS AFFECTING HEALTH SERVICE UTILISATION IN PATIENTS WITH GOUT: A LONGITUDINAL, POPULATION-LEVEL LINKED DATA STUDY IN WESTERN AUSTRALIA

Background:

Evidence suggests that gout is associated with high health care costs and that many inpatient admissions are preventable (1). Understanding the driver of health care costs will allow more targeted intervention.

Objectives:

To examine factors associated with high health service utilisation and cost in patients admitted to hospital with gout, using whole-population linked hospital, WA cancer registration, Emergency Department (ED) and death data (2).

Methods:

The study included patients (18 to 84 years) who had been admitted to hospital with a primary or co-diagnosis of gout for the first time between 1 Jan 02 and 31 Dec 09 Hospital costs were calculated per patient using DRG codes and ED costs were calculated from URG codes. Costs are presented in Australian dollars. Follow-up was completed at five years post their initial gout hospitalisation, at death, or at the 31th of December 2014. Both univariable and multivariable analysis was conducted for each patient characteristic. Independent variables were assessed for collinearity. Collinearity was assumed present where the correlation co-efficient was greater than 0.7.

Results:

4,379 individuals were included. In the following five years, there was 22,222 ED attendances (median cost, $1826 per patient (IQR: $433 - $4,414)), and 58,920 hospital admissions, (median cost, $25,009 per patient (IQR: $6,844 - $60,535)). 4,059 (18.3%) ED attendances and 3,834 (6.5%) hospital admissions were potentially preventable. Gout was not a major driver of events, with 341 (1.5%) ED attendances and 620 (1.1%) hospital admissions coded with a primary diagnosis of gout. In the univariable analysis (Table 1), Aboriginality and smoking were associated with an increased number of both ED attendances and hospital admissions. Increased socio-economic status was associated with a reduction in ED attendances, however, this was not reflected in hospital admissions.

Conclusion:

Patients admitted to hospital with gout are highly likely to be re-admitted or attend ED in the following 5 years. Many of these contacts are preventable, but are usually driven by comorbidities rather than gout.

References:

[1]Loh K, . Intern Med J. 2020 Mar;50(3):386.

[2]https://www.datalinkage-wa.org.au.

Acknowledgements:

The authors wish to thank the staff at the Western Australian Data Linkage Branch and the Hospital Morbidity Data Collection, and the Death Registrations and the Emergency Department Data Collection.

Disclosure of Interests:

None declared.

OP0286 CHARACTERISTICS ASSOCIATED WITH SEVERE COVID-19 OUTCOMES IN SYSTEMIC LUPUS ERYTHEMATOSUS (SLE): RESULTS FROM THE COVID-19 GLOBAL RHEUMATOLOGY ALLIANCE (COVID-19 GRA)

Background:

An increased risk of severe COVID-19 outcomes may be seen in patients with autoimmune diseases on moderate to high daily doses of glucocorticoids, as well as in those with comorbidities. However, specific information about COVID-19 outcomes in SLE is scarce.

Objectives:

To determine the characteristics associated with severe COVID-19 outcomes in a multi-national cross-sectional registry of COVID-19 patients with SLE.

Methods:

SLE adult patients from a physician-reported registry of the COVID-19 GRA were studied. Variables collected at COVID-19 diagnosis included age, sex, race/ethnicity, region, comorbidities, disease activity, time period of COVID-19 diagnosis, glucocorticoid (GC) dose, and immunomodulatory therapy. Immunomodulatory therapy was categorized as: antimalarials only, no SLE therapy, traditional immunosuppressive (IS) drug monotherapy, biologics/targeted synthetic IS drug monotherapy, and biologic and traditional IS drug combination therapy. We used an ordinal COVID-19 severity outcome defined as: not hospitalized/hospitalized without supplementary oxygen; hospitalized with non-invasive ventilation; hospitalized with mechanical ventilation/extracorporeal membrane oxygenation; and death. An ordinal logistic regression model was constructed to assess the association between demographic characteristics, comorbidities, medications, disease activity and COVID-19 severity. This assumed that the relationship between each pair of outcome groups is of the same direction and magnitude.

Results:

Of 1069 SLE patients included, 1047 (89.6%) were female, with a mean age of 44.5 (SD: 14.1) years. Patient outcomes included 815 (78.8%) not hospitalized/hospitalized without supplementary oxygen; 116 (11.2) hospitalized with non-invasive ventilation, 25 (2.4%) hospitalized with mechanical ventilation/extracorporeal membrane oxygenation and 78 (7.5%) died. In a multivariate model (n=804), increased age [OR=1.03 (1.01, 1.04)], male sex [OR =1.93 (1.21, 3.08)], COVID-19 diagnosis between June 2020 and January 2021 (OR =1.87 (1.17, 3.00)), no IS drug use [OR =2.29 (1.34, 3.91)], chronic renal disease [OR =2.34 (1.48, 3.70)], cardiovascular disease [OR =1.93 (1.34, 3.91)] and moderate/high disease activity [OR =2.24 (1.46, 3.43)] were associated with more severe COVID-19 outcomes. Compared with no use of GC, patients using GC had a higher odds of poor outcome: 0-5 mg/d, OR =1.98 (1.33, 2.96); 5-10 mg/d, OR =2.88 (1.27, 6.56); >10 mg/d, OR =2.01 (1.26, 3.21) (Table 1).

Table 1.

Characteristics associated with more severe COVID-19 outcomes in SLE. (N=804)

OR (95% CI)Age, years1.03 (1.01, 1.04)Sex, Male1.93 (1.21, 3.08)Race/Ethnicity, Non-White vs White1.47 (0.87, 2.50)RegionEuropeRef.North America0.67 (0.29, 1.54)South America0.67 (0.29, 1.54)Other1.93 (0.85, 4.39)Season, June 16th 2020-January 8th 2021 vs January-June 15th 20201.87 (1.17, 3.00)Glucocorticoids0 mg/dayRef.0-5 mg/day1.98 (1.33, 2.96)5-10 mg/day2.88 (1.27, 6.56)=>10 mg/day2.01 (1.26, 3.21)Medication CategoryAntimalarial onlyRef.No IS drugs2.29 (1.34, 3.91)Traditional IS drugs as monotherapy1.17 (0.77, 1.77)b/ts IS drugs as monotherapy1.00 (0.37, 2.71)Combination of traditional and b/ts IS1.00 (0.55, 1.82)Comorbidity BurdenNumber of Comorbidities (excluding renal and cardiovascular disease)1.39 (0.97, 1.99)Chronic renal disease2.34 (1.48, 3.70)Cardiovascular disease1.93 (1.34, 3.91)Disease Activity, Moderate/ high vs Remission/ low 2.24 (1.46, 3.43)

IS: immunosuppressive. b/ts: biologics/targeted synthetics

Conclusion:

Increased age, male sex, glucocorticoid use, chronic renal disease, cardiovascular disease and moderate/high disease activity at time of COVID-19 diagnosis were associated with more severe COVID-19 outcomes in SLE. Potential limitations include possible selection bias (physician reporting), the cross-sectional nature of the data, and the assumptions underlying the outcomes modelling.

Acknowledgements:

The views expressed here are those of the authors and participating members of the COVID-19 Global Rheumatology Alliance and do not necessarily represent the views of the ACR, EULAR) the UK National Health Service, the National Institute for Health Research (NIHR), or the UK Department of Health, or any other organization.

Disclosure of Interests:

Manuel F. Ugarte-Gil Grant/research support from: Pfizer, Janssen, Graciela S Alarcon: None declared, Andrea Seet: None declared, Zara Izadi: None declared, Cristina Reategui Sokolova: None declared, Ann E Clarke Consultant of: AstraZeneca, BristolMyersSquibb, GlaxoSmithKline, Exagen Diagnostics, Leanna Wise: None declared, Guillermo Pons-Estel: None declared, Maria Jose Santos: None declared, Sasha Bernatsky: None declared, Lauren Mathias: None declared, Nathan Lim: None declared, Jeffrey Sparks Consultant of: Bristol-Myers Squibb, Gilead, Inova, Janssen, and Optum unrelated to this work., Grant/research support from: Amgen and Bristol-Myers Squibb, Zachary Wallace Consultant of: Viela Bio and MedPace, Grant/research support from: Bristol-Myers Squibb and Principia/Sanofi, Kimme Hyrich Speakers bureau: Abbvie, Grant/research support from: MS, UCB, and Pfizer, Anja Strangfeld Speakers bureau: AbbVie, MSD, Roche, BMS, Pfizer, Grant/research support from: AbbVie, BMS, Celltrion, Fresenius Kabi, Lilly, Mylan, Hexal, MSD, Pfizer, Roche, Samsung, Sanofi-Aventis, and UCB, Laure Gossec Consultant of: Abbvie, Biogen, Celgene, Janssen, Lilly, Novartis, Pfizer, Sanofi-Aventis, UCB, Grant/research support from: Lilly, Mylan, Pfizer, Loreto Carmona: None declared, Elsa Mateus Grant/research support from: Pfizer, Abbvie, Novartis, Janssen-Cilag, Lilly Portugal, Sanofi, Grünenthal S.A., MSD, Celgene, Medac, Pharmakern, GAfPA, Saskia Lawson-Tovey: None declared, Laura Trupin: None declared, Stephanie Rush: None declared, Gabriela Schmajuk: None declared, Patti Katz: None declared, Lindsay Jacobsohn: None declared, Samar Al Emadi: None declared, Emily Gilbert: None declared, Ali Duarte-Garcia: None declared, Maria Valenzuela-Almada: None declared, Tiffany Hsu: None declared, Kristin D’Silva: None declared, Naomi Serling-Boyd: None declared, Philippe Dieudé Consultant of: Boerhinger Ingelheim, Bristol-Myers Squibb, Lilly, Sanofi, Pfizer, Chugai, Roche, Janssen unrelated to this work, Grant/research support from: Bristol-Myers Squibb, Chugaii, Pfizer, unrelated to this work, Elena Nikiphorou: None declared, Vanessa Kronzer: None declared, Namrata Singh: None declared, Beth Wallace: None declared, Akpabio Akpabio: None declared, Ranjeny Thomas: None declared, Suleman Bhana Consultant of: AbbVie, Horizon, Novartis, and Pfizer (all <$10,000) unrelated to this work, Wendy Costello: None declared, Rebecca Grainger Speakers bureau: Abbvie, Janssen, Novartis, Pfizer, Cornerstones, Jonathan Hausmann Consultant of: Novartis, Sobi, Biogen, all unrelated to this work (<$10,000), Jean Liew Grant/research support from: Pfizer outside the submitted work, Emily Sirotich Grant/research support from: Board Member of the Canadian Arthritis Patient Alliance, a patient run, volunteer based organization whose activities are largely supported by independent grants from pharmaceutical companies, Paul Sufka: None declared, Philip Robinson Speakers bureau: Abbvie, Eli Lilly, Janssen, Novartis, Pfizer and UCB (all < $10,000), Consultant of: Abbvie, Eli Lilly, Janssen, Novartis, Pfizer and UCB (all < $10,000), Pedro Machado Speakers bureau: Abbvie, BMS, Celgene, Eli Lilly, Janssen, MSD, Novartis, Pfizer, Roche and UCB, all unrelated to this study (all < $10,000)., Consultant of: Abbvie, BMS, Celgene, Eli Lilly, Janssen, MSD, Novartis, Pfizer, Roche and UCB, all unrelated to this study (all < $10,000), Milena Gianfrancesco: None declared, Jinoos Yazdany Consultant of: Eli Lilly and AstraZeneca unrelated to this project

OP0288 MACHINE LEARNING ALGORITHMS TO PREDICT COVID-19 ACUTE RESPIRATORY DISTRESS SYNDROME IN PATIENTS WITH RHEUMATIC DISEASES: RESULTS FROM THE GLOBAL RHEUMATOLOGY ALLIANCE PROVIDER REGISTRY

Background:

Acute Respiratory Distress Syndrome (ARDS) is a life-threatening complication of COVID-19 and has been reported in approximately one-third of hospitalized patients with COVID-191. Risk factors associated with the development of ARDS include older age and diabetes2. However, little is known about factors associated with ARDS in the setting of COVID-19, in patients with rheumatic disease or those receiving immunosuppressive medications. Prediction algorithms using traditional regression methods perform poorly with rare outcomes, often yielding high specificity but very low sensitivity. Machine learning algorithms optimized for rare events are an alternative approach with potentially improved sensitivity for rare events, such as ARDS in COVID-19 among patients with rheumatic disease.

Objectives:

We aimed to develop a prediction model for ARDS in people with COVID-19 and pre-existing rheumatic disease using a series of machine learning algorithms and to identify risk factors associated with ARDS in this population.

Methods:

We used data from the COVID-19 Global Rheumatology Alliance (GRA) Registry from March 24 to Nov 1, 2020. ARDS diagnosis was indicated by the reporting clinician. Five machine learning algorithms optimized for rare events predicted ARDS using 42 variables covering patient demographics, rheumatic disease diagnoses, medications used at the time of COVID-19 diagnosis, and comorbidities. Model performance was assessed using accuracy, area under curve, sensitivity, specificity, positive predictive value, and negative predictive value. Adjusted odds ratios corresponding to the 10 most influential predictors from the best performing model were derived using hierarchical multivariate mixed-effects logistic regression that accounted for within-country correlations.

Results:

A total of 5,931 COVID-19 cases from 67 countries were included in the analysis. Mean (SD) age was 54.9 (16.0) years, 4,152 (70.0%) were female, and 2,399 (40.5%) were hospitalized. ARDS was reported in 388 (6.5% of total and 15.6% of hospitalized) cases. Statistically significant differences in the risk of ARDS were observed by demographics, diagnoses, medications, and comorbidities using unadjusted univariate comparisons (data not shown). Gradient boosting machine (GBM) had the highest sensitivity (0.81) and was considered the best performing model (Table 1). Hypertension, interstitial lung disease, kidney disease, diabetes, older age, glucocorticoids, and anti-CD20 monoclonal antibodies were associated with the development of ARDS while tumor necrosis factor inhibitors were associated with a protective effect (Figure 1).

Table 1.

Performance of machine learning algorithms.

GBMSVMGLMNETNNETRFAccuracy0.790.680.660.660.67AUC0.750.700.740.580.74Sensitivity0.810.680.650.680.67Specificity0.490.600.730.480.68PPV0.960.960.970.950.97NPV0.160.120.130.090.13

GBM: Gradient Boosting Machine, SVM: Support vector machines, GLMNET: Lasso and Elastic-Net Regularized Generalized Linear Models, NNET: Neural Networks, RF: Random Forest. AUC: Area Under Curve; PPV: Positive Predictive Value; NPV: Negative Predictive Value.

Conclusion:

In this global cohort of patients with rheumatic disease, a machine learning model, GBM, predicted the onset of ARDS with 81% sensitivity using baseline information obtained at the time of COVID-19 diagnosis. These results identify patients who may be at higher risk of severe COVID-19 outcomes. Further studies are necessary to validate the proposed prediction model in external cohorts and to evaluate its clinical utility. Disclaimer: The views expressed here are those of the authors and participating members of the COVID-19 Global Rheumatology Alliance, and do not necessarily represent the views of the ACR, NIH, (UK) NHS, NIHR, or the department of Health.

References:

[1]Tzotzos SJ, Fischer B, Fischer H, Zeitlinger M. 2020;24(1):516.

[2]Wu C, Chen X, Cai Y, et al. JAMA Intern Med. 2020;180(7):934-943.

Acknowledgements:

The COVID-19 Global Rheumatology Alliance.

Disclosure of Interests:

Zara Izadi: None declared, Milena Gianfrancesco: None declared, Kimme Hyrich Speakers bureau: Abbvie and grant income from BMS, UCB, and Pfizer, all unrelated to this study., Anja Strangfeld Speakers bureau: AbbVie, MSD, Roche, BMS, Pfizer, outside the submitted work., Grant/research support from: A consortium of 13 companies (among them AbbVie, BMS, Celltrion, Fresenius Kabi, Lilly, Mylan, Hexal, MSD, Pfizer, Roche, Samsung, Sanofi-Aventis, and UCB) supporting the German RABBIT register., Laure Gossec Consultant of: Abbvie, Biogen, Celgene, Janssen, Lilly, Novartis, Pfizer, Sanofi-Aventis, UCB., Grant/research support from: Lilly, Mylan, Pfizer, all unrelated to this study., Loreto Carmona Consultant of: Loreto Carmona’s institute works by contract for laboratories among other institutions, such as Abbvie Spain, Eisai, Gebro Pharma, Merck Sharp & Dohme España, S.A., Novartis, Farmaceutica, Pfizer, Roche Farma, Sanofi Aventis, Astellas Pharma, Actelion Pharmaceuticals España, Grünenthal GmbH, and UCB Pharma., Elsa Mateus Grant/research support from: LPCDR received grants from Abbvie, Novartis, Janssen-Cilag, Lilly Portugal, Sanofi, Grünenthal S.A., MSD, Celgene, Medac, Pharmakern, GAfPA and Pfizer., Saskia Lawson-Tovey: None declared, Laura Trupin: None declared, Stephanie Rush: None declared, Gabriela Schmajuk: None declared, Lindsay Jacobsohn: None declared, Patti Katz: None declared, Samar Al Emadi: None declared, Leanna Wise: None declared, Emily Gilbert: None declared, Maria Valenzuela-Almada: None declared, Ali Duarte-Garcia: None declared, Jeffrey Sparks Consultant of: Bristol-Myers Squibb, Gilead, Inova, Janssen, and Optum unrelated to this work., Grant/research support from: Amgen and Bristol-Myers Squibb., Tiffany Hsu: None declared, Kristin D’Silva: None declared, Naomi Serling-Boyd: None declared, Suleman Bhana Employee of: Suleman Bhana reports non-branded marketing campaigns for Novartis (<$10,000)., Wendy Costello: None declared, Rebecca Grainger Speakers bureau: Abbvie, Janssen, Novartis, Pfizer, Cornerstones and travel assistance from Pfizer (all < $10,000)., Jonathan Hausmann Consultant of: Novartis, unrelated to this work (<$10,000)., Jean Liew Grant/research support from: Pfizer, outside the submitted work., Emily Sirotich Grant/research support from: Emily Sirotich is a Board Member of the Canadian Arthritis Patient Alliance, a patient run, volunteer-based organization whose activities are largely supported by independent grants from pharmaceutical companies., Paul Sufka: None declared, Zachary Wallace Consultant of: Viela Bio and MedPace, outside the submitted work., Grant/research support from: Bristol-Myers Squibb and Principia/Sanofi., Pedro Machado Speakers bureau: Abbvie, BMS, Celgene, Eli Lilly, Janssen, MSD, Novartis, Pfizer, Roche and UCB, all unrelated to this study (all < $10,000)., Philip Robinson Consultant of: Abbvie, Eli Lilly, Janssen, Novartis, Pfizer and UCB and travel assistance from Roche (all < $10,000)., Jinoos Yazdany Consultant of: Eli Lilly and Astra Zeneca, unrelated to this project.

OP0006 ASSOCIATIONS OF BASELINE USE OF BIOLOGIC OR TARGETED SYNTHETIC DMARDS WITH COVID-19 SEVERITY IN RHEUMATOID ARTHRITIS: RESULTS FROM THE COVID-19 GLOBAL RHEUMATOLOGY ALLIANCE

Background:

Targeted DMARDs may dampen the inflammatory response in COVID-19, perhaps leading to a less severe clinical course. However, some DMARD targets may impair viral immune defenses. Due to sample size limitations, previous studies of DMARD use and COVID-19 outcomes have combined several heterogeneous rheumatic diseases and medications, investigating a single outcome (e.g., hospitalization).

Objectives:

To investigate the associations of baseline use of biologic or targeted synthetic (b/ts) DMARDs with a range of poor COVID-19 outcomes in rheumatoid arthritis (RA).

Methods:

We analyzed voluntarily reported cases of COVID-19 in patients with rheumatic diseases in the COVID-19 Global Rheumatology Alliance physician registry (March 12, 2020 - January 6, 2021). We investigated RA treated with b/tsDMARD at the clinical onset of COVID-19 (baseline): abatacept (ABA), rituximab (RTX), Janus kinase inhibitors (JAK), interleukin-6 inhibitors (IL6i), or tumor necrosis factor inhibitors (TNFi). The outcome was an ordinal scale (1-4) for COVID-19 severity: 1) no hospitalization, 2) hospitalization without oxygen need, 3) hospitalization with any oxygen need or ventilation, or 4) death. Baseline covariates including age, sex, smoking, obesity, comorbidities (e.g., cardiovascular disease, cancer, interstitial lung disease [ILD]), concomitant non-biologic DMARD use, glucocorticoid use/dose, RA disease activity, country, and calendar time were used to estimate propensity scores (PS) for b/tsDMARD. The primary analysis used PS matching to compare each drug class to TNFi. Ordinal logistic regression estimated ORs for the COVID-19 severity outcome. In a sensitivity analysis, we used traditional multivariable ordinal logistic regression adjusting for covariates without matching.

Results:

Of the 1,673 patients with RA on b/tsDMARDs at the onset of COVID-19, (mean age 56.7 years, 79.6% female) there were n=154 on ABA, n=224 on RTX, n=306 on JAK, n=180 on IL6i, and n=809 on TNFi. Overall, 498 (34.3%) were hospitalized and 112 (6.7%) died. Among all patients, 353 (25.3%) were ever smokers, 197 (11.8%) were obese, 462 (27.6%) were on glucocorticoids, 1,002 (59.8%) were on concomitant DMARDs, and 299 (21.7%) had moderate/high RA disease activity. RTX users were more likely than TNFi users to have ILD (11.6% vs. 1.7%) and history of cancer (7.1% vs. 2.0%); JAK users were more likely than TNFi users to be obese (17.3% vs. 9.0%). After propensity score matching, RTX was strongly associated with greater odds of having a worse outcome compared to TNFi (OR 3.80, 95% CI 2.47, 5.85; Figure). Among RTX users, 42 (18.8%) died compared to 27 (3.3%) of TNFi users (Table). JAK use was also associated with greater odds of having a worse COVID-19 severity (OR 1.52, 95%CI 1.02, 2.28). ABA or IL6i use were not associated with COVID-19 severity compared to TNFi. Results were similar in the sensitivity analysis and after excluding cancer or ILD.

Table 1.

Frequencies for the ordinal COVID-19 severity outcome for patients with RA on biologic or targeted synthetic DMARDs (n=1673).

COVID-19 outcomes by severity scale (n,%)ABAn=154RTXn=224JAKn=306IL6in=180TNFi n=8091)Not hospitalized113 (73.3%)121 (54.0%)220 (71.9%)150 (83.3%)666 (82.3%)2)Hospitalization without oxygenation10 (6.5%)14 (6.2%)11 (3.6%)9 (5.0%)53 (6.5%)3)Hospitalization with any oxygenation or ventilation16 (10.4%)47 (21.0%)52 (17.0%)16 (8.9%)63 (7.8%)4)Death15 (9.7%)42 (18.8%)23 (7.5%)5 (2.8%)27 (3.3%)

Conclusion:

In this large global registry of patients with RA and COVID-19, baseline use of RTX or JAK was associated with worse severity of COVID-19 compared to TNFi use. The very elevated odds for poor COVID-19 outcomes in RTX users highlights the urgent need for risk-mitigation strategies, such as the optimal timing of vaccination. The novel association of JAK with poor COVID-19 outcomes requires replication.

Acknowledgements:

The views expressed here are those of the authors and participating members of the COVID-19 Global Rheumatology Alliance and do not necessarily represent the views of the ACR, EULAR, the UK National Health Service, the National Institute for Health Research, the UK Department of Health, or any other organization.

Disclosure of Interests:

Jeffrey Sparks Consultant of: Bristol-Myers Squibb, Gilead, Inova, Janssen, and Optum, unrelated to this work, Grant/research support from: Amgen and Bristol-Myers Squibb, unrelated to this work, Zachary Wallace Consultant of: Viela Bio and MedPace, outside the submitted work., Grant/research support from: Bristol-Myers Squibb and Principia/Sanofi, Andrea Seet: None declared, Milena Gianfrancesco: None declared, Zara Izadi: None declared, Kimme Hyrich Speakers bureau: Abbvie unrelated to this study, Grant/research support from: BMS, UCB, and Pfizer, all unrelated to this study, Anja Strangfeld Paid instructor for: AbbVie, MSD, Roche, BMS, Pfizer, outside the submitted work, Grant/research support from: grants from a consortium of 13 companies (among them AbbVie, BMS, Celltrion, Fresenius Kabi, Lilly, Mylan, Hexal, MSD, Pfizer, Roche, Samsung, Sanofi-Aventis, and UCB) supporting the German RABBIT register, outside the submitted work, Laure Gossec Consultant of: Abbvie, Biogen, Celgene, Janssen, Lilly, Novartis, Pfizer, Sanofi-Aventis, UCB, unrelated to this study, Grant/research support from: Lilly, Mylan, Pfizer, all unrelated to this study, Loreto Carmona: None declared, Elsa Mateus Grant/research support from: grants from Abbvie, Novartis, Janssen-Cilag, Lilly Portugal, Sanofi, Grünenthal S.A., MSD, Celgene, Medac, Pharmakern, GAfPA; grants and non-financial support from Pfizer, outside the submitted work, Saskia Lawson-Tovey: None declared, Laura Trupin: None declared, Stephanie Rush: None declared, Gabriela Schmajuk: None declared, Patti Katz: None declared, Lindsay Jacobsohn: None declared, Samar Al Emadi: None declared, Leanna Wise: None declared, Emily Gilbert: None declared, Ali Duarte-Garcia: None declared, Maria Valenzuela-Almada: None declared, Tiffany Hsu: None declared, Kristin D’Silva: None declared, Naomi Serling-Boyd: None declared, Philippe Dieudé Consultant of: Boerhinger Ingelheim, Bristol-Myers Squibb, Lilly, Sanofi, Pfizer, Chugai, Roche, Janssen unrelated to this work, Grant/research support from: Bristol-Myers Squibb, Chugaii, Pfizer, unrelated to this work, Elena Nikiphorou: None declared, Vanessa Kronzer: None declared, Namrata Singh: None declared, Manuel F. Ugarte-Gil Grant/research support from: Janssen and Pfizer, Beth Wallace: None declared, Akpabio Akpabio: None declared, Ranjeny Thomas: None declared, Suleman Bhana Consultant of: AbbVie, Horizon, Novartis, and Pfizer (all <$10,000) unrelated to this work, Wendy Costello: None declared, Rebecca Grainger Speakers bureau: Abbvie, Janssen, Novartis, Pfizer, Cornerstones, Jonathan Hausmann Consultant of: Novartis, Sobi, Biogen, all unrelated to this work (<$10,000), Jean Liew Grant/research support from: Yes, I have received research funding from Pfizer outside the submitted work., Emily Sirotich Grant/research support from: Board Member of the Canadian Arthritis Patient Alliance, a patient run, volunteer based organization whose activities are largely supported by independent grants from pharmaceutical companies, Paul Sufka: None declared, Philip Robinson Speakers bureau: Abbvie, Eli Lilly, Janssen, Novartis, Pfizer and UCB (all < $10,000), Consultant of: Abbvie, Eli Lilly, Janssen, Novartis, Pfizer and UCB (all < $10,000), Pedro Machado Speakers bureau: Yes, I have received consulting/speaker’s fees from Abbvie, BMS, Celgene, Eli Lilly, Janssen, MSD, Novartis, Pfizer, Roche and UCB, all unrelated to this study (all < $10,000)., Consultant of: Yes, I have received consulting/speaker’s fees from Abbvie, BMS, Celgene, Eli Lilly, Janssen, MSD, Novartis, Pfizer, Roche and UCB, all unrelated to this study (all < $10,000)., Jinoos Yazdany Consultant of: Eli Lilly and AstraZeneca unrelated to this project

POS1162 PREDICTORS OF HOSPITALISATION IN PATIENTS WITH RHEUMATIC DISEASE AND COVID-19 IN IRELAND: DATA FROM THE COVID-19 GLOBAL RHEUMATOLOGY ALLIANCE PHYSICIAN-REPORTED REGISTRY

Background:

There is limited data regarding the risk of hospitalisation in patients with rheumatic disease and COVID-19 in Ireland.

Objectives:

We used the COVID-19 Global Rheumatology Alliance (GRA) registry data to study outcomes and their predictors.

Methods:

We examined data on patients and their disease-related characteristics entered into the COVID-19 GRA provider registry from Ireland (24th March 2020 to 31st August 2020). Multivariable logistic regression was used to assess the association of demographic and clinical characteristics with hospitalisation.

Results:

Of 105 patients, 47 (45.6%) were hospitalised and 10 (9.5%) died. Multivariable logistic regression analysis showed age (OR=1.06, 95%CI 1.01 to 1.10), number of comorbidities (OR=1.93, 95%CI 1.11 to 3.35), and glucocorticoid use (OR=15.01, 95%CI 1.77 to 127.16) were significantly associated with hospitalisation. A diagnosis of inflammatory arthritis was associated with a lower odds of hospitalisation (OR=0.09, 95%CI 0.02 to 0.32).

All significant variable modelMost parsimonious modelUnadjusted OR (95% CI)Adjusted OR (95%CI)*Adjusted p-value*Adjusted OR (95%CI)&Adjusted p-value&Female0.45 (0.20-1.02)0.33 (0.05-2.23)0.34 (0.09-1.36)0.128Age (years)1.08 (1.05-1.11)1.04 (0.97-1.10)0.2241.06 (1.01-1.10)0.010Inflammatory arthritis0.11 (0.05-0.28)0.14 (0.02-0.95)0.0440.09 (0.02-0.32)<0.001Connective Tissue Disease and Other1.56 (0.62 - 3.92)No comorbidities0.11 (0.04-0.30)0.76 (0.09-6.58)0.802Most common comorbiditiesCOPD / asthma4.77 (1.23-18.54)3.09 (0.16-60.07)0.456CVD3.40 (1.31-8.85)0.11 (0.01-1.88)0.129Hypertension3.71 (1.52-9.08)0.56 (0.04-7.94)0.668Obesity0.58 (0.10-3.30)Number of comorbidities (Median, IQR)3.01 (1.92-4.72)2.99 (0.59-15.02)0.1841.93 (1.11-3.35)0.020Never Smokerref.0.889Ever Smoker3.17 (1.18-8.89)1.19 (0.10-13.68)Medication prior to COVID-19 diagnosisGlucocorticoids9.26 (1.95-43.89)18.14 (1.13-290.81)0.04115.01 (1.77-127.16)0.013csDMARD monotherapy0.42 (0.17-1.00)b/tsDMARD (monotherapy or in combination with csDMARD)0.24 (0.10-0.58)1.36 (0.19-9.72)0.557

Conclusion:

Increasing age, comorbidity burden, and glucocorticoid use were associated with hospitalisation, while a diagnosis of inflammatory arthritis was associated with lower odds of hospitalization.

Disclosure of Interests:

Richard Conway Speakers bureau: Janssen, Roche, Sanofi, Abbvie, Elena Nikiphorou Speakers bureau: AbbVie, Eli-Lilly, Gilead, Celltrion, Pfizer, Sanofi, Christiana Demetriou: None declared, Candice Low: None declared, Kelly Leamy: None declared, John Ryan: None declared, Ronan Kavanagh: None declared, Alexander Fraser: None declared, John Carey: None declared, Paul O’Connell: None declared, Rachael Flood: None declared, Ronan Mullan: None declared, David Kane: None declared, Philip Robinson Speakers bureau: UCB, Roche, Pfizer, Gilead, Janssen, Novartis, Eli Lilly, Abbvie, Grant/research support from: Abbvie, UCB, Novartis, Janssen, Pfizer, Jean Liew Grant/research support from: Pfizer, Rebecca Grainger Speakers bureau: Pfizer, Cornerstones, Janssen, Novartis, Abbvie, Geraldine McCarthy: None declared.

631 The Time to Therapeutic Serum Levels of Vancomycin in Orthopaedic Patients

Introduction

Vancomycin is a commonly used antibiotic in the treatment of deep-seated infections. However, the current dosing calculator utilized in NHS Lothian may not adequately achieve therapeutic vancomycin serum concentrations (VSC), of 15-20mg/L, in a timely manner. We aimed to reaudit the length of time for vancomycin to reach therapeutic levels in orthopaedic patients using the new Lothian calculator. A previous audit loop looked at the current calculator in 2018.

Method

Inclusion criteria orthopaedic patients who were treated with vancomycin at the Royal Infirmary Edinburgh, data collection to finish mid-September. The duration to reach the therapeutic SVC, initial trough SVC and serial levels were recorded. A life-table analysis will be used to examine the data.

Results

First audit had Twenty-three patients. The mean initial trough VSC was 12.7mg/L. The mean duration to therapeutic VSC was 5.2 (± 1.3) days. Statistics not completed for second cycle, but initial data shows improvement in time to VSC.

Conclusions

A delay in reaching therapeutic concentrations was observed in a significant proportion of patients using the current calculator. A more rapid achievement of therapeutic levels is required to maximize the period of antibiotic delivery and subsequently improve patient outcomes. The new calculator pilot will hopefully show that improvement.

MRI in acute muscle tears in athletes: can quantitative T2 and DTI predict return to play better than visual assessment?

OBJECTIVES

To assess the ability of quantitative T2, diffusion tensor imaging (DTI) and radiologist's scores to detect muscle changes following acute muscle tear in soccer and rugby players. To assess the ability of these parameters to predict return to play times.

METHODS

In this prospective, longitudinal study, 13 male athletes (age 19 to 34 years; mean 25 years) underwent MRI within 1 week of suffering acute muscle tear. Imaging included measurements of T2 and DTI parameters. Images were also assessed using modified Peetrons and British athletics muscle injury classification (BAMIC) scores. Participants returned for a second scan within 1 week of being determined fit to return to play. MRI measurements were compared between visits. Pearson's correlation between visit 1 measurements and return to play times was assessed.

RESULTS

There were significant differences between visits in BAMIC scores (Z = - 2.088; p = 0.037), modified Peetrons (Z = - 2.530; p = 0.011) and quantitative MRI measurements; T2, 13.12 ms (95% CI, 4.82 ms, 21.42 ms; p = 0.01); mean diffusivity (0.22 (0.04, 0.39); p = 0.02) and fractional anisotropy (0.07 (0.01, 0.14); p = 0.03). BAMIC scores showed a significant correlation with return to play time (Rs = 0.64; p = 0.02), but modified Peetrons scores and quantitative parameters did not.

CONCLUSIONS

T2 and DTI measurements in muscle can detect changes due to healing following muscle tear. Although BAMIC scores correlated well with return to play times, in this small study, quantitative MRI values did not, suggesting that T2 and DTI measurements are inferior predictors of return to play time compared with visual scoring.

KEY POINTS

• Muscle changes following acute muscle tear can be measured using T2 and diffusion measurements on MRI. • Measurements of T2 and diffusion using MRI are not as good as a radiologist's visual report at predicting return to play time after acute muscle tear.

Long-term safety and efficacy of bempedoic acid in patients at high risk of atherosclerotic cardiovascular disease: results from the CLEAR Harmony open-label extension study

Background

Bempedoic acid (BA) is an oral first-in-class, ATP-citrate lyase inhibitor that lowers low-density lipoprotein cholesterol (LDL-C) levels in adults with hypercholesterolemia. In the phase 3 CLEAR Harmony study (NCT02666664, n=2230), BA 180 mg for 52 weeks significantly lowered LDL-C at week 12 compared with placebo and was maintained for 52 weeks in hypercholesterolemic patients with atherosclerotic cardiovascular disease (ASCVD) and/or heterozygous familial hypercholesterolemia (HeFH) on stable, maximally tolerated statins.

Purpose

To report long-term safety, tolerability, and efficacy of BA from the CLEAR Harmony open-label extension (OLE) study (NCT03067441).

Methods

After completing the 52-week placebo-controlled CLEAR Harmony study, patients immediately entered the OLE and received BA for 78 weeks, followed by a 4-week washout period; the potential cumulative exposure to BA was 2.5 years. The primary endpoint was long-term safety of BA in the OLE.

Results

A total of 1462 patients enrolled in the OLE (BA n=970; placebo n=492 from CLEAR Harmony). At OLE baseline, mean (SD) age was 66.9 (8.7) years, 73.9% were male, 96.3% had ASCVD, 3.7% had HeFH with or without ASCVD, and all were receiving statins (93.5% moderate or high intensity). At baseline of CLEAR Harmony, patients had mean (SD) LDL-C of 102.9 (29.9) mg/dL (BA) and 99.0 (24.2) mg/dL (placebo). The majority of OLE patients (86.2%, n=1260) completed 78 weeks of BA treatment. At week 12 and 78 of OLE treatment, respectively, mean LDL-C lowering from CLEAR Harmony baseline was –14.9% and –14.4%. A total of 1143 patients (78.2%) reported a treatment-emergent adverse event (TEAE), and 299 (20.5%) reported a serious TEAE. TEAEs of special interest, determined by the therapeutic area or prior observations in preclinical or early clinical studies, occurred at similar rates as CLEAR Harmony (creatine kinase elevations, 1.8%; gout, 2.6%; hepatic enzyme elevations, 2.0%; hypoglycemia, 1.2%; muscular disorders, 8.5%; neurocognitive disorders, 0.9%; new onset/worsening diabetes mellitus, 5.5%; renal disorders, 2.8%) with biochemical changes that were stable over the course of the study and approached baseline levels after treatment discontinuation. Overall, 114 patients (7.8%) reported a TEAE leading to discontinuation of BA (most common: myalgia [0.6%], muscle spasm [0.5%]).

Conclusion

Durable lipid lowering was observed through 78 weeks of BA treatment and patient adherence to BA therapy was high (86.2%). Overall safety during the OLE was similar to results reported in the 52-week-long CLEAR Harmony study and the overall BA phase 3 clinical program, with no new safety findings.

Funding Acknowledgement

Type of funding source: Private company. Main funding source(s): Esperion Therapeutics, Inc., funded the research for this study and provided writing support for this abstract. Medical writing assistance was provided by Agnella Izzo Matic, PhD, CMPP, and Kelly M Cameron, PhD, CMPP, of JB Ashtin.

Core surgical field camps: a new deanery-based model for enhancing advanced skills in core surgical trainees through simulation

Hands-on wet lab simulation training is a vital part of modern surgical training. Since 2010, surgical 'boot camps' have been run by many UK deaneries to teach core surgical trainees basic entry level skills. Training in advanced skills often requires attendance at national fee-paying courses. In the Wessex Deanery, multiple, free of charge, core surgical 'field camps' were developed to provide more advanced level teaching in the particular specialty preference of each core surgical trainee. After the COVID-19 pandemic, national hands-on courses will be challenging to provide and deanery-based advanced skills training may be the way forward for craft-based specialties. The experiences over 2 years of delivering the Wessex core surgical field camps are shared, giving a guide and advice for other trainers on how to run a field camp.