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BackgroundRheumatoid arthritis (RA) and spondyloarthritis, including either Psoriatic Arthritis (PsA) and Ankylosing Spondylitis (AS), are some of the most diagnosed autoimmune rheumatic diseases (AIRDs) in rheumatologists' routine clinical practice [1]. Understanding patients' health and functional status is crucial to provide personalized management strategies to optimize disease control and enhance the quality of life.ObjectivesWe aimed to compare disease burden in patients with RA, PsA or AS by assessing Patient-Reported Outcome Measurement Information System (PROMIS) Physical Health, Global Mental Health, Physical Function and Fatigue 4a together with VAS Pain.MethodsData were obtained in the international COVID vaccination in autoimmune rheumatic diseases study second e-survey (COVAD study). Demographics, AIRD diagnosis, disease activity, PROMIS Global Physical health, PROMIS Global Mental Health, PROMIS Physical Function SF10 and PROMIS Fatigue 4a score were extracted from the COVAD study database. For this study, we only included patients with self-reported RA or spondyloarthritis (either PsA or AS) undergoing active treatment with conventional synthetic disease-modifying drugs (DMARDs) and/or biologic DMARDs, who answered all the survey questions. Active disease was defined as the patient's perception of their disease as active in the four weeks before their first COVID-19 vaccine shot. Analysis of Variance with Bartlett's and Tukey's test was used to compare continuous variables between groups.ResultsFrom January to June 2022, n.1907 patients with RA, female 87.62% (1671/1907), with mean age (±SD) 50.95 ±13.67, n.311 patients with PsA, female 67.20% (209/311), with a mean age of 50.42 ±12.70, and n.336 patients with AS, male 51.31% (209/311), with a mean age of 43.13 ±12.75 years, responded to the COVAD e-survey.In those with active disease, neither physical health, global mental health, physical function, fatigue, nor pain were different among groups (Table 1, Figure 1). Patients with inactive AS had higher mean global physical health scores than RA patients (13.13 ±2.93 VS RA 12.48 ±2.90, p=0.01, Table 1). Those with inactive RA or PsA showed more severe fatigue (PsA 10.58 ±2.22, RA 10.45 ±4.08 VS 9.4 ±4.13, p =0.01 for both). Patients with inactive RA also reported poorer physical function and more residual pain than those with AS (37.79 ±8.86 VS 41.13 ±7.79, p<0.001;3.87 ±2.45 VS 3.34 ±2.39, p=0.01, respectively). Similarly, residual pain was perceived as higher in patients with inactive PsA than those with AS (4.04 ±2.50 VS 3.34 ±2.39, p=0.01)ConclusionDisease burden is roughly comparable in patients with active RA, PsA or AS. Patients with inactive RA and PsA suffer higher disease burden than those with inactive AS.Reference[1]Mease PJ, Liu M, Rebello S, Kang H, Yi E, Park Y, Greenberg JD. Comparative Disease Burden in Patients with Rheumatoid Arthritis, Psoriatic Arthritis, or Axial Spondyloarthritis: Data from Two Corrona Registries. Rheumatol Ther. 2019 Dec;6(4):529-542.Table 1.Patient-Reported Outcome Measures between groups.Inactive diseaseAS (n.185)PsA (n.179)RA (n.1167)MeanSDMeanSDMeanSDPROMIS Global Physical Health13.13*2.9512.433.2712.482.90p=0.01, VS RAPROMIS Global Mental Health13.313.3612.973.3312.843.17PROMIS Fatigue 4a9.44.1310.58*4.2210.45*4.08p=0.01, bothPROMIS Physical Function SF10 Score41.137.3939.279.0137.79*8.86p<0.001, VS ASVAS Pain3.342.394.04*2.503.87*2.45p=0.01, bothActive DiseaseAS (n.35)PsA (n.38)RA (n.189)MeanSDMeanSDMeanSDPROMIS Global Physical Health11.053.1910.102.7611.243.41PROMIS Global Mental Health11.313.2610.843.6311.893.30PROMIS Fatigue 4a12.944.8712.844.4211.754.68PROMIS Physical Function SF10 Score35.829.6233.528.7634.909.80VAS Pain4.682.775.02.544.682.61Figure 1.Violin plots showing kernel densities, quartiles and median for Patient-Reported Outcome Measures for patients with RA, PsA and AS, stratified by disease activity status.[Figure omitted. See PDF]Acknowledgements:NIL.Disclosure of InterestsVincenzo Venerito: None declared, Marc Fornaro: None declared, Florenzo Iannone: None declared, Lorenzo Cavagna: None declared, Masataka Kuwana: None declared, Vishwesh Agarwal: None declared, Naveen Ravichandran: None declared, Jessica Day Grant/research support from: JD has received research funding from CSL Limited., Mrudula Joshi: None declared, Sreoshy Saha: None declared, Syahrul Sazliyana Shaharir: None declared, Wanruchada Katchamart: None declared, Phonpen Akarawatcharangura Goo: None declared, Lisa Traboco: None declared, Yi-Ming Chen: None declared, Parikshit Sen: None declared, James B. Lilleker Speakers bureau: JBL has received speaker honoraria/participated in advisory boards for Sanofi Genzyme, Roche, and Biogen. None is related to this manuscript., Consultant of: JBL has received speaker honoraria/participated in advisory boards for Sanofi Genzyme, Roche, and Biogen. None is related to this manuscript., Arvind Nune: None declared, John Pauling: None declared, Chris Wincup: None declared, Ai Lyn Tan Speakers bureau: ALT has received honoraria for advisory boards and speaking for Abbvie, Gilead, Janssen, Lilly, Novartis, Pfizer, and UCB., Nelly Ziade Speakers bureau: NZ has received speaker fees, advisory board fees, and research grants from Pfizer, Roche, Abbvie, Eli Lilly, NewBridge, Sanofi-Aventis, Boehringer Ingelheim, Janssen, and Pierre Fabre;none are related to this manuscript, Grant/research support from: NZ has received speaker fees, advisory board fees, and research grants from Pfizer, Roche, Abbvie, Eli Lilly, NewBridge, Sanofi-Aventis, Boehringer Ingelheim, Janssen, and Pierre Fabre;none are related to this manuscript, Marcin Milchert: None declared, Abraham Edgar Gracia-Ramos: None declared, Carlo Vinicio Caballero: None declared, COVAD Study: None declared, Vikas Agarwal: None declared, Rohit Aggarwal Speakers bureau: RA has a consultancy relationship with and/or has received research funding from the following companies: Bristol Myers-Squibb, Pfizer, Genentech, Octapharma, CSL Behring, Mallinckrodt, AstraZeneca, Corbus, Kezar, Abbvie, Janssen, Alexion, Argenx, Q32, EMD-Serono, Boehringer Ingelheim, and Roivant., Grant/research support from: RA has a consultancy relationship with and/or has received research funding from the following companies: Bristol Myers-Squibb, Pfizer, Genentech, Octapharma, CSL Behring, Mallinckrodt, AstraZeneca, Corbus, Kezar, Abbvie, Janssen, Alexion, Argenx, Q32, EMD-Serono, Boehringer Ingelheim, and Roivant., Latika Gupta: None declared.
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BackgroundAlthough many studies have been conducted on COVID-19 in recent years, there are still unanswered questions regarding breakthrough infections (BTIs), particularly in patients with systemic lupus erythematosus (SLE).ObjectivesThis study aimed to determine the occurrence of breakthrough COVID-19 infections in patients with SLE versus other autoimmune rheumatic diseases (AIRDs), non-rheumatic autoimmune diseases (nrAIDs), and healthy controls (HCs).MethodsThe study was based on data from the COVAD questionnaire which amassed a total of 10,783 complete responses from patients with SLE, AIRD, or nrAIRD, and HCs. After exclusion of individuals who were unvaccinated, those who received one vaccine dose only, and those with uncertain responses regarding the vaccine doses, a total of 9,595 patients formed the study population of the present investigation. If a COVID-19 infection occurred after the initial two vaccine doses and at least one booster dose (at least three doses in total, herein termed full vaccination), it was considered a BTI. Data were analysed using multivariable regression models. Statistically significant results were denoted by p values <0.05.ResultsA total of 7,016/9,595 (73.1%) individuals were fully vaccinated. Among those, 1,002 (14.2%) reported at least one BTI, and 166 (2.3%) reported at least two BTIs. Among SLE patients, 867/1,218 (71.2%) were fully vaccinated. Among fully vaccinated SLE patients, 137 (15.8%) reported at least one BTI while 28 (3.2%) reported at least two BTIs. BTI frequencies in fully vaccinated SLE patients were comparable to those of other AIRDs (OR: 1.0;95% CI: 0.8–1.3;p=0.447) and nrAIDS (OR: 0.9;95% CI: 0.6–1.3;p=0.856) but higher compared with HCs (OR: 1.2;95% CI: 1.0–1.6;p=0.022).For SLE patients with three vaccine doses, 113/137 (82.5%) reported at least one BTI while the corresponding number for four vaccine doses was 24/137 (17.5%). Compared with HCs (OR: 10.6;95% CI: 1.2–93.0;p=0.032) and other AIRDs (OR: 3.5;95% CI: 1.08–11.5;p=0.036), SLE patients showed higher frequencies of hospitalisation.AID multimorbidity was associated with a 15-fold increased risk for a need of advanced treatment for COVID-19 (OR: 15.3;95% CI: 2.6–88.2;p=0.002).ConclusionCOVID-19 BTIs occurred in nearly 1 every 6th fully vaccinated patient with SLE, and 20% more frequently in this patient population compared with fully vaccinated HCs. Moreover, BTIs in SLE patients were more severe compared with BTIs in HCs or patients with AIRDs other than SLE, resulting in a greater need for hospitalisation. AID multimorbidity contributed to a more severe COVID-19 BTI requiring advanced management. These insights call for greater attention to vaccination in the vulnerable group of SLE patients, with appropriate risk stratification towards optimised vaccination strategies.Figure 1.Survival analysis across patients with SLE, AIRDs, or nrAIDs, and HCs. SLE: systemic lupus erythematosus;AIRD: autoimmune rheumatic disease;nrAID: non-rheumatic autoimmune disease;HC: healthy control.[Figure omitted. See PDF]AcknowledgementsThe authors thank all survey respondents, as well as patient associations and all members of the COVAD study group for their invaluable role in the data collection.Disclosure of InterestsEmelie Kihlgren Olsson: None declared, Naveen Ravichandran: None declared, Elena Nikiphorou Speakers bureau: EN has received speaker honoraria/participated in advisory boards for Celltrion, Pfizer, Sanofi, Gilead, Galapagos, AbbVie, and Lilly., Consultant of: EN has received speaker honoraria/participated in advisory boards for Celltrion, Pfizer, Sanofi, Gilead, Galapagos, AbbVie, and Lilly., Grant/research support from: EN holds research grants from Pfizer and Lilly., Julius Lindblom: None declared, Sreoshy Saha: None declared, Syahrul Sazliyana Shaharir: None declared, Wanruchada Katchamart: None declared, Phonpen Akarawatcharangura Goo: None declared, Lisa Traboco: None declared, Yi-Ming Chen: None declared, Kshitij Jagtap: None declared, James B. Lilleker Speakers bureau:
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Background:COVID-19 vaccine hesitancy among pregnant and breastfeeding women with autoimmune diseases (AID) is often attributed to the fear of adverse events (AE) and disease flares (DF). No data are available regarding COVID-19 vaccine safety in this population.Objectives:We aimed at describing delayed-onset (>7 days) vaccine-related AE (minor and major), DF, and related AID treatment modifications from the COVID-19 Vaccination in Autoimmune Diseases (COVAD) study.Methods:Among complete responses from 9201 participants as of June 21, 2022, 6787 (73.8%) were women. Six subgroups were identified upon diagnosis of AID vs healthy controls (HC) and their pregnancy/breastfeeding status at the time of any dose of vaccine (Figure 1).Figure 1.Flowchart of the study. AID: autoimmune diseases;HC: healthy controls;rAID: rheumatic AID;nrAID: non-rheumatic AID.[Figure omitted. See PDF]ResultsForty pregnant and 52 breastfeeding AID patients were identified and their vaccination rates (at least one dose) was 100% and 96.2%, respectively (Table 1). Overall AE, minor AE, and major AE were reported significantly more frequently by pregnant than non-pregnant patients (45% vs. 26%, p=0.01;40% vs. 25.9%, p=0.03;17.5% vs. 4.6%, p<0.01), but no difference was found in comparison with pregnant HC. No difference was observed between breastfeeding patients and HC. Post-vaccination DF were reported by 17.5% of pregnant and 20% of breastfeeding patients, and by 18% of age- and disease-matched control patients (n=2315). All DF in pregnant/breastfeeding patients were managed with glucocorticoids and a fifth of them required initiation or change in immunosuppressive treatment.Table 1.Characteristics of female subjects according to groups. Percentages in parenthesis. *Pregnancy/breastfeeding status at the time of the survey and/or at the time of at least one dose of COVID-19 vaccine. Chi squared test: ~ p=0.01;° p=0.03;§ p<0.01.Total Women (n=6787)Group A Non-pregnant, non-breastfeeding with AID (n=4862)Group B Pregnant with AID* (n=40)Group C Breastfeeding with AID* (n=52)Group D Non-pregnant, non-breastfeeding HC (n=1749)Group E Pregnant HC* (n=31)Group F Breastfeeding HC* (n=53)Age (median, IQR)47, 35-5850, 38-6134, 31-35.2533, 30-3539, 29-4934, 30-36.533, 30-36Caucasian3225 (47.5)2634 (54.1)12 (30)22 (42.3)538 (30.8)7 (22.6)12 (22.6)No comorbidities3027 (44.6)1815 (37.3)19 (47.5)36 (69.2)1102 (63)17 (54.8)38 (71.7)Number of vaccinated women, n (%)6632 (97.7)4753 (97.8)40 (100)50 (96.2)1710 (97.8)30 (96.8)49 (92.5)≥3 doses4850 (71.5%)3583 (73.7%)26 (65%)33 (63.5%)1155 (66%)23 (74.2%)30 (56.6%)No AE4950 (74.6)3517 (74)~22 (55)~36 (72)1312 (76.7)22 (73.3)36 (73.5)Injection site (arm) pain and soreness630 (9.5)471 (9.9)7 (17.5)7 (14)138 (8.1)2 (6.7)5 (10.2)Minor AE1614 (24.3)1232 (25.9)°16 (40)°12 (24)338 (19.8)7 (23.3)10 (20.4)Major AE285 (4.3)196 (4.6)§7 (17.5)§1 (2)77 (4.5)1 (3.3)3 (6.1)Hospitalization74 (1.1)51 (1.1)2 (5)0 (0)20 (1.2)0 (0)1 (2)ConclusionThis study provides the first insights into the safety of COVID-19 vaccination during the antenatal period in women with AID. While AEs were more commonly reported by pregnant patients with AID, these were no higher than among pregnant healthy controls without AID. These observations are reassuring, likely to strengthen physician-patient communication and overcome hesitancy as the benefits for the mother and fetus by passive immunization are likely to overweigh the potential risks of AE and DF.Reference[1]Fazal ZZ, et al;COVAD Study Group. COVAD survey 2 long-term outcomes: unmet need and protocol. Rheumatol Int 2022;42:2151-2158.AcknowledgementsThe authors are grateful to all respondents, to all patients support groups, and to all COVAD Study Group collaborators from 106 Countries.Disclosure of InterestsNone Declared.
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Background: Traditional Chinese medicine (TCM) plays a crucial role in the prevention and control of coronavirus disease 2019 (COVID-19). Objective: The study aimed to reveal the distribution characteristics of COVID-19 TCM syndrome types and syndrome elements and the law of TCM treatment and medication. Methods: The TCM diagnosis and treatment protocol for COVID-19 and clinical research data were obtained through network retrieval, and Revman 5.3 and SPSS 23.0 were employed to analyze the composition of TCM syndromes and the situation of TCMs in meta and frequency. Results: The top three TCM syndromes of COVID-19 included damp-heat accumulation in the lung pattern, damp abundance due to spleen deficiency, and epidemic toxin invading the lung pattern, while the syndrome elements were dampness, heat, and toxin. Gypsum fibrosum, Pogostemonis herba, and Armeniacae semen were identified as the commonly used drugs. Different syndrome elements were identified at lung disease location: Forsythiae fructus, Glycyrrhizae radix, and Armeniacae semen can be used for "wind;" Glycyrrhizae radix, Armeniacae semen, and Scutellariae radix can be used for "Heat;" Armeniacae semen, Sheng Gypsum fibrosum, and Ephedrae herba can be used for "Toxin;" Ephedrae herba, Armeniacae semen, and Atractylodis rhizome can be used for "Damp;" Magnoliae officinalis Cortex, Ephedrae herba, and Zingiberis Rhizoma recens can be used for "cold;" and Armeniacae semen, Gypsum fibrosum, Ephedrae herba, and Lepidii/Descurainiae semen can be used for "epidemic. " Conclusion: The establishment of a treatment scheme based on the classification of disease syndrome elements should be considered for sudden infectious diseases, such as COVID-19. Pogostemonis herba, Armeniacae semen, Gypsum fibrosum, and Glycyrrhizae radix should be considered as effective drugs from TCM for the treatment of COVID-19.
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Introduction. Green Houses (GHs) have features that distinguish them from traditional nursing homes (NHs) including small size, home-like settings, humane model of care, and a sense of community. Literature shows these features have contributed to lower staff turnover, higher resident satisfaction, and lower COVID-19 case and mortality rates. Few studies use longitudinal data to quantify the differences between GHs and NHs by examining COVID-19 case and mortality rates. Methods. Nursing Home COVID-19 Data from CMS were used to compare case and mortality rates between GHs (n=4) and NHs (n=614) from 5/2020 to 1/2022. Case and mortality rates were calculated for GHs and NHs. Incidence rate ratio (IRR) of case and mortality rates were provided. Results. The preliminary results indicate GHs have lower COVID-19 case (3.76 vs. 6.8 per 1,000 resident weeks) and mortality rates (0.35 vs 1.21 per 1,000 resident weeks) compared to NHs. The IRR for COVID-19 cases is significantly higher in NHs compared to GHs (IRR = 1.8;95% CI 1.55, 2.11), likewise, for mortality (IRR = 3.45;95% CI 2.09, 5.75). Conclusions. The findings illuminate key differences in COVID-19 case and mortality rates among GHs and NHs. Factors such as GH size and their unique care model may contribute to the differences observed in COVID-19 case and mortality rates when compared to NHs. Future studies may include facility or resident characteristics in the study design.
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Background: Several studies have demonstrated immunogenicity after COVID-19 vaccination in patients with autoimmune rheumatic diseases (AIRD) [1], but the differences between mRNA-based and vector vaccines and the cellular responses to COVID-19 vaccines according to distinct immunogenicity in AIRD patients are still unclear. Objectives: To investigate the differences in efficacy and safety between the vector vaccine ChAdOx1 nCoV-19/AZD1222 (Oxford-AstraZeneca) and mRNA-based vaccine mRNA-1273 (Moderna) in patients with AIRD, and to explore the cell-cell interactions between high and low anti-SARS-CoV-2 IgG levels in patients with rheumatic arthritis (RA) by single-cell RNA sequencing (scRNA-seq). Methods: From September 16 to November 15, 2021, we consecutively enrolled 243 participants aged ≥20 years with AIRD who received COVID-19 vaccination, of whom 113 were immunized with AZD1222 and 130 with mRNA-1273. The level of serum IgG antibodies to the SARS-CoV-2 receptor-binding domain on the spike protein S1 subunit was quantifed by electrochemiluminescence immuno-assay at 4-6 weeks after vaccination. Moreover, peripheral blood mononuclear cells were isolated from two RA patient with high anti-SARS-CoV-2 IgG level and four RA patients with low level for scRNA-seq and cell-cell communication signal was analyzed by CellChat. Results: The anti-SARS-CoV-2 IgG seropositivity rate was 78.8% (89/113) for AZD1222 and 83.1% (108/130) for mRNA-1273. The level of anti-SARS-CoV-2 IgG was higher in patients who received mRNA-1273 than in those who received AZD1222 (β: 30.15, 95% CI: 11.67-48.63, p=0.002) (Table 1). Prednisolone-equivalent dose >5 mg/day and methotrexate (MTX) use in AIRD patients, and non-anti-tumor necrosis factor (TNF)-α biologics and Janus kinase (JAK) inhibitor use in RA patients were associated with inferior immunogenicity. ScRNA-seq revealed CD16-monocytes were predominant in RA patients with high anti-SARS-CoV2-IgG antibody level, and enriched pathways related to antigen presentation via major histocompatibility complex class II (MHC class II) were found (Figure 1). HLA-DRA and CD4 interaction was vigorous among all identifed MHC-II pathway and was enhanced in high anti-SARS-CoV2-IgG antibody group. Conclusion: mRNA-1273 and AZD1222 vaccines exhibited differential immunogenicity in patients with AIRD. Enriched pathways related to antigen presentation via MHC class II in CD16-monocytes might be associated with higher anti-SARS-CoV2-IgG level in RA patients and further study is warranted.
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COVID-19 is characterized by dysregulated immune responses, metabolic dysfunction and adverse effects on the function of multiple organs. To understand host responses to COVID-19 pathophysiology, we combined transcriptomics, proteomics, and metabolomics to identify molecular markers in peripheral blood and plasma samples of 66 COVID-19-infected patients experiencing a range of disease severities and 17 healthy controls. A large number of expressed genes, proteins, metabolites, and extracellular RNAs (exRNAs) exhibit strong associations with various clinical parameters. Multiple sets of tissue-specific proteins and exRNAs varied significantly in both mild and severe patients suggesting a potential impact on tissue function. Chronic activation of neutrophils, IFN-I signaling, and a high level of inflammatory cytokines were observed in patients with severe disease progression. In contrast, COVID-19-infected patients experiencing milder disease symptoms showed robust T-cell responses. Finally, we identified genes, proteins, and exRNAs as potential biomarkers that might assist in predicting the prognosis of SARS-CoV-2 infection. These data refine our understanding of the pathophysiology and clinical progress of COVID-19. SYNOPSIS image Proteomics, metabolomics and RNAseq data map immune responses in COVID-19 patients with different disease severity, revealing molecular makers associated with disease progression and alterations of tissue-specific proteins. A multi-omics profiling of the host response to SARS-CoV2 infection in 66 clinically diagnosed and laboratory confirmed COVID-19 patients and 17 uninfected controls. Significant correlations between multi-omics data and key clinical parameters. Alteration of tissue-specific proteins and exRNAs. Enhanced activation of immune responses is associated with COVID-19 pathogenesis. Biomarkers to predict COVID-19 clinical outcomes pending clinical validation as prospective marker.