Abstract
Objective
The coronavirus disease 2019 (COVID-19) pandemic created challenges for patients with RA. We examined the potential impact of the pandemic on patient-reported outcomes (PROs), disease activity and medication profiles, comparing the periods pre-pandemic and during the pandemic.
Methods
Patients enrolled in the Ontario Best Practices Research Initiative were included if they had at least one visit to a physician or study interviewer within 12 months before and after the start of pandemic-related closures in Ontario (15 March 2020). Baseline characteristics, disease activity, PROs [i.e. health assessment questionnaire disability index, RA disease activity index (RADAI), European quality of life five-dimension questionnaire], medication use and changes were included. Student’s paired two-sample t-tests and McNamar’s tests were performed for continuous and categorical variables between time periods.
Results
The sample for analysis consisted of 1508 patients, with a mean (s.d.) age of 62.7 (12.5) years, and 79% were female. Despite decreases in the number of in-person visits during the pandemic, there was no significant negative impact on disease activity or PRO scores. The DASs in both periods remained low, with either no clinically significant differences or slight improvement. Scores for mental, social and physical health were either stable or improved. There were statistically significant decreases in conventional synthetic DMARD use (P < 0.0001) and increased Janus kinase inhibitor usage (P = 0.0002). Biologic DMARD use remained stable throughout the pandemic.
Conclusion
In this cohort, disease activity and PROs of RA patients remained stable during the COVID-19 pandemic. The longer-term outcomes of the pandemic warrant investigation.
Keywords: COVID-19, coronavirus, patient-reported outcome, rheumatic diseases, RA, disease activity, medication adherence
Key messages.
Disease activity was generally stable during the pandemic period, similar to the pre-pandemic period.
Patient-reported outcomes of patients before and during the COVID-19 pandemic were similar.
Conventional synthetic DMARD use decreased, whereas Janus kinase inhibitor usage increased during the pandemic.
Introduction
Coronavirus disease 2019 (COVID-19) has impacted health-care systems across the globe. This disease has negatively affected mental health, social well-being and the economy and has disrupted longitudinal patient care [1–4]. Patients with autoimmune rheumatic diseases might be at a particularly elevated risk for poorer outcomes when infected by COVID-19 owing to being immune suppressed from their illness and treatment [5].
Although much attention has been placed on the direct impact of the infection concerning morbidity and mortality for patients, research is necessary to evaluate how this pandemic has affected other aspects of patient care. A few studies with small sample sizes examining the mental health status of patients with rheumatic diseases compared with controls during the pandemic suggest that these patients had higher levels of distress and panic, with others showing increased depression and anxiety on a group level [6, 7]. How the pandemic impacted the patient-reported outcomes (PROs) in RA patients individually by comparing the periods before and during the pandemic is not fully elucidated.
The Ontario Best Practices Research Initiative (OBRI) is an organization founded in 2005 on the collaborative efforts between patients, rheumatologists and researchers to help improve the treatment and outcomes of Ontarians living with RA, currently with >3900 patients being followed prospectively [Ontario Best Practices Research Initiative (obri.ca)]. In this database, patients are approached regularly by the research team to collect multiple domains of PROs. We used this dataset to evaluate the impact of the COVID-19 pandemic by comparing patients’ pre-pandemic disease activity, medication profiles and PROs with data collected during the pandemic.
Methods
Study design
The OBRI is a multicentre provincial registry in Canada that collects data prospectively on RA patients followed in routine care. Patients eligible for inclusion in the registry must have a diagnosis of RA confirmed by a rheumatologist, disease onset ≥16 years of age, be ≥18 years of age at registry enrolment and have at least one swollen joint. Treating rheumatologists collect data through patient assessment during routine care, and patients also provide data directly via telephone interviews occurring every 6 months. The OBRI registry was established in accordance with the Declaration of Helsinki. Ethics approval was obtained for institutional sites (University Health Network Research Ethics Board no. 07-0729-AE) and approval at each participating site. Written informed consent was provided by all patients before enrolment in the registry.
Study population
We defined two study periods, each of 1 year duration: a pre-COVID-19 pandemic phase (12 months before 15 March 2020) and a COVID-19 pandemic phase (12 months after 15 March 2020). We applied a time window period for data collection of ±60 days for 1 year before and during the COVID-19 pandemic (1 year + 60 days). Patients enrolled in OBRI were included if they had at least one visit to a physician or interviewer (virtually or in person) in both study periods. Patient characteristics, disease activity measurements, PROs, medication usage and the number of visits were recorded.
Statistical analyses
Baseline characteristics, defined as the demographic data collected 1 year before the COVID-19 pandemic was declared in Ontario, were reported as the mean (s.d.) and percentages where appropriate. Student’s [aired two-sample t-tests and McNemar’s tests were performed for continuous and categorical variables, respectively, between the two study periods, with statistical significance set at <0.05.
Results
The sample for analysis included 1508 patients who fulfilled the eligibility criteria. Of these, 1249 patients had at least one visit to a physician and 709 patients had at least one interview visit during both periods (Supplementary Fig. S1, available at Rheumatology Advances in Practice online). The mean (s.d.) age of patients was 62.7 (12.5) years; 1196 (79.3%) were female. The mean disease duration was 12.1 (10) years. The majority were seropositive, with either positive RF (70.9%) or positive ACPA (61.5%). The most common co-morbidities were hypertension (15.5%), diabetes (3.8%), respiratory disease (4.6%) and depression (5.3%).
In the pre-pandemic period, baseline disease activity was low, with the following scores reported [mean (s.d.)]: Clinical Disease Activity Index (CDAI) 8.66 (8.54), Simplified Disease Activity Index for Rheumatoid Arthritis (SDAI) 9.40 (8.95), DAS-28 2.97 (1.27) and RA Disease Activity Index (RADAI) 2.47 (1.95). Inflammatory markers were also low, with ESR of 19.3 (17.1) mm/h and CRP of 6.63 (11.0) mg/l. Patient-reported outcome measures were either low or moderate at baseline, with the following scores reported [mean (s.d.)]: Health Assessment Questionnaire-Disability Index (HAQ-DI) 0.91 (0.75), HAQ-pain 0.93 (0.76), fatigue 3.81 (2.87), sleep 2.92 (2.95), depression/anxiety 1.16 (0.35) and EQ5D EuroQoL 0.79 (0.17).
Table 1 highlights the physician-reported disease activity measures before and during the COVID-19 pandemic. Supplementary Fig. S2, available at Rheumatology Advances in Practice online, outlines the changes graphically. The number of physician visits per patient (virtual or in person) increased by an average of 0.21 (1.51). The number of days between visits decreased by 11.3 (66.9) days. Although improvements were noted in swollen and tender joint counts, there was no statistically significant difference in the overall patient global, physician global and some DASs (CDAI, SDAI and DAS). The ESR was elevated significantly when comparing laboratory investigations before and during the pandemic. There were statistically significant decreases in conventional synthetic DMARD (csDMARD) and CS use and increases in Janus kinase (JAK) inhibitor use between the two study periods. Use of biologic DMARDs (bDMARDs) remained unchanged between the two study periods.
Table 1.
Physician disease activity measures 1 year before and during first year of coronavirus disease 2019 (15 March 2020)
| Patients (n = 1249) | Within 1 year before COVID-19 | Within first year of COVID-19 | Paired comparison |
||
|---|---|---|---|---|---|
| Before | After | Difference, P-value | |||
| Number of visits per patient | |||||
| n | 1249 | 1249 | 1249 | 1249 | 1249 |
| Mean (s.d.) | 2.21 (1.02) | 2.42 (1.45) | 2.21 (1.02) | 2.42 (1.45) | 0.21 (1.51), <0.0001 |
| Total visits per patient | |||||
| n | 1249 | 1249 | – | – | – |
| One visit, n (%) | 299 (23.9) | 560 (44.8) | – | – | – |
| Two visits, n (%) | 569 (45.6) | – | – | – | – |
| Three or more visits, n (%) | 381 (30.5) | 689 (55.2) | – | – | – |
| Time (days) between visits for patients with more than one visit including virtual visits | |||||
| n | 947 | 686 | 578 | 578 | 578 |
| Mean (s.d.) | 148.2 (54.3) | 131.1 (53.5) | 139.7 (52.8) | 128.4 (52.0) | −11.3 (66.9), <0.0001 |
| Swollen joint count (0–10) | |||||
| n | 1241 | 810 | 804 | 804 | 804 |
| Mean (s.d.) | 1.66 (2.67) | 1.19 (2.67) | 1.66 (2.80) | 1.17 (2.67) | −0.49 (3.04), <0.0001 |
| Tender joint count (0–10) | |||||
| n | 1237 | 763 | 755 | 755 | 755 |
| Mean (s.d.) | 2.07 (3.30) | 1.57 (3.22) | 1.97 (3.20) | 1.57 (3.22) | −0.40 (3.73), 0.003 |
| Patient global assessment (0–10) | |||||
| n | 1055 | 591 | 570 | 570 | 570 |
| Mean (s.d.) | 2.98 (2.41) | 2.90 (2.41) | 2.90 (2.42) | 2.87 (2.41) | −0.03 (2.22), 0.77 |
| Physician global assessment (0–10) | |||||
| n | 1043 | 517 | 497 | 497 | 497 |
| Mean (s.d.) | 1.73 (1.82) | 1.60 (1.85) | 1.58 (1.80) | 1.57 (1.83) | −0.01 (1.71), 0.90 |
| Clinical disease activity index (0–76) | |||||
| n | 1109 | 480 | 460 | 460 | 460 |
| Mean (s.d.) | 8.66 (8.54) | 7.63 (8.68) | 8.07 (8.15) | 7.42 (8.54) | −0.65 (8.25), 0.09 |
| Simplified disease activity index (0.1–86) | |||||
| n | 949 | 369 | 342 | 342 | 342 |
| Mean (s.d.) | 9.40 (8.95) | 8.43 (9.02) | 8.47 (8.53) | 8.31 (9.02) | −0.16 (8.68), 0.73 |
| DAS-28 (0-9.4) | |||||
| n | 991 | 440 | 401 | 401 | 401 |
| Mean (s.d.) | 2.97 (1.27) | 2.91 (1.23) | 2.82 (1.25) | 2.89 (1.23) | 0.07 (1.12), 0.19 |
| ESR | |||||
| n | 916 | 769 | 703 | 703 | 703 |
| Mean (s.d.) | 19.3 (17.1) | 21.8 (19.1) | 19.5 (17.5) | 21.7 (19.1) | 2.20 (1.29), <0.0001 |
| CRP | |||||
| n | 1051 | 917 | 835 | 835 | 835 |
| Mean (s.d.) | 6.63 (11.0) | 6.55 (13.1) | 6.63 (10.8) | 6.34 (12.3) | −0.29 (11.5), 0.47 |
| Medication number reported by physician | |||||
| n | 1227 | 1216 | 1210 | 1210 | 1210 |
| Mean (s.d.) | 1.49 (0.64) | 1.50 (0.65) | 1.51 (0.63) | 1.50 (0.65) | −0.01 (0.42), 0.37 |
| bDMARDs use reported by physician | |||||
| Visits (n) | 3101 | 3101 | 3101 | 3101 | 3101 |
| Yes (%) | 1119 (36.1) | 1071 (34.5) | 1119 (36.1) | 1071 (34.5) | P = 0.001 |
| csDMARDs use reported by physician | |||||
| Visits (n) | 3101 | 3101 | 3101 | 3101 | 3101 |
| Yes (%) | 2486 (80.2) | 2439 (78.7) | 2486 (80.2) | 2439 (78.7) | P = 0.003 |
| Janus kinase inhibitor use reported by physician | |||||
| Visits (n) | 3101 | 3101 | 3101 | 3101 | 3101 |
| Yes (%) | 336 (10.8) | 425 (13.7) | 336 (10.8) | 425 (13.7) | <0.0001 |
| CS use reported by physician | |||||
| Visits (n) | 3101 | 3101 | 3101 | 3101 | |
| Yes (%) | 715 (23.1) | 700 (22.6) | 715 (23.1) | 700 (22.6) | P = 0.52 |
bDMARDs: biologic DMARDs; COVID-19: coronavirus disease 2019; csDMARDs: conventional synthetic DMARDs.
Table 2 highlights the PROs before and during the COVID-19 pandemic. Supplementary Fig. S3, available at Rheumatology Advances in Practice online, outlines the changes graphically. There was a statistically significant improvement in fatigue and in self-reported DASs (RADAI) during the pandemic (Table 2). Patients also reported a significant decrease in csDMARD and CS usage and a significant increase in JAK inhibitor usage.
Table 2.
Patient reported outcomes one year before and during first year of coronavirus disease 2019 (15 March 2020)
| n = 709 | Within 1 year before COVID-19 | Within 1 year after COVID-19 | Paired comparison |
||
|---|---|---|---|---|---|
| Before | After | Difference, P-value | |||
| Number of interview visits per patient | |||||
| n | 709 | 709 | 709 | 709 | 709 |
| Mean (s.d.) | 2.01 (52.0) | 1.83 (0.46) | 2.01 (52.0) | 1.83 (0.46) | −0.18 (0.66), <0.0001 |
| Total visits per patient | |||||
| n | 709 | 709 | – | – | – |
| One visit, n (%) | 65 (9.2) | 145 (20.5) | – | – | – |
| Two visits, n (%) | 574 (81.0) | 542 (76.5) | – | – | – |
| Three or more visits, n (%) | 70 (9.8) | 22 (3.0) | – | – | – |
| Time between visits for patients with more than one visit, days | |||||
| n | 644 | 564 | 515 | 515 | 515 |
| Mean (s.d.) | 173.6 (31.4) | 182.6 (18.7) | 171.8 (32.4) | 184.8 (15.8) | 13.0 (36.4), <0.0001 |
| HAQ-DI (0–3) | |||||
| n | 709 | 709 | 706 | 706 | 706 |
| Mean (s.d.) | 0.91 (0.75) | 0.90 (0.74) | 0.91 (0.75) | 0.90 (0.74) | −0.01 (0.59), 0.70 |
| HAQ pain (0–3) | |||||
| n | 709 | 709 | 705 | 705 | 705 |
| Mean (s.d.) | 0.93 (0.76) | 0.89 (0.78) | 0.93 (0.76) | 0.89 (0.78) | −0.04 (0.59), 0.05 |
| Fatigue (0–10) | |||||
| n | 709 | 709 | 706 | 706 | 704 |
| Mean (s.d.) | 3.81 (2.87) | 3.32 (2.89) | 3.80 (2.87) | 3.32 (2.89) | −0.48 (2.42), <0.0001 |
| Sleep (0–10) | |||||
| n | 709 | 709 | 706 | 706 | 706 |
| Mean (s.d.) | 2.92 (2.95) | 2.77 (2.95) | 2.91 (2.95) | 2.77 (2.95) | −0.14 (2.56), 0.14 |
| Depression/anxiety (0–3) | |||||
| n | 709 | 709 | 706 | 706 | 706 |
| Mean (s.d.) | 1.16 (0.35) | 1.18 (0.37) | 1.15 (0.35) | 1.18 (0.37) | 0.02 (0.36), 0.07 |
| RADAI morning stiffness duration (0–10) | |||||
| n | 709 | 709 | 706 | 706 | 706 |
| Mean (s.d.) | 2.34 (2.66) | 2.12 (2.51) | 2.34 (2.66) | 2.11 (2.52) | −0.23 (2.53), 0.02 |
| RADAI (0–10) | |||||
| n | 709 | 709 | 706 | 706 | 706 |
| Mean (s.d.) | 2.47 (1.95) | 2.30 (1.89) | 2.46 (1.95) | 2.29 (1.89) | −0.17 (1.40), 0.002 |
| EQ5D EuroQoL (0–1) | |||||
| n | 709 | 709 | 706 | 706 | 706 |
| Mean (s.d.) | 0.79 (0.17) | 0.80 (0.19) | 0.79 (0.17) | 0.80 (0.19) | 0.01 (0.14), 0.22 |
| Medication number reported by patient | |||||
| n | 672 | 660 | 653 | 653 | 653 |
| Mean (s.d.) | 1.40 (0.61) | 1.36 (0.63) | 1.44 (0.59) | 1.37 (0.63) | −0.07 (0.50), <0.0001 |
| bDMARDs use reported by patient | |||||
| Visits (n) | 1495 | 1495 | 1495 | 1495 | 1495 |
| Yes (%) | 440 (29.4) | 425 (28.4) | 440 (29.4) | 425 (28.4) | P = 0.16 |
| csDMARDs use reported by patient | |||||
| Visits (n) | 1495 | 1495 | 1495 | 1495 | 1495 |
| Yes (%) | 1152 (77.1) | 1079 (72.2) | 1152 (77.1) | 1079 (72.2) | P < 0.0001 |
| Janus kinase inhibitor use reported by patient | |||||
| Visits (n) | 1495 | 1495 | 1495 | 1495 | 1495 |
| Yes (%) | 160 (10.7) | 191 (12.8) | 160 (10.7) | 191 (12.8) | P = 0.0002 |
| CS use reported by patient | |||||
| Visits (n) | 1495 | 1495 | 1495 | 1495 | 1495 |
| Yes (%) | 231 (15.5) | 202 (13.5) | 231 (15.5) | 202 (13.5) | P = 0.0002 |
bDMARDs: biologic DMARDs; COVID-19: coronavirus disease 2019; csDMARDs: conventional synthetic DMARDs; EQ5D EuroQoL: European quality of life 5-dimension questionnaire HAQ-DI: health assessment questionnaire disability index; RADAI: RA disease activity index.
A sub-analysis was performed, limiting the comparison to in-person assessments within the two study periods (Supplementary Table S1, available at Rheumatology Advances in Practice online). There were increases in some of the disease activity measures (patient global assessment, SDAI, DAS-28 and ESR). bDMARD use was decreased, and both JAK inhibitor and CS use were increased significantly during the COVID-19 pandemic.
Discussion
In this study of >1500 RA patients, we found no significant negative impact on disease activity or PROs during the COVID-19 pandemic. To the best of our knowledge, this is the first study to examine the effects of the COVID-19 pandemic on patients with RA on disease activity, medication changes and PROs. Our study and analysis were initiated 1 year after the COVID-19 pandemic started. Therefore, the objective and subjective measures were limited to the first year. Although this might be seen as a limitation, the first year of the pandemic had the main periods of lockdown and, as such, was the time period where patient care was significantly modified.
Differences were seen in the average number of visits and time between visits. However, the differences themselves were not clinically significant. This was true for the average changes in swollen joint counts and tender joint counts. Overall, the DASs in both study periods remained low (CDAI, SDAI and DAS-28), or patients performed slightly better (RADAI). These findings were similar to the results of a study conducted by Glintborg et al. [8], who evaluated the impact of the COVID-19 pandemic on treat-to-target strategies and physical consultations in >7000 patients with inflammatory arthritis. They found that overall, PROs and remission rates remained stable despite the reduction in consultations in person. Furthermore, a study examining the effects of COVID-19 on care for those with JIA found no delays or significant differences in disease activity, disability or quality of life scores before and during the pandemic [9].
The PRO scores for mental, social and physical health were either stable or improved during the COVID-19 pandemic, with non-statistically significant improvements in HAQ-DI, HAQ-pain and sleep scores. Improvements in PROs might be explained by changes in patients’ lifestyles, such as being able to work from home. Other studies have found that the time of the pandemic resulted in different outcome measures. Gavigan et al. [10] found that the scores for mental health fluctuated widely depending on the month of the pandemic. They found that physical health assessment scores remained unchanged and that overall mental, social and physical health scores improved during the summer of 2021, when there was the widespread availability of vaccines. It is possible that patients experienced greater amounts of mental stress during periods with significant impacts on the health-care system, such as during lockdowns or periods of increasing incidence rates. However, the only mental health aspect that is included in our registry is the presence of depression, and we did not find any statistically significant changes in depression before and during the first year of the COVID-19 pandemic.
Some medication changes were statistically significant during the COVID-19 pandemic. Decreases in csDMARD use were accompanied by increases in JAK inhibitor use, and bDMARD usage before and during the pandemic remained high, although there was a noticeable decrease. Decreases in csDMARD and bDMARD use with increases in JAK inhibitor use might be explained by rheumatologists attempting to achieve disease control with an oral-based therapy instead of treatment modalities that require infusions at a clinic-based site when csDMARDs fail. Patient access to infusion centres was affected early during the pandemic. Furthermore, JAK inhibitors have been shown to be an effective treatment modality for severe COVID-19 infections [11]. Therefore, physicians might have perceived this class as safer for RA patients with active disease. These data represent the first half of the pandemic. Since then, there has been an important publication, the ORAL-Surveillance, a study showing the higher risk of cardiovascular diseases with JAK inhibitors in high-risk patients compared with biologics [12]. This information might have impacted the physicians’ therapy decisions in the second half of the pandemic.
It is essential to recognize that our work has several limitations. The study population focuses on patients with RA residing within Ontario, for which a specific strategy was undertaken with regard to lockdown and re-opening. This might not be representative of the approach that other countries globally took for the COVID-19 pandemic. The Premier of Ontario declared the first lockdown on 23 March 2020, forcing the closure of all non-essential businesses across the province for 14 days. This was followed by an extended period of using state-of-emergency measures until 15 July to facilitate a gradual reopening of the province. The reopening of regions across Ontario did not occur at the same time and was determined by the number of active/emerging cases in the area. Toronto, the largest city in Ontario, had one of the longest lockdown periods, with restrictions to services lasting >360 days. However, not all regions in Ontario had these constraints in place, and some areas had them removed sooner by comparison. Given the heterogeneity of each region having different reopening time lines, we did not explore the impact of this on the results. There is a risk of selection bias, because patients enrolled in OBRI who continued to attend in-person or interview assessments during the COVID-19 pandemic do not necessarily represent all patients with RA. These patients might be more willing to participate in their care and are more invested in their disease management. As a result, non-adherence to medical therapy increases disease activity, and PROs might be underestimated. Furthermore, given that this was an observational study, we were limited by missing data, particularly on disease activity measures owing to some patients being unable to attend appointments because of the pandemic. Moreover, our dataset did not include information on work status. During the COVID-19 pandemic in Ontario, the majority of individuals, except for essential workers, were working from home; therefore, we might not be able to evaluate the impact of work status on COVID-19 infections and disease outcomes.
The strengths of our study include having real-world patients, which enhances generalizability to cohorts with similar patient characteristics. We also examined several different disease activity indices and PROs and found similar results.
In conclusion, patients with RA during the first year of the COVID-19 pandemic either had no clinically significant change in their disease activity and PROs or performed slightly better in Ontario, Canada. Whether the impacts of the pandemic are increasing over time requires longer-term follow-up.
Supplementary Material
Acknowledgements
OBRI was funded by peer-reviewed grants from Canadian Institute for Health Research (CIHR), Ontario Ministry of Health and Long-Term Care (MOHLTC), Canadian Arthritis Network (CAN) and unrestricted grants from: Abbvie, Amgen, Celgene, Hospira, Janssen, Lilly, Merck, Novartis, Pfizer, Roche, Sanofi and UCB.
Contributor Information
Matthew Wong-Pack, Division of Rheumatology, University of Toronto, Toronto, ON, Canada.
Elliot Hepworth, Division of Rheumatology, University of Ottawa, Ottawa, ON, Canada.
Mohammad Movahedi, Toronto General Research Institute, University Health Network, Toronto, ON, Canada.
Bindee Kuriya, Division of Rheumatology, University of Toronto, Toronto, ON, Canada.
Janet Pope, Division of Rheumatology, University of Western Ontario, London, ON, Canada.
Edward Keystone, Department of Medicine, University of Toronto, Toronto, ON, Canada.
Carter Thorne, Centre of Arthritis Excellence, Newmarket, ON, Canada.
Vandana Ahluwalia, Division of Rheumatology, William Osler Health System, Brampton, ON, Canada.
Angela Cesta, Toronto General Research Institute, University Health Network, Toronto, ON, Canada.
Carol Mously, Toronto General Research Institute, University Health Network, Toronto, ON, Canada.
Claire Bombardier, Division of Rheumatology, University of Toronto, Toronto, ON, Canada.
Arthur Lau, Division of Rheumatology, McMaster University, Hamilton, ON, Canada.
Sibel Zehra Aydin, Division of Rheumatology, University of Ottawa, Ottawa, ON, Canada; The Ottawa Hospital Research Institute, Ottawa, ON, Canada.
Supplementary material
Supplementary material is available at Rheumatology Advances in Practice online.
Data availability
The data underlying this article will be shared on reasonable request to the corresponding author.
Funding
No specific funding was received from any funding bodies in the public, commercial or not-for-profit sectors to carry out the work described in this manuscript.
Disclosure statement: The authors have declared no conflicts of interest.
References
- 1. Nicola M, Alsafi Z, Sohrabi C. et al. The socio-economic implications of the coronavirus pandemic (COVID-19): a review. Int J Surg 2020;78:185–93. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2. Pfefferbaum B, North CS.. Mental health and the Covid-19 pandemic. N Engl J Med 2020;383:510–2. [DOI] [PubMed] [Google Scholar]
- 3. del Rio C, Collins LF, Malani P.. Long-term health consequences of COVID-19. JAMA 2020;324:1723–4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. Cutler DM, Summers LH.. The COVID-19 pandemic and the $16 trillion virus. JAMA 2020;324:1495–6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Grainger R, Kim AHJ, Conway R, Yazdany J, Robinson PC.. COVID-19 in people with rheumatic diseases: risks, outcomes, treatment considerations. Nat Rev Rheumatol 2022;18:191–204. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6. Picchianti Diamanti A, Cattaruzza MS, Di Rosa R. et al. Psychological distress in patients with autoimmune arthritis during the COVID-19 induced lockdown in Italy. Microorganisms 2020;8:1818. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Itaya T, Torii M, Hashimoto M. et al. Prevalence of anxiety and depression in patients with rheumatoid arthritis before and during the COVID-19 pandemic. Rheumatology 2021;60:2023–4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Glintborg B, Jensen DV, Terslev L. et al. Impact of the COVID-19 pandemic on treat-to-target strategies and physical consultations in >7000 patients with inflammatory arthritis. Rheumatology 2021;60:SI3–12. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Dushnicky MJ, Campbell C, Beattie KA. et al. ; for the CAPRI Registry Investigators. Impact of the COVID-19 pandemic on juvenile idiopathic arthritis presentation and research recruitment: results from the CAPRI registry. Rheumatology 2022;61:SI157–62. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Gavigan K, Rivera E, Curtis JR. et al. POS0088-pare changes in patient-reported outcome scores during COVID-19 pandemic: data from the ArthritisPower registry. Ann Rheum Dis 2022;81:265–6. [Google Scholar]
- 11. Kalil AC, Patterson TF, Mehta AK. et al. ; ACTT-2 Study Group Members. Baricitinib plus remdesivir for hospitalized adults with Covid-19. N Engl J Med 2021;384:795–807. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Ytterberg SR, Bhatt DL, Mikuls TR. et al. ; ORAL Surveillance Investigators. Cardiovascular and cancer risk with tofacitinib in rheumatoid arthritis. N Engl J Med 2022;386:316–26. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The data underlying this article will be shared on reasonable request to the corresponding author.