Flares in IIMs and the timeline following COVID-19 vaccination: a combined analysis of the COVAD-1 and -2 surveys

Objectives: Disease flares in the post-coronavirus disease 2019 (COVID-19) vaccination period represent a prominent concern, though risk factors are poorly understood. We studied these flares among patients with idiopathic inflammatory myopathies (IIMs) and other autoimmune rheumatic diseases (AIRDs). Methods: The COVAD-1 and -2 global surveys were circulated in early 2021 and 2022, respectively, and we captured demographics, comorbidities, AIRDs details, COVID-19 infection history and vaccination details. Flares of IIMs were defined as (a) patient self-reported, (b) immunosuppression (IS) denoted, (c) clinical sign directed and (d) with >7.9-point minimal clinically significant improvement difference worsening of Patient-Reported Outcomes Measurement Information System (PROMIS) PROMISPF10a score. Risk factors of flares were analysed using regression models. Results: Of 15 165 total respondents, 1278 IIMs (age 63 years, 70.3% female, 80.8% Caucasians) and 3453 AIRDs were included. Flares of IIM were seen in 9.6%, 12.7%, 8.7% and 19.6% patients by definitions (a) to (d), respectively, with a median time to flare of 71.5 (10.7-235) days, similar to AIRDs. Patients with active IIMs pre-vaccination (OR 1.2; 95% CI 1.03, 1.6, P = 0.025) were prone to flares, while those receiving rituximab (OR 0.3; 95% CI 0.1, 0.7, P = 0.010) and AZA (OR 0.3, 95% CI 0.1, 0.8, P = 0.016) were at lower risk. Female gender and comorbidities predisposed to flares requiring changes in IS. Asthma (OR 1.62; 95% CI 1.05, 2.50, P = 0.028) and higher pain visual analogue score (OR 1.19; 95% CI 1.11, 1.27, P < 0.001) were associated with disparity between self-reported and IS-denoted flares. Conclusion: A diagnosis of IIMs confers an equal risk of flares in the post-COVID-19 vaccination period to AIRDs, with active disease, female gender and comorbidities conferring a higher risk. Disparity between patient- and physician-reported outcomes represents a future avenue for exploration

Vaccine hesitancy decreases in rheumatic diseases, long-term concerns remain in myositis: A comparative analysis of the COVAD surveys

Objective: COVID-19 vaccines have a favorable safety profile in patients with autoimmune rheumatic diseases (AIRDs) such as idiopathic inflammatory myopathies (IIMs); however, hesitancy continues to persist among these patients. Therefore, we studied the prevalence, predictors and reasons for hesitancy in patients with IIMs, other AIRDs, non-rheumatic autoimmune diseases (nrAIDs) and healthy controls (HCs), using data from the two international COVID-19 Vaccination in Autoimmune Diseases (COVAD) e-surveys. Methods: The first and second COVAD patient self-reported e-surveys were circulated from March to December 2021, and February to June 2022 (ongoing). We collected data on demographics, comorbidities, COVID-19 infection and vaccination history, reasons for hesitancy, and patient reported outcomes. Predictors of hesitancy were analysed using regression models in different groups. Results: We analysed data from 18 882 (COVAD-1) and 7666 (COVAD-2) respondents. Reassuringly, hesitancy decreased from 2021 (16.5%) to 2022 (5.1%) (OR: 0.26; 95% CI: 0.24, 0.30, P < 0.001). However, concerns/fear over long-term safety had increased (OR: 3.6; 95% CI: 2.9, 4.6, P < 0.01). We noted with concern greater skepticism over vaccine science among patients with IIMs than AIRDs (OR: 1.8; 95% CI: 1.08, 3.2, P = 0.023) and HCs (OR: 4; 95% CI: 1.9, 8.1, P < 0.001), as well as more long-term safety concerns/fear (IIMs vs AIRDs - OR: 1.9; 95% CI: 1.2, 2.9, P = 0.001; IIMs vs HCs - OR: 5.4 95% CI: 3, 9.6, P < 0.001). Caucasians [OR 4.2 (1.7-10.3)] were likely to be more hesitant, while those with better PROMIS physical health score were less hesitant [OR 0.9 (0.8-0.97)]. Conclusion: Vaccine hesitancy has decreased from 2021 to 2022, long-term safety concerns remain among patients with IIMs, particularly in Caucasians and those with poor physical function

A 12-year prospective study of stroke risk in older Medicare beneficiaries

<p>Abstract</p> <p>Background</p> <p>5.8 M living Americans have experienced a stroke at some time in their lives, 780K had either their first or a recurrent stroke this year, and 150K died from strokes this year. Stroke costs about $66B annually in the US, and also results in serious, long-term disability. Therefore, it is prudent to identify all possible risk factors and their effects so that appropriate intervention points may be targeted.</p> <p>Methods</p> <p>Baseline (1993–1994) interview data from the nationally representative Survey on Assets and Health Dynamics among the Oldest Old (AHEAD) were linked to 1993–2005 Medicare claims. Participants were 5,511 self-respondents ≥ 70 years old. Two ICD9-CM case-identification approaches were used. Two approaches to stroke case-identification based on ICD9-CM codes were used, one emphasized sensitivity and the other emphasized specificity. Participants were censored at death or enrollment into managed Medicare. Baseline risk factors included sociodemographic, socioeconomic, place of residence, health behavior, disease history, and functional and cognitive status measures. A time-dependent marker reflecting post-baseline non-stroke hospitalizations was included to reflect health shocks, and sensitivity analyses were conducted to identify its peak effect. Competing risk, proportional hazards regression was used.</p> <p>Results</p> <p>Post-baseline strokes occurred for 545 (9.9%; high sensitivity approach) and 374 (6.8%; high specificity approach) participants. The greatest static risks involved increased age, being widowed or never married, living in multi-story buildings, reporting a baseline history of diabetes, hypertension, or stroke, and reporting difficulty picking up a dime, refusing to answer the delayed word recall test, or having poor cognition. Risks were similar for both case-identification approaches and for recurrent and first-ever vs. only first-ever strokes. The time-dependent health shock (recent hospitalization) marker did not alter the static model effect estimates, but increased stroke risk by 200% or more.</p> <p>Conclusion</p> <p>The effect of our health shock marker (a time-dependent recent hospitalization indicator) was large and did not mediate the effects of the traditional risk factors. This suggests an especially vulnerable post-hospital transition period from adverse effects associated with both their underlying health shock (the reasons for the recent hospital admission) and the consequences of their treatments.</p