Effects of the COVID‐19 Pandemic on Patients Living With Vasculitis
Bibliographic record
Abstract
This study aimed to analyze the concerns and health‐related behaviors in patients with vasculitis during the early phase of the coronavirus disease 2019 (COVID‐19) pandemic in North America. Patients with vasculitis in North America were invited to complete an online survey through the Vasculitis Patient‐Powered Research Network in collaboration with the Vasculitis Foundation and the Relapsing Polychondritis Foundation. Questions focused on concerns and behaviors related to doctors’ visits, tests, medication, and telehealth use. Factors affecting their concern and health‐related behaviors were determined. Data from 662 patients were included: 90% of patients were White, 78% were women, 83% expressed moderate or high levels of concern about COVID‐19, and 87% reported that their vasculitis moderately or extremely affected their level of concern. Older age, female sex, lung disease, and immunosuppression were associated with greater concern. Doctors’ visits, laboratory tests, and other tests were avoided by 66%, 46%, and 40% of patients, respectively. Younger age, urban location, higher income, higher concern levels, and prednisone use (>10 mg/day) were associated with greater likelihood of avoiding visits or tests. Ten percent of patients on immunosuppressive therapy stopped their medication. Twenty‐nine percent patients on rituximab avoided an infusion. Forty‐four percent of patients had telehealth visits; more visits were reported for younger patients, for patients on glucocorticoids, and in Canada versus the United States. During the COVID‐19 pandemic, patients with vasculitis have high levels of concern and exhibit potentially harmful health‐related behaviors. Health care use varies across different demographic groups and geographic regions. Specific strategies are warranted to facilitate engagement of these patients with the health care system during the pandemic.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".