Effects of the COVID-19 Pandemic in Patients with Systemic Autoinflammatory Diseases. An international survey
Bibliographic record
Abstract
Background: Early in the COVID-19 pandemic it was recognized that individuals who had worse prognoses had hyperinflammatory reactions associated with SARS CoV-2. This was worrisome for patients with systemic autoinflammatory diseases (SAID) who already have episodic hyperinflammation at baseline. Aim: To assess the effects of the COVID-19 pandemic and SARS CoV-2 infection on patients with SAID. Methods: An anonymous survey developed on the Survey Monkey platform was distributed online through social media and support groups of patients with SAID between January 20th and May 17th of 2021. Results: We analyzed 484 surveys that conveyed data from 593 patients with SAID. Seventy-four percent of the surveys were answered in the United States, US territories, and Canada (n=360/484) and the rest from other countries. Sixty percent (n=330/547) of patients with SAID did not experience changes in the frequency of flares during the first year of the pandemic. Ten percent (n=52/545) of patients had presumed or confirmed COVID-19. Of those, 81% (n=42/52) had mild and moderate symptoms and 4 were hospitalized. Thirty-one percent (n=16/52) experienced flares during or after the infection and 40% (n=21/52) reported post-COVID manifestations. The individuals who had moderate symptoms or were hospitalized for COVID-19 were more likely to report post-COVID manifestations, OR 5.25 (95%CI 1.57-17.6, p=0.0072). Post-COVID integumentary manifestations occurred after asymptomatic and mild COVID-19 whereas neurologic manifestations occurred after acute COVID-19 with moderate symptoms or requiring hospitalization. Conclusion: During the COVID-19 pandemic, over half of patients with SAID did not experience changes in the frequency of flares despite a decreased exposure to environmental triggers. Few individuals with SAID required hospitalization for COVID-19. The presence and type of post-COVID manifestations were associated with the severity of acute COVID-19 in patients with SAID.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".