COVID-19 Vaccine Uptake Among Patients With Systemic Lupus Erythematosus in the American Midwest: The Lupus Midwest Network (LUMEN)
Bibliographic record
Abstract
OBJECTIVE: Patients with systemic lupus erythematosus (SLE) are at higher risk of poor outcomes from coronavirus disease 2019 (COVID-19). The vaccination rate among such patients is unknown. We aimed to assess COVID-19 vaccine uptake among patients with SLE. METHODS: We included 342 patients with SLE from the Lupus Midwest Network (LUMEN) and 350 age-, sex-, race-, and county-matched comparators. Vaccination uptake for influenza, pneumococcal, and zoster vaccines before pandemic restrictions began (up to February 29, 2020) was assessed. First-dose COVID-19 vaccine uptake was electronically retrieved and manually ascertained (December 15, 2020, to July 31, 2021). Time to COVID-19 vaccination, demographics, SLE manifestations, medications, Charlson Comorbidity Index, Area Deprivation Index, and Rural-Urban Commuting Area codes were compared. RESULTS: On July 31, 2021, 83.3% of patients with SLE and 85.5% of comparators were vaccinated against COVID-19. The COVID-19 vaccination rates were similar among SLE and comparators (hazard ratio 0.93, 95% CI 0.79-1.10). Unvaccinated patients with SLE were more likely than vaccinated patients to be men (27.3% vs 14.1%), younger (mean age 54.1 vs 58.8 yrs), have a shorter SLE duration (median 7.3 vs 10.7 yrs), and be less frequently vaccinated with influenza and pneumococcal vaccines. CONCLUSION: Patients with SLE in the Lupus Midwest Network had similar COVID-19 vaccination uptake as matched comparators, most of whom were vaccinated early when the vaccine became available. One in 6 patients with SLE remain unvaccinated.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".