Investigating Factors Associated With Respiratory Syncytial Virus Vaccination and Breakthrough Infection Among Patients With Systemic Autoimmune Rheumatic Diseases
Bibliographic record
Abstract
OBJECTIVE: To investigate respiratory syncytial virus (RSV) vaccine uptake, associations, and breakthrough infection among patients with systemic autoimmune rheumatic diseases (SARDs). METHODS: We performed a retrospective cohort study investigating RSV vaccination among patients with SARDs at Mass General Brigham (Boston, Massachusetts, USA). We identified all patients with SARDs who were aged ≥ 60 years and thus eligible to receive the RSV vaccine between May 2023 and February 2025. We used multivariable logistic regression to identify factors associated with RSV vaccination. Among the vaccinated, we described documented cases of laboratory-confirmed breakthrough RSV infection. RESULTS: Among 10,587 patients with SARDs (median age 71.7 years, 72.4% female) eligible for RSV vaccination, 1075 (10.2%) received RSV vaccination. Factors associated with higher odds of RSV vaccination included higher median census-tract household income and comorbidities, such as cancer and interstitial lung disease. Associations with lower odds of RSV vaccination included Black race, lack of previous influenza or COVID-19 vaccinations, and glucocorticoid use. RSV vaccination was not associated with specific SARD types or disease-modifying antirheumatic drugs (DMARDs), including CD20 inhibitors. Among the 1075 who were vaccinated, there were 9 (0.8%) documented cases of RSV breakthrough infection (2 hospitalizations and no deaths). CONCLUSION: Only 10.2% of eligible patients with SARDs received RSV vaccination. Glucocorticoid users were less likely to receive RSV vaccination, whereas specific SARD types and DMARDs were not associated. Although some predictors of vaccine uptake were observed in this dataset, there are many unmeasured factors that may play a role in vaccine uptake. There were few documented breakthrough infections and no deaths. Future studies are needed to optimize RSV vaccine use and establish safety and efficacy in this vulnerable population.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".