Brazilian recommendations on the safety and effectiveness of the yellow fever vaccination in patients with chronic immune-mediated inflammatory diseases
Bibliographic record
Abstract
BACKGROUND: In Brazil, we are facing an alarming epidemic scenario of Yellow fever (YF), which is reaching the most populous areas of the country in unvaccinated people. Vaccination is the only effective tool to prevent YF. In special situations, such as patients with chronic immune-mediated inflammatory diseases (CIMID), undergoing immunosuppressive therapy, as a higher risk of severe adverse events may occur, assessment of the risk-benefit ratio of the yellow fever vaccine (YFV) should be performed on an individual level. Faced with the scarcity of specific orientation on YFV for this special group of patients, the Brazilian Rheumatology Society (BRS) endorsed a project aiming the development of individualized YFV recommendations for patients with CIMID, guided by questions addressed by both medical professionals and patients, followed an internationally validated methodology (GIN-McMaster Guideline Development). Firstly, a systematic review was carried out and an expert panel formed to take part of the decision process, comprising BRS clinical practitioners, as well as individuals from the Brazilian Dermatology Society (BDS), Brazilian Inflammatory Bowel Diseases Study Group (GEDIIB), and specialists on infectious diseases and vaccination (from Tropical Medicine, Infectious Diseases and Immunizations National Societies); in addition, two representatives of patient groups were included as members of the panel. When the quality of the evidence was low or there was a lack of evidence to determine the recommendations, the decisions were based on the expert opinion panel and a Delphi approach was performed. A recommendation was accepted upon achieving ≥80% agreement among the panel, including the patient representatives. As a result, eight recommendations were developed regarding the safety of YFV in patients with CIMID, considering the immunosuppression degree conferred by the treatment used. It was not possible to establish recommendations on the effectiveness of YFV in these patients as there is no consistent evidence to support these recommendations. CONCLUSION: This paper approaches a real need, assessed by clinicians and patient care groups, to address specific questions on the management of YFV in patients with CIMID living or traveling to YF endemic areas, involving specialists from many areas together with patients, and might have global applicability, contributing to and supporting vaccination practices. We recommended a shared decision-making approach on taking or not the YFV.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".