The Herpes Zoster Vaccine in Rheumatic Diseases: Duration of Response
Bibliographic record
Abstract
Shingles is painful. Anyone who has experienced shingles will tell you that in no uncertain terms. By now, we are quite aware of the increased risk of herpes zoster (HZ) in patients with autoimmune diseases due to immunosuppressive medication use or from immune dysregulation from the underlying disease. Unfortunately the very same risks for HZ reactivation are precisely those that raise concern for theoretical risks of contracting vaccine-strain varicella infection from the live-attenuated HZ vaccine (Zostavax, Merck); and this has resulted in undervaccination of many people with rheumatic diseases who would otherwise be eligible for vaccination. Until recombinant varicella vaccines become commercially available, the live-attenuated vaccine is the only protective measure available for our patients. While it is easy to provide arguments for increased vaccination of patients with rheumatic disease in whom levels of immunosuppression are mild to moderate (with tofacitinib being a notable contraindication1), it is also time to focus on the available data for safety, efficacy, and duration of protection provided by the HZ vaccine when given to patients who may have blunted responses because of underlying autoimmune diseases and/or chronic … Address correspondence to Dr. E.F. Chakravarty, Associate Member, Arthritis and Clinical Immunology, Oklahoma Medical Research Foundation, 825 NE 13th St., Oklahoma City, Oklahoma 73104, USA. E-mail: chakravartye{at}omrf.org
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".