Rubella virus vaccine associated arthropathy in postpartum immunized women: influence of preimmunization serologic status on development of joint manifestations.
Bibliographic record
Abstract
OBJECTIVE: To measure preimmunization rubella virus (RV)-specific IgG levels and to relate these to the development of acute and chronic (persistent or recurrent) joint manifestations following rubella vaccination. METHODS: Specific IgG was determined by whole RV enzyme immunoassays (EIA) (Abbott Rubazyme and M33, an in-house method), immunoblot, neutralization domain peptide (BCH-178c) EIA, and neutralization bioassay in prevaccine samples of 268 RV seronegative women (Abbott absorbance < 0.999 units) who had received monovalent live attenuated RA27/3 strain RV vaccine in a clinical trial that recorded joint manifestations. RESULTS: Of rubella vaccinated women tested for prevaccine antibodies, 21.7% were actually positive (> or = 10 IU/ml) by M33 EIA, 33.2% had Abbott values > or = 0.250 units, and 47.6% had RV protein-specific antibody (immunoblot), while only 17.6% were positive (> or = 10 IU/ml) by neutralization domain peptide EIA and 12.7% had neutralization titers > or = 1:8. Seropositivity by the various methods was compared to recorded occurrence of acute and chronic arthropathy (arthralgia and/or arthritis) after RV vaccination. Relative to women who had no joint manifestations, prevaccine seropositivity rates for subjects with acute arthropathy were significantly (p < 0.05) lower in the Abbott test (< 0.250 units), BCH-178c peptide EIA, and neutralization bioassay, while those who also developed chronic arthropathy had significantly lower prevaccine seropositivity rates for the Abbott (< 0.250 units) and M33 EIA and neutralization bioassay. CONCLUSION: Results suggest that risk for arthropathy following RA27/3 rubella vaccination may be higher in women who have very low prevaccine levels of antibody, particularly in assays measuring functional (neutralizing) antibodies.
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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 | 0.000 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".