P-1284. Impact of Timing of Measles Vaccine Doses on IgG Levels
Bibliographic record
Abstract
Abstract Background Although measles was eliminated from Canada, recent outbreaks worldwide are increasing the risk of importation with local transmission. Healthcare workers (HCWs) are known to be at higher risk of measles, compared to the general population. Recent measles breakthrough infection in immune individuals have raised several questions about levels of immunity. We examined the proportion of HCWs who were considered seropositive for measles and evaluated factors associated with lower IgG levels. Methods Measles IgG were measured in a convenient sample of HCWs from the Centre hospitalier universitaire Sainte-Justine (CHUSJ), a tertiary-care hospital, located in Montreal, Canada, in the context of an outbreak and the need to rapidly assess our workforce protection. Data from the Occupational Health clinic was used (age, vaccination history, sex). Sera were tested using LIAISON® Measles IgG (Diasorin) for quantitative measurement of measles-specific IgG. IgG levels > 16.5 IU/L were considered protective. Data were compared using the Welch’s t-test on Microsoft Excel. Results A total of 114 HCWs were tested. Of the 42 individuals born before 1970 without vaccination, 92.9% were considered protected with a mean IgG level of 239.07 IU/L (SD - 103). A total of 45 HCWs were born in 1970 or thereafter; of those 32 received two doses of vaccine, with a first dose received between 12 and 15 months of age. HCWs (n = 8) who received their second dose between 17 and up to 21 months of age had mean IgG titers of 71.38 IU/L (SD - 104). In comparison, the 24 HCWs who received their second dose after 21 months of age, at a mean age of 142.43 months (range [28,393]), had a mean IgG level of 177.12 IU/L (p = 0.03). Conclusion These results suggest that the second dose of measles vaccine administered at a later age is associated with a higher IgG level. The clinical impact of these higher IgG levels remains to be explored. Disclosures All Authors: No reported disclosures
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".