Immunogenicity and Safety of an Intradermal Boosting Strategy for Vaccination Against Influenza in Lung Transplant Recipients
Bibliographic record
Abstract
The immunogenicity of influenza vaccine is suboptimal in lung transplant recipients. Use of a booster dose and vaccine delivery by the intradermal rather than intramuscular route may improve response. We prospectively evaluated the immunogenicity and safety of a 2-dose boosting strategy of influenza vaccine. Sixty lung transplant recipients received a standard intramuscular injection of the 2006-2007 inactivated influenza vaccine, followed 4 weeks later by an intradermal booster of the same vaccine. Immunogenicity was assessed by measurement of geometric mean titer of antibodies after both the intramuscular injection and the intradermal booster. Vaccine response was defined as 4-fold or higher increase of antibody titers to at least one vaccine antigen. Thirty-eight out of 60 patients (63%) had a response after intramuscular vaccination. Geometric mean titers increased for all three vaccine antigens following the first dose (p < 0.001). However, no significant increases in titer were observed after the booster dose for all three antigens. Among nonresponders, 3/22 (13.6%) additional patients responded after the intradermal booster (p = 0.14). The use of basiliximab was associated with a positive response (p = 0.024). After a single standard dose of influenza vaccine, a booster dose given by intradermal injection did not significantly improve vaccine immunogenicity in lung transplant recipients.
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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 | 0.001 |
| 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) | 0.000 | 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 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".