Influenza vaccine strategies for solid organ transplant recipients
Bibliographic record
Abstract
PURPOSE OF REVIEW: The aim of this study was to highlight recent evidence on important aspects of influenza vaccination in solid organ transplant recipients. RECENT FINDINGS: Influenza vaccine is the most evaluated vaccine in transplant recipients. The immunogenicity of the vaccine is suboptimal after transplantation. Newer formulations such as inactivated unadjuvanted high-dose influenza vaccine and the administration of a booster dose within the same season have shown to increase response rates. Intradermal vaccination and adjuvanted vaccines did not show clear benefit over standard influenza vaccines. Recent studies in transplant recipients do not suggest a higher risk for allograft rejection, neither after vaccination with a standard influenza vaccine nor after the administration of nonstandard formulation (high-dose, adjuvanted vaccines), routes (intradermally) or a booster dose. Nevertheless, influenza vaccine coverage in transplant recipients is still unsatisfactory low, potentially due to misinterpretation of risks and benefits. SUMMARY: Annual influenza vaccination is well tolerated and is an important part of long-term care of solid organ transplant recipients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".