The implications of immunization in the daily practice of pediatric anesthesia
Bibliographic record
Abstract
PURPOSE OF REVIEW: Vaccination is an important prevention measure, but requires an intact immune system. Surgery and anesthesia suppress the immune system and may interfere with the benefits of immunization. Moreover, common vaccine side-effects may be misinterpreted as postsurgical complications. This review summarizes the essential basis of immunization and its potential interactions with anesthesia. RECENT FINDINGS: Vaccines have mild side-effects, such as fever, but may lead to serious complications in immunocompromised patients. Surgery and anesthesia may decrease the efficacy of a vaccine, or promote vaccine-related complications. It, therefore, reasonable to schedule surgery and anesthesia with a delay either before or after vaccine administration, but there is no consensus among anesthesiologists and pediatricians regarding this timing. SUMMARY: Inactive vaccines are generally well tolerated. Live vaccines provide an effective and long-lasting immunization, but may carry more serious complications. Elective operations should be postponed 1 week after an inactive vaccine and 3 weeks after immunization with a live vaccine. To avoid misinterpretation of vaccine-related side-effects, vaccination should be also delayed after surgery.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".