Prevention of respiratory syncytial virus infections in high‐risk infantsby monoclonal antibody (palivizumab)
Bibliographic record
Abstract
Respiratory syncytial virus (RSV) is a major viral pathogen which causes serious respiratory illness in infants and children worldwide. Palivizumab (Synagis) is an anti-RSV monoclonal antibody administered intramuscularly for the prevention of severe RSV respiratory disease in high-risk infants and young children. The IMpact-RSV trial, the pivotal multicenter, randomized, placebo-controlled trial performed in the USA, Canada and the United Kingdom demonstrated an overall 55% reduction in hospitalization rate due to RSV infection in preterm infants (< or = 35 weeks gestation) with and without chronic lung disease (CLD). Subgroup analysis in premature infants without CLD revealed an even greater reduction in RSV hospitalization rates (78%). Adverse events were infrequent and did not differ between placebo and palivizumab groups. Injection site reactions were infrequent and mild; no differences were observed between palivizumab and placebo subjects. Palivizumab does not interfere with administration of other pediatric vaccines. Comprehensive parent education programs regarding prevention of infection, avoidance of risk factors for infection, careful adherence to infection control policies, and recognition of early symptoms of RSV infection remain important components of RSV prevention strategies. In light of the lack of effective vaccines for this serious health risk, palivizumab offers the only option for prophylaxis against RSV disease in high-risk infants.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".