Serious Adverse Events in the Canadian Registry of Children Receiving Palivizumab (CARESS) for Respiratory Syncytial Virus Prevention
Bibliographic record
Abstract
OBJECTIVES: To evaluate the safety and tolerability of palivizumab for RSV prophylaxis in high-risk children in everyday practice. METHODS: High-risk children prophylaxed against RSV infection were recruited into a prospective, observational, Canadian RSV Evaluation Study of Palivizumab (CARESS) registry with active, serious adverse event (SAE) monitoring from 2008 to 2013. SAE reports were systematically collected and assessed for severity and relationship to palivizumab. Data were analyzed by Chi-square or Fisher Exact Tests to examine group differences in proportions. RESULTS: 13025 infants received 57392 injections. Hospitalizations for respiratory-related illness (RIH) were reported in 915 patients, and SAEs other than RIH were reported in 52 patients. Of these, 6 (0.05%) patients had a total of 14 hypersensitivity reactions that were deemed possibly or probably related to palivizumab (incidence: 2.8 per 10,000 patient-months). The SAEs of 42 patients were assessed as not related to palivizumab. SAEs in the remaining 4 patients were not classifiable as their records were incomplete. There were no significant demographic predictors of SAE occurrence. CONCLUSIONS: Under active surveillance, a small proportion of infants in the CARESS registry experienced SAEs that had a potential relationship with palivizumab and these appeared to be unpredictable in terms of onset. Palivizumab appears to be a safe and well-tolerated antibody for RSV prophylaxis in high-risk children in routine practice.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".