Serious Adverse Events Associated with Bacille Calmette-Guérin Vaccine in Canada
Bibliographic record
Abstract
BACKGROUND: Targeted Bacille Calmette-Guérin (BCG) vaccination is offered to neonates in some First Nations and Inuit (FNI) communities in Canada. Serious adverse events associated with BCG vaccine prompted a review to assess causality. METHODS: The Immunization Monitoring Program Active (IMPACT), a pediatric hospital-based active surveillance network, reported admissions for BCG-related adverse events between 1993 and April 2002. The Canadian Advisory Committee on Causality Assessment (ACCA) reviewed the reports to assess causality. Data between 1987 and September 2002 from the Vaccine-Associated Adverse Event Surveillance (VAAES) Program, a passive national reporting system, were also reviewed. RESULTS: IMPACT identified 21 pediatric cases; 19 were Canadian-born, and 18 were FNI. Six disseminated BCG cases were identified; 5 were FNI infants who subsequently died. All had immunodeficiencies and concurrent infections. Other adverse events included 2 cases of osteomyelitis, BCG abscesses and lymphadenitis. ACCA reviewed the 21 cases and determined that 14 were very likely associated with the vaccine, including the 6 disseminated BCGs; 5 were probably associated and 1 was possibly associated with the vaccine; 1 was unclassifiable. The VAAES program identified 157 adverse events. No additional serious systemic adverse events (disseminated BCG or osteomyelitis) were identified. CONCLUSIONS: Serious BCG vaccine-associated complications continue to occur in Canada. The numbers of FNI children with disseminated disease was greater than expected from reported rates in the literature.
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 | 0.005 |
| 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 | 0.000 | 0.000 |
| 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".