BCG Moreau Vaccine Safety Profile and NK Cells—Double Protection Against Disseminated BCG Infection in Retrospective Study of BCG Vaccination in 52 Polish Children with Severe Combined Immunodeficiency
Bibliographic record
Abstract
OBJECTIVES: The aim of the study was to estimate the rate of adverse reactions to live BCG Moreau vaccine, manufactured by Biomed in Poland, in severe combined immunodeficiency (SCID) patients. MATERIAL: The profiles of 52 SCID patients vaccinated at birth with BCG, hospitalized in Children's Memorial Health Institute, Warsaw (CMHI), in the years 1980-2015 were compared with those of 349 BCG-vaccinated SCID patients from other countries analyzed by Beatriz E. Marciano et al. in a retrospective study (Marciano et al. J Allergy Clin Immunol. 2014;133(4):1134-1141). RESULTS: Significantly less disseminated BCG infections (10 out of 52 SCID, 19%) occurred in comparison with Marciano study-119 out of 349, 34% (p = 0.0028), with no death in patients treated with SCID anti-TB drug, except one in lethal condition. In our study, disseminated BCG infection was observed only in SCID with T-B+NK- phenotype and significantly lower NK cell counts (p = 0.0161). NK cells do not influence on the frequency of local BCG reaction. A significantly higher number of hematopoietic stem cells transplantations (HSCT) were performed in CMHI study (p = 0.0001). Anti-TB treatment with at least two medicines was provided. CONCLUSION: The BCG Moreau vaccine produced in Poland, with well-documented genetic characteristics, seems to be safer than other BCG substrains used in other regions of the world. Importantly, NK cells seem to play a role in protecting SCID patients against disseminated BCG complications, which NK- SCID patients are more prone to. HSCT and TB therapy could be relevant due to the patients' survival and the fact that they protect against BCG infection.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".