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Record W3153621454 · doi:10.1093/infdis/jiab220

Immediate Bacille Calmette-Guérin Vaccination to Neonates Requiring Perinatal Treatment at the Maternity Ward in Guinea-Bissau: A Randomized Controlled Trial

2021· article· en· W3153621454 on OpenAlexaff
Frederik Schaltz‐Buchholzer, Peter Aaby, Ivan Monteiro, Luis Camala, Simone Faurholt Simonsen, Hannah Nørtoft Frankel, Kristina Lindberg Larsen, Christian N Golding, Tobias R. Kollmann, Nelly Amenyogbe, Christine Stabell Benn, Morten Bjerregaard-Andersen

Bibliographic record

VenueThe Journal of Infectious Diseases · 2021
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune responses and vaccinations
Canadian institutionsUniversity of British Columbia
FundersEuropean and Developing Countries Clinical Trials PartnershipFonden til Lægevidenskabens FremmeNovo Nordisk FondenNovo NordiskEuropean Research CouncilSyddansk UniversitetKaren Elise Jensens FondCentre National d’Etudes SpatialesDanmarks GrundforskningsfondNational Research Foundation
KeywordsMedicineVaccinationRandomized controlled trialPediatricsObstetricsSurgeryImmunology

Abstract

fetched live from OpenAlex

BACKGROUND: Randomized controlled trials (RCTs) indicate that bacille Calmette-Guérin (BCG) vaccination provides broad beneficial "nonspecific" protection against infections. We investigated the effect on in-hospital mortality of providing BCG immediately upon admission to a neonatal intensive care unit (NICU), rather than BCG-at-discharge. The pretrial NICU mortality was 13% and we hypothesized that BCG would reduce mortality by 40%. METHODS: Parallel-group, open-label RCT was initiated in 2013 in Guinea-Bissau. Neonatal intensive care unit-admitted neonates were randomized 1:1 to BCG + oral polio vaccine (OPV) immediately (intervention) versus BCG + OPV at hospital discharge (control; usual practice). The trial was discontinued due to decreasing in-hospital mortality and major NICU restructuring. We assessed overall and disease-specific mortality by randomization allocation in cox proportional hazards models providing mortality rate ratios (MRRs). RESULTS: We recruited 3353 neonates, and the overall mortality was 3.1% (52 of 1676) for BCG-vaccinated neonates versus 3.3% (55 of 1677) for controls (MRR = 0.94; 0.64-1.36). For noninfectious causes of death, the MRR was 1.20 (0.70-2.07), and there tended to be fewer deaths from infections in the BCG group (N = 14) than among controls (N = 21) (MRR = 0.65; 0.33-1.28). CONCLUSIONS: Providing BCG + OPV to frail neonates was safe and might protect against fatal infection in the immediate newborn period. Deaths due to prematurity and perinatal complications were unaffected by BCG.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Randomized triallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Randomized trialhigh
models agreeAgreement compares identical category sets and study designs across arms.

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0060.000

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.

Opus teacher head0.009
GPT teacher head0.266
Teacher spread0.257 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations20
Published2021
Admission routes1
Has abstractyes

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