Bacillus Calmette‐Guérin (<scp>BCG</scp>) Vaccination in Infancy and Risk of Childhood Diabetes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: A narrow time window in infancy may be relevant for the aetiology of immune-mediated type 1 diabetes. We investigated whether a non-specific immune stimulation in the first year of life, as resulting from Bacillus Calmette-Guérin (BCG) vaccination, was associated with childhood diabetes. METHODS: Using data from a birth cohort assembled through linkage of administrative databases, 78,492 subjects born in 1974 were the object of the present analysis. Information was extracted from the birth, death, and BCG vaccination registries. Diabetes-related health services were obtained from administrative health databases (physician billing claims and hospitalisation data) until 1994. Subjects were classified as having diabetes according to two validated definitions: (1) ≥2 diabetes-related medical visits within 2 years or ≥1 hospitalisation for diabetes; and 2) ≥4 diabetes-related medical visits within 2 years. Cox proportional hazards regression was used to estimate adjusted hazard ratios (HR) and 95% confidence interval (CI), adjusted for potential confounders. RESULTS: Forty-four per cent of subjects were BCG vaccinated in the first year of life. According to the first and second definition, respectively, 293 (0.37%) and 230 (0.29%) subjects were classified as having diabetes. There was no association between BCG vaccination in the first year of life and risk of diabetes with either definition (HR(def1) = 0.92, 95% CI 0.73, 1.17; HR(def2) = 1.04, 95% CI 0.80, 1.37), and results did not differ by sex. CONCLUSIONS: Given the potentially critical importance of the exposure window and paucity of studies addressing BCG vaccination timing in relation to diabetes risk, this question deserves further investigation.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it