Nationwide population‐based study showed that the rotavirus vaccination had no impact on the incidence of biliary atresia in Korea
Bibliographic record
Abstract
AIM: Rotaviruses have been associated with biliary atresia. This study investigated whether the rotavirus vaccine, which was introduced to Korea in 2008, had an impact on the incidence of biliary atresia. METHODS: We identified all rotavirus infections (n = 436 826) and biliary atresia cases (n = 528) diagnosed from 2006 to 2015 from insurance and health databases. The annual and seasonal incidence of biliary atresia and rotavirus infection rates in neonates and children were calculated. The difference in the risk of biliary atresia between rotavirus-infected and non-infected neonates was analysed. RESULTS: The incidence of rotavirus infections was 20.6 versus 13.4 per 1000 cases before (2006-2008) and after (2009-2015) vaccine implementation. However, neonatal rotavirus infection rates did not decrease, with an incidence of 14.5 versus 14.8 per 1000 cases before and after vaccination. The biliary atresia incidence remained constant at 12.0 per 100 000 cases. Rotavirus infections in neonates were a risk factor for biliary atresia (odds ratio 3.14, 95% confidence interval 1.87-5.26). CONCLUSION: Rotavirus vaccination had no impact on the incidence of biliary atresia, possibly because the vaccination did not change the neonatal rotavirus infection rate through herd immunity. However, rotavirus infections in neonates were significantly associated with biliary atresia.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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".