Neonatal Vitamin K Refusal and Nonimmunization
Bibliographic record
Abstract
BACKGROUND: Neonatal Vitamin K prophylaxis is an effective intervention for reducing vitamin K deficiency bleeding. A recently published report of parental refusal of vitamin K prompted an investigation of the prevalence and characteristics of this group, and exploration of whether these same parents were likely to subsequently refuse immunization for their children. METHODS: We conducted a retrospective population-based cohort study of all infants born in Alberta between 2006 and 2012 by using linkage of administrative health data. Risk factors for vitamin K refusal were determined by using Poisson regression. The association between vitamin K refusal and nonimmunization was assessed using relative risk. RESULTS: Among the 282378 children in the cohort, 99.7% received vitamin K and 0.3% declined. Midwife-assisted deliveries were more likely to be associated with vitamin K refusal compared with physician-attended delivery (risk ratio 8.4, 95% confidence interval [CI] 6.5-11.0). Planned home delivery (risk ratio 4.9, CI 3.8-6.4) or delivery in a birth center (risk ratio 3.6, CI 2.3-5.6) were more likely to result in decline of vitamin K compared with hospital delivery. Vitamin K refusal was associated with a 14.6 (CI 13.9-15.3) higher relative risk of having no recommended childhood vaccines at 15 months. CONCLUSIONS: This is the first population-based study to characterize parents who are likely to decline vitamin K for their infants and whose children are likely to be unimmunized. These findings enable earlier identification of high-risk parents and provide an opportunity to enact strategies to increase uptake of vitamin K and childhood immunizations.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".