Ethical and policy considerations for COVID-19 vaccination modalities: delayed second dose, fractional dose, mixed vaccines
Bibliographic record
Abstract
Background To investigate whether neonatal hyperglycaemia in the first postnatal week is associated with treatment-demanding retinopathy of prematurity (ROP). Methods This is a Danish national, retrospective, case–control study of premature infants (birth period 2003–2006). Three national registers were searched, and data were linked through a unique civil registration number. The study sample consisted of 106 cases each matched with two comparison infants. Matching criteria were gestational age (GA) at birth, ROP not registered and born at the same neonatal intensive care unit. Potential ‘new’ risk factors were analysed in a multivariate logistic regression model, while adjusted for previously recognised risk factors (ie, GA at birth, small for gestational age, multiple birth and male sex). Results Hospital records of 310 preterm infants (106 treated; 204 comparison infants) were available. Nutrition in terms of energy (kcal/kg/week) and protein (g/kg/week) given to the preterm infants during the first postnatal week were statistically insignificant between the study groups (Mann-Whitney U test; p=0.165/p=0.163). Early postnatal weight gain between the two study groups was borderline significant (t-test; p=0.047). Hyperglycaemic events (indexed value) were statistically significantly different between the two study groups (Mann-Whitney U test; p<0.001). Hyperglycaemia was a statistically independent risk factor (OR: 1.022; 95% CI 1.002 to 1.042; p=0.031). Conclusion An independent association was found between the occurrence of hyperglycaemic events during the first postnatal week and later development of treatment-demanding ROP, when adjusted for known risk factors.
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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 | 0.163 | 0.204 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.018 | 0.012 |
| Insufficient payload (model declined to judge) | 0.031 | 0.010 |
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".