Hypothyroidism in neonates post‐iodinated contrast media: a systematic review
Bibliographic record
Abstract
AIM: To determine if neonates exposed to iodinated contrast media are at risk of hypothyroidism. METHODS: A systematic review was conducted by searching electronic databases (e.g. MEDLINE), contacting experts and scanning reference lists. Studies examining the effects of contrast media on neonatal thyroid function were included. Two reviewers independently screened the literature and assessed the risk of bias, while one reviewer abstracted data. RESULTS: Eleven studies were included; nine studies directly examined the risk of hypothyroidism (n = 182 neonates exposed to contrast media). All were highly affected by bias. In the three studies including term infants, one showed a trend towards increased thyroid-stimulating hormone (TSH) and decreased free thyroxine (FT4) among exposed groups. Six of 72 (8.3%) term infants exposed were treated for hypothyroidism. In studies of premature infants, there was a trend towards increased TSH (n = 3/7 studies), lower total thyroxine (n = 1), decreased triidothyronine and FT4 (n = 3) and hypothyroidism (n = 5). Twenty of 110 (18.2%) premature infants exposed were treated for hypothyroidism. CONCLUSION: Hospitalized neonates exposed to iodinated contrast media are at risk for abnormal thyroid function and development of hypothyroidism. Premature infants might be at increased risk. Well-controlled studies are required to replicate our findings because the included studies were highly affected by bias.
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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 | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".