Gadolinium in pediatric cardiovascular magnetic resonance: what we know and how we practice
Bibliographic record
Abstract
BACKGROUND: The association of gadolinium-based contrast agents (GBCAs) with nephrogenic systemic fibrosis (NSF) has led to a heightened awareness towards patients' renal function. Whereas detailed guidelines exist for the use of GBCAs in adult patients, best practice is less well defined in children, especially in the very young. We aimed at identifying current practice with regards to the use of GBCAs in children who undergo cardiovascular magnetic resonance. METHODS: We conducted a worldwide survey among cardiac imagers with pediatric expertise. The questionnaire contained 21 questions covering the imagers' work environments, GBCAs used, monitoring of renal function, and a special emphasis was placed on the practice in neonates. RESULTS: The survey yielded 70 replies. The single most commonly used GBCA was gadopentetate dimeglumine 34/70 (49%). Among the respondents, the choice of GBCA was more importantly based on availability 26/70 (37%) and approval by a pharmaceutical licensing body that most closely reflects the indication 16/70 (23%) than image quality 7/70 (10%) and side effect profile 8/70 (11%). 55/70 (79%) of respondents performed scans in neonates <1 week of age and 52/55 (95%) of them used GBCA in neonates. 65/70 (93%) respondents at least assess some of their patients' renal functions. Formula-based estimate of glomerular filtration rate is the most popular assessment method 35/65 (54%). In patients with a glomerular filtration rate < 30 ml/min/1.73 m(2) 62/70 (89%) of respondents do not administer gadolinium at all. The single most common side effect of gadolinium was noted to be nausea/emesis 34/57 (60%) followed by discomfort at injection site 17/57 (30%). CONCLUSIONS: Cardiac imagers are aware of the immature renal function and physiological differences of their pediatric patients that place them at risk for NSF. Epidemiological data is needed for pediatric cardiovascular licensure of gadolinium compounds and for the creation of practice guidelines which will replace current-day practice based on individual clinical judgment.
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".