Can Children Be Considered for Transradial Interventions?
Bibliographic record
Abstract
Background: Transradial intervention is increasingly replacing approaches, due to lower access complications, cost, and improved patient satisfaction. There are limited supporting data in the pediatric literature, largely due to concerns regarding arterial size. The objective of this study was to measure radial artery diameters in children across all age groups, to establish reference ranges for clinical use. Methods: This prospective study was carried out in children ≤18 years of age who underwent ultrasound for measuring radial artery diameters from November 2018 to November 2019. The cohort was divided into age groups: ≤2, 3 to 5, 6 to 8, 9 to 11, 12 to 14, 15 to 18 years, and into pre- and post-adolescent (≥12 years) groups. Results: One hundred thirty-four children (M:F=63:71) were included, with bilateral measurements resulting in 268 data points. Mean age was 8.9±5.8 years (range, 29 days to 18 years), mean weight 37.2±27.5 kg (range, 1.7–149.1 kg). Mean-corrected radial artery diameter was 1.86±0.44 mm. There was no difference in arterial diameters between males and females (1.90±0.50 versus 1.81±0.53 mm; P =0.73) or between right and left sides (1.87±0.46 versus 1.87±0.47, P =0.98). There was a strong correlation of diameter with age (R=0.75; P <0.00001) and weight (R=0.74; P <0.00001). There was linear increase in arterial growth rates in early childhood, followed by plateauing to adult sizes in adolescents. Inter-reader agreement was 0.95. Conclusions: We provide a reference range for radial artery diameters across childhood ages, which can be used for decision-making. This could be the basis for designing a trial of transradial intervention in children, to establish clinical safety and efficacy.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".