Transradial versus Transfemoral Neuroangiography in a Tertiary Pediatric Hospital – a Propensity Score Matched Study
Bibliographic record
Abstract
## Introduction To evaluate the feasibility and safety of transradial access (TRA) in comparison to transfemoral access (TFA) for pediatric neurovascular procedures. ## Materials and Methods Retrospective cohort study including 729 pediatric neurovascular procedures performed between January 2020 and December 2024, with 175 TRAs and 540 TFAs. Primary outcomes included technical success and adverse events, while secondary outcomes assessed radiation dose, fluoroscopy time and procedural duration. Propensity score matching (1:1) was applied to adjust for imbalance in baseline covariates. Statistical significance was set at P<.05. ## Results 100 matched pairs of TRA and TFA were analyzed (TRA median age 13.9 [IQR 11.7–15.3] years, 52 females; TFA median age 14.5 [IQR 11.6–16.4] years, 51 females). Technical success rates were similar between TRA and TFA (98% vs 99%, P >.99). TRA was associated with a higher rate of vasospasm (7% vs 1%, P=.03) and a lower rate of hematoma formation (2% vs 9%, P=.03). Fluoroscopy time was longer in the TRA group (19.4 vs 8.8 minutes, P <0.001), but the radiation dose and procedural time were comparable between both groups. Asymptomatic radial artery occlusion (RAO) was detected in 5.1% (9/175) of radial accesses. A sheath-to-artery (S/A) ratio ≥1 was independently associated with RAO (OR 6.13; 95% CI:1.32-28.4; P=.021). ## Discussion TRA is a technically feasible and safe alternative to TFA for pediatric neurovascular procedures. Although vasospasm is more frequent, TRA reduces hematoma risk and offers comparable procedural outcomes. Pre-procedural US assessment of radial artery and optimization of S/A ratio are important to reducing the risk of RAO.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".