The wise radialist's guide to optimal transfemoral access: Selection, performance, and troubleshooting
Bibliographic record
Abstract
Transradial access (TRA) has reduced vascular access-site complication (VASC) and bleeding rates in patients undergoing coronary angiography and intervention. A "radial-first" approach should be adopted and indications of TRA extended in order to maximize its beneficial effect. However, in certain clinical scenarios, transfemoral access (TFA) is a preferable or a mandatory route to successfully perform the procedure. Since the widespread adoption of TRA, a paradoxical increase in VASC rates has been observed in patients undergoing TFA, which might be attributed to a combination of increased risk profile of both the procedures and the patients, and a loss of skills in securing TFA by those who are now default radial operators. In the present article we provide recommendations on how to optimize patient selection for TRA and TFA, how to manage access site crossover, and how to perform state-of-the-art femoral artery puncture. © 2016 Wiley Periodicals, Inc.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.006 | 0.012 |
| Insufficient payload (model declined to judge) | 0.019 | 0.029 |
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".