Heparin use for diagnostic cardiac catheterization with a radial artery approach: An international survey of practice patterns
Bibliographic record
Abstract
OBJECTIVES: We aimed to describe global practice patterns of unfractionated heparin (UFH) use for diagnostic transradial cardiac catheterization. BACKGROUND: The use of the radial artery approach for cardiac catheterization is increasing globally. Limited contemporary data exist to support the use or optimal dosing of UFH to prevent radial artery occlusion (RAO) and other thromboembolic complications. METHODS: We performed a web-based international survey of 450 interventional cardiologists from 34 countries. We collected information regarding the experience and use of UFH for diagnostic transradial cardiac catheterization. RESULTS: The survey was conducted between June and July 2016 and was completed by 227 (50.4%) interventional cardiologists. Overall, 83.3% performed >75% of their coronary angiograms via a radial approach, with the plurality (41.9%) having 10-20 years of clinical experience. Of all respondents, 7.5% did not use UFH for routine diagnostic transradial heart catheterization. Of the 92.5% who did use UFH, it was preferentially administered intra-arterially by 60% and intravenously by 40%. The majority (62.6%) of interventionalists used a fixed UFH dose with 5,000 IU being the most common dose (used in 48%). For those using a weight-based UFH (50 IU/kg) dosing regimen for diagnostic procedures (36.1%), the administered UFH dose ranged from 2,000 up to 10,000 IU. CONCLUSIONS: Despite the lack of firm evidence, the majority of interventional cardiologists who participated in the survey use UFH to prevent RAO for diagnostic transradial coronary angiography. However, there exist large practice disparities with regards to dose and route of administration. Given this knowledge gap, a dedicated randomized trial is warranted.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".