Design and rationale of the HD PCI trial: A cluster randomized crossover trial of higher vs. lower dose heparin for elective percutaneous coronary intervention
Bibliographic record
Abstract
BACKGROUND: Balancing ischemic versus bleeding complications following percutaneous coronary intervention (PCI) remains challenging. However, the optimal dose of unfractionated heparin (UFH) for elective PCI is currently unclear. METHODS: A Randomized Trial of Higher versus Lower Dose Heparin for PCI (HD-PCI) is a multicenter, randomized, controlled, registry-based, open-label, cluster crossover trial of a lower-dose (70 units/kg) versus higher-dose (100 units/kg) UFH dosing hospital-level policy for elective PCI conducted in 11 centres in Ontario, Canada. The primary efficacy outcome was defined as a composite of all-cause death, myocardial infarction or target vessel revascularization; the key safety outcome was defined as major bleeding; and the key net benefit outcome was defined as the composite of all-cause death, myocardial infarction, target vessel revascularization or major bleeding. All outcomes were evaluated within 30 days of the index PCI. CONCLUSIONS: HD-PCI is a large cluster randomized crossover trial that will inform the ischemic and bleeding effects of lower-dose (70 units/kg) versus higher-dose (100 units/kg) in patients undergoing elective PCI. TRIAL REGISTRATION: ClinicalTrials.gov Identifier NCT04049591.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.035 | 0.030 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 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".