Percutaneous Coronary Intervention with Procedural Unfractionated Heparin without Activated Clotting Time Guidance: A Unique Opportunity to Assess Thrombotic and Bleeding Events
Bibliographic record
Abstract
Background. Rates of major bleeding and intraprocedural thrombotic events (IPTE) in the setting of percutaneous coronary intervention (PCI) using weight-adjusted unfractionated heparin (UFH) without activated clotting time (ACT) monitoring are not known. Methods. We reviewed 2,748 consecutive patients who underwent coronary angiography at our tertiary care university hospital between January 2017 and December 2020. All patients who underwent PCI with weight-adjusted UFH without ACT guidance were considered for further analysis. Major bleeding complications occurring within 48 hours of PCI were collected from patients’ medical records. IPTE were collected independently by two interventional cardiologists after review of coronary angiograms. Results. There were 718 patients included in the analysis (65.4 ± 12.2 years old; 81.3% male). In total, 45 patients (7.8%) experienced a major bleed or IPTE. The most common IPTE were slow/no reflow (1.5%) and coronary artery dissection with decreased flow (1.1%). Other IPTE occurred in <1% of cases. Major bleeding occurred in 11 patients (1.5%), of whom 8 required blood transfusion and 3 required vascular intervention. Bleeding complications were more common with femoral compared with radial access (6.6% vs. 0.2%, P<0.001 ). Conclusion. Weight-adjusted UFH use during PCI without ACT monitoring was related to low rates of major bleeding or IPTE.
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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 | 0.001 |
| 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) | 0.001 | 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".