Global Chronic Total Occlusion Crossing Algorithm
Bibliographic record
Abstract
The authors developed a global chronic total occlusion crossing algorithm following 10 steps: 1) dual angiography; 2) careful angiographic review focusing on proximal cap morphology, occlusion segment, distal vessel quality, and collateral circulation; 3) approaching proximal cap ambiguity using intravascular ultrasound, retrograde, and move-the-cap techniques; 4) approaching poor distal vessel quality using the retrograde approach and bifurcation at the distal cap by use of a dual-lumen catheter and intravascular ultrasound; 5) feasibility of retrograde crossing through grafts and septal and epicardial collateral vessels; 6) antegrade wiring strategies; 7) retrograde approach; 8) changing strategy when failing to achieve progress; 9) considering performing an investment procedure if crossing attempts fail; and 10) stopping when reaching high radiation or contrast dose or in case of long procedural time, occurrence of a serious complication, operator and patient fatigue, or lack of expertise or equipment. This algorithm can improve outcomes and expand discussion, research, and collaboration.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".