Novel Approaches for the Treatment of Chronic Total Coronary Occlusions
Bibliographic record
Abstract
Despite major advancements in the technology used for the percutaneous treatment of coronary artery disease, chronic total occlusions (CTOs) persist as a major challenge to the interventional cardiologist with relatively low success rates. CTOs are evident in 20% of patients undergoing cardiac catheterization and are responsible for the majority of cases that are referred to bypass surgery. There is growing evidence that patients may benefit from recanalization of a CTO by alleviation of angina, improving left ventricular function, and potentially long-term survival. The major obstacle to percutaneous recanalization of CTOs is the inability to cross the occlusion with coronary guidewires. Even when crossed, the operator has to deal with the exact location of the distal wire (e.g., dissection or true lumen) and the existence of relatively long lesion requiring multiple stents with high restenosis rates. New technologies for CTO revascularization have been focused mainly on a mechanical approach including specialized guidewires and more recently, specific devices using highly sophisticated technology such as laser guidewire, optical coherence reflectometry, and a blunt microdissection catheter. An alternate biological approach involves the local administration of enzymes such as plasminogen activators (urokinase) or collagenase, which can act locally to specifically degrade the collagen content of the CTO, thereby "softening" the occlusion and allowing easier guidewire crossing. In conclusion, CTOs emerge as a great technical challenge and are the focus of novel series of mechanical and biological approaches.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".