Rotational Atherectomy and Stent Implantation for Calcified Left Main Lesions
Bibliographic record
Abstract
BACKGROUND: Left main coronary artery (LMCA) bifurcation and heavily calcified lesions are common and challenging to treat percutaneously. Rotational atherectomy (RA) may be beneficial in this setting to facilitate stent placement though direct supporting evidence is lacking. This study sought to analyze patients who underwent RA of the LMCA. METHODS: Consecutive cases involving RA of the LMCA between 1/1/2004 and 12/31/2009 at a private, tertiary referral hospital were reviewed retrospectively. Medical records, angiograms and clinically driven follow-up were reviewed. RESULTS: Thirty-one cases were identified (20 protected, 11 unprotected), including 23 with stent implantation (21 drug-eluting, 2 bare metal). All 31 lesions had moderate to severe calcification, 84% involved the distal segment. Mean burr-to-vessel ratio was 0.43. Overall angiographic success was 90% (28/31) and was higher with a drug-eluting stent versus no stent (100% vs. 62%; P = 0.0153). In-hospital major adverse cardiovascular events (MACE) occurred in 1 patient (3%). Mid-term MACE occurred in 6 patients (26%) and tended to occur less frequently in patients with protected LMCAs (P = 0.0697). At final follow-up, patients were more likely to be alive and free from angina with a protected LMCA (94% vs. 57% unprotected; P = 0.0564) and with a drug-eluting stent (89% vs. 50% with no stent; P = 0.0281). CONCLUSIONS: RA of the LMCA to facilitate stent implantation appears to be safe and effective with favorable mid-term outcomes. In the setting of severe calcification and distal LMCA involvement RA and drug-eluting stent implantation should be considered.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".