Long-term clinical follow-up after successful direct coronary stenting without predilatation.
Bibliographic record
Abstract
BACKGROUND: Direct stent implantation without predilatation is considered a promising new technique that may reduce procedural time, radiation exposure, ischemic time and cost, but little information is available concerning the long-term outcome. The aim of this study was to investigate the long-term clinical outcome of successful direct stenting without predilatation. METHODS: We prospectively undertook a clinical follow-up program (minimum 8 months) in a consecutive series of 101 patients (113 lesions) who were successfully treated with direct stenting without predilatation. RESULTS: Clinical follow-up was obtained in all 101 patients at a mean period of 12.8 months (range 8 to 18.9). Stress test results were available in 94 patients (94%). During the follow-up period, 23 patients (23%) had one or more events, which included death in 2 patients (2%), target vessel revascularization in 14 (14%), myocardial infarction in 1 (1%) and positive stress test results or recurrence of symptoms (Canadian Cardiovascular Society I to II) treated medically in 6 (6%). Cumulative event-free survival at 8 and 18 months were 80% and 72%, respectively. Long-term clinical event rate was not significantly different among the clinical presentations, lesion types, or stent types. Angiographic follow-up was performed in 43 (43%) patients with 45 lesions. Restenosis (defined as 50% diameter stenosis) was observed in 14 of the lesions (31%). CONCLUSIONS: Direct stenting without predilatation is an effective method of coronary intervention in terms of low long-term clinical event rate.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".