One‐year clinical outcomes after sirolimus‐eluting coronary stent implantation in diabetics enrolled in the worldwide e‐<scp>SELECT</scp> registry
Bibliographic record
Abstract
BACKGROUND: Diabetes mellitus has worse outcome after percutaneous coronary intervention. AIM: We assessed stent thrombosis (ST), major adverse cardiac events (MACE), and major bleeding rates at 1 year after implantation of sirolimus-eluting stents (SES) in patients with diabetes mellitus in a large multicenter registry. METHODS: From May 2006 to April 2008, 15,147 unselected consecutive patients were enrolled at 320 centers in 56 countries in a prospective, observational registry after implantation of ≥ 1 SES. Source data were verified in 20% randomly chosen patients at > 100 sites. Adverse events were adjudicated by an independent Clinical Event Committee. RESULTS: Complete follow-up at 1 year was obtained in 13,693 (92%) patients, 4,577 (30%) of whom were diabetics. Within diabetics, 1,238 (9%) were insulin-treated diabetics (ITD). Diabetics were older (64 vs. 62 years, P < 0.001), with higher incidence of major coronary risk factors, co-morbidities, and triple-vessel coronary artery disease. Coronary lesions had smaller reference vessel diameter (2.88 ± 0.46 vs. 2.93 ± 0.45 mm, P < 0.001) and were more often heavily calcified (26.1% vs. 22.6%, P < 0.001). At 1 year, diabetics had higher MACE rate (6.8% vs. 3.9%, P < 0.001) driven by ITD (10.6% vs. 5.5%, P < 0.001). Finally, diabetics had significant increase in ST (1.7% vs. 0.7%, P < 0.001), principally owing to ITD (3.4% vs. 1.1%, P < 0.001). There was an overall low risk of major bleeding during follow-up, without significant difference among subgroups. CONCLUSIONS: In the e-SELECT registry, diabetics represented 30% of patients undergoing SES implantation and had significantly more co-morbidities and complex coronary lesions. Although 1-year follow-up documented good overall outcome in diabetics, higher ST and MACE rates were observed, mainly driven by ITD. © 2015 Wiley Periodicals, Inc.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".