Aortocoronary Bypass Surgery in Patients with Recurrent Post-Coronary Stenting Angina
Bibliographic record
Abstract
Background. A wide adoption of percutaneous coronary operations has led to an average one-third reduction in the aortocoronary bypass surgery (ACB) rate and altering of the ACB patient profile to mainly represent advanced occlusive coronary atherosclerosis. Materials and methods. The study analyses treatment outcomes in coronary heart disease patients with recurrent angina after a previous endovascular intervention. Over years 2009–2015, 1,023 ACB operations were performed at the Almetyevsk — OAO Tatneft Medical Unit cardiac surgery rooms. Pre-surgery coronary artery stenting (CAS) was rendered at various terms in 96 patients (23 % women, 76 % men; cohort 1). The main cohort (n = 96) was divided into 2 subgroups: IA (n = 64), single CAS; IB (n = 32), multiple CAS patients. For statistical significance, cohort 2 (control) comprised 185 patients (21 % women, 79 % men) to include every 5th history of the remaining 927 patients operated within same period. Results and discussion. The mean aortic occlusion time was shorter in multiple CAS patients vs. other cohorts (61.3 ± 31.2 vs. 72.5 ± 27.8 and 70.7 ± 41.2 min). Cohort 1 had an overall higher emergency resternotomy rate due to ongoing bleeding (7.4 and 8.3 vs. 2.0 %). Furthermore, pre-surgery multiple CAS patients more likely faced the complications of perioperative MI (8.5 vs. 3.1 and 1.4 %) and acute postoperative heart failure (7.2 vs. 2.3 and 1.4 %, p < 0.01). This cohort often required inotropic support (9.3 vs. 3.8 and 2.1 %). Conclusion. Statistical analysis revealed a significantly higher complication and mortality rate in patients with previous coronary stenting compared to ACB patients. Adverse ACB outcomes were observed with multiple-coronary stenting cases, in contrast to the cohort with no pre-surgery interventions.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".