Consequences of Hybrid Procedure Addition to Robotic-Assisted Direct Coronary Artery Bypass
Bibliographic record
Abstract
OBJECTIVE: Patients postcoronary artery revascularization surgery often receives blood product transfusion, which could delay their intensive care unit and hospital discharge. We investigated our robotic-assisted direct coronary artery bypass (RADCAB) transfusion rate to determine whether performing the minimal invasive coronary surgery with percutaneous coronary intervention in one stage would increase the incidence of blood transfusion, morbidity, and length of stay. METHODS: Between November 2003 and November 2015, 483 consecutive patients underwent RADCAB surgery. They were divided into two groups. Group 1 (147 patients; mean ± SD age, 61.2 ± 11 years; 23% females) underwent robotic-assisted hybrid coronary artery revascularization with left internal thoracic artery to the left anterior descending coronary artery with percutaneous coronary intervention to a nonleft anterior descending coronary artery vessel in the same stage. Group 2 (336 patients; mean ± SD age, 61.2 ± 10.5 years; 25% females) underwent nonhybrid RADCAB. Early and late postoperative follow-up at mean ± SD of 83.6 ± 11.1 months was obtained. RESULTS: Blood transfusion rate in group 1 was statistically different, as illustrated in Table 2. Based on the intraoperative cardiac catheterization, the incidence of graft revision was higher in the nonhybrid group. There was no difference between the two groups in terms of renal failure, neurological complication, prolonged mechanical ventilation, and gastrointestinal bleed. CONCLUSIONS: Despite similar preoperative demographics in the two groups, we have observed a significant difference in the blood transfusion rate in group 1. However, this did not lead into a statistically significant re-exploration rate for bleeding. Hence, we assume that dual antiplatelet therapy usage in the hybrid group might be the cause of the increase in blood transfusion rate. Nevertheless, it did not affect postoperative morbidity and length of hospital stay. A randomized multicenter clinical trial is needed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.003 | 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".