Totally endoscopic bilateral internal thoracic artery bypass grafting in a young diabetic patient.
Bibliographic record
Abstract
BACKGROUND: The introduction of robotics into cardiosurgical practice in 1998 has enabled totally endoscopic closed chest procedures. Totally endoscopic grafting of the LAD (TECAB) is no longer an experimental procedure. CASE REPORT: We report on a case with totally endoscopic bilateral internal thoracic artery bypass grafting to the left anterior descending and right coronary artery in a 36-year-old obese female diabetic patient using the daVinci surgical system. The patient, suffering from juvenile diabetes for 26 years, presented with stable angina (CCS class II). A coronary angiogram revealed 2-vessel disease with a long complex proximal lesion of the left anterior descending artery (LAD) (90%) and 80% stenosis of the proximal right coronary artery (RCA). Due to the condition of the proximal LAD (high risk PTCA with rather poor prognosis), the patient was referred for minimally invasive operative revascularisation of the LAD and the RCA. After informed consent was obtained the patient underwent totally endoscopic double internal thoracic artery bypass revascularisation on the arrested heart using computer-enhanced telemanipulation technology. RESULTS: The feasibility and safety of successful closed chest, totally endoscopic double coronary bypass grafting with two internal thoracic arteries is demonstrated in this case. Preservation of a stable chest cavity and reduced risk for wound healing complications in diabetics with an excellent cosmetic result are the obvious advantages of the techniques described.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".