Robotic-enhanced coronary surgery in octogenarians
Bibliographic record
Abstract
Objectives: Robotic-enhanced minimally invasive direct coronary artery bypass grafting surgery (RE-MIDCAB) is based on the use of a robotic console and instrumentation for the dissection of the left internal thoracic artery (LITA). The LITA to left anterior descending (LAD) artery anastomosis is subsequently constructed through a mini thoracotomy. The purpose of this study is to present our experience of RE-MIDCAB outcomes in elderly patients. Methods: From 2002 until 2015, 44 octogenarians (the mean age of 82.9 years) underwent RE-MIDCAB. The mean logistic EuroSCORE was 9.2. The majority of the patients were male with a medical history of hypertension, dyslipidaemia and previous coronary interventions. Of these patients 25% underwent RE-MIDCAB combined with percutaneous coronary intervention (PCI) for the treatment of multi-vessel disease (hybrid revascularization). Results: All RE-MIDCABs and combined 'hybrid' PCI procedures were successfully completed. The mean intensive care unit (ICU) and hospital stay were 1.6 days and 10.9 days, respectively. There was 1 in-hospital mortality (2.3%). After an average follow-up period of 29.2 months, 5 patients required repeat revascularization procedures (9.1%). Mortality on follow-up was estimated at 25.6%. Conclusions: Our report suggests that considering the age and frailty of the octogenarian population, RE-MIDCAB is a feasible and safe procedure which is associated with acceptable mid-term results.
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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 | 0.000 | 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) | 0.001 | 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".