Ultrafast Track Robotic-Assisted Minimally Invasive Coronary Artery Surgical Revascularization
Bibliographic record
Abstract
OBJECTIVE: Contemporary anesthetic techniques have enabled shorter sedation and early extubation in off-pump and minimally invasive coronary artery bypass (CABG) surgery. Robotic-assisted CABG represents the optimal surgical approach for ultrafast track anesthesia, with patients able to bypass the cardiac surgical intensive care unit with recovery in the postanesthesia care unit (PACU) and inpatient ward. METHODS: In-hospital postoperative outcomes from ninety patients who underwent either elective or urgent robotically-assisted CABG at our institution were reviewed. These patients were carefully selected by a multidisciplinary team to undergo fast-track anesthesia: extubation in the operating room, 4-hour recovery in the postanesthesia care unit and transfer to the inpatient ward. Intrathecal, paravertebral local, and patient-controlled anesthesia techniques were used to facilitate transition to oral analgesics. RESULTS: Average patient age was 61 ± 9 years. Sixty-six patients (73%) were male. Seventy cases were elective, and 20 patients required urgent revascularization. All patients underwent intraoperative angiography after graft construction, which revealed Fitzgibbon class A grafts. There were no in-hospital mortalities. One patient required re-exploration for bleeding, through the same minimally invasive incision, did not require conversion to sternotomy for bleeding, and was transferred to the intensive care unit postexploration for bleeding for standard postoperative care. Postoperative complications were limited to one superficial wound infection. The mean hospital length of stay was 3.5 ± 1.17 days. CONCLUSIONS: In patients undergoing robotic-assisted CABG, ultrafast-track cardiac surgery with immediate postprocedure extubation and transfer to the inpatient ward has been demonstrated to be safe with no increase in perioperative morbidity or mortality. It requires a dedicated heart team with a carefully selected group of patients. Avoiding cardiac surgical intensive care unit expedites recovery, with possible avoidance of infection and early discharge from hospital.
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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) | 0.002 | 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".