Thoracoscopic closure of atrial septal defect in perfused beating hearts
Bibliographic record
Abstract
OBJECTIVE: This study aims to characterize the mid and long-term clinical outcomes of 856 atrial septal defect cases that underwent closure using MTCST without the assistance of a robotic system. METHODS: From June 2009 to September 2023, a total of 856 cases at our center underwent selective repair of a secundum-type atrial septal defect using MTCST without Da Vinci robotic assistance. According to whether the operation was performed during an arrested heart or not, patients were divided into arrested heart group (n = 110) and beating heart group (n = 746). Cardiopulmonary bypass was established peripherally. Three-port incisions in the right chest were conducted first, followed by a pericardiotomy, superior and inferior vena cava snaring, atriotomy, and the closure of atrial septal defect under a thoracoscope. Patients were followed up from 3 months to 12 years postoperatively. RESULTS: The exclusively MTCST for atrial septal defect closure was successfully performed without any in-hospital mortality in both groups. None of the procedures required an alternative technique for the closure. There were significant learning curves for cardiopulmonary bypass time and operation time. No residual shunt was observed in all patients during the follow-up transthoracic echocardiography at 5-day and 3-month timepoints postoperatively. CONCLUSIONS: This study demonstrates that an exclusively MTCST for atrial septal defect repair is safe, simple, and minimally invasive. Exclusively MTCST is a new desirable alternative beside robotic-assisted atrial septal defect repair.
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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".