Transcatheter Closure Versus Repeat Surgery for the Treatment of Postoperative Left-to-Right Shunts: A Single Center 15-Year Experience
Bibliographic record
Abstract
BACKGROUND: Repeat surgery and the percutaneous approach (transcatheter closure (TCC)) have been used for the management of postoperative left-to-right shunts. In this study, we described our 15 years of experience in treating postoperative left-to-right shunts with these two approaches. METHODS: From February 2002 to February 2017, 50 patients with residual left-to-right shunts, following cardiac surgery, were treated using TCC or repeat surgery. Clinical examination, standard 12-lead electrocardiography, chest X-ray, and a transthoracic echocardiogram were performed before hospital discharge and at all follow-ups. RESULTS: The closure rate was 100% in both groups and there was no procedure-related mortality. Patients with TCC had few complications. The procedure time and duration of hospital stay for TCC patients were 58.9 ± 27.7 min and 6.1 ± 0.8 days, respectively. Eleven out of 19 patients receiving reoperation suffered serious complications after surgery, e.g., bleeding and nosocomial infections. The operation time and duration of hospital stay for reoperation patients were 256.7 ± 60.5 min and 17.0 ± 4.0 days, respectively. No other serious complications were seen at all follow-up visits for both groups. CONCLUSIONS: In conclusions, TCC is safe and effective for the management of postoperative left-to-right shunts, and is associated with few complications, which can be the favored closure strategy over repeat surgery for the management of postoperative left-to-right shunts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".