Single-stage repair for multiple muscular septal defects: a single-centre experience across 16 years
Bibliographic record
Abstract
OBJECTIVES: Multiple muscular ventricular septal defects (VSDs) are surgically challenging and its management remains controversial. We present a technique of surgical repair for muscular VSDs, which includes surgical exposure and detection of these defects and has excellent clinical outcomes. METHODS: We have analysed consecutive patients who underwent surgical repair of isolated multiple muscular VSDs under cardiopulmonary bypass over a 16-year period (from January 2001 to November 2016) in a single centre from the southern part of India. These defects were accessed through the right atrium in most cases and closed directly; completeness of closure was confirmed by pressurizing the left ventricle with blood cardioplegia. There were no haemodynamically significant residual VSDs following repair. RESULTS: One hundred and two patients with an average time of follow-up of 4.1 years (1 month-12 years) were included. The mean age of our patients at the time of operation was 23.5 months (3 months-22 years) with a mean weight of 7.9 kg (2-55 kg). The mean cardiopulmonary bypass and cross-clamp time was 118.8 ± 39.2 min (mean ± SD) and 76.5 ± 29.4 min (mean ± SD), respectively. There were 10 (9.8%) hospital deaths and 3 late deaths in the entire study group. Permanent pacemaker was implanted in 2 patients. Seventy patients could be followed up after discharge. Postoperative pulmonary artery pressure was normal in 52% of the patients, mild-to-moderate hypertension in 27% and severe in 7% of the patients. The ejection fraction was >60% among the survivors, and there were no reoperations or reinterventions. CONCLUSIONS: This surgical approach to multiple muscular VSDs is safe and effective with minimal risk of complete heart block and diminution of ventricular function.
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 | 0.002 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".