Surgery for Left Ventricular Aneurysm: Is There Still Any Role for Simple Linear Repair?
Bibliographic record
Abstract
The aim of left ventricular aneurysm (LVA) surgery is to eliminate the diskinetic portion of the left ventricle and to restore the patient's clinical condition. This can be obtained with two surgical procedures: linear repair and endoventricular patch technique. We investigated early- and long-term results in patients who underwent both procedures. From January 1980 to December 2004, 158 patients underwent surgical repair of LVA: 86 had linear repair and 72 patch repair. Operative mortality was 6.9%, with no differences between the two groups. Logistic regression revealed older age, higher left ventricular end-diastolic volume, and an ejection fraction (EF) less than 30% as independent risk factors for in-hospital mortality; the type of operation "per se" did not influence the early mortality. At the follow-up extending up to 25 years, there was no statistically significant difference in survival between the two study groups, as well as in New York Heart Association and Canadian Cardiovascular Society classes. Cox regression revealed older age, EF less than 30%, urgent operation, and a history of cerebrovascular accident as independent risk factors for late mortality: the type of operation did not influence mortality at follow-up. We conclude that aneurysm resection associated with myocardial revascularization is the best treatment for LVA. The choice of the technique should be tailored on an individual basis, according to aneurism location, extension, residual ventricular function, and septal involvement.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".