The novel use of Perceval valve for pulmonary valve replacement in carcinoid syndrome: a case report
Bibliographic record
Abstract
Background: Sutureless prosthetic aortic valves have continued to play an expansive role in addressing aortic valve disease in patients undergoing heart surgery. These valves have been shown to be safe and associated with excellent clinical and hemodynamic outcomes. While these prostheses are indicated for aortic valve replacement, there are case studies that have reported their use in the pulmonic position in high surgical risk patients. For the first time, herein, we report the implantation of a Perceval sutureless valve in the pulmonic position of a patient with severe carcinoid syndrome. The case adds to the growing body of literature supporting the use of sutureless valves to facilitate complex cardiac operations. The case also demonstrates that patients with severe carcinoid syndrome affecting cardiac structures should be considered for sutureless valves if indicated. Case Description: We report the case of a Perceval sutureless valve implanted into the pulmonary position in a patient with severe carcinoid cardiac disease. The patient was a 64-year-old male who was admitted with heart failure after presenting with anasarca and unintentional weight loss. Investigations confirmed a diagnosis of carcinoid syndrome involving the heart and intra-cardiac structures. The patient underwent a median sternotomy, tricuspid valve repair, and pulmonary valve replacement using a Perceval sutureless valve. At 18-month follow-up, the patient does not endorse any cardiovascular symptoms and echocardiography findings are consistent with a well-seated and normally functioning prosthetic valve. Given the small right ventricular tract, the operation involved using a bovine pericardium to accommodate the deployment of the Perceval valve. Conclusions: A sutureless valve played an important role in facilitating this complex operation on a patient with a high surgical risk profile.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".