First Case of Regression of Carcinoid Heart Disease on Serial Transthoracic Echocardiograms following Octreotide Monotherapy in a Patient with Metastatic Pancreatic Neuroendocrine Tumor
Bibliographic record
Abstract
Well-differentiated neuroendocrine tumors (NETs) arising in the gastrointestinal (GI) tract and pancreas are relatively rare; however, the annual incidence has been increasing. Carcinoid syndrome (CS) is a constellation of symptoms that occur when a GI NET metastasizes to the liver and releases high levels of vasoactive substances into the systemic circulation. CS occurs in 19% of NETs patients at diagnosis and is associated with shorter survival. Carcinoid heart disease (CHD) occurs in over 50% of patients with CS and is associated with poor long-term prognosis. NET-induced valvular fibrosis is a significant cause of mortality and morbidity in these patients. Somatostatin analogs relieve CS symptoms, but they have never been shown to reverse CHD progression or improve overall survival. Surgical therapy for right-sided valve disease is associated with improved symptoms and quality of life and possibly improved survival, despite relatively high morbidity and mortality associated with cardiac intervention. A 65-year-old woman with a metastatic pancreatic NET had typical signs and symptoms of CS. She presented in congestive heart failure and was found to have severe tricuspid regurgitation with characteristic features of CHD on transthoracic echocardiogram (TTE). Following octreotide monotherapy, serial TTEs demonstrated regression of tricuspid valve involvement. The patient improved clinically and remained asymptomatic on subsequent visits. This is the first case of CHD regression with medical therapy supported by serial TTEs. Developing a deeper understanding of cases like this will help us unlock new intervention targets and strategies for treatments in the future.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| 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".