Cancerous Left Atrial Mass: A Rare Case Report of Cardiac Sarcoma in a 71-Year-Old Woman
Bibliographic record
Abstract
Background: Diagnosing cardiac masses is inherently complex due to overlapping differential diagnoses, including thrombi, vegetations, artifacts, and tumours. Primary cardiac tumours are exceptionally rare, with a prevalence between 0.001% and 0.3%. Approximately 25% of these are malignant, with cardiac sarcomas being a rare but aggressive subset. These tumours may manifest with symptoms such as arrhythmias, obstruction of blood flow, and systemic signs, necessitating timely and precise differentiation for optimal patient management. Methods: This report examines a case of malignant cardiac sarcoma in the left atrium of a 71-year-old woman. Diagnostic modalities included electrocardiography, transthoracic echocardiography, transesophageal echocardiography, and CT, with biopsy confirming the diagnosis. Key clinical approaches, imaging findings, and management strategies are detailed in this article. Results: The patient presented with gastrointestinal symptoms, pneumonia, and heart block. Imaging revealed a 3 × 4.2 cm immobile mass in the left atrium. Initial differentials included thrombus and benign tumours, but further investigations confirmed malignancy. Biopsy established the final diagnosis of high-grade sarcoma. Given the advanced stage, palliative care was selected. Discussion: Differentiating cardiac masses, including thrombi and benign and malignant tumours, requires a multimodal imaging approach complemented by histopathological analysis. Early diagnosis and a multidisciplinary care strategy are pivotal, though prognosis for cardiac sarcomas remains poor due to their aggressive nature.
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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 | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".