Bibliographic record
Abstract
Pulmonary artery pseudoaneurysm secondary to metastatic angiosarcoma A70 year old woman presented to the emergency department with haemoptysis and right sided chest pain.Of significance was a prior history of angiosarcoma arising from soft tissues in the neck.A contrast enhanced helical CT scan of the thorax was performed to exclude pulmonary emboli.Multiple lung nodules were seen, some of which were cavitary.This was associated with a small left hydropneumothorax and a small right pleural effusion (fig 1A).Several lung nodules were surrounded by ground glass opacity, and one of the right lower lobe lung metastases was observed to be contiguous with a subsegmental branch of the right anterior basal pulmonary artery and a pseudoaneurysm (fig 1B) which was better appreciated on the maximum intensity projection (MIP) image (fig 2).There was no history of pulmonary angiography, Swan-Ganz catheterisation, percutaneous needle biopsy of the lung, or pneumonia.The patient had no further haemoptysis and the chest pain abated on its own after a few hours so, because of her age and diffuse metastatic disease, no intervention was performed.It is presumed that the pseudoaneurysm resulted from erosion of an angiosarcoma metastasis into a subsegmental pulmonary artery resulting in haemoptysis.Angiosarcoma lung metastases are commonly solid nodules and thin walled cysts often admixed with haemorrhage. 1 The CT halo sign (lung nodule with surrounding ground glass density) has been described in angiosarcoma metastases because of haemorrhage into the surrounding lung parenchyma.Subpleural cystic lesions can give rise to pneumothorax, as illustrated in this case.However, pulmonary artery pseudoaneurysm is an unusual and previously unreported manifestation of angiosarcoma metastases.Pulmonary artery pseudoaneurysms are commonly iatrogenic or mycotic in origin. 2 They have rarely been reported secondary to tumours.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".