Transient mediastinal mass from fluid overload
Bibliographic record
Abstract
Mediastinal masses incidentally discovered on chest imaging often suggest underlying malignancy such as lymphoma or metastatic cancer. However, the radiographic appearance of mediastinal edema can mimic a mediastinal mass in the context of acute fluid overload. We describe the case of a 75 year old woman known for end-stage renal disease on hemodialysis who presented with acute pulmonary edema in the context of a Non ST-Elevation Myocardial Infarction. Chest CT imaging showed pulmonary edema, pleural effusions, and a middle mediastinum soft-tissue mass of 4.2 × 2.5cm. Malignancy was initially suspected, however given the clinical context of fluid overload and absence of other signs of malignancy, the possibility of the mass representing soft-tissue edema was raised. Therefore, the patient's fluid overload was treated with a progressive reduction in the dry weight used for dialysis and a repeat chest CT was obtained 8 weeks later once the patient was euvolemic. The repeat CT showed complete resolution of the mediastinal mass. Fluid overload can manifest in many different ways on chest imaging. Mediastinal masses lead to concerns about a potentially malignant process and often prompt further evaluation with invasive procedures that carry significant risks. In the appropriate clinical context, it is important to consider the possibility of mediastinal edema presenting as a mass on chest imaging. Under such circumstances, it is more prudent to correct the fluid overload and repeat chest imaging before undertaking invasive diagnostic procedures with the potential to cause harm.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".