Bibliographic record
Abstract
Cavitary lung lesions are most often associated with infectious processes, but cavities can develop rapidly in the setting of pulmonary infarction due to venous thromboemboli or malignant necrosis most comonly due to squamous cell carcinoma. Venous tumor embolism occurs when tumor cells invade the vasculature and then disseminate. Initial symptoms of tumor emboli to the lungs are typically similar to those of non-malignant pulmonary thromboembolism including dyspnea, hypoxemia, and normal or minimally abnormal chest radiography, but may also include progressive pulmonary hypertension and cor pulmonale. Definitive diagnosis can be made via lung tissue biopsy or demonstration of malignant cells from blood samples aspirated from the distal port of a wedged pulmonary artery catheter. We report the case of a patient who developed rapidly-developing, large lung cavities due to diffuse tumor emboli. A 64 year-old man with a history of lung adenocarcinoma previously treated with lobectomy and chemotherapy was admitted with respitatory distress. He was tachycardic and hypoxic on presentation. Imaging studies revealed a small pulmonary embolus within the pulmonary artery supplying the left upper lobe as well as two large right-sided pulmonary cavities which were not present on outpatient imaging just one week prior. Laboratory studies revealed leukocytosis and abnormal liver enzymes but no definitive evidence of infectious or autoimmune pathology. Despite treatment with systemic anticoagulation and broad-spectrum antibiotics, he developed progressive respiratory failure as well as neurologically-devastating cerebral ischemic events. After discussion with his family, he was transitioned to comfort care and died shortly thereafter. Post-mortem examination revealed widespread occlusion of pulmonary vessels with malignant cells, including the vessels supplying the areas of the lung containing the cavities. Histopathologic staining was consistent with adenocarcinoma. Non-malignant thromboemboli were not found on gross or microscopic examination of his lung vasculature. He also had neoplastic involvement of the vessels in his splanchnic circulation. We believe that widespread tumor emboli caused his pulmonary cavities, respiratory failure, and neurologic deterioration. J Med Cases. 2011;2(6):292-295 doi: https://doi.org/10.4021/jmc263w
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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 | 0.000 |
| 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 | 0.001 | 0.001 |
| 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".