Multiple pulmonary nodules in a patient with polyarteritis nodosa
Bibliographic record
Abstract
We are reporting the case of a 58-year-old woman, investigated for a 6 weeks history of abdominal pain, nausea, shortness of breath and weight loss of 25 pounds. Her medical history was otherwise insignificant. Upon presentation, the woman was febrile at 38,5 C, had tachycardia, low blood pressure despite aggressive volume repletion, leukocytosis and acute renal failure. A CT scan of the thorax and abdomen showed multiple nodules within the thyroid gland, the lungs, liver and kidney parenchyma. The patient was put on broad-spectrum antibiotics and anti-fungal medication. BAL (bronchoscopy) and all cultures remained negative. A screen for vasculitis and virus were negative. A liver biopsy showed areas of necrosis due to ischemic insults. Later, the patient developed gastro-intestinal bleeding. An angio-embolization meant to be curative turned out to be diagnostic. We discovered many small aneurysms affecting the mesenteric, hepatic, gastroepiploic and the bleeding site from an ileal branch was succesfully embolized. A vasculitic origin (PAN) to the patient's symptoms was undeniable: unexplained weight loss 4 kg; myalgias; elevated creatinine; characteristic angiographic abnormalities. The patient rapidly recovered with IV steroids and cyclophosphamide. Polyarteritis nodosa is known to affect multiple organs, but the lung. Very few cases of polyarteritis nodosa involving the lung have been reported. Necropsy reports also described pulmonary fibrosis. Cases of acute interstitial pneumonia, BOOP and alveolar hemorrhage have been described. To our knowledge, it would be the first case of micronodular lung involvement in association to PAN. This case raises awareness to a possible pulmonary involvement in PAN.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 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".