Diagnosing Disseminated Nocardiosis in a Patient With COVID-19 Pneumonia
Bibliographic record
Abstract
Signs and symptoms of atypical pneumonia include fever, shortness of breath, cough, and chest pain. During the coronavirus disease 2019 (COVID-19) pandemic, identifying other causes of febrile respiratory illness in patients who tested positive for COVID-19 has been very challenging. Concerns over infecting healthcare personnel and other patients can impede further evaluations like bronchial lavage, lung biopsies, and other invasive tests. A very high index of suspicion, perhaps unreasonably so, is required to perform invasive tests to investigate alternative possible causes of the illness. We present the case of a 63-year-old man who presented to the hospital with dyspnea. Chest X-ray demonstrated a consolidation in the left lower lobe lung field with a possible underlying mass, and the patient tested positive for COVID-19. He received the standard treatment for COVID pneumonia at the time in our institution (remdesivir and dexamethasone), empiric antibiotics for community-acquired pneumonia, and was eventually discharged home with supplemental oxygen. Several days later, the patient returned to the hospital again with worsening dyspnea and was readmitted. Persistent illness and worsening imaging prompted bronchoscopy. The bronchoscopy showed narrowing of the airway in the left upper lobe, and Nocardia asteroides was isolated from bronchial aspirate. The isolation of Nocardia prompted an investigation for central nervous system involvement with an magnetic resonance imaging (MRI) of the head. The MRI demonstrated multiple bilateral ring-enhancing lesions in the brain. To our knowledge, this is the first reported case of disseminated nocardiosis superimposed on COVID-19 pneumonia. J Med Cases. 2021;12(8):319-324 doi: https://doi.org/10.14740/jmc3716
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".