Invasive <i>Conidiobolus</i> infection in an immunocompromised pediatric patient in Southern California
Bibliographic record
Abstract
ABSTRACT Background Conidiobolus species are largely known to cause rhinofacial cellulitis in healthy individuals but can manifest as an invasive infection in immunocompromised patients. Few cases have been described in the literature as they are difficult to diagnose and rarely observed in North America, particularly in the pediatric population. Case Summary A 15-year-old boy with a history of multiple bone marrow transplants for mixed phenotype acute leukemia presented to the emergency department with febrile neutropenia and chills. His clinical course was complicated by potential Rothia mucilaginosa bacteremia, but imaging revealed a potential invasive pulmonary fungal infection. Following rapid decompensation and admission in the intensive care unit, plasma cell-free DNA sequencing was ordered, identifying Conidiobolus species. The same organism was then isolated in the patient’s sputum culture shortly thereafter. This organism was found to demonstrate high minimum inhibitory concentration to antifungals tested in vitro . Ultimately, the patient was discharged on posaconazole and trimethoprim-sulfamethoxazole. Conclusion Conidiobolus can be an agent of invasive fungal infection and may be considered a potential infectious agent in the immunocompromised patient. Treatment and outcomes of invasive Conidiobolus remain elusive.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".