Acute invasive fungal sinusitis in a new diagnosis of type 1 diabetes mellitus
Bibliographic record
Abstract
ABSTRACT: A 32-year-old man diagnosed with type 1 diabetes mellitus presented to the ED following loss of consciousness and was ultimately diagnosed with acute invasive fungal sinusitis (AIFS). AIFS is a disease that most commonly affects people with immunocompromise such as those with a hematologic malignancy, diabetes, or HIV; those on immunosuppressant drugs posttransplant; and those on chemotherapy or long-term corticosteroids. In this case, the patient's diabetic ketoacidosis put him in a high-risk physiologic state. Following presentation, the patient was managed in the ICU to reverse his immunocompromise. He underwent six surgical debridements and received systemic broad-spectrum antifungal and antibacterial therapies. Ultimately, the patient developed intracranial arteritis, thromboses, and subsequent infarction, which were incompatible with meaningful life. This case highlights the variable presentation and mortality of AIFS, showing that an absence of sinonasal symptoms does not rule out the condition and that, though outcomes are generally thought to be more favorable in diabetes mellitus than other immunocompromised states, AIFS is a serious diagnosis for any individual with immunosuppression. The patient's clinical picture correlated well with radiologic progression of the disease; however, this is not always the case.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 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".