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Acute invasive fungal sinusitis in a new diagnosis of type 1 diabetes mellitus

2025· article· en· W4412720221 on OpenAlexaff
Natalie Dies, Justin Chen, Vincent L. Biron, Hadi Seikaly

Bibliographic record

VenueJAAPA · 2025
Typearticle
Languageen
FieldMedicine
TopicAntifungal resistance and susceptibility
Canadian institutionsUniversity of Alberta Hospital
Fundersnot available
KeywordsMedicineDiabetic ketoacidosisImmunosuppressionDiabetes mellitusMeningitisFluconazoleSinusitisKetoacidosisMalignancyIntensive care medicineDiseaseType 1 diabetesCellulitisType 2 Diabetes MellitusSepsisBrain abscessCoronary artery diseaseSurgeryDermatologyAntifungalInternal medicineAbscess

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.062
Threshold uncertainty score0.364

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.285
Teacher spread0.271 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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