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Record W3158844314 · doi:10.21037/abs-20-155

Bilateral male idiopathic granulomatous mastitis of the breast: a case report

2021· article· en· W3158844314 on OpenAlexaff
Tina R. Madzima, V. M. Yuen, Fang‐I Lu, Belinda Curpen, Mia Skarpathiotakis

Bibliographic record

VenueAnnals of Breast Surgery · 2021
Typearticle
Languageen
FieldMedicine
TopicBreast Lesions and Carcinomas
Canadian institutionsSunnybrook Health Science CentreHealth Sciences CentreUniversity of Toronto
Fundersnot available
KeywordsGranulomatous mastitisMastitisMedicineDermatologyPathology

Abstract

fetched live from OpenAlex

Abstract: Idiopathic granulomatous mastitis (IGM) is a rare benign inflammatory disease of the breast of unclear etiology, which can mimic breast cancer or infection. It is usually seen in parous women and is very seldom seen in males, with a few reported cases in the literature. We report a rare case of a 46-year-old male presenting with bilateral breast lumps and left-sided peri-areolar discharge from sinus tracts, who had failed antibiotic treatment. Bilateral mammogram, ultrasound, and core needle biopsies of the breast masses were performed, which revealed pathological findings consistent with granulomatous mastitis. The case was reported as bilateral IGM after exclusion of all known secondary causes of the disease, specifically tuberculosis and corynebacteria infection, as well as autoimmune diseases. To the best of our knowledge, this is the first case presentation of bilateral IGM in a male. Our patient was treated pharmacologically, initially using corticosteroids followed by methotrexate, and demonstrated good response with decreased swelling bilaterally and resolution of left peri-areolar discharge. Therefore, similar to women, IGM can present with bilateral disease in males. It is important for clinicians to be aware of IGM and its presentation in males to be able to correlate typical clinical findings with imaging and biopsy in order to avoid extended antibiotic therapy.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.260
Threshold uncertainty score0.584

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.042
GPT teacher head0.276
Teacher spread0.234 · 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".

Quick stats

Citations2
Published2021
Admission routes1
Has abstractyes

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