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Record W4308769183 · doi:10.1177/10668969221102551

Breast Implanted-Associated Anaplastic Large Cell Lymphoma: A Case of Advanced Disease with Flow Cytometric Findings

2022· article· en· W4308769183 on OpenAlexaff
Nadine Demko, Tyler Safran, Joshua Vorstenbosch, René P. Michel

Bibliographic record

VenueInternational Journal of Surgical Pathology · 2022
Typearticle
Languageen
FieldMedicine
TopicBreast Implant and Reconstruction
Canadian institutionsMcGill University Health CentreMcGill University
Fundersnot available
KeywordsAnaplastic large-cell lymphomaBreast implantMedicineImmunophenotypingBiopsyPathologyLymphomaCD30ImplantPopulationRadiologyFlow cytometrySurgeryImmunology

Abstract

fetched live from OpenAlex

Breast implant-associated anaplastic large cell lymphoma (breast implant-associated ALCL) is a recently described, distinct clinicopathological entity associated with macrotextured breast implants. The diagnostic workup of a patient suspected to have breast implant-associated ALCL includes cytological assessment of effusions and tissue biopsies of any masses or enlarged lymph nodes, with morphologic and immunophenotypic evaluation and possible flow cytometric and molecular testing. We report the case of a woman found to have breast implant-associated ALCL on fine needle aspirate and core biopsy, who on surgical resection, had extensive local disease with involvement of the resection margins and lymph nodes, requiring systemic treatment. We focus on the flow cytometric findings that identified a population of large cells on the CD30/side scatter dot plot and whose immunophenotype was consistent with breast implant-associated ALCL, highlighting the value of flow cytometry as an adjunct to morphological and immunophenotypic evaluation.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.007
GPT teacher head0.250
Teacher spread0.243 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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

Citations0
Published2022
Admission routes1
Has abstractyes

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