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Record W4321850936 · doi:10.14740/jh1081

Soft-Tissue Anaplastic Lymphoma Kinase-Positive Anaplastic Large Cell Lymphoma in a Child Unmasked by COVID-19

2023· article· en· W4321850936 on OpenAlexvenueno aff
Diego Alberto Lozano-Jaramillo, Esperanza Millan-Arreola, Oscar Omar Esquer-Cota, Jesus Manuel Lozano-Garcia, Miguel Alfonso Valenzuela-Espinoza

Bibliographic record

VenueJournal of Hematology · 2023
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsAnaplastic large-cell lymphomaMedicineAnaplastic lymphoma kinaseLymphomaPathologyDifferential diagnosisBiopsyLarge-cell lymphomaLarge cellLymph nodeNot Otherwise SpecifiedRhabdomyosarcomaSarcomaInternal medicineAdenocarcinomaCancer

Abstract

fetched live from OpenAlex

Anaplastic large cell lymphoma (ALCL) is children's most common mature T-cell neoplasm. The majority is positive for anaplastic lymphoma kinase (ALK). Initial presentation as a soft-tissue pelvic mass without nodal involvement is rare and can be easily misdiagnosed. We report a case of a 12-year-old male presenting with pain and movement restriction in the right extremity. Computed tomography (CT) scan revealed a solitary pelvic mass. Initial biopsy examination concluded rhabdomyosarcoma. After developing pediatric multisystemic inflammatory syndrome due to coronavirus disease 2019 (COVID-19), central and peripheral lymph node enlargement appeared. New cervical adenopathy and pelvic mass biopsies were performed. Immunohistochemistry concluded an ALK-positive ALCL with a small-cell pattern. The patient was treated with brentuximab-based chemotherapy and eventually improved. Differential diagnosis of pelvic masses in children and adolescents must include ALCL. An inflammatory trigger may promote the appearance of a typical nodal disease, previously absent. Attention is warranted during histopathological examination to avoid diagnostic errors.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.240
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.010
GPT teacher head0.281
Teacher spread0.270 · 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.

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

Citations3
Published2023
Admission routes1
Has abstractyes

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