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Record W4409649755 · doi:10.1080/09273948.2025.2495070

Successful Treatment of Ocular Post-Transplant Lymphoproliferative Disorder with Obinutuzumab in an 8-Year-Old Boy Following Kidney Transplant: A Case Report

2025· article· en· W4409649755 on OpenAlexaff
Charlotte Lussier, Cynthia L Larche, Julie Vadboncoeur

Bibliographic record

VenueOcular Immunology and Inflammation · 2025
Typearticle
Languageen
FieldMedicine
TopicViral-associated cancers and disorders
Canadian institutionsNOSM UniversityUniversité de Montréal
Fundersnot available
KeywordsMedicinePost-transplant lymphoproliferative disorderKidney transplantLymphoproliferative disordersObinutuzumabOrgan transplantationKidney transplantationKidneyPediatricsInternal medicineDermatologyRituximabTransplantationLymphoma

Abstract

fetched live from OpenAlex

PURPOSE: To report a case of an eight-year-old boy who developed an intraocular recurrence of lymphoproliferative disorder following a kidney transplant. METHODS: Retrospective single case report. RESULTS: The patient initially presented with systemic post-transplant lymphoproliferative disorder (PTLD), which later recurred as a masquerade syndrome with iris nodules and granulomatous uveitis. Initial treatment with systemic rituximab led to recurrence after 6 months. Complete recurrence resolution of both ocular and systemic disease was achieved with obinutuzumab. CONCLUSION: This case highlights the importance of early recognition and multidisciplinary management in PTLD. It also emphasizes the delicate balance between immunosuppression and antitumor therapy in transplant recipients, aiming to preserve graft function while effectively treating PTLD.

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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.004
GPT teacher head0.240
Teacher spread0.235 · 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
Published2025
Admission routes1
Has abstractyes

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