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Record W2511415742 · doi:10.3747/co.23.3006

Concurrent Hypopituitarism and Leukemic Retinopathy in a Child with B-Precursor Acute Lymphoblastic Leukemia and Isolated Central Nervous System Relapse

2016· article· en· W2511415742 on OpenAlexvenueno aff
Kang‐Hsi Wu, Han‐Ping Wu, Hsin-Chin Lin, Chia-Han Wang, H. Y. Chen, Te‐Fu Weng, Cheng Peng, Yu‐Hua Chao

Bibliographic record

VenueCurrent Oncology · 2016
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHypopituitarismChemotherapyRadiation therapyRetinopathyPediatricsLeukemiaOncologyInternal medicineEndocrinology

Abstract

fetched live from OpenAlex

Hypopituitarism in leukemia is very rare. In addition, central nervous system (cns) relapse and leukemic retinopathy in childhood acute lymphoblastic leukemia (all) have declined with the use of modern systemic chemotherapy that includes cns prophylaxis. Here, we report the case of a 4-year-old girl who received chemotherapy and intrathecal therapy without cns radiation after a diagnosis of B-precursor all without cns involvement. Three months after chemotherapy completion, she presented with lower-extremity weakness and was diagnosed with an isolated cns relapse. Concurrent hypopituitarism and leukemic retinopathy were also found. After receiving craniospinal radiotherapy and systemic chemotherapy, her retinopathy and vision improved. She is now in complete remission, and she is still on chemotherapy according to the guideline from the Pediatric Oncology Group. Although rare, hypopituitarism and leukemic retinopathy should be taken into consideration in patients with cns involvement by leukemia.

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 score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
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 head0.017
GPT teacher head0.278
Teacher spread0.261 · 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
Published2016
Admission routes1
Has abstractyes

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