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Record W2333688516 · doi:10.1055/s-0031-1297165

Childhood Immune Thrombocytopenia: A Changing Therapeutic Landscape

2011· review· en· W2333688516 on OpenAlexaff
Vicky R. Breakey, Victor S. Blanchette

Bibliographic record

VenueSeminars in Thrombosis and Hemostasis · 2011
Typereview
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMedicineSplenectomyRituximabCommon variable immunodeficiencyAutoimmune lymphoproliferative syndromeSepsisPediatricsAutoimmune thrombocytopeniaEvans syndromeImmunologyLymphomaAutoimmune hemolytic anemiaPlateletAntibodySpleen

Abstract

fetched live from OpenAlex

Childhood immune thrombocytopenia (ITP) is generally a benign self-limiting disorder of young children with <10% of cases requiring regular platelet enhancing therapy at 1 year following diagnosis. Increasingly, children with newly diagnosed ITP, who have isolated thrombocytopenia and no atypical features in the history or physical examination, are managed with minimal investigation and observation alone. The role of up-front, short-course corticosteroid therapy without bone marrow aspiration in this subgroup of cases merits further investigation. For children with clinically significant chronic ITP, the timing of elective splenectomy and the role of splenectomy-sparing strategies such as rituximab continues to be debated. Management of children with combined autoimmune cytopenias secondary to systemic lupus erythematosus, common variable immunodeficiency, and the autoimmune lymphoproliferative syndrome is often a challenge. Splenectomy should be avoided in cases with documented immunodeficiencies because of the increased risk of overwhelming sepsis postsplenectomy. For these cases, as well as for children with resistant primary chronic ITP who have failed splenectomy, the role of therapies such as mycophenolate mofetil, sirolimus, and the thrombopoietins remains to be determined.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.991
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.063
GPT teacher head0.340
Teacher spread0.278 · 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 designOther design
Domainnot available
GenreReview

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

Citations29
Published2011
Admission routes1
Has abstractyes

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