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What is in a name: defining pediatric refractory ITP

2024· article· en· W4401012430 on OpenAlexaff
Taizo A. Nakano, Amanda B. Grimes, Robert J. Klaassen, Michele P. Lambert, Cindy Neunert, Jennifer Rothman, Kristin A. Shimano, Christina Amend, Megan Askew, Sherif M. Badawy, Jillian M. Baker, Vicky R. Breakey, Shelley E. Crary, Monica Davini, Stephanie FritchLilla, Megan Gilbert, Taru Hays, Kerry Hege, Kirsty Hillier, Amanda Jacobson‐Kelly, Shipra Kaicker, Taylor Olmsted Kim, Manpreet Kochhar, Thierry Leblanc, Marie Martinelli, Maria Araceli Garcia Núñez, Allison Remiker, Ruchika Sharma, Rachael F. Grace

Bibliographic record

VenueBlood Advances · 2024
Typearticle
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsMcMaster UniversitySickKids FoundationHospital for Sick ChildrenSt. Michael's HospitalChildren's Hospital of Eastern Ontario
FundersNational Institutes of HealthSwedish Orphan BiovitrumHorizon TherapeuticsArgenxbluebird bioAgios PharmaceuticalsFoundation for Women and Girls with Blood DisordersSanofiPfizer
KeywordsMedicineImmune thrombocytopeniaRefractory (planetary science)DiseaseIntensive care medicinePediatricsTerminologyClinical trialInternal medicinePlatelet

Abstract

fetched live from OpenAlex

ABSTRACT: There are no agreed upon terminology to define "refractory" pediatric immune thrombocytopenia (ITP). Guidelines are therefore limited to arbitrary and outdated definitions. The Pediatric ITP Consortium of North America held a meeting in 2023 to define this entity. With 100% agreement, the faculty established that pediatric ITP that is refractory to emergent therapy could be defined as no platelet response after treatment with all eligible emergent pharmacotherapies. With 100% agreement, the working group established that pediatric patients with ITP that continue to demonstrate high disease burden and/or no platelet response despite treatment with multiple classes of disease-modifying therapies represent a challenging subset of ITP. These patients are at higher risk of ongoing disease burden and merit additional investigation as well as consideration for clinical trials or novel therapies. Future efforts to define disease burden and disease response will be completed in collaboration with the ITP International Working Group.

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)0.003
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0020.002
Scholarly communication0.0030.004
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.009
GPT teacher head0.287
Teacher spread0.277 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations8
Published2024
Admission routes1
Has abstractyes

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