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Record W4313254692 · doi:10.1002/pbc.30173

Pediatric refractory immune thrombocytopenia: A systematic review

2022· review· en· W4313254692 on OpenAlexaff
Layan Ibrahim, Selina X. Dong, Katie O’Hearn, Amanda B. Grimes, Shipra Kaicker, Stephanie FritchLilla, Vicky R. Breakey, Rachael F. Grace, Jeffrey D. Lebensburger, Robert J. Klaassen, Michele P. Lambert

Bibliographic record

VenuePediatric Blood & Cancer · 2022
Typereview
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsMcMaster UniversityChildren's Hospital of Eastern OntarioUniversity of Ottawa
Fundersnot available
KeywordsMedicineImmune thrombocytopeniaPediatricsIntensive care medicineRefractory (planetary science)MEDLINEPlateletImmunology

Abstract

fetched live from OpenAlex

Pediatric immune thrombocytopenia (ITP) is an acquired disorder associated with autoimmune destruction and impairment of platelet production in children. Some children exhibit poor or transient response to ITP-directed treatments and are referred to as having refractory ITP (rITP). There is currently no consensus on the definition of rITP, nor evidence-based treatment guidelines for patients with rITP. After a survey of pediatric ITP experts demonstrated lack of consensus on pediatric rITP, we pursued a systematic review to examine the reported clinical phenotypes and treatment outcomes in pediatric rITP. The search identified 253 relevant manuscripts; following review, 11 studies proposed a definition for pediatric rITP with no consensus amongst them. Most definitions included suboptimal response to medical management, while some outlined specific platelet thresholds to define this suboptimal response. Common attributes identified in this study should be used to propose a comprehensive definition, which will facilitate outcome comparisons of future rITP studies.

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)0.002
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: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0070.007
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.042
GPT teacher head0.342
Teacher spread0.300 · 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 designSystematic review
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

Citations17
Published2022
Admission routes1
Has abstractyes

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