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Record W2016693483 · doi:10.4021//jmc.v3i2.506

Case Review: Idiopathic Thrombocytopenic Purpura

2012· article· en· W2016693483 on OpenAlexvenueno aff
Ronny Cohen, Christine Garcia, Derrick Mena, Mariely Castellanos, Li-The Wu

Bibliographic record

VenueJournal of Medical Cases · 2012
Typearticle
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineThrombocytopenic purpuraAsymptomaticThrombopoietinPlateletImmune thrombocytopeniaSplenectomyPurpura (gastropod)Internal medicineGastroenterologyImmunologySpleen

Abstract

fetched live from OpenAlex

Idiopathic Thrombocytopenic Purpura (ITP) is defined as a hematologic disorder, characterized by isolated thrombocytopenia without a clinically apparent cause. The major causes of accelerated platelet consumption include immune thrombocytopenia, decreased bone marrow production and increased splenic sequestration. The clinical presentation may be acute with severe bleeding, or insidious with slow development with mild or no symptoms. The initial laboratory tests useful at the first visit to predict future diagnosis were erythrocyte count, leukocyte count, anti-glycoprotein (GP) IIb/IIIa antibodies, reticulated platelets, plasma thrombopoietin level. Treatment should be restricted to those patients with moderate or severe thrombocytopenia who are bleeding or at risk of bleeding. It should be limited in duration unless demonstrated that symptomatic thrombocytopenia persists. Patients with mild, asymptomatic thrombocytopenia, discovered incidentally on a routine blood count, should not be treated. We present a case report on ITP and summarize the key points in the diagnosis and management of ITP. doi:10.4021/jmc506w

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)0.003
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: none
Teacher disagreement score0.013
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0060.004
Science and technology studies0.0020.001
Scholarly communication0.0020.003
Open science0.0020.002
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.0130.008

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 head0.054
GPT teacher head0.356
Teacher spread0.301 · 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

Citations1
Published2012
Admission routes1
Has abstractyes

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