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Record W2010357516 · doi:10.1160/th09-04-0225

Glanzmann’s thrombasthenia (defective platelet integrin αIIb-β3): proposals for management between evidence and open issues

2009· review· en· W2010357516 on OpenAlexaff
Giovanni Di Minno, Matteo Nicola Dario Di Minno, Man-Chiu Poon, Antonio Coppola

Bibliographic record

VenueThrombosis and Haemostasis · 2009
Typereview
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineGlanzmann's thrombastheniaThrombastheniaGuidelinePlatelet disorderPlateletSurgeryIntensive care medicinePediatricsInternal medicinePathologyPlatelet aggregation

Abstract

fetched live from OpenAlex

Glanzmann's Thrombasthenia (GT) is a rare autosomal recessive bleeding disorder, characterized by a quantitative or qualitative defect of platelet surface alpha(IIb)-beta(3) integrin. Presently, no specific guideline/algorithm for clinical management for GT is available. Due to the rarity and heterogeneity of inherited platelet abnormalities, recommendations and guidelines are based on reports from opinions and clinical experience of panel of experts, and refer to the general management of platelet disorders. Based on the limited evidence in the area and on the strategies in clinical settings of inherited/acquired platelet defects, proposals for management of minor bleeding, moderate/major bleeding unresponsive to conservative management, major surgery, minor surgery and dental procedures for GT patients without, or with anti-platelet isoantibodies are reported. In addition to life-style advices and continuous patient education programs, when and how to employ/combine local measures, antifibrinolytic agents, hormone treatment, platelet transfusions and recombinant activated Factor VII is described. The prospective collection of treatments in GT patients recently established (Glanzmann's Thrombasthenia Registry, GTR), based on a careful definition of clinical settings and outcomes, is likely to provide newer insight for optimising clinical management in GT.

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)0.001
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 score0.980
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.251
GPT teacher head0.470
Teacher spread0.219 · 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

Citations60
Published2009
Admission routes1
Has abstractyes

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