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Congenital platelet disorders: overview of their mechanisms, diagnostic evaluation and treatment

2006· review· en· W2061963455 on OpenAlexaff
Catherine P.M. Hayward, A. Koneti Rao, Marco Cattaneo

Bibliographic record

VenueHaemophilia · 2006
Typereview
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPlateletMedicinePlatelet disorderCoagulationPlatelet activationPopulationImmunologyBioinformaticsInternal medicineBiology

Abstract

fetched live from OpenAlex

The bleeding problems associated with common and rare inherited platelet disorders illustrate the importance of platelets to normal haemostasis. At sites of injury, platelets normally adhere, undergo activation, secretion and aggregate formation, and they provide the membrane surface for the assembly of coagulation to generate thrombin. The causes of inherited disorders that alter platelet haemostatic functions are quite diverse, ranging from defects in receptors critical to platelet adhesion and aggregation, to defects in signalling molecules or in transcription factors important for production of functional platelets. The mechanisms of impaired platelet function are largely unknown for the more common disorders that alter platelet activation, secretion and the secondary wave of platelet aggregation. The diagnostic evaluation of congenital platelet disorders has been challenging as some 'platelet-type' bleeding symptoms, such as bruising, are quite common in the general population. Moreover, the diagnostic tests used by clinical laboratories to evaluate disorders of platelet function have not been standardized. In individuals recognized to have an inherited defect in platelet function, therapy is important for controlling and preventing bleeding episodes. Presently, there are a number of choices to consider for the management of bleeding symptoms, including menorrhagia. This paper reviews the causes, diagnostic evaluation and therapies for common and rare congenital platelet disorders.

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 score0.993
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
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 head0.081
GPT teacher head0.353
Teacher spread0.272 · 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

Citations123
Published2006
Admission routes1
Has abstractyes

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