Glanzmann’s thrombasthenia (defective platelet integrin αIIb-β3): proposals for management between evidence and open issues
Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".