Bibliographic record
Abstract
Immune-mediated thrombocytopenia Immune-mediated thrombocytopenia is the term used to describe the group of thrombocytopenic disorders in which platelets are destroyed by immune mechanisms. The thrombocytopenia develops when the rate of platelet destruction is greater than the ability of the megakaryocytes in the bone marrow to compensate with increased platelet production. Different investigators have attempted to quantitate this rate of platelet destruction; however, the estimates are relatively imprecise. Many investigators feel that the marrow can compensate at least fivefold without a detectable fall in the platelet count. The platelet destruction in immune-mediated thrombocytopenia can be caused by autoantibodies, alloantibodies, and immune complexes. These are illustrated schematically in Fig. 36.1. Most episodes of immune-mediated platelet destruction are caused by the binding of IgG antibodies to platelet-specific membrane components. General approach to a patient with suspected immune-mediated thrombocytopenia When a patient presents with suspected immune-mediated thrombocytopenia, the physician must simultaneously confirm that the patient is thrombocytopenic, begin to determine the general mechanism responsible for the thrombocytopenia, and determine what, if any, treatment is required. Although these various aspects of thrombocytopenia are covered elsewhere in this book, it is appropriate to briefly address each question. Is the patient thrombocytopenic? Today, most platelet counts are performed using automated particle counters. With cutbacks in budgets for health care, it has become far less common for every blood film of suspected thrombocytopenic patients to be examined, and even less common for manual (phase-contrast) platelet counts to be performed.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.011 |
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".