Plasma-derived biological medicines used to promote haemostasis
Bibliographic record
Abstract
Several biological medicines derived from human and animal plasmas can effectively improve haemostasis in individuals with inherited or acquired defects in haemostasis. Factor VIII and factor VIII/vWF and factor IX concentrates are used to treat haemophilia A, von Willebrand disease and hemophilia B respectively. Cryoprecipitates are used to treat hypofibrinogenemia and von Willebrand disease where desmopressin (DDAVP) is ineffective or when plasma-derived factor VIII/vWF concentrates are unavailable. Thrombin-containing topical haemostatic agents and fibrin sealants are used to control perioperative bleeding. Intravenous immunoglobulin has several uses, including management of patients with autoimmune thrombocytopenias and patients with acquired factor VIII deficiency. Similar to most protein-based biological medicines, all the above products can elicit some level of antibody response, with clinical consequences that vary from mild anaphylaxis to loss of product efficacy. An ongoing potential safety concern with any biological medicine derived from blood/plasma is transmission of blood-borne pathogens. This safety concern has lessened significantly in the past decade as a result of the institution of more effective pre- and post-donation screening that tests for potential pathogens, and institution of pathogen reduction strategies to which many plasma-derived biological medicines are now routinely subjected. This article considers the manufacture, standardization, clinical efficacy and adverse event profiles of the plasma-derived biological medicines currently used to promote haemostasis in patients with inherited or acquired functional defects in haemostasis. It also considers approaches employed to minimize infectivity of biological medicines derived from human and animal plasmas and to manage patients who develop antibodies (inhibitors) to clotting factor concentrate infusions.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".