The role of recombinant activated factor VII in neurosurgery: hope or hype?
Bibliographic record
Abstract
Recombinant activated factor VII (rFVIIa) is a relatively new pharmaceutical agent developed for use in patients with hemophilia in whom inhibitors to clotting factors VIII or IX have developed. Use of this drug has become common in recent years because of its efficacy and safety in patients with coagulation disorders as well as in patients who are at high risk for thromboembolism, even when other means of establishing hemostasis have failed. The use of rFVIIa in neurosurgery has lagged behind its use in other fields, although there is a growing body of literature on such uses. In this article the authors review the history and science of rFVIIa as well as dosing and safety information. Various uses pertinent to the neurosurgeon are reviewed, including the treatment of patients with coagulation disorders, those suffering trauma, and those with perioperative hemorrhage, intracerebral hemorrhage, or subarachnoid hemorrhage. Based on their review of the uses of rFVIIa, the authors conclude that rFVIIa is a safe and effective agent with the potential to revolutionize the treatment of neurosurgical patients with hemorrhage. Cost is a major impediment to the widespread use of rFVIIa, and there is some evidence that its use in the neurosurgical population may be subject to higher risk than in other populations studied thus far. Although further study is needed to better delineate the safety and efficacy of the drug in many nonlicensed uses, it is clear that rFVIIa is an agent with tremendous promise.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".