The top clinical trial opportunities in therapeutic apheresis and neurology
Bibliographic record
Abstract
OBJECTIVE: The National Heart, Lung, and Blood Institute, of The National Institutes of Health, convened the 2012 State-of-the-Science Symposium in therapeutic apheresis (TA) with the goals of identifying and prioritizing future research concept proposals to optimize the use of TA over the next decade. METHODS: Six subcommittees, including neurology, were formed based on organ system, pathophysiology, and technology/special considerations. The subcommittees consisted of physicians, clinical subject matter experts, and basic scientists. Each subcommittee developed concept proposals that were presented, evaluated, and prioritized based on scientific importance, clinical significance, and feasibility. RESULTS: The neurology subcommittee developed eight concept proposals. The proposals include therapeutic plasma exchange (TPE) in neuromyelitis optica; TPE versus intravenous immunoglobulin (IVIG) in anti-muscle specific kinase associated myasthenia gravis, severe acute disseminated encephalomyelitis, and anti-NMDA encephalitis; extracorporeal photopheresis in relapsing remitting multiple sclerosis and polymyositis; fibrinogen/low-density lipoprotein apheresis in idiopathic sudden sensorineural hearing loss; and creation of a rare neurologic disease registry and biorepository. CONCLUSIONS: Key clinical research priorities to evaluate and optimize the use of TA on selected neurologic disorders exist. The research opportunities if addressed would provide evidence-based data to inform the care of patients with these selected neurologic diseases.
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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 | 0.200 | 0.137 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.014 | 0.011 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.010 | 0.013 |
| Insufficient payload (model declined to judge) | 0.013 | 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".