The varieties of therapeutic experience: navigating treatment options for patients with PNH
Bibliographic record
Abstract
Paroxysmal nocturnal hemoglobinuria (PNH) is a rare, acquired disorder of complement dysregulation, predisposing patients to complications of intravascular hemolysis, thrombophilia, and marrow failure, with a high risk of mortality without treatment. Allogeneic stem cell transplantation is the only current cure but is typically reserved for marrow failure-predominant disease or when targeted therapies are not available. Terminal complement inhibition with eculizumab has significantly altered management and outcomes for patients with PNH, and the last several years have seen the development and approval of many new complement inhibitors with different molecular targets. Newer inhibitors may also provide options for extended time between doses, for self-administration, and for management of iatrogenic extravascular hemolysis, which can occur secondary to C5 inhibition. This essay reviews the various therapeutic options potentially available to PNH patients, the pros and cons of each treatment, considerations regarding the monitoring of side effects, and the possible complications, as well as breakthrough hemolysis and an approach to shared decision-making.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".