How we treat paroxysmal nocturnal hemoglobinuria: A consensus statement of the Canadian PNH Network and review of the national registry
Bibliographic record
Abstract
Paroxysmal nocturnal hemoglobinuria (PNH) is a rare hematologic disease characterized by intravascular hemolysis, thrombophilia, and marrow failure. Its phenotype is due to absent or reduced expression of GPI-linked complement regulators and subsequent sensitivity of hematopoietic cells to complement-mediated damage and lysis. Introduction of the terminal complement inhibitor eculizumab drastically improved outcomes in PNH patients; however, despite this improvement, there remain several challenges faced by PNH patients and physicians who care for them. One of the most important is increasing awareness of the heterogeneity with which patients can present, which can lead to significant delays in recognition. Data from the Canadian PNH Registry are presented to demonstrate the variety of presenting symptoms. In Canada, geography precludes consolidation of care to just a few centers, so management is distributed across academic hospitals, linked together as the Canadian PNH Network. The Network over the last several years has developed educational programs and clinical checklists and has worked to standardize access to diagnostics across the country. Herein, we address some of the common diagnostic and therapeutic challenges faced by PNH physicians and give our recommendations. Gaps in knowledge are also addressed, and where appropriate, consensus opinion is provided.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| 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".