Striving for excellence in paroxysmal nocturnal hemoglobinuria in Canada: the EPIC program
Bibliographic record
Abstract
Abstract Paroxysmal nocturnal hemoglobinuria (PNH) is a rare, life-threatening disease marked by complement-mediated intravascular hemolysis, thrombosis, and marrow failure, often leading to nonspecific symptoms like fatigue and dyspnea. This can lead to delayed diagnosis, impacting patients’ quality of life (QoL) and survival. The Canadian PNH Network (cPNHn) aims to aid diagnosis using the “CATCH criteria” (cytopenias, aplastic anemia/myelodysplasia, thrombosis, Coombs-negative hemolysis, hemoglobinuria). This quality improvement study at University Health Network (UHN) and Sunnybrook Health Sciences Centre (SHSC) aimed to identify care gaps, assess diagnosis and treatment initiation times, and develop strategies for improvement. Retrospective chart reviews and interviews were conducted on PNH patients. Findings from 28 chart reviews and 23 interviews showed a mean age at diagnosis of 45.1 years, with fatigue being the most common symptom. Patients consulted a median of 4 healthcare providers before diagnosis, experiencing a median delay of 168 months from symptom onset to referral. Interviews highlighted diverse patient experiences and emphasized the positive impact of anti-complement therapy on quality of life. Despite challenges posed by COVID-19, virtual visits maintained care quality. This study highlighted diverse patient journeys and delays in PNH assessment, influenced by participants’ backgrounds and diagnostic technology availability. This study underscores the importance of tailored interventions to address the complex needs of PNH patients and improve their overall healthcare experience. Our study demonstrated that the patient participants are key stakeholders of their care, who are often under-represented in our healthcare system due to the rarity of the disease.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".