Identification of Patients with Potential Undiagnosed Atypical Hemolytic Uremic Syndrome (aHUS) in the North American Pediatric Renal Trials and Collaborative Studies (NAPRTCS) Registry
Bibliographic record
Abstract
Background: Atypical Hemolytic Uremic Syndrome (aHUS) is a rare disease characterized by thrombocytopenia, microangiopathic hemolytic anemia, and impaired kidney function. Diagnosis of aHUS is complicated by its similarity to other forms of thrombotic microangiopathy (TMA). The recognition of aHUS has become more commonplace in the last 10 years due to advancements in laboratory diagnostics and targeted complement inhibition. Although acute presentation with fulminant TMA are readily diagnosed, more indolent presentations may not be recognized as aHUS but may progress if untreated to end-stage kidney disease. Methods: Potential participants were identified from the 3 NAPRTCS registry arms through a query of underlying diagnoses that could be associated with TMA or unknown etiology and transplant eligibility (defined as eGFR <30 ml/min/1.73m2, history of maintenance dialysis or kidney transplant). Identified participants were eligible if they had evidence of TMA (thrombocytopenia, schistocytes, decreased hemoglobin levels, elevated lactate dehydrogenase, and/or decreased haptoglobin levels). Enrollees were evaluated for evidence of thrombocytopenia and severe anemia as a marker of microangiopathic hemolysis. Major organ symptoms and growth factors (height or weight z-score <-2.0), were also reviewed at the time of potential TMA. Results: Ninety-five participants were identified in the query of diagnosis and transplant eligibility. Thirty-three (35%) participant records from 9 NAPRTCS centers were available for retrospective review and had at least one marker of potential TMA. The most common CKD diagnoses were AKI (27%), Lupus (27%) and unknown (22%). They were 55% biological female and median age at enrollment was 15 years. Thrombocytopenia OR microangiopathic hemolysis were each suspected in 74% of participants, while 42% had evidence of both. Major organ involvement most frequently identified at time of suspected TMA episodes included cardiac (hypertension; 31%) and gastrointestinal (19%), while 44% of participants had evidence of growth failure or were underweight. Conclusions: This analysis shows that there may be a higher prevalence of aHUS in the NAPRTCS registries than was previously thought. Funding: Commercial Support - Alexion Pharmaceuticals, Inc.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".