Characterization of patients with <scp>aHUS</scp> and associated triggers or clinical conditions: A Global <scp>aHUS</scp> Registry analysis
Why this work is in the frame
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Bibliographic record
Abstract
INTRODUCTION: Atypical haemolytic uremic syndrome (aHUS) is a rare form of thrombotic microangiopathy (TMA) associated with complement dysregulation; aHUS may be associated with other 'triggers' or 'clinical conditions'. This study aimed to characterize this patient population using data from the Global aHUS Registry, the largest collection of real-world data on patients with aHUS. METHODS: Patients enrolled in the Global aHUS Registry between April 2012 and June 2021 and with recorded aHUS-associated triggers or clinical conditions prior/up to aHUS onset were analysed. aHUS was diagnosed by the treating physician. Data were classified by age at onset of aHUS (< or ≥18 years) and additionally by the presence/absence of identified pathogenic complement genetic variant(s) and/or anti-complement factor H (CFH) antibodies. Genetically/immunologically untested patients were excluded. RESULTS: 1947 patients were enrolled in the Global aHUS Registry by June 2021, and 349 (17.9%) met inclusion criteria. 307/349 patients (88.0%) had a single associated trigger or clinical condition and were included in the primary analysis. Malignancy was most common (58/307, 18.9%), followed by pregnancy and acute infections (both 53/307, 17.3%). Patients with an associated trigger or clinical condition were generally more likely to be adults at aHUS onset. CONCLUSION: Our analysis suggests that aHUS-associated triggers or clinical conditions may be organized into clinically relevant categories, and their presence does not exclude the concurrent presence of pathogenic complement genetic variants and/or anti-CFH antibodies. Considering a diagnosis of aHUS with associated triggers or clinical conditions in patients presenting with TMA may allow faster and more appropriate treatment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 it