Atypical hemolytic uremic syndrome: a nationwide Colombian pediatric series
Bibliographic record
Abstract
Abstract Background Atypical hemolytic uremic syndrome (aHUS) is a rare complement-mediated kidney disease with genetic predisposition and represents up to 10% of pediatric hemolytic uremic syndrome (HUS) cases. Few studies have evaluated aHUS in Latin American population. We studied a Colombian pediatric cohort to delineate disease presentation and outcomes. Methods A multicenter cohort of 27 Colombian children with aHUS were enrolled between 2010 to 2019. Patients were grouped by age at onset. Clinical features were compared using analysis of variance (ANOVA) and Fisher exact tests. Renal biopsy was performed on six patients who were suspected of having other renal diseases before aHUS diagnosis. Results Most patients were male (70%). The onset of aHUS occurred frequently before age 4 years (60%) and followed gastroenteritis as the main triggering event (52%). Age groups were comparable in clinical presentation, disease severity, treatment, and outcomes. Pulmonary involvement (67%) was the main extrarenal manifestation. A higher frequency was observed in the 1–7 age group (p = 0.01). Renal biopsies were as follows: three had membranoproliferative glomerulonephritis (MPGN) type I, one MPGN type III, one C3-glomerulonephritis, and one rapidly progressive glomerulonephritis. Genetic screening was available in five patients and identified 2x CFHR5 , 2xMCP , and 1xADAMTS-13/THBD mutations. A total of 15 relapses were seen, of which 8 (72%) occurred in the 1–7 age group. The renal outcome was not significantly different regardless of age group. Conclusion In our cohort, we observed a relatively high frequency of extrarenal involvement at first presentation represented by pulmonary manifestations. The renal prognosis at initial presentation was worse than in previous reports.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".