Bibliographic record
Abstract
Abstract Background and Aims Atypical HUS (aHUS) is a rare form of thrombotic microangiopathy (TMA) that results in complement-mediated damage of the microvascular endothelium, with renal impairment being the most common manifestation. Genetic defects result in over-activation of the alternative complement cascade and complement factor H (CFH) mutations are the most commonly detected. Due to incomplete penetrance, external factors ultimately trigger clinical manifestations of this disease in those who are genetically predisposed. Here, we describe an atypical first presentation of aHUS in an elderly female patient with rapidly worsening renal function and no obvious precipitating factor. She was successfully treated with eculizumab, a terminal complement cascade inhibitor, with biochemical improvement in her hemolytic parameters and renal function. Genetic testing later confirmed the presence of a pathogenic CFH mutation. This case highlights the role of genetic testing in all cases of suspected aHUS. Results A previously healthy 82-year-old female with normal baseline renal function presented to hospital with lower gastrointestinal bleeding and developed microangiopathic hemolytic anemia and rapidly worsening renal function requiring dialysis initiation. A renal biopsy demonstrated features compatible with thrombotic microangiopathy (Fig. 1). An extensive TMA workup including infectious panels, autoimmune serologies, malignancy screening, and ADAMTS levels returned normal. Eculizumab approval was acquired on an expedited basis and she was started on treatment. Two months later, her renal function and hemolytic parameters improved to the point of dialysis discontinuation. Her Blueprint Genetics HUS panel later returned, showing a pathogenic heterozygous missense variant of CFH. In light of her positive CFH genetic variant, she has received approval for ongoing eculizumab treatment and her case will be reviewed by the Ministry of Health annually for ongoing medication renewal. Conclusion Although aHUS is a rare condition, it is associated with a poor prognosis, with estimates of progression to end stage renal disease or death ranging between 50 to 80%, respectively [1]. The median initial age of aHUS presentation is 35 years old, with infection, pregnancy, autoimmune disease, and malignancy considered common precipitating factors for this disease [2]. This is an unusual case of a patient with a pathogenic CFH mutation who developed her first presentation of aHUS at age 82 with no clear precipitating factor. This case highlights the importance of considering the diagnosis of aHUS in patients with TMA, and the utility of genetic testing in helping to guide treatment for those with suspected aHUS.
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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) | 0.001 | 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".