Spectrum of Complement-Mediated Thrombotic Microangiopathies: Pathogenetic Insights Identifying Novel Treatment Approaches
Bibliographic record
Abstract
Thrombotic microangiopathy (TMA) is a rare but severe disorder characterized by endothelial cell activation and thrombus formation. It manifests with the triad of hemolytic anemia, thrombocytopenia, and organ failure. Prompt diagnosis and treatment initiation are crucial for long-term outcome. TMA often manifests subsequent to infectious events, of which (enterohemorrhagic) Escherichia coli is the most frequently reported. TMA also occurs on the background of genetic/autoimmune defects in the complement system (atypical hemolytic uremic syndrome [aHUS]) and underlying conditions, such as pregnancy, transplantation, drugs, other glomerulopathies, vasculitides, or metabolic defects. Complement activation or defects in its regulation have now been described in an increasing number of acquired diseases with TMA. Coinciding with this expanding spectrum of complement-mediated diseases, the question arises which patients might benefit from a complement-targeted therapy. Success of therapy depends on the individual contribution of complement activation in disease pathogenesis. The advent of eculizumab, a monoclonal antibody that blocks terminal complement activation, has markedly improved outcome and quality of life in patients with aHUS. This review discusses the contribution of complement and highlights its complex interaction with inflammation, coagulation, and the endothelium. Treatment experiences focusing on eculizumab therapy are discussed in detail across the emerging spectrum of complement-mediated thrombotic microangiopathies.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".