Thrombotic microangiopathies: new insights and new challenges
Bibliographic record
Abstract
PURPOSE OF REVIEW: Thrombotic microangiopathies (TMAs) manifest as a spectrum of related disorders in the form of thrombocytopenic purpura (TTP) and hemolytic uremic syndrome (HUS). New data on both diseases support more and more the relatedness of the disorders and reveal related pathomechanisms, which, however, manifest in different organs. TTP develops primarily at neurological sites, and also in the kidney, and HUS is a kidney disease. In TTP thrombi formation occurs subsequently to the release of multimers of von Willebrand factor (vWF), and in HUS endothelial cell damage is considered the reason for complement and platelet activation leading to thrombus formation. RECENT FINDINGS: Genetic mutations are associated with both disorders: in TTP the ADAMTS13 gene, the vWF cleaving protease, is affected, and in HUS several complement genes are mutated. In addition autoimmune forms, with acquired, de-novo generated inhibitors in the form of autoantibodies exist for both disorders, affecting ADAMTS13 in TTP or the central complement inhibitor factor H in HUS. In HUS autoantibodies can develop in the context of a specific mostly homozygous chromosomal deletion that represents a new subform of the disease, which is termed DEAP-HUS (deficient for CFHR proteins and autoantibody positive HUS). SUMMARY: As the underlying disease mechanisms of TMA are now being better understood new options for a more precise diagnosis, improved therapy and prognosis for kidney transplantation become available for the benefit of patients. Here we summarize the recent developments in this rapidly progressing field.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".