Bibliographic record
Abstract
Thrombotic microangiopathy (TMA) refers to phenotypically similar disorders, including hemolytic uremic syndromes (HUS) and thrombotic thrombocytopenic purpura (TTP). This review explores the role of the influenza virus as trigger of HUS or TTP. We conducted a literature survey in PubMed and Google Scholar using HUS, TTP, TMA, and influenza as keywords, and extracted and analyzed reported epidemiological and clinical data. We identified 25 cases of influenza-associated TMA. Five additional cases were linked to influenza vaccination and analyzed separately. Influenza A was found in 83%, 10 out of 25 during the 2009 A(H1N1) pandemic. Two patients had bona fide TTP with ADAMTS13 activity <10%. Median age was 15 years (range 0.5-68 years), two thirds were male. Oligoanuria was documented in 81% and neurological involvement in 40% of patients. Serum C3 was reduced in 5 out of 14 patients (36%); Coombs test was negative in 7 out of 7 and elevated fibrin/fibrinogen degradation products were documented in 6 out of 8 patients. Pathogenic complement gene mutations were found in 7 out of 8 patients tested (C3, MCP, or MCP combined with CFB or clusterin). Twenty out of 24 patients recovered completely, but 3 died (12%). Ten of the surviving patients underwent plasma exchange (PLEX) therapy, 5 plasma infusions. Influenza-mediated HUS or TTP is rare. A sizable proportion of tested patients demonstrated mutations associated with alternative pathway of complement dysregulation that was uncovered by this infection. Further research is warranted targeting the roles of viral neuraminidase, enhanced virus-induced complement activation and/or ADAMTS13 antibodies, and rational treatment approaches.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".