Examination of genetic variants involved in generation and biodisposition of kinins in patients with angioedema
Bibliographic record
Abstract
BACKGROUND: Angioedema (AE) is idiopathic in the majority of cases. We studied patients with AE for genetic variants of proteins involved with bradykinin generation and biodisposition. METHODS: One hundred sixty one patients with AE were recruited at a university hospital clinic. Patients were categorized according to the proposed pathogenesis of AE: low C1 inhibitor (C1-INH) and C4 levels, autoimmune disease, cancer, angiotensin-converting enzyme (ACE) inhibitor-induced, nonsteroidal antiinflammatory drug (NSAID)-induced, or idiopathic. In addition, each patient had a blood sample analyzed for a complement profile and enzymes (C1-INH and C4). Fifty-two of the patients were tested for genetic variants in factor XII, plasminogen-activator inhibitor-1 (PAI-1), ACE, and aminopeptidase P (APP). RESULTS: The cause of angioedema was identified in 59/161 (37%) of the cases: 3 (2%) patients had a low plasma C1-INH and C4; 20 (12%) were ACE inhibitor-induced; 12 (7%) were associated with autoimmune disorders; 7 (4%) were associated with malignancy; and 17 (11%) were associated with NSAIDs. In the remaining 102 (63%) patients the cause of angioedema was idiopathic. Of 52 patients with genetic analysis, 13 (25%) had a genetic variant in APP, 10 (19%) in ACE, 13 (25%) in PAI-1, and 0 in Factor XII. CONCLUSIONS: In addition to related diseases and medications causing AE, certain genetic variants encoding proteins involved in bradykinin generation and/or catabolism pathways may be involved in the pathogenesis of AE.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".