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Record W2121005224 · doi:10.1517/14656566.6.11.1851

Acute adverse reactions associated with angiotensin-converting enzyme inhibitors: genetic factors and therapeutic implications

2005· review· en· W2121005224 on OpenAlexaff
Borzoo Nikpoor, Qing Duan, Guy A. Rouleau

Bibliographic record

VenueExpert Opinion on Pharmacotherapy · 2005
Typereview
Languageen
FieldMedicine
TopicCoagulation, Bradykinin, Polyphosphates, and Angioedema
Canadian institutionsHôpital Notre-DameMcGill UniversityMcGill Genome Centre
Fundersnot available
KeywordsAngioedemaMedicineBradykininAngiotensin-converting enzymeAdverse effectEnzymePharmacologyBioinformaticsInternal medicineBiochemistryBlood pressureBiologyReceptor

Abstract

fetched live from OpenAlex

Angiotensin-converting enzyme inhibitors (ACEIs) have been used in the treatment of various cardiovascular diseases. Despite the therapeutic benefits of ACEIs, there are several reported side effects, including chronic cough, angioedema and anaphylactoid reactions. These adverse events cannot be explained by the vasodilatory effects of this group of medications. Preliminary studies have shown that patients with a history of developing these side effects have a lower activity of an enzyme called aminopeptidase-P. This enzyme has an important role in degrading bradykinin. This defect in enzymatic activity can be partially explained by genetic variation. Using genome-wide screening strategies, the locus (loci), gene(s) and untimely polymorphisms that explain the low enzymatic activity and side effects can be identified.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.991
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.072
GPT teacher head0.384
Teacher spread0.312 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations29
Published2005
Admission routes1
Has abstractyes

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