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The Role of Angiotensin II Receptor Blockers in the Treatment of Heart Failure Patients

2003· review· en· W2060024674 on OpenAlexaff
Michael Theal, Catherine Demers, Robert S. McKelvie

Bibliographic record

VenueCongestive Heart Failure · 2003
Typereview
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsMcMaster UniversityHamilton Health SciencesHamilton General Hospital
Fundersnot available
KeywordsMedicineHeart failureSpironolactoneAngiotensin Receptor BlockersAngiotensin IIAngiotensin-converting enzymeAngiotensin receptorInternal medicineClinical trialCardiologyRandomized controlled trialPharmacologyACE inhibitorAngiotensin II receptor type 1ReceptorBlood pressure

Abstract

fetched live from OpenAlex

Evidence from large, randomized, controlled clinical trials supports the use of angiotensin-converting enzyme (ACE) inhibitors, beta blockers, and spironolactone to reduce mortality and morbidity. Despite these effective therapies, event rates related to heart failure remain high. Although ACE inhibitors reduce angiotensin II production, they do not fully suppress the increased angiotensin II production in heart failure. Angiotensin II receptor blockers (ARBs) directly block the effect of angiotensin II, derived from any source, at the receptor level and have the potential to be as effective or even more effective than ACE inhibitors. The results of a number of clinical studies have demonstrated ARBs are effective and well tolerated. However, no studies have demonstrated a convincing decrease in mortality with ARB use, although a decrease has been observed for heart failure hospitalization. The results from further studies are awaited to clarify the role of ARBs in the treatment of heart failure.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.021
GPT teacher head0.290
Teacher spread0.269 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations7
Published2003
Admission routes1
Has abstractyes

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