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Record W2122121618 · doi:10.1080/080370500439335

Candesartan in Heart Failure - Assessment of Reduction in Mortality and Morbidity (CHARM) Study Programme

2000· article· en· W2122121618 on OpenAlexaff
K. Swedberg, M. Pfeffer, G. B. GRANGER, John J.V. McMurray, Salim Yusuf

Bibliographic record

VenueBlood Pressure · 2000
Typearticle
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsMcMaster University
Fundersnot available
KeywordsCandesartanMedicineHeart failureACE inhibitorInternal medicineCardiologyAngiotensin-converting enzymePopulationAngiotensin IIIntensive care medicineBlood pressure

Abstract

fetched live from OpenAlex

Heart failure is a major cause of death, hospital admissions and poor quality of life. It affects some 1-2% of the general population, increasing to up to 8% in people over 75 years of age. Although treatment with angiotensin-converting enzyme (ACE) inhibitors reduces symptoms and mortality, 50-70% of patients with heart failure still die within 5 years of diagnosis. There is thus clear scope for improving the treatment of patients with this condition. The CHARM programme is designed to define the clinical benefits of the long-acting angiotensin II type 1 (AT 1 ) receptor blocker, candesartan cilexetil, in a wide variety of patients with symptomatic heart failure. Candesartan cilexetil will be evaluated in three double-blind, randomized studies involving patients grouped according to left ventricular function and ACE inhibitor tolerance/intolerance.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.040
GPT teacher head0.339
Teacher spread0.299 · 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 designRandomized trial
Domainnot available
GenreEmpirical

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

Citations1
Published2000
Admission routes1
Has abstractyes

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