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Treatment of High‐Risk African American Patients: Left Ventricular Dysfunction, Heart Failure, Renal Disease, and Postmyocardial Infarction

2003· article· en· W2047787134 on OpenAlexaff
Rohit Arora, Luther T. Clark, Malcolm P. Taylor

Bibliographic record

VenueJournal of Clinical Hypertension · 2003
Typearticle
Languageen
FieldMedicine
TopicBlood Pressure and Hypertension Studies
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsMedicineHeart failureInternal medicineMyocardial infarctionCardiologyStroke (engine)ACE inhibitorRegimenInfarctionAngiotensin-converting enzymeBlood pressure

Abstract

fetched live from OpenAlex

African Americans experience more mortality and morbidity from hypertension-related complications than other racial groups. Although angiotensin-converting enzyme (ACE) inhibitors have clearly been shown to reduce mortality and morbidity in hypertensive white patients with heart failure, renal dysfunction, stroke, and acute myocardial infarction, African American patients have been underrepresented in these trials. The lack of direct evidence of the benefit of ACE inhibitors in these individuals and the suggestion that ACE inhibitors are less efficacious in this group has resulted in a reluctance to use ACE inhibitors in African Americans. However, retrospective analyses in black patients with heart failure and a recent randomized clinical trial in African Americans with renal dysfunction suggest that a regimen based on ACE inhibitors is efficacious in this racial group. Although diuretics remain first-line therapy, data now suggest that ACE inhibitors provide additional benefit and should be considered for use in patients with high-risk complications regardless of race.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.144
Threshold uncertainty score0.500

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
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 head0.025
GPT teacher head0.292
Teacher spread0.266 · 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.

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

Citations2
Published2003
Admission routes1
Has abstractyes

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