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Record W2080862159 · doi:10.1136/bmj.329.7463.420-e

Study warns of danger of combining spironolactone and ACE inhibitors in heart patients

2004· article· en· W2080862159 on OpenAlexaboutno aff
Scott Gottlieb

Bibliographic record

VenueBMJ · 2004
Typearticle
Languageen
FieldMedicine
TopicPotassium and Related Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsSpironolactoneMedicineComputer scienceHeart failureData scienceInternal medicine

Abstract

fetched live from OpenAlex

The diuretic spironolactone can cause dangerous hyperkalaemia in patients who are also taking angiotensin converting enzyme (ACE) inhibitors, another drug that, like spironolactone, is used to treat congestive heart failure. After the publication of a major heart study that promoted the use of spironolactone, prescribing rose, but so did cases of hyperkalaemia, according to Dr David Juurlink, a clinical pharmacologist at the University of Toronto and author of a new study that found a threefold increase in the rates of admission to hospital for high potassium levels across Ontario and a twofold increase in deaths involving high potassium levels ( New England Journal of Medicine 2004;351:543-51). The randomised aldactone evaluation study (RALES), which was reported in 1999, found …

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.188

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.014
GPT teacher head0.291
Teacher spread0.277 · 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
Published2004
Admission routes1
Has abstractyes

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