MétaCan
Menu
Back to cohort
Record W2036066969 · doi:10.1136/bmj.g6242

Antibiotics and sudden death in adults taking renin-angiotensin system blockers

2014· letter· en· W2036066969 on OpenAlexaffabout
Mahyar Etminan, James M. Brophy

Bibliographic record

VenueBMJ · 2014
Typeletter
Languageen
FieldMedicine
TopicPotassium and Related Disorders
Canadian institutionsChild and Family Research InstituteMcGill UniversityUniversity of British Columbia
Fundersnot available
KeywordsHyperkalemiaMedicineOdds ratioDrugCohortIntensive care medicineEmergency medicinePharmacologyInternal medicine

Abstract

fetched live from OpenAlex

Is there a cause for concern? Adverse drug reactions have been associated with up to 10% of hospital admissions in older adults,1 a considerable number of which involve drug-drug interactions. Traditionally, information about drug-drug interactions was of poor quality, usually isolated case reports or small uncontrolled case series, resulting in much uncertainty about any clinical relevance. In recent years, large administrative databases that are linkable to health outcomes data have allowed investigators to better quantify rare drug-drug interactions and examine their effect on both morbidity and mortality. In the linked paper (doi:10.1136/bmj.g6196), Fralick and colleagues examined the risk of sudden death in users of both co-trimoxazole and renin-angiotensin system blockers (RASBs), two potassium sparing drugs.2 In an earlier study, the same authors reported that their joint administration was associated with a sevenfold increase in the risk of hyperkalemia induced hospital admission compared with RASB users exposed to other antibiotics.3 The new paper considers this same cohort of older RASB users from Ontario’s administrative databases, but now extends follow-up to 18 years and uses a nested case-control approach. The authors report adjusted odds ratios describing the risk of …

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), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.667
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.017
GPT teacher head0.265
Teacher spread0.248 · 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
GenreCommentary

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

Citations3
Published2014
Admission routes2
Has abstractyes

Explore more

Same venueBMJSame topicPotassium and Related DisordersFrench-language works237,207