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Record W2125266996 · doi:10.1183/09031936.05.00079004

Low-dose inhaled corticosteroids and the risk of acute myocardial infarction in COPD

2005· article· en· W2125266996 on OpenAlexafffundabout
Laëtitia Huiart, Pierre Ernst, Xavier Ranouil, Samy Suissa

Bibliographic record

VenueEuropean Respiratory Journal · 2005
Typearticle
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsMcGill UniversityRoyal Victoria Hospital
FundersCanadian Institutes of Health ResearchMcGill UniversityGlaxoSmithKlineAstraZeneca
KeywordsMedicineCOPDMyocardial infarctionInhaled corticosteroidsCardiologyInternal medicineAsthma

Abstract

fetched live from OpenAlex

Inflammation plays a major role in the development and complications of atherosclerosis. Here, the dose-related impact of inhaled corticosteroids (ICS), used for their anti-inflammatory properties, on the risk of acute myocardial infarction (AMI) is studied in a cohort of chronic obstructive pulmonary disease (COPD) patients. Saskatchewan (Canada) health services databases were used to form a population-based cohort of 5,648 patients, > or =55 yrs, who received a first treatment for COPD between 1990 and 1997. A nested case-control analysis was conducted, where 371 cases presenting with a first AMI were matched with 1,864 controls, based on the date of cohort entry and age. A conditional logistic regression was used to estimate the effect of ICS, after adjusting for use of oral corticosteroids, severity of COPD, sex, systemic hypertension, diabetes and cardiovascular disease. ICS were used in the prior year by 42.2% of cases and 46.4% of controls. Overall, current use of ICS was not associated with a significant decrease in the risk of AMI. However, a 32% reduction in the risk of AMI was observed for doses ranging 50-200 microg x day(-1). In conclusion, very low doses of inhaled corticosteroids may be associated with a reduction in the risk of acute myocardial infarction.

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)0.002
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 score0.394
Threshold uncertainty score0.489

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.014
GPT teacher head0.276
Teacher spread0.261 · 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

Citations108
Published2005
Admission routes3
Has abstractyes

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