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Record W6907971439 · doi:10.25384/sage.c.6701397

Association of statin use and lipid levels with cerebral microbleeds and intracranial hemorrhage in patients with atrial fibrillation: A prospective cohort study

2023· other· en· W6907971439 on OpenAlexaff

Bibliographic record

VenueSage Journals Data · 2023
Typeother
Languageen
FieldMedicine
TopicMedical and Health Sciences Research
Canadian institutionsMcMaster UniversityPopulation Health Research Institute
Fundersnot available
KeywordsStatinAtrial fibrillationProspective cohort studyLogistic regressionOdds ratioCohort studyCohortAngiologyPopulation

Abstract

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Background:An increased risk of intracranial hemorrhage (ICH) associated with statins has been reported, but data on the relationship between statin use and cerebral microbleeds (CMBs) in patients with atrial fibrillation (AF), a population at high bleeding and cardiovascular risk, are lacking.Aims:To explore the association between statin use and blood lipid levels with the prevalence and progression of CMBs in patients with AF with a particular focus on anticoagulated patients.Methods:Data of Swiss-AF, a prospective cohort of patients with established AF, were analyzed. Statin use was assessed during baseline and throughout follow-up. Lipid values were measured at baseline. CMBs were assessed using magnetic resonance imagining (MRI) at baseline and at 2 years follow-up. Imaging data were centrally assessed by blinded investigators. Associations of statin use and low-density lipoprotein (LDL) levels with CMB prevalence at baseline or CMB progression (at least one additional or new CMB on follow-up MRI at 2 years compared with baseline) were assessed using logistic regression models; the association with ICH was assessed using flexible parametric survival models. Models were adjusted for hypertension, smoking, body mass index, diabetes, stroke/transient ischemic attack, coronary heart disease, antiplatelet use, anticoagulant use, and education.Results:Of the 1693 patients with CMB data at baseline MRI (mean ± SD age 72.5 ± 8.4 years, 27.6% women, 90.1% on oral anticoagulants), 802 patients (47.4%) were statin users. The multivariable adjusted odds ratio (adjOR) for CMBs prevalence at baseline for statin users was 1.10 (95% CI = 0.83–1.45). AdjOR for 1 unit increase in LDL levels was 0.95 (95% CI = 0.82–1.10). At 2 years, 1188 patients had follow-up MRI. CMBs progression was observed in 44 (8.0%) statin users and 47 (7.4%) non-statin users. Of these patients, 64 (70.3%) developed a single new CMB, 14 (15.4%) developed 2 CMBs, and 13 developed more than 3 CMBs. The multivariable adjOR for statin users was 1.09 (95% CI = 0.66–1.80). There was no association between LDL levels and CMB progression (adjOR 1.02, 95% CI = 0.79–1.32). At follow-up 14 (1.2%) statin users had ICH versus 16 (1.3%) non-users. The age and sex adjusted hazard ratio (adjHR) was 0.75 (95% CI = 0.36–1.55). The results remained robust in sensitivity analyses excluding participants without anticoagulants.Conclusions:In this prospective cohort of patients with AF, a population at increased hemorrhagic risk due to anticoagulation, the use of statins was not associated with an increased risk of CMBs.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.047
GPT teacher head0.346
Teacher spread0.300 · 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 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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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