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Record W2168044922 · doi:10.1136/bmj.h246

The association between kidney function and major bleeding in older adults with atrial fibrillation starting warfarin treatment: population based observational study

2015· article· en· W2168044922 on OpenAlexafffundabout
Min Jun, Matthew T. James, Braden Manns, Robert R. Quinn, Pietro Ravani, Marcello Tonelli, Vlado Perkovic, Wolfgang C. Winkelmayer­, Zhuguo Ma, Brenda R. Hemmelgarn

Bibliographic record

VenueBMJ · 2015
Typearticle
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsUniversity of Calgary
FundersNational Health and Medical Research CouncilNational Institute of Diabetes and Digestive and Kidney DiseasesMedical Research CouncilCanadian Institutes of Health ResearchAlberta Innovates
KeywordsMedicineWarfarinAtrial fibrillationInterquartile rangeRenal functionKidney diseaseInternal medicinePopulationDialysisConfidence intervalRetrospective cohort studyStroke (engine)Cohort studyCohortSurgery

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine rates of major bleeding by level of kidney function for older adults with atrial fibrillation starting warfarin. DESIGN: Retrospective cohort study. SETTING: Community based, using province wide laboratory and administrative data in Alberta, Canada. PARTICIPANTS: 12,403 adults aged 66 years or more, with atrial fibrillation who started warfarin treatment between 1 May 2003 and 31 March 2010 and had a measure of kidney function at baseline. Kidney function was estimated using the Chronic Kidney Disease Epidemiology Collaboration equation and participants were categorised based on estimated glomerular filtration rate (eGFR): ≥ 90, 60-89, 45-59, 30-44, 15-29, <15 mL/min/1.73 m(2). We excluded participants with end stage renal disease (dialysis or renal transplant) at baseline. MAIN OUTCOME MEASURES: Admission to hospital or visit to an emergency department for major bleeding (intracranial, upper and lower gastrointestinal, or other). RESULTS: Of 12,403 participants, 45% had an eGFR <60 mL/min/1.73 m(2). Overall, 1443 (11.6%) experienced a major bleeding episode over a median follow-up of 2.1 (interquartile range: 1.0-3.8) years. During the first 30 days of warfarin treatment, unadjusted and adjusted rates of major bleeding were higher at lower eGFR (P for trend <0.001 and 0.001, respectively). Adjusted bleeding rates per 100 person years were 63.4 (95% confidence interval 24.9 to 161.6) in participants with eGFR <15 mL/min/1.73 m(2) compared with 6.1 (1.9 to 19.4) among those with eGFR >90 mL/min/1.73 m(2) (adjusted incidence rate ratio 10.3, 95% confidence interval 2.3 to 45.5). Similar associations were observed at more than 30 days after starting warfarin, although the magnitude of the increase in rates across eGFR categories was attenuated. Across all eGFR categories, adjusted rates of major bleeding were consistently higher during the first 30 days of warfarin treatment compared with the remainder of follow-up. Increases in major bleeding rates were largely due to gastrointestinal bleeding (3.5-fold greater in eGFR <15 mL/min/1.73 m(2) compared with ≥ 90 mL/min/1.73 m(2)). Intracranial bleeding was not increased with worsening kidney function. CONCLUSIONS: Reduced kidney function was associated with an increased risk of major bleeding among older adults with atrial fibrillation starting warfarin; excess risks from reduced eGFR were most pronounced during the first 30 days of treatment. Our results support the need for careful consideration of the bleeding risk relative to kidney function when assessing the risk-benefit ratio of warfarin treatment in people with chronic kidney disease and atrial fibrillation, particularly in the first 30 days of treatment.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.012
Threshold uncertainty score0.333

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.114
GPT teacher head0.349
Teacher spread0.235 · 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

Citations142
Published2015
Admission routes3
Has abstractyes

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