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Record W2965644221 · doi:10.1161/circ.135.suppl_1.p023

Abstract P023: Association of Sickle Cell Trait with Common Electrocardiographic Abnormalities in The REasons for Geographic and Racial Differences in Stroke (REGARDS) Study

2017· article· en· W2965644221 on OpenAlexaff
Daniel Douce, Elsayed Z. Soliman, Rakhi P. Naik, Hyacinth I. Hyacinth, Mary Cushman, Cheryl A. Winkler, George Howard, Neil A. Zakai

Bibliographic record

VenueCirculation · 2017
Typearticle
Languageen
FieldMedicine
TopicFolate and B Vitamins Research
Canadian institutionsCegep de Saint Hyacinthe
Fundersnot available
KeywordsMedicineInternal medicineLeft ventricular hypertrophyCardiologyStroke (engine)Atrial fibrillationSickle cell traitMyocardial infarctionDiabetes mellitusQT intervalKidney diseaseDiseaseBlood pressureEndocrinology

Abstract

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Introduction: Sickle cell disease (SCD) arises from an autosomal recessive mutation that leads to progressive vascular obstruction and early death. Sickle cell trait (SCT), the carrier status, is present in ~8% of African-Americans (AA) and is thought to be a benign condition, although evidence now suggests an association with worse cardiovascular and renal outcomes. Electrocardiogram (ECG) changes have been documented in SCD patients; however, similar studies in SCT individuals are lacking. We hypothesized that left ventricular hypertrophy (LVH), atrial fibrillation (AF) and QTc prolongation would be more common in SCT carriers than non-carriers. Methods: SCT was genotyped in 10,731 AA participants in the REasons for Geographic and Racial Differences in Stroke (REGARDS) study. Baseline risk factors were recorded from 2003-7. LVH was determined using Sokolow-Lyon criteria for all participants, and Cornell criteria in those with 12 lead ECGs (n = 8,690). AF was based on both self-report and ECG criteria. We assessed the association of SCT with LVH, AF, and QTc using multivariable logistic regression adjusting for age, sex, income, education, self-reported history of stroke, myocardial Infarction, diabetes, hypertension, and chronic kidney disease. Results: Among AA participants with ECG data and genotyping, 787 of 10,553 were SCT carriers (7.5%). AF was present in 814 (7.8%), LVH in 1,556 (14.7%) and QTc prolongation in 357 (3.4%). SCT status was associated with AF with an adjusted OR of 1.36 (95% CI 1.05, 1.76). SCT was not associated with LVH by Cornell criteria or Sokolow-Lyon (OR 1.16; 95% CI 0.94, 1.42). There was a significant age (continuous) by SCT interaction (p=0.02) with SCT associated with increased risk of LVH in younger but not older individuals. When stratified by the mean age of the cohort (65 years), younger individuals with SCT had an OR of 1.50 (95% CI 1.14, 1.97) for LVH, an association not seen in older individuals (OR 0.86; 95% CI 0.63-1.18). QTc prolongation was not associated with SCT (OR 0.97, 95% CI 0.64-1.47). Conclusions: SCT was associated with increased prevalence of AF in all individuals and with LVH in younger but not older individuals and was not associated with QTc prolongation. These data suggest SCT is not benign, and for the first time report the association of SCT with common ECG abnormalities. The association with AF and LVH is concerning with respect to increased stroke risk, especially the increased prevalence of LVH seen at younger ages in SCT. These data raise the question of whether individuals with SCT need more intensive monitoring and/or hypertension control than the general population.

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)0.002
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 score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.024
GPT teacher head0.291
Teacher spread0.267 · 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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Citations2
Published2017
Admission routes1
Has abstractyes

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