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Longitudinal associations between 4-hydroxynonenal and depression in coronary artery disease patients

2018· article· en· W2890482435 on OpenAlexafffund
Michael Rosen, Parco Chan, Mahwesh Saleem, Nathan Herrmann, Alexander Adibfar, Ana C. Andreazza, Paul Oh, Krista L. Lanctôt

Bibliographic record

VenuePsychiatry Research · 2018
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsToronto Rehabilitation InstituteUniversity of TorontoUniversity Health NetworkHealth Sciences CentreSunnybrook Health Science Centre
FundersCanadian Institutes of Health Research
KeywordsDepression (economics)Coronary artery diseaseInternal medicineLipid peroxidationMedicineOxidative stress4-HydroxynonenalCardiology

Abstract

fetched live from OpenAlex

Depressive symptoms in patients with coronary artery disease (CAD) attenuate the cardiovascular benefits of cardiac rehabilitation (CR). Given that oxidative stress may be an important mechanism underlying depression, this study aimed to understand the longitudinal relationship between lipid peroxidation markers and depression in CAD. Serum levels of early (lipid hydroperoxides, LPH) and late (4‑hydroxy‑2-nonenal, 4-HNE; 8-isoprotane, 8-ISO) lipid peroxidation markers were measured in 120 CAD patients undergoing CR. The Structured Clinical Interview for DSM Axis I Disorders - Depression Module (SCID) was used to diagnose depression at baseline and the Center for Epidemiological Studies Depression Scale (CES-D) was used to measure depressive symptom severity. Multivariate mixed models compared the trajectories of serum LPH, 4-HNE, and 8-ISO between depressed and non-depressed CAD patients undergoing 6 months of CR. Similar models evaluated the associations between serum LPH, 4-HNE, and 8-ISO and CES-D score over the course of CR. Serum 4-HNE decreased less in CAD patients with depression compared to those without. In addition, a decrease in 4-HNE concentrations was significantly associated with a decrease in CES-D scores over 6 months. These findings suggest that 4-HNE may be an important marker of depressive symptoms in CAD and may be involved in its progression.

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)0.000
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 score0.008
Threshold uncertainty score0.344

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.074
GPT teacher head0.437
Teacher spread0.363 · 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

Citations10
Published2018
Admission routes2
Has abstractyes

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