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Record W2001163284 · doi:10.4088/jcp.v64n1209

Increased Cholesterol Levels During Paroxetine Administration in Healthy Men

2003· article· en· W2001163284 on OpenAlexaff
Nathalie Lara, Glen B. Baker, Stephen L. Archer, Jean‐Michel Le Mellédo

Bibliographic record

VenueThe Journal of Clinical Psychiatry · 2003
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsParoxetineDiscontinuationFluoxetineMedicineInternal medicineCholesterolTriglycerideReuptake inhibitorEndocrinologySerotonin reuptake inhibitorPharmacologySerotonin

Abstract

fetched live from OpenAlex

BACKGROUND: Despite the frequent use of selective serotonin reuptake inhibitors in patients with coronary heart disease (CHD), their effects on plasma lipid levels have not been systematically investigated. Our objective was to assess the effects of 8 weeks of paroxetine administration on plasma cholesterol and triglyceride levels. METHOD: Blood samples were collected at baseline, after 8 weeks of paroxetine administration, and post-discontinuation in 18 healthy male volunteers. RESULTS: In the 16 of 18 patients whose plasma levels of paroxetine indicated an unequivocal compliance to treatment, paroxetine administration induced an 11.5% increase in low-density lipoprotein cholesterol (LDL-C), which normalized after paroxetine discontinuation. CONCLUSION: The magnitude of the paroxetine-induced increase in LDL-C would lead to a minor increase in CHD risk in a minority of healthy male volunteers without associated CHD risk factors but might increase LDL-C sufficiently to warrant therapeutic intervention in patients with established CHD, based on the National Cholesterol Education Program guidelines.

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)0.000
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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.070
GPT teacher head0.451
Teacher spread0.381 · 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".

Quick stats

Citations47
Published2003
Admission routes1
Has abstractyes

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