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Record W2903357133 · doi:10.1016/j.artres.2018.10.050

5.3 CAROTID ARTERY STIFFNESS INCREASES THE RISK OF INCIDENT DEPRESSIVE SYMPTOMS: THE PARIS PROSPECTIVE STUDY 3

2018· article· en· W2903357133 on OpenAlexaboutno aff
Thomas T. van Sloten, Pierre Boutouyrie, Muriel Tafflet, Lucile Offredo, Frédérique Thomas, Catherine Guibout, Rachel E. Climie, Cédric Lemogne, Bruno Pannier, Stéphane Laurent, Xavier Jouven, Jean‐Philippe Empana

Bibliographic record

VenueArtery Research · 2018
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Health and Disease Prevention
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCarotid arteriesCardiologyDepressive symptomsProspective cohort studyInternal medicineArterial stiffnessPsychiatryBlood pressureCognition

Abstract

fetched live from OpenAlex

Objective: The study aims to investigate the role of cardiorespiratory fitness as a mediator of the relationship between arterial stiffness and cognitive function in apparently healthy seniors.Methods: This is a cross-sectional study comprising 155 participants (75.5 Æ 6.5 years; 69.7% female).Arterial stiffness and cognitive function were assessed with carotid-femoral pulse wave velocity (cfPWV) (Sphygmo-Cor, AtCor Medical, Australia), and Montreal Cognitive Assessment (MoCA), respectively.Cardiorespiratory fitness was calculated using the 6-minute walk test.Simple mediation analysis with bootstrapped procedures was calculated with Hayes's PROCESS macro for SPSS.Results: After adjustments for gender and age, cardiorespiratory fitness significantly mediated the relationship between arterial stiffness and cognitive function (Indirect effectZ À0.229 [95% CI, À0.455 to À0.046]).Conclusion: The present findings suggest that cardiorespiratory fitness, independently of gender and age, is a mediator of the relationship between arterial stiffness and cognitive function.

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 score0.019
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.032
GPT teacher head0.363
Teacher spread0.331 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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