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Record W2890969507 · doi:10.1161/circ.133.suppl_1.p201

Abstract P201: Ischemia with Mental Stress is Associated with Greater Left Ventricular Dyssynchrony

2016· article· en· W2890969507 on OpenAlexaff
Pratik Pimple, Ernest Garcia, Jonathon A. Nye, Muhammad Hammadah, Ibhar Al Mheid, Kobina Wilmot, Ronnie Ramadan, Amit Shah, Paolo Raggi, Fábio Esteves, Michael Kutner, Qi Long, Laura M. Ward, J. Douglas Bremner, Arshed A. Quyyumi, Viola Vaccarino

Bibliographic record

VenueCirculation · 2016
Typearticle
Languageen
FieldMedicine
TopicCardiac pacing and defibrillation studies
Canadian institutionsCanadian VIGOUR Centre
Fundersnot available
KeywordsMedicineCardiologyInternal medicineVentricleIschemiaStress testing (software)Myocardial perfusion imagingPerfusion

Abstract

fetched live from OpenAlex

Introduction: Synchronized contraction of left ventricle (LV) is necessary for normal cardiac pump function. Delayed activation of LV segments, known as “dyssynchrony,” can result in systolic and diastolic function deterioration and clinical heart failure. The autonomic nervous system regulates LV conduction and is influenced by psychological stress. We used mental stress testing to examine the effects of psychological stress on LV dyssynchrony and assess whether patients who develop mental stress-induced myocardial ischemia (MSI), a condition associated with doubling of risk for mortality and cardiovascular events, have greater LV dyssynchrony at baseline and/or during stress as compared to MSI negative subjects. We compared results with a control condition of conventional physical (exercise/ pharmacological) stress. Methods: 660 patients with CAD underwent 99mTc[[Unable to Display Character: ‐]]sestamibi myocardial perfusion imaging at rest and following both mental and physical stress. Dyssynchrony parameters, measured using the Emory Cardiac Toolbox software, included phase standard deviation (SD) and phase bandwidth; higher levels indicate higher desynchronized contraction. Ischemia with both conditions was blindly assessed by 2 independent readers, with consensus reading for any discordance. The Gensini score was calculated from angiographic data to assess CAD burden. Dyssynchrony data at baseline and during mental/physical stress were log-transformed for analyses. Results: Mean age was 63 years (SD: 9), 180 (27%) were females and 432 (66%) were whites. Overall, 108 (16%) subjects developed mental stress ischemia (MSI+), while 232 (35%) developed physical stress ischemia (PSI+). After adjusting for age, sex, race, traditional CAD risk factors, indicators of CAD burden, history of heart failure, and LV ejection fraction, at baseline MSI+ subjects compared with MSI- had 11% higher phase SD (95% CI: 1% to 19%), and 11% higher phase bandwidth (95% CI: 3% to 20%). PSI+ subjects compared with PSI- had a more modest and non-significant increase in phase SD (mean increase of 4%, 95% CI: -3% to 12%) and phase bandwidth (4%, 95% CI: -3% to 11%). The associations of MSI with baseline dyssynchrony was independent of PSI status. A similar association was noted between MSI and dyssyncrony during mental stress. Among the covariates, male sex (P=0.01), smoking (P=0.02), Gensini score (P=0.01), history of MI (P<0.001), history of heart failure (P<0.001), and LV ejection fraction (P<0.001) were significantly associated with higher baseline dyssynchrony. Conclusion: MSI is associated with greater LV dyssynchrony at rest and during stress. Baseline LV dyssynchrony may be a marker of susceptibility to stress-induced ischemia possibly due to recurrent or chronic subclinical ischemia during daily life. LV dyssynchrony may be a potential mechanism for adverse cardiac events in patients with MSI.

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 score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0100.001

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 head0.015
GPT teacher head0.244
Teacher spread0.229 · 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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Citations0
Published2016
Admission routes1
Has abstractyes

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