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Record W2527111702 · doi:10.1111/echo.13375

Echocardiographic consequences of smoking status in middle‐aged subjects

2016· article· en· W2527111702 on OpenAlexfundno aff
Morten Kraen, Sophia Frantz, Ulf Nihlén, Gunnar Engström, Claes‐Göran Löfdahl, Per Wollmer, Magnus Dencker

Bibliographic record

VenueEchocardiography · 2016
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Function and Risk Factors
Canadian institutionsnot available
FundersSkånes universitetssjukhusHjärt-LungfondenLunds UniversitetCrafoordska StiftelsenAstraZeneca Canada
KeywordsMedicineCardiologyInternal medicinePulmonary diseasePopulationDiseaseRespiratory systemHemodynamicsCardiac indexObstructive lung diseaseCardiac output

Abstract

fetched live from OpenAlex

Background Smoking is known to have many short‐ and long‐term cardiovascular effects. Cardiac index ( CI ), which is cardiac output indexed to body surface area, is considered to be a valid measure of cardiac performance. We investigated whether there were any differences in CI or other echocardiographic variables between never smokers, ex‐smokers, and current smokers in a cardiopulmonary healthy population. Methods Subjects (n=355) from a previous population‐based respiratory questionnaire survey (never smokers, ex‐smokers, and current smokers without significant chronic obstructive lung disease) were examined with echocardiography, and CI (L/min/m 2 ) was calculated. Results Current smokers had a higher CI than never smokers 2.61±0.52 L/min/m 2 vs. 2.42±0.49 L/min/m 2 ( P <.01). Ex‐smokers had a nonsignificant, numerically higher value for CI than never smokers 2.54±0.54 L/min/m 2 vs. 2.42±0.49 L/min/m 2 ( P >.05). Smoking status had no significant effect on other echocardiographic variables. Conclusion We conclude that currents smokers without known cardiac disease or significant chronic obstructive lung disease show signs of slightly altered hemodynamics.

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 score0.006
Threshold uncertainty score0.761

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.003
Science and technology studies0.0000.001
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 head0.019
GPT teacher head0.237
Teacher spread0.218 · 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

Citations3
Published2016
Admission routes1
Has abstractyes

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