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Record W4224324000 · doi:10.26443/mjm.v20i1.861

Acute Cardiovascular Effects of Vaping Compared to Cigarette Smoking in Young Adults

2022· article· en· W4224324000 on OpenAlexaffvenue
Keana Shahin, Sarah West, Ingrid Brenner

Bibliographic record

VenueMcGill Journal of Medicine · 2022
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Disease and Adiposity
Canadian institutionsTrent University
Fundersnot available
KeywordsMedicineCigarette smokingTraditional medicineInternal medicine

Abstract

fetched live from OpenAlex

Background: First introduced as the safer alternative to smoking, vaping has become a popular activity among young adults. However, little is known about the potential health effects of vaping. This pilot project examined the acute cardiovascular effects of nicotine vapes/e-cigarettes (EC) in comparison to tobacco cigarettes (TC) in young adults in order to determine if vaping is more detrimental to cardiovascular health than traditional cigarettes. Methods: 16 healthy participants (7 M, 9 F; 20.2 ± 1.9 years) were recruited to participate in the study. Anthropometric measures were determined upon entry into the study. Circulatory measures (heart rate [HR], blood pressure [BP] and heart rate variability [HRV]) were measured prior to and 10-min following vaping or cigarette smoking and in response to an orthostatic challenge. Results: Resting circulatory and HRV measures were not different between chronic EC-users and TC-smokers. Vaping and cigarette smoking induced a significant increase in cardiovascular measures (HR and BP) but not HRV measures. Both groups responded similarly to the orthostatic challenge prior to and following vaping/smoking. Conclusion: These results indicate that, from a cardiovascular perspective, vaping induces similar acute effects as cigarette smoking and that young adults should be counselled about these adverse effects accordingly.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.511
Threshold uncertainty score0.603

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.011
GPT teacher head0.249
Teacher spread0.238 · 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

Citations2
Published2022
Admission routes2
Has abstractyes

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