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O062 Smoking and perioperative cardiovascular and medical outcomes in patients undergoing non-cardiac surgery

2014· article· en· W60198797 on OpenAlexaff
Clara K Chow, Matthew T.V. Chan, Richard Halliwell, Pramesh Kovoor, Vincent Lee, John Mooney, Aravinda Thiagalingam, Séverine Bompoint, P.J. Devereaux, Graham S. Hillis

Bibliographic record

VenueGlobal Heart · 2014
Typearticle
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsMcMaster UniversityPopulation Health Research Institute
Fundersnot available
KeywordsMedicinePerioperativeCohortInternal medicinePopulationCohort studyDemographySurgeryEnvironmental health

Abstract

fetched live from OpenAlex

Early smoking onset age (SOA) is a public health concern with scant empirical evidence of its role in health outcomes. The study had two aims: i) to assess whether an early SOA was associated with the risk of fatal and non-fatal CVD and all-cause and CVD mortality and ii) to explore the linear and non-linear association between SOA and the outcomes of interest. Data from 4499 current or former smokers, recruited from 1995 to 2005, aged 25 to 79 years, and with a median 7.02 years of follow-up, were obtained from the REGICOR population-based cohort. In the present analysis, performed in 2018, the independent variable was SOA and the dependent variables were CVD events, CVD mortality, and all-cause mortality. Penalized smoothing spline methods were used to assess the linear and non-linear association. During follow-up, 361 deaths and 210 CVD events were recorded. A significant non-linear component was identified in the association between SOA and CVD outcomes with a cut-off point at 12 years: In the group aged ≤12 years, each year of delay in SOA was inversely associated with CVD risk (HR = 0.71; 95%CI = 0.53–0.96) and CVD mortality (HR = 0.58; 95%CI = 0.37–0.90). No association was observed in the older SOA group. A linear association was observed between SOA and all-cause mortality, and each year of delay was associated with 4% lower risk of mortality (HR = 0.96; 95%CI = 0.93–0.98). The associations were adjusted for lifelong exposure to tobacco and cardiovascular risk factors. These results reinforce the value of preventing tobacco use among teenagers and adolescents.

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)0.001
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 score0.035
Threshold uncertainty score0.595

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.007
GPT teacher head0.245
Teacher spread0.237 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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