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Bariatric Surgery and Cardiovascular Outcomes in Patients With Obesity and Cardiovascular Disease:

2021· article· en· W3151490690 on OpenAlexaffabout
Aristithes G. Doumouras, Jorge Wong, J. Michael Paterson, Yung Lee, Branavan Sivapathasundaram, Jean‐Éric Tarride, Lehana Thabane, Dennis Hong, Salim Yusuf, Mehran Anvari

Bibliographic record

VenueCirculation · 2021
Typearticle
Languageen
FieldMedicine
TopicBariatric Surgery and Outcomes
Canadian institutionsSt. Joseph’s Healthcare HamiltonPrograms for Assessment of Technology in Health Research InstituteHamilton Health SciencesUniversity of TorontoPopulation Health Research InstituteMcMaster UniversityHamilton General Hospital
Fundersnot available
KeywordsMedicineDiseaseObesityDiabetes mellitusSurgeryInternal medicineIntensive care medicineEndocrinology

Abstract

fetched live from OpenAlex

Background: Bariatric surgery has been shown to significantly reduce cardiovascular risk factors. However, whether surgery can reduce major adverse cardiovascular events (MACE), especially in patients with established cardiovascular disease, remains poorly understood. The present study aims to determine the association between bariatric surgery and MACE among patients with cardiovascular disease and severe obesity. Methods: This was a propensity score–matched cohort study using province-wide multiple-linked administrative databases in Ontario, Canada. Patients with previous ischemic heart disease or heart failure who received bariatric surgery were matched on age, sex, heart failure history, and a propensity score to similar controls from a primary care medical record database in a 1:1 ratio. The primary outcome was the incidence of extended MACE (first occurrence of all-cause mortality, myocardial infarction, coronary revascularization, cerebrovascular events, and heart failure hospitalization). Secondary outcome included 3-component MACE (myocardial infarction, ischemic stroke, and all-cause mortality). Outcomes were evaluated through a combination of matching via propensity score and subsequent multivariable adjustment. Results: A total of 2638 patients (n=1319 in each group) were included, with a median follow-up time of 4.6 years. The primary outcome occurred in 11.5% (151/1319) of the surgery group and 19.6% (259/1319) of the controls (adjusted hazard ratio [HR], 0.58 [95% CI, 0.48–0.71]; P <0.001). The association was notable for those with heart failure (HR, 0.44 [95% CI, 0.31–0.62]; P <0.001; absolute risk difference, 19.3% [95% CI, 12.0%–26.7%]) and in those with ischemic heart disease (HR, 0.60 [95% CI, 0.48–0.74]; P <0.001; absolute risk difference, 7.5% [95% CI, 4.7%–10.5%]). Surgery was also associated with a lower incidence of the secondary outcome (HR, 0.66 [95% CI, 0.52–0.84]; P =0.001) and cardiovascular mortality (HR, 0.35 [95% CI, 0.15–0.80]; P =0.001). Conclusions: Bariatric surgery was associated with a lower incidence of MACE in patients with cardiovascular disease and obesity. These findings require confirmation by a large-scale randomized trial.

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 score0.068
Threshold uncertainty score0.136

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.201
Teacher spread0.189 · 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

Citations201
Published2021
Admission routes2
Has abstractyes

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