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Record W3015007222 · doi:10.2196/14936

Effectiveness of Gastric Bypass Versus Gastric Sleeve for Cardiovascular Disease: Protocol and Baseline Results for a Comparative Effectiveness Study

2020· article· en· W3015007222 on OpenAlexvenueno aff
Karen J. Coleman, Heidi Fischer, David Arterburn, Douglas Barthold, Lee J. Barton, Anirban Basu, Anita P. Courcoulas, Cecelia L. Crawford, Peter N. Fedorka, Benjamin Kim, Edward C. Mun, Sameer B. Murali, Kristi Reynolds, Kangho Suh, Rong Wei, Tae Ki Yoon, Robert E. Zane

Bibliographic record

VenueJMIR Research Protocols · 2020
Typearticle
Languageen
FieldMedicine
TopicBariatric Surgery and Outcomes
Canadian institutionsnot available
FundersNational Heart, Lung, and Blood Institute
KeywordsMedicineBaseline (sea)Gastric bypassInternal medicineProtocol (science)SurgeryWeight lossObesityPathologyAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: When compared with conventional weight loss strategies, bariatric surgery results in substantially greater durable weight loss and rates of disease remission. OBJECTIVE: The ENGAGE CVD (Effectiveness of Gastric Bypass versus Gastric Sleeve for Cardiovascular Disease) cohort study aimed to provide population-based, comprehensive, rigorous evidence for clinical and policy decision making regarding the choice between gastric bypass and gastric sleeve for overall cardiovascular disease (CVD) risk reduction, risk factor remission, and safety. METHODS: The cohort had 22,095 weight loss surgery patients from a large integrated health care system in Southern California assembled from 2009 to 2016 who were followed up through 2018. Bariatric surgery patients were followed up for the length of their membership in the health care system. Of the patients who had at least five years of follow-up (surgery between 2009 and 2013), 85.86% (13,774/16,043) could contribute to the outcome analyses for the ENGAGE CVD cohort. RESULTS: at the time of surgery. When compared with patients who did not contribute data to the 5-year outcome analysis for the ENGAGE CVD cohort (2269/16,043; 14.14%), patients who contributed data (13,774/16,043; 85.86%) were older (P=.002), more likely to be women (P=.02), more likely to be non-Hispanic white (P<.001), more likely to have had an emergency department visit in the year before surgery (P=.006), less likely to have a mental illness before surgery (P<.001), and more likely to have had a CVD event at any time before surgery (P<.001). CONCLUSIONS: This study had one of the largest populations of gastric sleeve patients (n=13,459). The 5-year follow-up for those patients who had surgery between 2009 and 2013 was excellent for a retrospective cohort study at 85.86% (13,774/16,043). Unlike almost any study in the literature, the majority of the ENGAGE CVD cohort was racial and ethnic minority, providing a rare opportunity to study the effects of bariatric surgery for different racial and ethnic groups, some of whom have the highest rates of severe obesity in the United States. Finally, it also used state-of-the-art statistical and econometric comparative effectiveness methods to mimic the effect of random assignment and control for sources of confounding inherent in large observational studies. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/14936.

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)0.053
metaresearch head score (Gemma)0.060
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.053
Threshold uncertainty score0.281

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0530.060
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0060.009
Bibliometrics0.0030.005
Science and technology studies0.0020.002
Scholarly communication0.0050.004
Open science0.0030.003
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0500.008

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 head0.300
GPT teacher head0.526
Teacher spread0.226 · 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 designNot applicable
Domainnot available
GenreProtocol

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

Citations8
Published2020
Admission routes1
Has abstractyes

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