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Record W4296768781 · doi:10.1016/j.jvs.2022.07.033

Association Between Body Mass Index and Outcomes Following Endovascular Aneurysm Repair

2022· article· en· W4296768781 on OpenAlexaff
Ahmed A. Naiem, Mohammad Ahsan Habib, Robert-James Doonan, Daniel I. Obrand, Kent S. MacKenzie, Oren K. Steinmetz, Jason Bayne, Elie Girsowicz, Heather L. Gill

Bibliographic record

VenueJournal of Vascular Surgery · 2022
Typearticle
Languageen
FieldMedicine
TopicAortic aneurysm repair treatments
Canadian institutionsJewish General HospitalMcGill University Health CentreMcGill University
Fundersnot available
KeywordsMedicineBody mass indexUnderweightOverweightSurgeryPerioperativePost-hoc analysisPopulationAbdominal aortic aneurysmDyslipidemiaInternal medicineUnivariate analysisObesityAneurysmMultivariate analysis

Abstract

fetched live from OpenAlex

Objective: We assessed the association between body mass index and outcomes for patients who had undergone endovascular aneurysm repair (EVAR) for infrarenal abdominal aortic aneurysms (AAAs).Methods: We performed a retrospective analysis of consecutive patients who had undergone EVAR for AAAs between January 1998 and December 2019.Normal weight, overweight, and obese patients were compared.The primary outcome was 30-day mortality and mortality during follow-up.The secondary outcomes were freedom from reintervention and sac regression.Continuous variables were compared using one step analysis of variance.Univariate analysis was used to compare the cohorts against normal weight as the reference via a c 2 test.All-cause mortality and freedom from reintervention were compared between cohorts using Kaplan-Meier survival estimates.Sac regression was measured using mixed model analysis of variance with pairwise comparison using the Bonferroni post hoc test.Results: The study included 515 patients with 83% men and a mean age of 776 8 years.The mean follow-up was 45 6 34 months.Underweight, normal weight, overweight, obese, and morbidly obese patients constituted 2.1%, 32.4%, 41.6%, and 21.2%, and 2.7% of the study population, respectively.More obese patients had diabetes mellitus (33.3% vs 10.6%) and dyslipidemia (82.4% vs 60.9%) compared with normal weight (Table ).No differences were found in perioperative mortality.The Kaplan-Meier survival estimates showed no differences in survival or freedom from reintervention.Normal weight (57.3 6 8.7 to 54.7 6 10.2 kg; P ¼ .009)and overweight (58.4 6 9.3 to 56.4 6 10.8 kg; P ¼ .026)patients had had significant sac regression that was not evident in obese patients (58.1 6 9.4 to 58.5 6 12.4; P ¼ .786)during follow-up (Figs 1 and 2).Conclusions: Obese patients were less likely to experience AAA sac regression during follow-up than were normal weight and overweight patients.No association was found between obesity and increased mortality or reintervention for patients undergoing EVAR for AAAs.

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)0.003
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.014
GPT teacher head0.256
Teacher spread0.243 · 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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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