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Record W4399071345 · doi:10.1016/j.avsg.2024.02.032

Comparison of Various Functional Assessment Tools to Identify Older Patients Undergoing Aortic Aneurysm Repair at Risk for Postoperative Complications

2024· article· en· W4399071345 on OpenAlexaboutno aff
Louise B.D. Banning, Barbara C. Van Munster, Barbara L van Leeuwen, Monika Trzpis, Clark J Zeebregts, Robert A Pol

Bibliographic record

VenueAnnals of Vascular Surgery · 2024
Typearticle
Languageen
FieldMedicine
TopicAortic aneurysm repair treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAbdominal aortic aneurysmProspective cohort studyAortic aneurysmAneurysmEndovascular aneurysm repairCohort studySurgeryCohortRisk assessmentInternal medicineCardiology

Abstract

fetched live from OpenAlex

BACKGROUND: To estimate whether the benefits of aortic aneurysm repair will outweigh the risks, determining individual risks is essential. This single-center prospective cohort study aimed to compare the association of functional tools with postoperative complications in older patients undergoing aortic aneurysm repair. METHODS: Ninety-eight patients (≥65 years) who underwent aortic aneurysm repair were included. Four functional tools were administered: the Montreal Cognitive Assessment (MoCA); the 4-Meter Walk Test (4-MWT); handgrip strength; and the Groningen Frailty Indicator (GFI). Primary outcome was the association between all tests and 30-day postoperative complications. RESULTS: After adjusting for confounders, the odds ratio for MoCA was 1.39 (95% confidence interval [CI] 0.450; 3.157; P = 0.723), for 4-MWT 0.63 (95% CI 0.242; 1.650; P = 0.348), for GFI 1.82 (95% CI 0.783; 4.323, P = 0.162), and for weak handgrip strength 4.78 (95% CI 1.338; 17.096, P = 0.016). CONCLUSIONS: Weak handgrip strength is significantly associated with the development of postoperative complications after aortic aneurysm repair. This study strengthens the idea that implementing a quick screening tool for risk assessment at the outpatient clinic, such as handgrip strength, identifies patients who may benefit from preoperative enhancement with help from, for example, Comprehensive Geriatric Assessment, eventually leading to better outcomes for this patient group.

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 score0.037
Threshold uncertainty score0.833

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.088
GPT teacher head0.398
Teacher spread0.310 · 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
Published2024
Admission routes1
Has abstractyes

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