MétaCan
Menu
Back to cohort
Record W2020837966 · doi:10.1155/2011/308685

Should Endovascular Repair Be Reimbursed for Low Risk Abdominal Aortic Aneurysm Patients? Evidence from Ontario, Canada

2011· article· en· W2020837966 on OpenAlexafffundabout
Jean‐Éric Tarride, Gord Blackhouse, Guy De Rose, James M. Bowen, Hamid Reza Nakhai-Pour, Daria O’Reilly, Feng Xie, Teresa Novick, Robert Hopkins, Ron Goeree

Bibliographic record

VenueInternational Journal of Vascular Medicine · 2011
Typearticle
Languageen
FieldMedicine
TopicAortic aneurysm repair treatments
Canadian institutionsWestern UniversityLondon Health Sciences CentreMcMaster UniversitySt. Joseph’s Healthcare HamiltonPrograms for Assessment of Technology in Health Research Institute
FundersOntario Ministry of Health and Long-Term Care
KeywordsMedicineAbdominal aortic aneurysmGeneral surgeryAortic aneurysmAneurysmSurgery

Abstract

fetched live from OpenAlex

Background. This paper presents unpublished clinical and economic data associated with open surgical repair (OSR) in low risk (LR) patients and how it compares with EVAR and OSR in high risk (HR) patients with an AAA > 5.5 cm. Design. Data from a 1-year prospective observational study was used to compare EVAR in HR patients versus OSR in HR and LR patients. Results. Between 2003 and 2005, 140 patients were treated with EVAR and 195 with OSR (HR: 52; LR: 143). The 1-year mortality rate with EVAR was statistically lower than HR OSR patients and comparable to LR OSR patients. One-year health-related quality of life was lower in the EVAR patients compared to OSR patients. EVAR was cost-effective compared to OSR HR but not when compared to OSR LR patients. Conclusions. Despite a similar clinical effectiveness, these results suggest that, at the current price, EVAR is more expensive than open repair for low risk patients.

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)0.003
metaresearch head score (Gemma)0.021
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 score0.031
Threshold uncertainty score0.210

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.004
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.000

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 head0.040
GPT teacher head0.282
Teacher spread0.242 · 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

Citations9
Published2011
Admission routes3
Has abstractyes

Explore more

Same venueInternational Journal of Vascular MedicineSame topicAortic aneurysm repair treatmentsFrench-language works237,207