MétaCan
Menu
Back to cohort
Record W4400323737 · doi:10.1080/14796678.2024.2367875

Double arterial vs. single axillary cannulation in acute type A aortic dissections: a meta-analysis

2024· review· en· W4400323737 on OpenAlexaff
Yoshiyuki Yamashita, Serge Sicouri, Aleksander Dokollari, Khalid Ridwan, Nicholas Clarke, Roberto Rodríguez, Scott Goldman, Basel Ramlawi

Bibliographic record

VenueFuture Cardiology · 2024
Typereview
Languageen
FieldMedicine
TopicAortic Disease and Treatment Approaches
Canadian institutionsUniversity of ManitobaSt. Boniface Hospital
Fundersnot available
KeywordsMedicineAxillary arterySurgeryCardiologyAortic dissectionMeta-analysisInternal medicineRadiologyAorta

Abstract

fetched live from OpenAlex

Aim: To evaluate the effects of double (axillary and femoral) vs. single (axillary) cannulation on early outcomes of acute type A aortic dissection (ATAAD). Materials & methods: Meta-analysis using PubMed/MEDLINE, Scopus, and Cochrane databases through August 23, 2023. Focused on operative mortality, postoperative stroke, re-exploration for bleeding, spinal cord injury, and renal replacement therapy. Results: Among 5 propensity score-matched studies with 2127 patients, double cannulation showed comparable mortality and higher rates of postoperative stroke (pooled odds ratio: 1.69, 95% confidence interval: 1.19–2.39) and need for renal replacement therapy (pooled odds ratio: 1.35, 95% confidence interval: 1.13–1.60) compared with single cannulation. Conclusion: Double arterial cannulation in ATAAD surgery is associated with increased postoperative stroke and renal replacement therapy than single cannulation.

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)0.006
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.013
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0120.028
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.126
GPT teacher head0.378
Teacher spread0.252 · 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 designMeta-analysis
Domainnot available
GenreReview

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

Citations4
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueFuture CardiologySame topicAortic Disease and Treatment ApproachesFrench-language works237,207