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Record W2167576704 · doi:10.1016/s1569-9293(03)00035-5

Use of nitinol-U clips and flow characteristics of LIMA-LAD anastomoses

2003· article· en· W2167576704 on OpenAlexaff
Gabriele D’Ancona, Tomas A. Salerno, Pierre S. Aoukar, Hratch L. Karamanoukian

Bibliographic record

VenueInteractive Cardiovascular and Thoracic Surgery · 2003
Typearticle
Languageen
FieldMedicine
TopicCardiac and Coronary Surgery Techniques
Canadian institutionsMontreal Heart Institute
Fundersnot available
KeywordsMedicineCLIPSAnastomosisCardiologySurgeryInternal medicine

Abstract

fetched live from OpenAlex

The aim of this study was to compare flow characteristics of LIMA-LAD anastomoses constructed using two different techniques. Thirty patients underwent MIDCAB using either simple continuous suture (20) or separate nitinol U-clips (10). Intraoperative transit time flow measurements were recorded. Preoperative variables were similar in the two groups. Anastomosis time was significantly higher in the U-clipped group (9.9+/-1.5 min. vs. 11.4+/-1.5 min; P=0.016). Average flow value in the 20 continuous suture LIMA-LAD anastomoses was 26.7+/-8.8 ml/min versus 36.3+/-10.6 ml/min in the 10 U-clipped grafts (P=0.014). Pulsatility Index value was significantly lower in the U-clipped group (3.1+/-0.9 vs. 1.8+/-0.3, P=0.0001) and diastolic flow index was significantly higher (0.7+/-0.04 vs. 0.8+/-0.03, P=0.046). Perioperative results were similar in the two groups (P=ns). No mortality was reported. Postoperative trans-thoracic Doppler confirmed patency of the LIMA in all 30 patients. At short-term clinical follow-up (60+/-4 days), all patients were in CCSI. Nitinol U-clips can be used to construct LIMA-LAD anastomoses on the beating heart. Flow dynamics of these anastomoses are superior to those of grafts constructed using continuous suture technique. Particularly, total flow is higher and diastolic flow may reach values of 80% of the total measured flow.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.039
GPT teacher head0.279
Teacher spread0.240 · 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

Citations12
Published2003
Admission routes1
Has abstractyes

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