MétaCan
Menu
Back to cohort
Record W2505046913 · doi:10.1177/0267659116662701

Del Nido cardioplegia in the setting of minimally invasive aortic valve surgery

2016· article· en· W2505046913 on OpenAlexaff
Nicola Vistarini, Éric Laliberté, Philippe Beauchamp, Ismail Bouhout, Yoan Lamarche, Raymond Cartier, Michel Carrier, Louis P. Perrault, Denis Bouchard, Ismaı̈l El-Hamamsy, Michel Pellerin, Philippe Demers

Bibliographic record

VenuePerfusion · 2016
Typearticle
Languageen
FieldMedicine
TopicCardiac and Coronary Surgery Techniques
Canadian institutionsUniversité de MontréalMontreal Heart Institute
Fundersnot available
KeywordsMedicineAortic valveAortic valve replacementInvasive surgeryAortic surgerySurgeryCardiologyAortaStenosis

Abstract

fetched live from OpenAlex

The purpose of this study is to report our experience with del Nido cardioplegia (DNC) in the setting of minimally invasive aortic valve surgery. Forty-six consecutive patients underwent minimally invasive aortic valve replacement (AVR) through a "J" ministernotomy: twenty-five patients received the DNC (Group 1) and 21 patients received standard blood cardioplegia (SBC) (Group 2). The rate of ventricular fibrillation at unclamping was significantly lower in the DNC group (12% vs 52%, p=0.004), as well as postoperative creatinine kinase-MB (CK-MB) values (11.4±5.2 vs 17.7±6.9 µg/L, p=0.004). There were no deaths, myocardial infarctions or major complications in either group. Less postoperative use of intravenous insulin (28% vs 81%, p<0.001) was registered in the DNC group. In conclusion, the DNC is easy to use and safe during minimally invasive AVR, providing a myocardial protection at least equivalent to our SBC, improved surgical efficiency, minimal cost and less blood glucose perturbations.

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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.015
GPT teacher head0.253
Teacher spread0.238 · 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

Citations57
Published2016
Admission routes1
Has abstractyes

Explore more

Same venuePerfusionSame topicCardiac and Coronary Surgery TechniquesFrench-language works237,207