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Record W2618782669 · doi:10.1155/2017/8605313

Adhesive-Enhanced Sternal Closure: Feasibility and Safety of Late Sternal Reentry

2017· article· en· W2618782669 on OpenAlexafffund
Aaron Spooner, H.E. Mewhort, Lisa Difrancesco, Paul W.M. Fedak

Bibliographic record

VenueCase Reports in Surgery · 2017
Typearticle
Languageen
FieldMedicine
TopicReconstructive Surgery and Microvascular Techniques
Canadian institutionsLibin Cardiovascular Institute of AlbertaUniversity of Calgary
FundersAlberta InnovatesAlberta Innovates - Health SolutionsHeart and Stroke Foundation of Canada
KeywordsReentryMedicineSternumSurgeryClosure (psychology)Soft tissueCardiology

Abstract

fetched live from OpenAlex

This clinical case report describes sternal reentry performed years after adhesive-enhanced sternal closure using Kryptonite bone cement. This report provides novel data on the late effects of this innovation. We observed that sternal reentry is feasible and safe. The adhesive did not weaken from biodegradation over a period of several years. There was no evidence of adherence to adjacent soft tissues or other nonbony deep mediastinal structures. Surgeons who receive patients who require redoing cardiac surgery after adhesive-enhanced closure with Kryptonite can be reassured that sternal reentry is safe and feasible.

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)0.002
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 score0.101
Threshold uncertainty score0.684

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.038
GPT teacher head0.307
Teacher spread0.269 · 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

Citations8
Published2017
Admission routes2
Has abstractyes

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