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Record W4378744975 · doi:10.1308/rcsann.2023.0004

Myocardial protection in paediatric cardiac surgery: building an evidence-based strategy

2023· article· en· W4378744975 on OpenAlexfundno aff
NE Drury

Bibliographic record

VenueAnnals of The Royal College of Surgeons of England · 2023
Typearticle
Languageen
FieldMedicine
TopicCardiac Ischemia and Reperfusion
Canadian institutionsnot available
FundersNational Heart, Lung, and Blood InstituteBritish Heart FoundationHospital for Sick ChildrenGreat Ormond Street Hospital for ChildrenUniversity of WarwickUniversity Hospital Southampton NHS Foundation Trust
KeywordsMedicineTroponinClinical trialCardiac surgeryIschemiaCardiologyTroponin IMyocardial ischemiaInternal medicineIntensive care medicineMyocardial infarction

Abstract

fetched live from OpenAlex

Cardioplegia is fundamental to the surgical repair of congenital heart defects by protecting the heart against ischaemia/reperfusion injury, characterised by low cardiac output and troponin release in the early postoperative period. The immature myocardium exhibits structural, physiological and metabolic differences from the adult heart, with a greater sensitivity to calcium overload-mediated injury during reperfusion. Del Nido cardioplegia was designed specifically to protect the immature heart, is widely used in North America and may provide better myocardial protection in children; however, it has not been commercially available in the UK, where most centres use St Thomas' blood cardioplegia. There are no phase 3 clinical trials in children to support one solution over another and this lack of evidence, combined with variations in practice, suggests the presence of clinical equipoise. The best cardioplegia solution for use in children, and the impact of age and other clinical factors remain unknown. In this Hunterian lecture, I propose an evidence-based strategy to improve myocardial protection during cardiac surgery in children through: (1) conducting multicentre clinical trials of established techniques; (2) improving our knowledge of ischaemia/reperfusion injury in the setting of cardioplegic arrest; (3) applying this to drive innovation, moving beyond current cardioplegia solutions; (4) empowering personalised medicine, through combining clinical and genomic data, including ethnic diversity; and (5) understanding the impact of cardioplegic arrest on the late outcomes that matter to patients and their families.

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)0.003
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 score0.389
Threshold uncertainty score0.473

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
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 head0.064
GPT teacher head0.301
Teacher spread0.236 · 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

Citations5
Published2023
Admission routes1
Has abstractyes

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