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Record W4310733868 · doi:10.1016/j.cjcpc.2022.11.007

Factors Associated With Acute Kidney Injury After Cardiopulmonary Bypass in Children

2022· article· en· W4310733868 on OpenAlexaff
Michael Gritti, Pedrom Farid, Cedric Manlhiot, Damien Noone, Seaher Sakha, Sam Ali, Bailey Bernknopf, Brian W. McCrindle

Bibliographic record

VenueCJC Pediatric and Congenital Heart Disease · 2022
Typearticle
Languageen
FieldMedicine
TopicAcute Kidney Injury Research
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsMedicineAcute kidney injuryCreatinineCardiopulmonary bypassPerioperativeInternal medicineVon Willebrand factorIntensive care unitRisk factorGastroenterologyCardiologyAnesthesiaSurgeryPlatelet

Abstract

fetched live from OpenAlex

Background Acute kidney injury (AKI) is a common complication after cardiovascular surgery in children, noted in approximately 40% of children undergoing cardiopulmonary bypass (CPB). We sought to determine the risk factors including inflammatory and vascular endothelial markers associated with AKI in children undergoing cardiac surgery. Methods A secondary analysis of a prospective observational cohort study of paediatric patients with a cardiac defect requiring CPB and a weight of >2.5 kg was performed. AKI was defined as a 1.5 times increase from the preoperative value in serum creatinine or an absolute increase by ≥0.3 mg/dL (≥26.5 μmol/L). Plasma inflammatory markers (interleukin [IL]-1a, IL-1b, IL-2, IL-4, IL-6, IL-8, IL-10, IL-12p70, and tumour necrosis factor α) and vascular endothelial markers (vascular endothelial growth factor, von Willebrand factor, regulated on activation, normal T-cell expressed and secreted, granulocyte macrophage colony-stimulating factor, monocyte chemoattractant protein-1, platelet-derived growth factor, and microparticles) were assessed at 5 perioperative time points. Associations with AKI were found using generalized linear regression models adjusted for repeated measures. Results A total of 207 patients were assessed, of whom 56% (n = 116) were male. Thirty-three percent (n = 68) developed AKI. In univariable analyses, adverse outcomes significantly related to the presence of AKI included increased intensive care unit stay (3.0 vs 5.6 hours, P < 0.001). In multivariable analysis, independent factors that were significantly associated with AKI included longer duration of CPB (111 vs 154 minutes, P < 0.001) and lower preoperative creatinine. Inflammatory and vascular endothelial biomarkers were not associated with AKI. Conclusions AKI remains a prevalent problem after cardiac surgery, and renal ischemia related to longer bypass time potentially plays a key role in the etiology. Inflammatory and vascular endothelial biomarkers were not significantly related to AKI.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.019
Threshold uncertainty score0.975

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.012
GPT teacher head0.262
Teacher spread0.249 · 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

Citations7
Published2022
Admission routes1
Has abstractyes

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