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Record W2883930534 · doi:10.1097/pcc.0000000000001656

Cardiac Surgery–Associated Kidney Injury in Children and Renal Oximetry

2018· article· en· W2883930534 on OpenAlexaffabout
Rachel Joffe, Mohammed Al Aklabi, Sudeshna Bhattacharya, Dominic Cave, Thomas Calleja, Daniel Garros, Nicholas Majesic, Lindsay M. Ryerson, Catherine Morgan

Bibliographic record

VenuePediatric Critical Care Medicine · 2018
Typearticle
Languageen
FieldMedicine
TopicAcute Kidney Injury Research
Canadian institutionsWomen and Children’s Health Research InstituteStollery Children's Hospital
Fundersnot available
KeywordsMedicineAcute kidney injuryCardiopulmonary bypassCardiac surgeryRenal replacement therapyIntensive careKidney diseaseCardiologyAnesthesiaInternal medicineIntensive care medicine

Abstract

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OBJECTIVES: Cardiac surgery-associated acute kidney injury is common in children and associates with negative outcomes. Novel interventions to reduce cardiac surgery-associated acute kidney injury require knowledge of its pathophysiology. States of altered perfusion, oxygen delivery, and energy consumption occur during cardiopulmonary bypass and could protect against or contribute to renal cellular injury and recovery. Near-infrared spectroscopy is noninvasive technology for monitoring regional blood flow and tissue oxygenation. This study evaluated the relationship between renal regional oxygen saturation and cardiac surgery-associated acute kidney injury, using near-infrared spectroscopy monitoring before, during, and after cardiopulmonary bypass in children. DESIGN: Prospective cohort study. SETTING: Single-center, tertiary care pediatric hospital (Stollery Children's Hospital, Edmonton, AB, Canada). PATIENTS: Children less than or equal to 10 kg undergoing congenital heart disease repair with cardiopulmonary bypass. Heart transplant, preoperative dialysis, sepsis, extracorporeal life support, congenital renal disease, and preoperative nephrotoxins were exclusions. INTERVENTIONS: Renal regional near-infrared spectroscopy monitoring before, during, and after cardiopulmonary bypass. MEASUREMENTS AND MAIN RESULTS: Outcome measure was cardiac surgery-associated acute kidney injury (defined according to Kidney Disease: Improving Global Outcomes criteria). Regional oxygen saturation was measured continuously using near-infrared spectroscopy (INVOS 5100C Cerebral/Somatic Oximeter; Medronic, Troy, MI) from time of anesthesia to time of transfer to intensive care. Cardiac surgery-associated acute kidney injury occurred in 65%. Lower baseline (precardiopulmonary bypass) regional oxygen saturation was associated with decreased risk of cardiac surgery-associated acute kidney injury (p = 0.01); children with baseline regional oxygen saturation in the highest tertile were 7.14 times more likely to get cardiac surgery- associated acute kidney injury (vs lowest tertile). Area under the curve for ability of baseline regional oxygen saturation to predict cardiac surgery-associated acute kidney injury was 0.73 (95% CI, 0.60-0.85). Children with lower baseline glomerular filtration rate had lower mean renal regional oxygen saturation. CONCLUSIONS: Findings demonstrate that preoperative oxygen supply/demand balance is an important predictor of cardiac surgery-associated acute kidney injury, suggesting lower preoperative (and intraoperative) renal blood flow may be protective. There is not yet a definite link between remote ischemic preconditioning and prevention of cardiac surgery-associated acute kidney injury; however, renal protective effects of sublethal ischemia should continue to be explored.

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)0.004
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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.345
Teacher spread0.328 · 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

Citations43
Published2018
Admission routes2
Has abstractyes

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