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Record W1807477446 · doi:10.1053/j.ajkd.2015.06.018

Urinary, Plasma, and Serum Biomarkers’ Utility for Predicting Acute Kidney Injury Associated With Cardiac Surgery in Adults: A Meta-analysis

2015· review· en· W1807477446 on OpenAlexafffund
Julie Ho, Navdeep Tangri, Paul Komenda, Amit Kaushal, Manish M. Sood, Ranveer Brar, Kamal Gill, S. R. Walker, Kerry Macdonald, Brett Hiebert, Rakesh C. Arora, Claudio Rigatto

Bibliographic record

VenueAmerican Journal of Kidney Diseases · 2015
Typereview
Languageen
FieldMedicine
TopicAcute Kidney Injury Research
Canadian institutionsSt. Boniface HospitalUniversity of OttawaSeven Oaks General HospitalUniversity of Manitoba
FundersCanadian Institutes of Health ResearchManitoba Medical Service Foundation
KeywordsMedicineAcute kidney injuryUrinary systemCardiac surgeryBiomarkerKidneyInternal medicineUrologyIntensive care medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Early accurate detection of acute kidney injury (AKI) occurring after cardiac surgery may improve morbidity and mortality. Although several novel biomarkers have been developed for the early detection of AKI, their clinical utility in the critical intraoperative and immediate postoperative period remains unclear. STUDY DESIGN: Systematic review and meta-analysis. SETTING & POPULATION: Adult patients having cardiac surgery. SELECTION CRITERIA FOR STUDIES: EMBASE, CINAHL, Cochrane Library, Scopus, and PubMed from January 1990 until January 2015 were systematically searched for cohort studies reporting the utility of novel biomarkers for the early diagnosis of AKI after adult cardiac surgery. Reviewers extracted data for study design, population, timing of biomarker measurement and AKI occurrence, biomarker performance (area under the receiver operating characteristic curve [AUROC]), and risk of bias. INDEX TESTS: Novel urine, plasma, and serum AKI biomarkers, measured intraoperatively and in the early postoperative period (<24 hours). REFERENCE TESTS: AKI was defined according to the RIFLE, AKIN, or 2012 KDIGO criteria. RESULTS: We found 28 studies reporting intraoperative and/or early postoperative measurement of urine (n=23 studies) or plasma or serum (n=12 studies) biomarkers. Only 4 of these studies measured biomarkers intraoperatively. Overall, intraoperative discrimination by the urine biomarkers neutrophil gelatinase-associated lipocalin (NGAL) and kidney injury marker 1 (KIM-1) demonstrated AUROCs<0.70, whereas N-acetyl-β-d-glucosaminidase (NAG) and cystatin C had AUROCs<0.75. In the immediate 24-hour postoperative period, the urine biomarkers NGAL (16 studies), KIM-1 (6 studies), and liver-type fatty acid binding protein (6 studies) exhibited composite AUROCs of 0.69 to 0.72. The composite AUROCs for postoperative urine cystatin C, NAG, and interleukin 18 were ≤0.70. Similarly, the composite AUROCs for postoperative plasma NGAL (6 studies) and cystatin-C (5 studies) were <0.70. LIMITATIONS: Heterogeneous AKI definitions. CONCLUSIONS: In adults, known urinary, plasma, and serum biomarkers of AKI possess modest discrimination at best when measured within 24 hours of cardiac surgery.

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)0.006
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.013
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0120.037
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0020.002
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 head0.067
GPT teacher head0.370
Teacher spread0.303 · 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 designMeta-analysis
Domainnot available
GenreReview

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

Citations273
Published2015
Admission routes2
Has abstractno

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