Dataset Information

Proteomic identification of early biomarkers of acute kidney injury after cardiac surgery in children.

ABSTRACT:

Background

Serum creatinine is a delayed marker of acute kidney injury (AKI). Our purpose is to discover and validate novel early urinary biomarkers of AKI after cardiac surgery.

Study design

Diagnostic test study.

Setting & participants

Children undergoing cardiopulmonary bypass surgery. The test set included 15 participants with AKI and 15 matched controls (median age, 1.5 year) of 45 participants without AKI. The validation set included 365 children (median age, 1.9 year).

Index tests

Biomarkers identified using proteomic profiling: α(1)-microglobulin, α(1)-acid glycoprotein, and albumin.

Reference test

AKI, defined as ≥50% increase in serum creatinine level from baseline within 3 days of surgery.

Results

Proteomic profiling using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) showed 3 protein peaks that appeared consistently within 2 hours in children who developed AKI after cardiopulmonary bypass surgery. The proteins were identified as α(1)-microglobulin, α(1)-acid glycoprotein, and albumin. Using clinical assays, results were confirmed in a test set and validated in an independent prospective cohort. In the validation set, 135 (37%) developed AKI, in whom there was a progressive increase in urinary biomarker concentrations with severity of AKI. Areas under the curve for urinary α(1)-microglobulin, α(1)-acid glycoprotein, and albumin at 6 hours after cardiac surgery were 0.84 (95% CI, 0.79-0.89), 0.87 (95% CI, 0.83-0.91), and 0.76 (95% CI, 0.71-0.81), respectively. Participants with increasing quartiles of biomarkers showed increasing lengths of hospital stays and durations of AKI (P < 0.001).

Limitations

Single-center study of children with normal kidney function at recruitment. The SELDI-TOF MS technique has limited sensitivity for the detection of proteins greater than the 20-kDa range.

Conclusions

Urinary α(1)-microglobulin, α(1)-acid glycoprotein, and albumin represent early, accurate, inexpensive, and widely available biomarkers of AKI after cardiac surgery. They also offer prognostic information about the duration of AKI and length of hospitalization after cardiac surgery.

SUBMITTER: Devarajan P

PROVIDER: S-EPMC2943007 | biostudies-literature | 2010 Oct

REPOSITORIES: biostudies-literature

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Publications

Proteomic identification of early biomarkers of acute kidney injury after cardiac surgery in children.

Devarajan Prasad P Krawczeski Catherine D CD Nguyen Mai T MT Kathman Thelma T Wang Zhu Z Parikh Chirag R CR

American journal of kidney diseases : the official journal of the National Kidney Foundation 20101001 4

<h4>Background</h4>Serum creatinine is a delayed marker of acute kidney injury (AKI). Our purpose is to discover and validate novel early urinary biomarkers of AKI after cardiac surgery.<h4>Study design</h4>Diagnostic test study.<h4>Setting & participants</h4>Children undergoing cardiopulmonary bypass surgery. The test set included 15 participants with AKI and 15 matched controls (median age, 1.5 year) of 45 participants without AKI. The validation set included 365 children (median age, 1.9 year ...[more]

PMID: 20599305

Similar Datasets

Project description:BackgroundCardiac surgery-associated acute kidney injury (AKI) is associated with increased morbidity and mortality. We examined the utility of combining biomarkers of kidney function loss (serum cystatin C) and kidney tubular damage (urine neutrophil gelatinase-associated lipocalin [NGAL] and Kidney Injury Molecule-1 [KIM-1]) for the prediction of post-cardiac surgery AKI.MethodsSingle-center prospective cohort study of 106 adults undergoing coronary artery bypass grafting and/or valve surgery with cardiopulmonary bypass (CPB). Primary outcome was postoperative in-hospital AKI defined by serum creatinine (SCr)-Kidney Disease: Improving Global Outcomes criteria. Biomarkers were measured preoperatively, 6 hours after CPB and on postoperative days (PODs) 1 to 4.ResultsA total of 23 subjects (21.7%) developed AKI. After adjusting for preoperative left ventricular ejection fraction, body mass index >30 kg/m2, and estimated glomerular filtration rate (eGFR) <60 ml/min per 1.73 m2, the combination of peak serum cystatin C and peak urine KIM-1/creatinine (Cr) (6 hours post-CPB to POD 1) above optimal cutoff significantly associated with postoperative AKI (odds ratio [OR]: 5.32; 95% confidence interval [CI]: 1.31-21.67; P = 0.020). This biomarker combination significantly improved the performance of the clinical model for the prediction of postoperative AKI (area under the curve [AUC]: 0.77, 95% CI: 0.65-0.90 for the clinical model alone versus 0.83, 95% CI: 0.73-0.93 for the clinical model with the addition of biomarker data, P = 0.049).ConclusionsCombining biomarkers of postoperative kidney function loss and postoperative kidney tubular damage significantly improved prediction of in-hospital AKI following cardiac surgery. Future large, multicenter studies are warranted to assess whether panels of biomarkers reflecting distinct pathobiology can be used to guide interventions and improve short- and long-term outcomes in patients undergoing cardiac surgery.

Project description:PurposeTo establish novel prediction models for predicting acute kidney injury (AKI) after cardiac surgery based on early postoperative biomarkers.Patients and methodsThis study enrolled patients who underwent cardiac surgery in a Chinese tertiary cardiac center and consisted of a discovery cohort (n = 452, from November 2018 to June 2019) and a validation cohort (n = 326, from December 2019 to May 2020). 43 biomarkers were screened using the least absolute shrinkage and selection operator and logistic regression to construct a nomogram model. Three tree-based machine learning models were also established: eXtreme Gradient Boosting (XGBoost), random forest (RF) and deep forest (DF). Model performance was accessed using area under the receiver operating characteristic curve (AUC). AKI was defined according to the Kidney Disease Improving Global Outcomes criteria.ResultsFive biomarkers were identified as independent predictors of AKI and were included in the nomogram: soluble ST2 (sST2), N terminal pro-brain natriuretic peptide (NT-proBNP), heart-type fatty acid binding protein (H-FABP), lactic dehydrogenase (LDH), and uric acid (UA). In the validation cohort, the nomogram achieved good discrimination, with AUC of 0.834. The machine learning models also exhibited adequate discrimination, with AUC of 0.856, 0.850, and 0.836 for DF, RF, and XGBoost, respectively. Both nomogram and machine learning models had well calibrated. The AUC of sST2, NT-proBNP, H-FABP, LDH, and UA to discriminate AKI were 0.670, 0.713, 0.725, 0.704, and 0.749, respectively. In addition, all of these biomarkers were significantly correlated with AKI after adjusting clinical confounders (odds ratio and 95% confidence interval of the third vs. the first tertile: sST2, 3.55 [2.34-5.49], NT-proBNP, 5.50 [3.54-8.71], H-FABP, 6.64 [4.11-11.06], LDH, 7.47 [4.54-12.64], and UA, 8.93 [5.46-15.06]).ConclusionOur study provides a series of novel predictive models and five biomarkers for enhancing the risk stratification of AKI after cardiac surgery.

Dataset Information

Proteomic identification of early biomarkers of acute kidney injury after cardiac surgery in children.

Background

Study design

Setting & participants

Index tests

Reference test

Results

Limitations

Conclusions

Publications

Proteomic identification of early biomarkers of acute kidney injury after cardiac surgery in children.

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