Is serum cystatin C an early predictor for acute kidney injury following cardiopulmonary bypass surgery in infants and young children?

Using Serum Cystatin C to Predict Acute Kidney Injury Following Infant Cardiac Surgery

Acute kidney injury (AKI) following cardiopulmonary bypass (CPB) is associated with increased morbidity and mortality. Serum Cystatin C (CysC) is a novel biomarker synthesized by all nucleated cells that may act as an early indicator of AKI following infant CPB. Prospective observational study of infants (< 1 year) requiring CPB during cardiac surgery. CysC was measured at baseline and 12, 24, 48, and 72 h following CPB initiation. Each post-op percent difference in CysC (e.g. %CysC_12h) from baseline was calculated. Clinical variables along with urine output (UOP) and serum creatinine (SCr) were followed. Subjects were divided into two groups: AKI and non-AKI based upon the Kidney Disease Improving Global Outcomes (KDIGO) classification. AKI occurred in 41.9% (18) of the 43 infants enrolled. Patient demographics and baseline CysC levels were similar between groups. CysC levels were 0.97 ± 0.28 mg/L over the study period, and directly correlated with SCr (R = 0.71, p < 0.0001). Although absolute CysC levels were not significant between groups, the %CysC_12h was significantly greater in the AKI group (AKI: - 16% ± 22% vs. Non-AKI - 28% ± 9% mg/L; p = 0.003). However, multivariate analysis demonstrated that a lower UOP (Odds Ratio:0.298; 95% CI 0.073, 0.850; p = 0.02) but not %CysC_12h was independently associated with AKI. Despite a significant difference in the %CysC_12h, only UOP was independently associated with AKI. Larger studies of a more homogenous population are needed to understand these results and to explore the variability in this biomarker seen across institutions.

Machine learning in predicting cardiac surgery-associated acute kidney injury: A systemic review and meta-analysis

Background

Cardiac surgery-associated acute kidney injury (CSA-AKI) is a common complication following cardiac surgery. Early prediction of CSA-AKI is of great significance for improving patients' prognoses. The aim of this study is to systematically evaluate the predictive performance of machine learning models for CSA-AKI.

Methods

Cochrane Library, PubMed, EMBASE, and Web of Science were searched from inception to 18 March 2022. Risk of bias assessment was performed using PROBAST. Rsoftware (version 4.1.1) was used to calculate the accuracy and C-index of CSA-AKI prediction. The importance of CSA-AKI prediction was defined according to the frequency of related factors in the models.

Results

There were 38 eligible studies included, with a total of 255,943 patients and 60 machine learning models. The models mainly included Logistic Regression (n = 34), Neural Net (n = 6), Support Vector Machine (n = 4), Random Forest (n = 6), Extreme Gradient Boosting (n = 3), Decision Tree (n = 3), Gradient Boosted Machine (n = 1), COX regression (n = 1), κNeural Net (n = 1), and Naïve Bayes (n = 1), of which 51 models with intact recording in the training set and 17 in the validating set. Variables with the highest predicting frequency included Logistic Regression, Neural Net, Support Vector Machine, and Random Forest. The C-index and accuracy wer 0.76 (0.740, 0.780) and 0.72 (0.70, 0.73), respectively, in the training set, and 0.79 (0.75, 0.83) and 0.73 (0.71, 0.74), respectively, in the test set.

Conclusion

The machine learning-based model is effective for the early prediction of CSA-AKI. More machine learning methods based on noninvasive or minimally invasive predictive indicators are needed to improve the predictive performance and make accurate predictions of CSA-AKI. Logistic regression remains currently the most commonly applied model in CSA-AKI prediction, although it is not the one with the best performance. There are other models that would be more effective, such as NNET and XGBoost.

Systematic review registration

https://www.crd.york.ac.uk/; review registration ID: CRD42022345259.

Biomarkers of acute kidney injury after pediatric cardiac surgery: a meta-analysis of diagnostic test accuracy

Acute kidney injury (AKI) occurs frequently after cardiac surgery in children. Although current diagnostic criteria rely on serum creatinine and urine output, changes occur only after considerable loss of kidney function. This meta-analysis aimed to synthesize the knowledge on novel biomarkers and compare their ability to predict AKI. PubMed/MEDLINE, Embase, Scopus, and reference lists were searched for relevant studies published by March 2021. Diagnostic accuracy parameters were extracted and analyzed using hierarchical summary receiver operating characteristic (HSROC) method. Pooled estimates of the area under the curve (AUC) were calculated using conventional random-effects meta-analysis. Fifty-six articles investigating 49 biomarkers in 8617 participants fulfilled our eligibility criteria. Data from 37 studies were available for meta-analysis. Of the 10 biomarkers suitable for HSROC analysis, urinary neutrophil gelatinase-associated lipocalin (uNGAL) to creatinine (Cr) ratio yielded the highest diagnostic odds ratio (91.0, 95% CI 90.1-91.9), with a sensitivity of 91.3% (95% CI 91.2-91.3%) and a specificity of 89.7% (95% CI 89.6-89.7%). These results were confirmed in pooled AUC analysis, as uNGAL-to-Cr ratio and uNGAL were the only elaborately studied biomarkers (> 5 observations) with pooled AUCs ≥ 0.800. Liver fatty acid-binding protein (L-FABP), serum cystatin C (sCysC), serum NGAL (sNGAL), and interleukin-18 (IL-18) all had AUCs ≥ 0.700.

CONCLUSION

A variety of biomarkers have been proposed as predictors of cardiac surgery-associated AKI in children, of which uNGAL was the most prominent with excellent diagnostic qualities. However, more consolidatory evidence will be required before these novel biomarkers may eventually help realize precision medicine in AKI management.

WHAT IS KNOWN

• Acute kidney injury (AKI) occurs in about 30-60% of children undergoing cardiac surgery and is associated with increased in-hospital mortality and adverse short-term outcomes. However, in current clinical practice, AKI definitions and detection often rely on changes in serum creatinine and urine output, which are late and insensitive markers of kidney injury. • Although various novel biomarkers have been studied for the diagnosis of AKI in children after cardiac surgery, it remains unclear how these compare to one another in terms of diagnostic accuracy.

WHAT IS NEW

• Pooled analyses suggest that for the diagnosis of AKI in children who underwent cardiac surgery, NGAL is the most accurate among the most frequently studied biomarkers. • A number of other promising biomarkers have been reported, although they will require further research into their diagnostic accuracy and clinical applicability.

Biomarkers of acute kidney injury in pediatric cardiac surgery

Acute kidney injury (AKI) is characterized by a sudden decrease in kidney function. Children with congenital heart disease are a special group at risk of developing AKI. We performed a systematic review of the literature to search for studies reporting the usefulness of novel urine, serum, and plasma biomarkers in the diagnosis and progression of AKI and their association with clinical outcomes in children undergoing pediatric cardiac surgery. In thirty studies, we analyzed the capacity to predict AKI and poor outcomes of five biomarkers: Cystatin C, Neutrophil gelatinase-associated lipocalin, Interleukin-18, Kidney injury molecule-1, and Liver fatty acid-binding protein. In conclusion, we suggest the need for further meta-analyses with the availability of additional studies.

The future for diagnostic tests of acute kidney injury in critical care: evidence synthesis, care pathway analysis and research prioritisation

BACKGROUND

Acute kidney injury (AKI) is highly prevalent in hospital inpatient populations, leading to significant mortality and morbidity, reduced quality of life and high short- and long-term health-care costs for the NHS. New diagnostic tests may offer an earlier diagnosis or improved care, but evidence of benefit to patients and of value to the NHS is required before national adoption.

OBJECTIVES

To evaluate the potential for AKI in vitro diagnostic tests to enhance the NHS care of patients admitted to the intensive care unit (ICU) and identify an efficient supporting research strategy.

DATA SOURCES

We searched ClinicalTrials.gov, The Cochrane Library databases, Embase, Health Management Information Consortium, International Clinical Trials Registry Platform, MEDLINE, metaRegister of Current Controlled Trials, PubMed and Web of Science databases from their inception dates until September 2014 (review 1), November 2015 (review 2) and July 2015 (economic model). Details of databases used for each review and coverage dates are listed in the main report.

REVIEW METHODS

The AKI-Diagnostics project included horizon scanning, systematic reviewing, meta-analysis of sensitivity and specificity, appraisal of analytical validity, care pathway analysis, model-based lifetime economic evaluation from a UK NHS perspective and value of information (VOI) analysis.

RESULTS

The horizon-scanning search identified 152 potential tests and biomarkers. Three tests, Nephrocheck^® (Astute Medical, Inc., San Diego, CA, USA), NGAL and cystatin C, were subjected to detailed review. The meta-analysis was limited by variable reporting standards, study quality and heterogeneity, but sensitivity was between 0.54 and 0.92 and specificity was between 0.49 and 0.95 depending on the test. A bespoke critical appraisal framework demonstrated that analytical validity was also poorly reported in many instances. In the economic model the incremental cost-effectiveness ratios ranged from £11,476 to £19,324 per quality-adjusted life-year (QALY), with a probability of cost-effectiveness between 48% and 54% when tests were compared with current standard care.

LIMITATIONS

The major limitation in the evidence on tests was the heterogeneity between studies in the definitions of AKI and the timing of testing.

CONCLUSIONS

Diagnostic tests for AKI in the ICU offer the potential to improve patient care and add value to the NHS, but cost-effectiveness remains highly uncertain. Further research should focus on the mechanisms by which a new test might change current care processes in the ICU and the subsequent cost and QALY implications. The VOI analysis suggested that further observational research to better define the prevalence of AKI developing in the ICU would be worthwhile. A formal randomised controlled trial of biomarker use linked to a standardised AKI care pathway is necessary to provide definitive evidence on whether or not adoption of tests by the NHS would be of value.

STUDY REGISTRATION

The systematic review within this study is registered as PROSPERO CRD42014013919.

FUNDING

The National Institute for Health Research Health Technology Assessment programme.

Accuracy of cystatin C in prediction of acute kidney injury in children; serum or urine levels: which one works better? A systematic review and meta-analysis

BACKGROUND

There is still an ongoing discussion on the prognostic value of cystatin C in assessment of kidney function. Accordingly, the present study aimed to conduct a meta-analysis to provide evidence for the prognostic value of this biomarker for acute kidney injury (AKI) in children.

METHODS

An extensive search was performed in electronic databases of Medline, Embase, ISI Web of Science, Cochrane library and Scopus until the end of 2015. Standardized mean difference (SMD) with a 95% of confidence interval (95% CI) and the prognostic performance characteristics of cystatin C in prediction of AKI were assessed. Analyses were stratified based on the sample in which the level of cystatin C was measured (serum vs. urine).

RESULTS

A total of 24 articles were included in the meta-analysis [1948 children (1302 non-AKI children and 645 AKI cases)]. Serum (SMD = 0.96; 95% CI: 0.68-1.24; p < 0.0001) and urine (SMD = 0.54; 95% CI:0.34-0.75; p < 0.0001) levels of cystatin C were significantly higher in children with AKI. Overall area under the curve of serum cystatin C and urine cystatin C in prediction of AKI were 0.83 (95% CI: 0.80-0.86) and 0.85 (95% CI: 0.81-0.88), respectively. The best sensitivity (value = 0.85; 95% CI: 0.78-0.90) and specificity (value = 0.61; 95% CI: 0.48-0.73), were observed for the serum concentration of this protein and in the cut-off points between 0.4-1.0 mg/L.

CONCLUSION

The findings of the present study showed that cystatin C has an acceptable prognostic value for prediction of AKI in children. Since the serum level of cystatin C rises within the first 24 h of admission in patients with AKI, this biomarker can be a suitable alternative for traditional diagnostic measures.

Long-term prognostic impact of cystatin C on acute coronary syndrome octogenarians with diabetes mellitus

Objective

Cystatin C (Cys C) is a marker of renal dysfunction. Prior studies have shown that blood Cys C is related to the prognosis of coronary heart disease. The aim of the present study was to evaluate the long-term prognostic impact of Cys C on acute coronary syndrome (ACS) octogenarians with diabetes mellitus (DM).

Methods

We enrolled 660 consecutive ACS octogenarians who underwent coronary angiography and were classified into two groups based on diabetes. The baseline characters and Cys C level were measured on admission. Survival curve was calculated using the Kaplan-Meier method. Multivariate Cox regression was used to identify predictors of mortality and of major adverse cardiac events (MACE) rate.

Results

There were 223 and 398 patients in groups DM and non-DM who fulfilled the follow-up. The average follow-up period was 28 (IQR 16–38) months. Diastolic blood pressure (DBP) was lower, ratios of hypertension and chronic renal failure (CRF), fasting blood glucose, HbA1c and Cys C levels were higher in DM group than those in non-DM group (P<0.01). The cumulative survival of DM group was significantly lower than that of non-DM group in the long term (P = 0.018). All cause mortality and MACE of DM group were higher than those of non-DM group (P<0.05). The plasma Cys C concentration (OR = 3.32, 95% CI = 1.18-10.92, P = 0.023) was the uniqueness independent predictor for long-term all cause mortality. The plasma Cys C concentration (OR = 2.47, 95% CI = 1.07-7.86, P = 0.029) and Genesis score (OR = 1.01, 95% CI = 1.00-1.03, P = 0.043) were independent predictors for MACE in DM group. ROC curve analysis showed that the predictive cut-off value of Cys C for mortality of DM group was 1.605 (0.718, 0.704).

Conclusions

Cys C is an independent predictor for long-term mortality and MACE of ACS octogenarians with DM.