Alternative definition of acute kidney injury following liver transplantation: based on serum creatinine and cystatin C levels

The Kinetics of Cystatin C and Serum Creatinine in AKI

Key Points

Modeling shows that serum cystatin C can detect AKI 6–48 hours earlier than serum creatinine, regardless of baseline kidney function. Absolute value diagnostic cutoffs are more effective than percentage-based thresholds for AKI detection across different CKD stages.

Background

AKI is a common condition affecting a significant portion of hospitalized and critically ill patients. Current AKI diagnosis relies on serum creatinine (sCr), which has several recognized limitations that affect the timely detection and response to AKI management. Serum cystatin C (sCys) has characteristics that can overcome the limitations of sCr, but head-to-head comparisons of these biomarkers are difficult to study prospectively. A quantitative assessment of the kinetics of sCys and sCr during AKI is necessary to support clinical workflow implementation for AKI diagnosis and management.

Methods

A quantitative systems pharmacology model was developed using Matrix Laboratories and Simbiology (The MathWorks, Natick, MA), to simulate the concentration–time profiles of sCr and sCys under varying degrees of AKI across a spectrum of baseline kidney function. The model incorporated parameters from existing literature and used a contemporary sCr and sCys GFR equation to assess the time to reach AKI diagnostic criteria for both biomarkers.

Results

The model demonstrated that sCys achieves steady-state concentration and meets AKI diagnostic thresholds significantly faster than sCr, with an advantage of 6–48 hours, depending on CKD stage. sCys exhibited greater sensitivity in detecting GFR reductions, with the ability to detect AKI within 12–24 hours after AKI, compared with 12–72 hours for sCr. The study also identified that for sCys, absolute value diagnostic cutoffs are more effective than percentage-based thresholds and can provide consistent detection across different CKD stages.

Conclusions

sCys has superior kinetics for early AKI detection compared with sCr, making it a valuable addition to AKI diagnostic protocols, particularly in high-risk populations. Daily monitoring of sCys in patients at risk of AKI would facilitate more timely detection and potentially improve clinical outcomes. Future research should focus on validating sCys diagnostic criteria and integrating it with other biomarkers to enhance AKI management.

Predictive value of serum cystatin C for acute kidney injury in adults: a meta-analysis of prospective cohort trials

The role of serum cystatin C (Scys) for the detection of acute kidney injury (AKI) has not been fully discussed. This meta-analysis was aimed to investigate the overall diagnostic accuracy of Scys for AKI in adults, and further identify factors affecting its performance. Studies before Sept. 2016 were retrieved from PubMed, Embase, Web of Science and the Cochrane Library. A total of 30 prospective cohort studies (involving 4247 adults from 15 countries, 982 patients occurring AKI) were included. The revised Quality Assessment for Studies of Diagnostic Accuracy (QUADAS-2) tools demonstrated no significant bias had influenced the methodological quality of the included studies. Scys showed a high predictive power for all-cause AKI, that the area under the receiver operating characteristic curve was 0.89. The detailed assessment parameters, such as sensitivity, specificity, positive likelihood ratio, negative likelihood ratio and diagnostic odds ratio for Scys were 0.82, 0.82, 4.6, 0.22 and 21, respectively. Although Scys could be slightly influenced by the following factors: settings, AKI diagnostic criteria, ethnicity, determination method, age and gender, these factors above did not reach statistically significance. In conclusion, Scys could be a vital promising marker to screen out AKI.

Protecting the Kidney in Liver Transplant Recipients: Practice-Based Recommendations From the American Society of Transplantation Liver and Intestine Community of Practice

Both acute and chronic kidney disease are common after liver transplantation and result in significant morbidity and mortality. The introduction of the Model for End-stage Liver Disease score has directly correlated with an increased prevalence of perioperative renal dysfunction and the number of simultaneous liver-kidney transplantations performed. Kidney dysfunction in this population is typically multifactorial and related to preexisting conditions, pretransplantation renal injury, perioperative events, and posttransplantation nephrotoxic immunosuppressive therapies. The management of kidney disease after liver transplantation is challenging, as by the time the serum creatinine level is significantly elevated, few interventions affect the course of progression. Also, immunological factors such as antibody-mediated kidney rejection have become of greater interest given the rising liver-kidney transplant population. Therefore, this review, assembled by experts in the field and endorsed by the American Society of Transplantation Liver and Intestine Community of Practice, provides a critical assessment of measures of renal function and interventions aimed at preserving renal function early and late after liver and simultaneous liver-kidney transplantation. Key points and practice-based recommendations for the prevention and management of kidney injury in this population are provided to offer guidance for clinicians and identify gaps in knowledge for future investigations.

Novel biomarkers for the prediction of acute kidney injury in patients undergoing liver transplantation

AIM

Because of the delayed rise of serum creatinine concentrations, novel biomarkers such as NGAL, GST and KIM-1 are proposed to detect acute kidney injury (AKI). In this study we evaluated these biomarkers.

MATERIALS & METHODS

Twenty-six consecutive adult liver transplantations were evaluated. Markers were measured at four different time points during an intensive care unit admission.

RESULTS

Plasma NGAL detected AKI with an optimal area under the curve at 8 h after admission (0.86; p = 0.004) and at 4 h after admission for urinary NGAL (0.80; p = 0.012). The other markers failed to detect AKI.

CONCLUSION

NGAL is a promising biomarker for detecting AKI in patients after liver transplantation.

The impacts of thyroid function on the diagnostic accuracy of cystatin C to detect acute kidney injury in ICU patients: a prospective, observational study

INTRODUCTION

Cystatin C (Cysc) could be affected by thyroid function both in vivo and in vitro and thereby may have limited ability to reflect renal function. We aimed to assess the association between Cysc and thyroid hormones as well as the effect of thyroid function on the diagnostic accuracy of Cysc to detect acute kidney injury (AKI).

METHODS

A total of 446 consecutive intensive care unit (ICU) patients were screened for eligibility in this prospective AKI observational study. Serum Cysc, thyroid hormones and serum creatinine (Scr) were measured upon entry to the ICU. We also collected each patient's baseline characteristics including the Acute Physiology and Chronic Health Evaluation II (APACHE-II) score. The diagnostic performance of Cysc was assessed from the area under the receiver operator characteristic curve (AUC) in each quartile of thyroid hormone(s).

RESULTS

A total of 114 (25.6%) patients had a clinical diagnosis of AKI upon entry to the ICU. The range of free thyroxine (FT4) value was 4.77 to 39.57 pmol/L. Multivariate linear regression showed that age (standardized beta = 0.128, P < 0.0001), baseline Scr level (standardized beta = 0.290, P < 0.0001), current Scr (standardized beta = 0.453, P < 0.0001), albumin (standardized beta = -0.086, P = 0.006), and FT4 (standardized beta = 0.062, P = 0.039) were related with Cysc. Patients were divided into four quartiles based on FT4 levels. The AUC for Cysc in detecting AKI in each quartile were as follows: 0.712 in quartile I, 0.754 in quartile II, 0.829 in quartile III and 0.797 in quartile IV. There was no significant difference in the AUC between any two groups (all P > 0.05). The optimal cut-off value of Cysc for diagnosing AKI increased across FT4 quartiles (1.15 mg/L in quartile I, 1.15 mg/L in quartile II, 1.35 mg/L in quartile III and 1.45 mg/L in quartile IV).

CONCLUSIONS

There was no significant impact of thyroid function on the diagnostic accuracy of Cysc to detect AKI in ICU patients. However, the optimal cut-off value of Cysc to detect AKI could be affected by thyroid function.

Intrarenal resistance index for the assessment of acute renal injury in a rat liver transplantation model

Background

Acute kidney injury (AKI) is a common complication after liver transplantation (LT) and associated with a high mortality. The renal resistive index (RI) is used to assess early renal function impairment in critical care patients. However, limited data are available concerning changes of renal RI and the development of AKI early after reperfusion. We approached to investigate the changes of renal RI and AKI after reperfusion in a rat liver transplantation model.

Methods

Rats were randomly divided into sham group or LT group. Ten rats in each group were used for the hemodynamic study and twenty for Doppler measurements during the procedure. Ten rats were sacrificed 30 min or 2 h after the reperfusion. We harvested kidneys, serum and urine for further analysis of the renal function.

Results

The intrarenal RI increased significantly in the anhepatic stage and decreased significantly after the reperfusion in the LT group compared with sham group (P < 0.05). AKI was seen after the reperfusion in the LT group. No correlation was noted between the RI and renal function parameters 30 min after reperfusion.

Conclusions

The intrarenal RI increased significantly during the anhepatic stage, and decreased significantly early after the reperfusion. Intrarenal RI was unable to assess renal function in a rat liver transplantation model.

Clinical review: Biomarkers of acute kidney injury: where are we now?

The recognition that acute kidney injury (AKI) is a significant independent risk factor for morbidity and mortality has resulted in a substantial number of publications over the past 5 years or more. In no small part these have, to a degree, highlighted the inadequacy of conventional markers of renal insufficiency in the acute setting. Much effort has been invested in the identification of early, specific AKI markers in order to aid early diagnosis of AKI and hopefully improve outcome. The search for a 'biomarker' of AKI has seen early promise replaced by a degree of pessimism due to the lack of a clear candidate molecule and variability of results. We outline the major studies described to date as well as discuss potential reasons for the discrepancies observed and suggest that evolution of the field may result in success with ultimately an improvement in patient outcomes.

Cystatin C in prediction of acute kidney injury: a systemic review and meta-analysis

BACKGROUND

Cystatin C (CysC) has been proposed as a filtration marker for the early detection of acute kidney injury (AKI); however, a wide range of its predictive accuracy has been reported.

STUDY DESIGN

Meta-analysis of diagnostic test studies.

SETTING & POPULATION

Various clinical settings of AKI, including patients after cardiac surgery, pediatric patients, and critically ill patients.

SELECTION CRITERIA

Computerized search of PubMed, Current Contents, CINAHL, and EMBASE from inception until November 15, 2010, was performed to identify potentially relevant articles. Inclusion criteria were studies investigating the diagnostic accuracy of CysC level to predict AKI. There were no language restrictions in the search.

INDEX TESTS

Increasing or increased serum CysC level or urinary CysC excretion.

REFERENCE TESTS

The outcome was the development of AKI, primarily based on serum creatinine level (definition varied across studies).

RESULTS

We analyzed data from 19 studies and 11 countries involving 3,336 patients. Of these studies, 13 could be included in the meta-analysis. Across all settings, the diagnostic OR for serum CysC level to predict AKI was 27.7 (95% CI, 12.8-59.8), with sensitivity and specificity of 0.86 and 0.82, respectively. The area under the receiver operating characteristic curve (AUROC) of serum CysC levelto predict AKI was 0.87 (95% CI, 0.81-0.93). In an analysis excluding studies that did not clearly define the measurement time point, early serum CysC (within 24 hours after renal insult or intensive care unit admission) remained of diagnostic value. For the diagnostic value of urinary CysC excretion, the diagnostic OR was 3.10 (95% CI, 2.00-4.81), with sensitivity and specificity of0.61 and 0.67, respectively. TheAUROC of urinary CysC excretion to predict AKI was 0.67 (95% CI, 0.63-0.71) [corrected].

LIMITATIONS

Variation in criteria for definitions of index and reference tests, absence of measured glomerular filtration rate in most studies.

CONCLUSION

Serum CysC appears to be a good biomarker in the prediction of AKI, whereas urinary CysC excretion has only moderate diagnostic value.

Neutrophil gelatinase--associated lipocalin predicts acute kidney injury in patients undergoing liver transplantation

Postoperative acute kidney injury (AKI) increases morbidity and mortality after liver transplantation (LT). Novel methods of assessing AKI including cystatin C (CyC) and neutrophil gelatinase-associated lipocalin (NGAL) have been identified as potential markers of AKI. We compare the ability of standard renal markers (serum creatinine [sCr], estimated glomerular filtration rate [eGFR] and intensive therapy unit organ failure scores with CyC and NGAL to predict AKI within the first 48 hours after LT. 95 patients (median age 50 [interquartile range = 41-59], 60% male) underwent LT (25% with acute liver failure). AKI was defined according to the Acute Kidney Injury Network criteria. Severe AKI was classified as ≥stage 2. NGAL (urine [u] and plasma [p]) and CyC concentrations taken immediately after transplantation on admission to the Liver Intensive Care Unit were compared with standard markers of renal function. Predictive ability was assessed using the area under the curve generated by receiver operator characteristic analysis (AUROC) and logistic regression. Day 0 sCr, uNGAL, pNGAL, CyC, and eGFR predicted AKI as did SOFA (Sequential Organ Failure Assessment) and APACHE II (Acute Physiology and Chronic Health Evaluation II) scores. APACHE II and pNGAL were the most powerful predictors of severe AKI (APACHE II AUROC = 0.87 [0.77-0.97], P < 0.001; pNGAL AUROC = 0.87 [0.77-0.92], P < 0.001). Using multivariate logistic regression, APACHE II (odds ratio 1.64/point [95% confidence interval = 1.22-2.21, P = 0.001] and pNGAL [odds ratio = 1.01/ng/mL [95% confidence interval = 1.00-1.02], P = 0.002) retained independent significance. A "renal risk score" using APACHE II > 13 and pNGAL > 258 ng/mL was calculated with a score of ≥1 having a 100% sensitivity and 76% specificity for severe AKI. In conclusion, a combination of NGAL and APACHE II predicts AKI with high sensitivity and specificity after LT.

Cystatin C: current position and future prospects

Cystatin C is a low-molecular-weight protein which has been proposed as a marker of renal function that could replace creatinine. Indeed, the concentration of cystatin C is mainly determined by glomerular filtration and is particularly of interest in clinical settings where the relationship between creatinine production and muscle mass impairs the clinical performance of creatinine. Since the last decade, numerous studies have evaluated its potential use in measuring renal function in various populations. More recently, other potential developments for its clinical use have emerged. This review summarises current knowledge about the physiology of cystatin C and about its use as a renal marker, either alone or in equations developed to estimate the glomerular filtration rate. This paper also reviews recent data about the other applications of cystatin C, particularly in cardiology, oncology and clinical pharmacology.