Urinary biomarkers predict advanced acute kidney injury after cardiovascular surgery

[Artificial intelligence and acute kidney injury]

Digitalization is increasingly finding its way into intensive care units and with it artificial intelligence (AI) for critically ill patients. One promising area for the use of AI is in the field of acute kidney injury (AKI). The use of AI is primarily focused on the prediction of AKI, but further approaches are also being used to classify existing AKI into different phenotypes. Different AI models are used for prediction. The area under the receiver operating characteristic curve values (AUROC) achieved with these models vary and are influenced by several factors, such as the prediction time and the definition of AKI. Most models have an AUROC between 0.650 and 0.900, with lower values for predictions further into the future and when applying Acute Kidney Injury Network (AKIN) instead of KDIGO criteria. Classification into phenotypes already makes it possible to categorize patients into groups with different risks of mortality or requirement of renal replacement therapy (RRT), but the etiologies or therapeutic consequences derived from this are still lacking. However, all the models suffer from AI-specific shortcomings. The use of large databases does not make it possible to promptly include recent changes in therapy and the implementation of new biomarkers in a relevant proportion. For this reason, serum creatinine and urinary output, with their known limitations, dominate current AI models for prediction impairing the performance of the current models. On the other hand, the increasingly complex models no longer allow physicians to understand the basis on which the warning of a threatening AKI is calculated and subsequent initiation of therapy should take place. The successful use of AIs in routine clinical practice will be highly determined by the trust of the physicians in the systems and overcoming the aforementioned weaknesses. However, the clinician will remain irreplaceable as the decisive authority for critically ill patients by combining measurable and nonmeasurable parameters.

Recovery Dynamics and Prognosis After Dialysis for Acute Kidney Injury

Importance

The interplay among baseline kidney function, severity of acute kidney disease (AKD), and post-AKD kidney function has significant associations with patient outcomes. However, a comprehensive understanding of how these factors are collectively associated with mortality, major adverse cardiac events (MACEs), and end-stage kidney disease (ESKD) in patients with dialysis-requiring acute kidney injury (AKI-D) is yet to be fully explored.

Objective

To investigate the associations of baseline kidney function, AKD severity, and post-AKD kidney function with mortality, MACEs, and ESKD in patients with AKI-D.

Design, Setting, and Participants

This nationwide, population-based cohort study of patients with AKI-D was conducted between January 1, 2015, and December 31, 2018, using data from various health care settings included in the Taiwan nationwide population-based cohort database. Data analysis was conducted from April 28, 2022, to June 30, 2023.

Exposure

Exposure to severe AKI and baseline and post-AKD kidney function.

Main Outcomes and Measures

The primary outcomes were all-cause mortality and incident MACEs, and secondary outcomes were risks of permanent dialysis and readmission.

Results

A total of 6703 of 22 232 patients (mean [SD] age, 68.0 [14.7] years; 3846 [57.4%] male) with AKI-D with post-AKD kidney function follow-up and AKD stage data were enrolled. During a mean (SD) 1.2 (0.9) years of follow-up, the all-cause mortality rate was 28.3% (n = 1899), while the incidence rates of MACEs and ESKD were 11.1% (n = 746) and 16.7% (n = 1119), respectively. After adjusting for known covariates, both post-AKD kidney function and baseline kidney function, but not AKD severity, were independently associated with all-cause mortality, MACEs, ESKD, and readmission. Moreover, worse post-AKD kidney function correlated with progressive and significant increases in the risk of adverse outcomes.

Conclusions and Relevance

In this cohort study of patients with AKI-D, more than one-quarter of patients died after 1.2 years of follow-up. Baseline and post-AKD kidney functions serve as important factors associated with the long-term prognosis of patients with AKI-D. Therefore, concerted efforts to understand the transition from post-AKD to chronic kidney disease are crucial.

An early warning model to predict acute kidney injury in sepsis patients with prior hypertension

Background

In the context of sepsis patients, hypertension has a significant impact on the likelihood of developing sepsis-associated acute kidney injury (S-AKI), leading to a considerable burden. Moreover, sepsis is responsible for over 50 % of cases of acute kidney injuries (AKI) and is linked to an increased likelihood of death during hospitalization. The objective of this research is to develop a dependable and strong nomogram framework, utilizing the variables accessible within the first 24 h of admission, for the anticipation of S-AKI in sepsis patients who have hypertension.

Methods

In this study that looked back, a total of 462 patients with sepsis and high blood pressure were identified from Nanfang Hospital. These patients were then split into a training set (consisting of 347 patients) and a validation set (consisting of 115 patients). A multivariate logistic regression analysis and a univariate logistic regression analysis were performed to identify the factors that independently predict S-AKI. Based on these independent predictors, the model was constructed. To evaluate the efficacy of the designed nomogram, several analyses were conducted, including calibration curves, receiver operating characteristics curves, and decision curve analysis.

Results

The findings of this research indicated that diabetes, prothrombin time activity (PTA), thrombin time (TT), cystatin C, creatinine (Cr), and procalcitonin (PCT) were autonomous prognosticators for S-AKI in sepsis individuals with hypertension. The nomogram model, built using these predictors, demonstrated satisfactory discrimination in both the training (AUC = 0.823) and validation (AUC = 0.929) groups. The S-AKI nomogram demonstrated superior predictive ability in assessing S-AKI within the hypertension grade I (AUC = 0.901) set, surpassing the hypertension grade II (AUC = 0.816) and III (AUC = 0.810) sets. The nomogram exhibited satisfactory calibration and clinical utility based on the calibration curve and decision curve analysis.

Conclusion

In patients with sepsis and high blood pressure, the nomogram that was created offers a dependable and strong evaluation for predicting S-AKI. This evaluation provides valuable insights to enhance individualized treatment, ultimately resulting in improved clinical outcomes.

Proenkephalin as a biomarker correlates with acute kidney injury: a systematic review with meta-analysis and trial sequential analysis

BACKGROUND

Proenkephalin A 119-159 (PENK) is freely filtered in the glomerulus with plasma levels correlating with glomerular filtration rate. Therefore, PENK has been proposed as an early indicator of acute kidney injury (AKI) although its performance is dependent on the clinical setting. This meta-analysis aimed to investigate the correlation between PENK levels and the development of AKI.

METHODS

We conducted a comprehensive search on the PubMed, Embase, Cochrane databases, the website ClinicalTrials.gov and Cnki.net until June 26, 2023. Summary receiver operating characteristic (SROC) curves were used to amalgamate the overall test performance. Diagnostic odds ratio (DOR) was employed to compare the diagnostic accuracy of PENK with other biomarkers. Quality of the evidence was assessed using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) criteria.

RESULTS

We incorporated 11 observational studies with 3969 patients with an incidence of AKI of 23.4% (929 out of 3969 patients) with the best optimal cutoff value of PENK for early detection of AKI being 57.3 pmol/L. The overall sensitivity and specificity of PENK in identifying AKI were 0.69 (95% CI 0.62-0.75) and 0.76 (95% CI 0.68-0.82), respectively. The combined positive likelihood ratio (LR) stood at 2.83 (95% CI 2.06-3.88), and the negative LR was 0.41 (95% CI 0.33-0.52). The SROC curve showcased pooled diagnostic accuracy of 0.77 (95% CI 0.73-0.81). Interestingly, patients with a history of hypertension or heart failure demonstrated a lower specificity of PENK in correlating the development of AKI.

CONCLUSION

Our results indicate that PENK possesses significant potential as a biomarker for the early detection of the development of AKI, using a cutoff point of 57.3 pmol/L for PENK.

Serum procalcitonin, C-reactive protein, and neutrophil gelatinase-associated lipocalin in early diagnosis of acute kidney injury after upper urinary tract calculi

Objective

To investigate the value of serum procalcitonin(PCT), C-reactive protein(CRP), and neutrophil gelatinase-associated lipocalin(NGAL) in the early diagnosis of acute kidney injury(AKI) after upper urinary tract calculi(UUTC).

Methods

The clinical data of 86 patients who underwent UUTC surgery in our hospital from March 2020 to April 2021 were analyzed retrospectively(Approval number: 20211205L, Date: 2021-12-21). Patients were divided into an AKI group (AKI≥7 days after the operation) and a Non-AKI group. PCT, CRP, and NGAL concentrations were compared before and two hours after the operation. Multivariate logistic regression analysis was used to identify risk factors affecting the early occurrence of AKI post-operation. The receiver operating characteristic curve evaluated PCT, CRP, and NGAL in the early AKI diagnosis.

Results

A total of 86 patients (30 with AKI and 56 with Non-AKI) were included. Kidney injury molecule-1(KIM-1) and urinary microalbumin(mAlb) concentrations were significantly higher in the AKI group (P<0.05). PCT, CRP, and NGAL concentrations were significantly higher two hours after the operation than before the operation (P<0.05). KIM-1 levels and elevated PCT, CRP and NGAL concentrations affected the establishment of AKI after UUTC. The sensitivity of PCT, CRP, and NGAL in evaluating AKI after UUTC were 81.17%, 84.42%, and 79.02%; the specificity was 62.31%, 71.48%, and 73.32%; and the AUC was 0.812, 0.885 and 0.804 respectively.

Conclusions

PCT, CRP, and NGAL concentrations in patients with AKI after UUTC were significantly increased two hours after the operation, which can be used for the early diagnosis of AKI after UUTC operation.

Circulating Fibroblast Growth Factor-23 Levels Can Predict Rapid Kidney Function Decline in a Healthy Population: A Community-Based Study

BACKGROUND

Fibroblast growth factor-23 (FGF-23) associates with decreased kidney function in patients with chronic kidney disease (CKD). However, the correlation between circulating FGF-23 levels and the rate of renal function decline in healthy individuals is largely unknown. We aimed to evaluate the predictive performance of FGF-23 for rapid kidney function decline (RKFD) in a community-based study.

METHODS

A total of 2963 people residing in northern Taiwan were enrolled from August 2013 to May 2018 for an annual assessment of kidney function for five years. The baseline estimated glomerular filtration rates (eGFR) were calculated using the 2009 and 2021 Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation, which aggregates the values of serum creatinine and cystatin C (eGFRcr-cys). The outcome was RKFD-a 15% decrease in estimated glomerular filtration rate (eGFR) within the first four years, and a reduction in eGFR without improvement in the 5th year. A generalized additive model (GAM) was used to determine the cut-off value of FGF-23 to predict RKFD.

RESULTS

The incidence of RKFD was 18.0% (114/634). After matching for age and sex at a 1:1 ratio, a total of 220 subjects were analyzed. eGFRcr-cys was negatively correlated with total vitamin D level but seemed irrelevant to FGF-23. Multivariable logistic regression analysis showed that FGF-23, eGFRcr-cys, and urine albumin-to-creatinine ratio (UACR) were independent predictors of the possibility of RKFD. FGF-23 showed the best predictive performance for RKFD (AUROC: 0.803), followed by baseline eGFRcr-cys (AUROC: 0.639) and UACR (AUROC: 0.591). From the GAM, 32 pg/mL was the most appropriate cut-off value of FGF-23 with which to predict RKFD. The subgroup and sensitivity analyses showed consistent results that high-FGF-23 subjects had higher risks of RKFD.

CONCLUSIONS

Circulating FGF-23 level could be a helpful predictor for RKFD in this community-based population.

Predicting Risk Factors of Acute Kidney Injury in the First 7 Days after Admission: Analysis of a Group of Critically Ill Patients

Background

Acute kidney injury (AKI) is a common complication in critically ill patients. Some predictive models have been reported, but the conclusions are controversial. The aim of this study was the formation of nomograms to predict risk factors for AKI in critically ill patients within the first 7 days after admission to the intensive care unit (ICU).

Methods

Data were extracted from the Medical Information Mart for Intensive Care- (MIMIC-) III database. The random forest method was used to fill in the missing values, and least absolute shrinkage and selection operator (Lasso) regression analysis was performed to screen for possible risk factors.

Results

A total of 561 patients were enrolled. Complication with AKI is significantly associated with a longer length of stay (LOS). For all patients, the predictors contained in the prediction nomogram included hypertension, coronary artery disease (CAD), cardiopulmonary bypass (CPB), coronary artery bypass grafting (CABG), Simplified Acute Physiology Score II (SAPS II), central venous pressure (CVP) measured for the first time after admission, and maximum and minimum mean artery pressure (MAP). The model showed good discrimination (C - index = 0.818, 95% CI: 0.779-0.857). In the subgroup of patients with well-controlled blood glucose levels, the significant predictors included hypertension, CABG, CPB, SAPS II, and maximum and minimum MAP. Good discrimination was also present before (C - index = 0.785, 95% CI: 0.736-0.834) and after adjustment (adjusted C - index = 0.770).

Conclusion

Hypertension, CAD, CPB, CABG, SAPS II, CVP measured for the first time after admission, and maximum and minimum MAP were independent risk factors for AKI in critically ill patients.

Artificial intelligence for the prediction of acute kidney injury during the perioperative period: systematic review and Meta-analysis of diagnostic test accuracy

BACKGROUND

Acute kidney injury (AKI) is independently associated with morbidity and mortality in a wide range of surgical settings. Nowadays, with the increasing use of electronic health records (EHR), advances in patient information retrieval, and cost reduction in clinical informatics, artificial intelligence is increasingly being used to improve early recognition and management for perioperative AKI. However, there is no quantitative synthesis of the performance of these methods. We conducted this systematic review and meta-analysis to estimate the sensitivity and specificity of artificial intelligence for the prediction of acute kidney injury during the perioperative period.

METHODS

Pubmed, Embase, and Cochrane Library were searched to 2nd October 2021. Studies presenting diagnostic performance of artificial intelligence in the early detection of perioperative acute kidney injury were included. True positives, false positives, true negatives and false negatives were pooled to collate specificity and sensitivity with 95% CIs and results were portrayed in forest plots. The risk of bias of eligible studies was assessed using the PROBAST tool.

RESULTS

Nineteen studies involving 304,076 patients were included. Quantitative random-effects meta-analysis using the Rutter and Gatsonis hierarchical summary receiver operating characteristics (HSROC) model revealed pooled sensitivity, specificity, and diagnostic odds ratio of 0.77 (95% CI: 0.73 to 0.81),0.75 (95% CI: 0.71 to 0.80), and 10.7 (95% CI 8.5 to 13.5), respectively. Threshold effect was found to be the only source of heterogeneity, and there was no evidence of publication bias.

CONCLUSIONS

Our review demonstrates the promising performance of artificial intelligence for early prediction of perioperative AKI. The limitations of lacking external validation performance and being conducted only at a single center should be overcome.

TRIAL REGISTRATION

This study was not registered with PROSPERO.

STXBP3 and GOT2 predict immunological activity in acute allograft rejection

Background

Acute allograft rejection (AR) following renal transplantation contributes to chronic rejection and allograft dysfunction. The current diagnosis of AR remains dependent on renal allograft biopsy which cannot immediately detect renal allograft injury in the presence of AR. In this study, sensitive biomarkers for AR diagnosis were investigated and developed to protect renal function.

Methods

We analyzed pre- and postoperative data from five databases combined with our own data to identify the key differently expressed genes (DEGs). Furthermore, we performed a bioinformatics analysis to determine the immune characteristics of DEGs. The expression of key DEGs was further confirmed using the real-time quantitative PCR (RT-qPCR), enzyme-linked immunosorbent assay (ELISA), and immunohistochemical (IHC) staining in patients with AR. ROC curves analysis was used to estimate the performance of key DEGs in the early diagnosis of AR.

Results

We identified glutamic-oxaloacetic transaminase 2 (GOT2) and syntaxin binding protein 3 (STXBP3) as key DEGs. The higher expression of STXBP3 and GOT2 in patients with AR was confirmed using RT-qPCR, ELISA, and IHC staining. ROC curve analysis also showed favorable values of STXBP3 and GOT2 for the diagnosis of early stage AR.

Conclusions

STXBP3 and GOT2 could reflect the immunological status of patients with AR and have strong potential for the diagnosis of early-stage AR.

Construction and validation of an early warning model for predicting the acute kidney injury in elderly patients with sepsis

BACKGROUND

Sepsis-induced acute kidney injury (S-AKI) is a significant complication and is associated with an increased risk of mortality, especially in elderly patients with sepsis. However, there are no reliable and robust predictive models to identify high-risk patients likely to develop S-AKI. We aimed to develop a nomogram to predict S-AKI in elderly sepsis patients and help physicians make personalized management within 24 h of admission.

METHODS

A total of 849 elderly sepsis patients from the First Affiliated Hospital of Xi'an Jiaotong University were identified and randomly divided into a training set (75%, n = 637) and a validation set (25%, n = 212). Univariate and multivariate logistic regression analyses were performed to identify the independent predictors of S-AKI. The corresponding nomogram was constructed based on those predictors. The calibration curve, receiver operating characteristics (ROC)curve, and decision curve analysis were performed to evaluate the nomogram. The secondary outcome was 30-day mortality and major adverse kidney events within 30 days (MAKE30). MAKE30 were a composite of death, new renal replacement therapy (RRT), or persistent renal dysfunction (PRD).

RESULTS

The independent predictors for nomogram construction were mean arterial pressure (MAP), serum procalcitonin (PCT), and platelet (PLT), prothrombin time activity (PTA), albumin globulin ratio (AGR), and creatinine (Cr). The predictive model had satisfactory discrimination with an area under the curve (AUC) of 0.852-0.858 in the training and validation cohorts, respectively. The nomogram showed good calibration and clinical application according to the calibration curve and decision curve analysis. Furthermore, the prediction model had perfect predictive power for predicting 30-day mortality (AUC = 0.813) and MAKE30 (AUC = 0.823) in elderly sepsis patients.

CONCLUSION

The proposed nomogram can quickly and effectively predict S-AKI risk in elderly sepsis patients within 24 h after admission, providing information for clinicians to make personalized interventions.

A Predictive Model Based on Inflammatory and Coagulation Indicators for Sepsis-Induced Acute Kidney Injury

Background

Sepsis-induced acute kidney injury (S-AKI) is associated with systemic inflammatory responses and coagulation system dysfunction, and it is associated with an increased risk of mortality. However, there was no study to explore the predictive value of inflammatory and coagulation indicators for S-AKI.

Methods

In this retrospective study, 1051 sepsis patients were identified and divided into a training cohort (75%, n = 787) and a validation cohort (25%, n = 264) in chronological order according to the date they were admitted. Univariate analyses and multivariate logistic regression analyses were performed to identify the independent predictors of S-AKI. The logistic regression analyses (enter methods) were used to conducted the prediction models. The ROC curves were used to determine the predictive value of the constructed models on S-AKI. To test whether the increase in the AUC is significant, we used a two-sided test for ROC curves available online (http://vassarstats.net/roc_comp.html). The secondary outcome was different AKI stages and major adverse kidney events within 30 days (MAKE30). Stage 3B of S-AKI was defined as both meeting the stage 3 criteria [increase of Cr level by > 300% (≥ 4.0 mg/dL with an acute increase of ≥ 0.5 mg/dL) and/or UO < 0.3 mL/kg/h for > 24 h or anuria for > 12 h and/or acute kidney replacement therapy] and having cystatin C positive. MAKE30 were a composite of death, new renal replacement therapy (RRT), or persistent renal dysfunction (PRD).

Results

We discovered that cardiovascular disease, white blood cell (WBC), mean arterial pressure (MAP), platelet (PLT), serum procalcitonin (PCT), prothrombin time activity (PTA), and thrombin time (TT) were independent predictors for S-AKI. The predictive value (AUC = 0.855) of the simplest model 3 (constructed with PLT, PCT, and PTA), with a sensitivity of 77.6% and a specificity of 82.4%, had a similar predictive value comparing with the model 1 (AUC = 0.872) and the model 2 (AUC = 0.864) in the training cohort (P > 0.05). Compared with the model 1 (AUC = 0.888) and the model 2 (AUC = 0.887), the model 3 (AUC = 0.887) had a similar predictive value in the validation cohort. Moreover, model 3 had the best predictive power for predicting S-AKI in the stage 3 (AUC = 0.777), especially in stage 3B (AUC = 0.771). Finally, the model 3 (AUC = 0.843) had perfect predictive power for predicting MAKE30 in sepsis patients.

Conclusion

Within 24 hours after admission, the simplest model 3 (constructed with PLT, PCT, and PTA) might be a robust predictor of the S-AKI in sepsis patients, providing information for timely and efficient intervention.

Neuroblastoma suppressor of tumorigenicity 1 is a circulating protein associated with progression to end-stage kidney disease in diabetes

Circulating proteins associated with transforming growth factor-β (TGF-β) signaling are implicated in the development of diabetic kidney disease (DKD). It remains to be comprehensively examined which of these proteins are involved in the pathogenesis of DKD and its progression to end-stage kidney disease (ESKD) in humans. Using the SOMAscan proteomic platform, we measured concentrations of 25 TGF-β signaling family proteins in four different cohorts composed in total of 754 Caucasian or Pima Indian individuals with type 1 or type 2 diabetes. Of these 25 circulating proteins, we identified neuroblastoma suppressor of tumorigenicity 1 (NBL1, aliases DAN and DAND1), a small secreted protein known to inhibit members of the bone morphogenic protein family, to be most strongly and independently associated with progression to ESKD during 10-year follow-up in all cohorts. The extent of damage to podocytes and other glomerular structures measured morphometrically in 105 research kidney biopsies correlated strongly with circulating NBL1 concentrations. Also, in vitro exposure to NBL1 induced apoptosis in podocytes. In conclusion, circulating NBL1 may be involved in the disease process underlying progression to ESKD, and its concentration in circulation may identify subjects with diabetes at increased risk of progression to ESKD.

Distinct Subtyping of Successful Weaning from Acute Kidney Injury Requiring Renal Replacement Therapy by Consensus Clustering in Critically Ill Patients

Background: Clinical decisions regarding the appropriate timing of weaning off renal replacement therapy (RRT) in critically ill patients are complex and multifactorial. The aim of the current study was to identify which critical patients with acute kidney injury (AKI) may be more likely to be successfully weaned off RRT using consensus cluster analysis. Methods: In this study, critically ill patients who received RRT at three multicenter referral hospitals at several timepoints from August 2016 to July 2018 were enrolled. An unsupervised consensus clustering algorithm was used to identify distinct phenotypes. The outcomes of interest were the ability to wean off RTT and 90-day mortality. Results: A total of 124 patients with AKI requiring RRT (AKI-RRT) were enrolled. The 90-day mortality rate was 30.7% (38/124), and 49.2% (61/124) of the patients were successfully weaned off RRT for over 90 days. The consensus clustering algorithm identified three clusters from a total of 45 features. The three clusters had distinct features and could be separated according to the combination of urinary neutrophil gelatinase-associated lipocalin to creatinine ratio (uNGAL/Cr), Sequential Organ Failure Assessment (SOFA) score, and estimated glomerular filtration rate at the time of weaning off RRT. uNGAL/Cr (hazard ratio [HR] 2.43, 95% confidence interval [CI]: 1.36–4.33) and clustering phenotype (cluster 1 vs. 3, HR 2.7, 95% CI: 1.11–6.57; cluster 2 vs. 3, HR 44.5, 95% CI: 11.92–166.39) could predict 90-day mortality or re-dialysis. Conclusions: Almost half of the critical patients with AKI-RRT could wean off dialysis for over 90 days. Urinary NGAL/Cr and distinct clustering phenotypes could predict 90-day mortality or re-dialysis.

Construction and Validation of a Risk Prediction Model for Acute Kidney Injury in Patients Suffering from Septic Shock

Background. Acute kidney injury (AKI) is an important complication in critically ill patients, especially in sepsis and septic shock patients. Early prediction of AKI in septic shock can provide clinicians with sufficient information for timely intervention so that improve the patients’ survival rate and quality of life. The aim of this study was to establish a nomogram that predicts the risk of AKI in patients with septic shock in the intensive care unit (ICU). Methods. The data were collected from the Medical Information Mart for Intensive Care III (MIMIC-III) database between 2001 and 2012. The primary outcome was AKI in the 48 h following ICU admission. Univariate and multivariate logistic regression analyses were used to screen the independent risk factors of AKI. The performance of the nomogram was evaluated according to the calibration curve, receiver operating characteristic (ROC) curve, decision curve analysis, and clinical impact curve. Results. A total of 2415 patients with septic shock were included in this study. In the training and validation cohort, 1091 (64.48%) of 1690 patients and 475 (65.52%) of 725 patients developed AKI, respectively. The predictive factors for nomogram construction were gender, ethnicity, congestive heart failure, diabetes, obesity, Simplified Acute Physiology Score II (SAPS II), angiotensin-converting enzyme inhibitors (ACEI) or angiotensin receptor blockers (ARBs), bilirubin, creatinine, blood urea nitrogen (BUN), and mechanical ventilation. The model had a good discrimination with the area under the ROC curve of 0.756 and 0.760 in the training and validation cohorts, respectively. The calibration curve for probability of AKI in septic shock showed optimal agreement between prediction by nomogram and actual observation. Decision curve and clinical impact curve analysis indicated that the nomogram conferred high clinical net benefit. Conclusion. The proposed nomogram can quickly and effectively predict the risk of AKI at an early stage in patients with septic shock in ICU, which can provide information for timely and efficient intervention in patients with septic shock in the ICU setting.

The value of kidney injury molecule 1 in predicting acute kidney injury in adult patients: a systematic review and Bayesian meta-analysis

Introduction

The aim of the study was to systematically review relevant studies to evaluate the diagnostic value of urinary kidney injury molecule 1 (uKIM-1) for acute kidney injury (AKI) in adults.

Method

We searched PubMed and Embase for literature published up to November 1st, 2019 and used the Quality Assessment Tool for Diagnosis Accuracy Studies (QUADAS-2) to assess the quality. Then, we extracted useful information from each eligible study and pooled sensitivity, specificity, and area under the curve (AUC) values.

Results

A total of 14 studies with 3300 patients were included. The estimated sensitivity of urinary KIM-1 (uKIM-1) in the diagnosis of AKI was 0.74 (95% CrI 0.62–0.84), and the specificity was 0.84 (95% CrI, 0.76–0.90). The pooled diagnostic odds ratio (DOR) was 15.22 (95% CrI, 6.74–42.20), the RD was 0.55 (95% CrI 0.43–0.70), and the AUC of uKIM-1 in diagnosing AKI was 0.62 (95% CrI 0.41–0.76). The results of the subgroup analysis showed the influence of different factors.

Conclusion

Urinary KIM-1 is a good predictor for AKI in adult patients with relatively high sensitivity and specificity. However, further research and clinical trials are still needed to confirm whether and how uKIM-1 can be commonly used in clinical diagnosis.

Urinary sodium potassium ratio is associated with clinical success after adrenalectomy in patients with unilateral primary aldosteronism

Background

The urinary sodium potassium (NaK) ratio is associated with dietary sodium and potassium intake and blood pressure, and it also reflects the activity of aldosterone. Herein we evaluated the value of the urinary NaK ratio in predicting the surgical outcomes of patients with unilateral primary aldosteronism (uPA).

Methods

This non-concurrent prospective cohort study was conducted from 2011 to 2017 and included 241 uPA patients who had undergone adrenalectomy. Predictors of successful clinical outcomes were analyzed using logistic regression.

Results

Among the 241 uPA patients, 197 (81.7%) achieved clinical complete or partial success. A urinary sodium potassium ratio <3 (odds ratio (OR): 2.5; 95% confidence interval (CI): 1.2-5.4; p = 0.015), body mass index <25 kg/m² (OR: 2.82; 95% CI: 1.31-6.06; p = 0.008), renin <1 ng/mL/h (OR: 2.51; 95% CI: 1.01-6.21; p = 0.047) and mean preoperative blood pressure >115 mmHg (OR: 5.02; 95% CI: 2.10-11.97; p < 0.001) could predict clinical success after adrenalectomy. Furthermore, higher pre-treatment plasma aldosterone (OR: 1.014; 95% CI 1.005-1.024; p = 0.002) or lower serum potassium (OR: 0.523; 95% CI: 0.328-0.836; p = 0.007) were correlated with lower urinary NaK ratio (<3), and log urinary NaK ratio was positively correlated with serum C-reactive protein (β value 2.326; 95% CI 0.029-4.623; p = 0.047).

Conclusions

uPA patients with a lower urinary NaK ratio, due to high plasma aldosterone and low serum potassium concentrations, were more likely to have clinical success after adrenalectomy. uPA patients with a higher urinary NaK ratio were associated with more severe inflammatory status, and possibly more resistant hypertension post-operatively.

Intraoperative Urinary Biomarkers and Acute Kidney Injury After Cardiac Surgery

OBJECTIVES

To evaluate the association of intraoperative urinary biomarker excretion during cardiac surgery and the subsequent development of acute kidney injury (AKI).

DESIGN

Prospective, nonrandomized, observational study.

SETTING

Single tertiary-level, university-affiliated hospital.

PARTICIPANTS

Ninety patients undergoing cardiac surgery with cardiopulmonary bypass (CPB).

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Urinary samples were collected every 30 minutes intraoperatively and then at four, 12, and 24 hours after CPB. Samples were measured for interleukin 18 (IL-18), kidney injury molecule-1 (KIM1), and creatinine concentrations. Urinary biomarker excretion (raw and indexed to creatinine) for four intraoperative and three postoperative points were compared between patients with and those without subsequent AKI defined by increased serum creatinine concentration ≥0.3 mg/dL within the first 48 hours or ≥1.5 times baseline within seven days. Raw and indexed median IL-18 values were similar between AKI groups at all intraoperative points, but became significantly different at 12 hours after CPB. Raw and indexed median KIM1 values were significantly different between AKI groups at multiple intraoperative points and at four and 12 hours after CPB. During intraoperative and postoperative points, patients in the fourth quartile of KIM1 excretion had greater AKI incidence and longer intensive care and hospital lengths of stay than those in the first quartile. Only postoperatively did the differences in these outcomes between the fourth and first quartile of IL-18 excretion occur.

CONCLUSIONS

Intraoperative KIM1 but not IL-18 excretion was associated with postoperative development of AKI.

High plasma C-terminal FGF-23 levels predict poor outcomes in patients with chronic kidney disease superimposed with acute kidney injury

Background:

Elevated plasma C-terminal fibroblast growth factor-23 (cFGF-23) levels are associated with higher mortality in patients with chronic kidney disease (CKD) and acute kidney injury (AKI). Our study explored the outcome forecasting accuracy of cFGF-23 in critically ill patients with CKD superimposed with AKI (ACKD).

Methods:

Urine and plasma biomarkers from 149 CKD patients superimposed with AKI before dialysis were checked in this multicenter prospective observational cohort study. Endpoints were 90-day mortality and 90 days free from dialysis after hospital discharge. Associations with study endpoints were assessed using hierarchical clustering analysis, the generalized additive model, the Cox proportional hazard model, competing risk analysis, and discrimination evaluation.

Results:

Over a median follow up of 40 days, 67 (45.0%) patients died before the 90th day after hospital discharge and 39 (26.2%) progressed to kidney failure with replacement therapy (KFRT). Hierarchical clustering analysis demonstrated that cFGF-23 levels had better predictive ability for 90-day mortality than did other biomarkers. Higher serum cFGF-23 levels were independently associated with greater risk for 90-day mortality [hazard ratio (HR): 2.5; 95% confidence interval (CI) 1.5–4.1; p < 0.001]. Moreover, adding plasma cFGF-23 to the Demirjian AKI risk score model substantially improved risk prediction for 90-day mortality than the Demirjian model alone (integrated discrimination improvement: 0.06; p < 0.05; 95% CI 0.02–0.10). The low plasma cFGF-23 group was predicted having more weaning from dialysis in surviving patients (HR = 0.53, 95% CI, 0.29–0.95, p = 0.05).

Conclusions:

In patients with ACKD, plasma cFGF-23 levels are an independent risk factor to forecast 90-day mortality and 90-day progression to KFRT. In combination with the clinical risk score, plasma cFGF-23 levels could substantially improve mortality risk prediction.

A long journey for acute kidney injury biomarkers

Acute kidney injury (AKI) is a life-threatening illness that continues to have an in-hospital mortality rate of patients with AKI ranges from 20% to 50% or greater, depending on underlying conditions. However, it has only marginally declined over the past 25 years. Previous authoritative publications have been pointed out that the lack of useful biomarkers for AKI has limited progress in improving the outcomes of this disorder. The purpose of this paper is to review the recent biomarkers involved in the early detection of AKI and main reasons for the failure to identify new AKI biomarkers. So far, several new AKI biomarkers have been discovered and validated to improve early diagnosis, degree of severity, pathophysiology, differential diagnosis, prediction for major kidney adverse events (MAKE, risk groups for progressive renal failure, need for renal replacement therapy [RRT], or death). These biomarkers can be classified into functional, damage and pre-injury phase biomarkers. However, the clinical use of the studied biomarkers in AKI prediction remains unclear because large prospective multicenter trials have failed to demonstrate troponin-like diagnostic performance. Reasons for the failure to identify AKI biomarkers are the heterogeneity of AKI itself, biomarker limitations and long roads to the validation of candidates for new AKI biomarkers. In an effort to overcome these barriers to identifying new AKI biomarkers, kidney biopsy specimens should be obtained and assessed in human AKI populations. Research in this field should be carried out in a pan-social approach rather than conducted by just a few medical institutions.

Nomogram to predict the risk of septic acute kidney injury in the first 24 h of admission: an analysis of intensive care unit data

Background: Acute kidney injury (AKI) is a significant cause of morbidity and mortality, especially in sepsis patients. Early prediction of AKI can help physicians determine the appropriate intervention, and thus, improve the outcome. This study aimed to develop a nomogram to predict the risk of AKI in sepsis patients (S-AKI) in the initial 24 h following admission.Methods: Sepsis patients with AKI who met the Sepsis 3.0 criteria and Kidney Disease: Improving Global Outcomes criteria in the Massachusetts Institute of Technology critical care database, Medical Information Mart for Intensive Care (MIMIC-III), were identified for analysis. Data were analyzed using multiple logistic regression, and the performance of the proposed nomogram was evaluated based on Harrell's concordance index (C-index) and the area under the receiver operating characteristic curve.Results: We included 2917 patients in the analysis; 1167 of 2042 patients (57.14%) and 469 of 875 patients (53.6%) had AKI in the training and validation cohorts, respectively. The predictive factors identified by multivariate logistic regression were blood urea nitrogen level, infusion volume, lactate level, weight, blood chloride level, body temperature, and age. With the incorporation of these factors, our model had well-fitted calibration curves and achieved good C-indexes of 0.80 [95% confidence interval (CI): 0.78-0.82] and 0.79 (95% CI: 0.76-0.82) in predicting S-AKI in the training and validation cohorts, respectively.Conclusion: The proposed nomogram effectively predicted AKI risk in sepsis patients admitted to the intensive care unit in the first 24 h.

Transtubular potassium gradient predicts kidney function impairment after adrenalectomy in primary aldosteronism

Background:

In primary aldosteronism (PA), kidney function impairment could be concealed by relative hyperfiltration and emerge after adrenalectomy. We hypothesized transtubular gradient potassium gradient (TTKG), a kidney aldosterone bioactivity indicator, could correlate to end organ damage and forecast kidney function impairment after adrenalectomy.

Methods:

In the present prospective study, we enrolled lateralized PA patients who underwent adrenalectomy and were followed up 12 months after operation in the Taiwan Primary Aldosteronism Investigation (TAIPAI) registry from 2010 to 2018. The clinical outcome was kidney function impairment, defined as estimated glomerular filtration rate (eGFR) <60 ml/min/1.73 m² at 12 months after adrenalectomy. End organ damage is determined by microalbuminuria and left ventricular mass.

Results:

In total, 323 patients [mean, 50.8 ± 10.9 years old; female 178 (55.1%)] were enrolled. Comparing pre-operation and post-operation data, systolic blood pressure, serum aldosterone, urinary albumin to creatinine ratio and eGFR decreased. TTKG ⩾ 4.9 correlated with pre-operative urinary albumin to creatinine ratio >50 mg/g [odds ratio (OR) = 2.42; p = 0.034] and left ventricular mass (B = 20.10; p = 0.018). Multivariate logistic regression analysis demonstrated that TTKG ⩾ 4.9 could predict concealed chronic kidney disease (OR = 5.42; p = 0.011) and clinical success (OR = 2.90, p = 0.017) at 12 months after adrenalectomy.

Conclusions:

TTKG could predict concealed kidney function impairment and cure of hypertension in PA patients after adrenalectomy. TTKG more than 4.9 as an adverse surrogate of aldosterone and hypokalaemia correlated with pre-operative end organ damage in terms of high proteinuria and cardiac hypertrophy.

Controversies in acute kidney injury: conclusions from a Kidney Disease: Improving Global Outcomes (KDIGO) Conference

In 2012, Kidney Disease: Improving Global Outcomes (KDIGO) published a guideline on the classification and management of acute kidney injury (AKI). The guideline was derived from evidence available through February 2011. Since then, new evidence has emerged that has important implications for clinical practice in diagnosing and managing AKI. In April of 2019, KDIGO held a controversies conference entitled Acute Kidney Injury with the following goals: determine best practices and areas of uncertainty in treating AKI; review key relevant literature published since the 2012 KDIGO AKI guideline; address ongoing controversial issues; identify new topics or issues to be revisited for the next iteration of the KDIGO AKI guideline; and outline research needed to improve AKI management. Here, we present the findings of this conference and describe key areas that future guidelines may address.

Acute kidney injury prediction models: current concepts and future strategies

PURPOSE OF REVIEW

Acute kidney injury (AKI) is a critical condition associated with poor patient outcomes. We aimed to review the current concepts and future strategies regarding AKI risk prediction models.

RECENT FINDINGS

Recent studies have shown that AKI occurs frequently in patients with common risk factors and certain medical conditions. Prediction models for AKI risk have been reported in medical fields such as critical care medicine, surgery, nephrotoxic agent exposure, and others. However, practical, generalizable, externally validated, and robust AKI prediction models remain relatively rare. Further efforts to develop AKI prediction models based on comprehensive clinical data, artificial intelligence, improved delivery of care, and novel biomarkers may help improve patient outcomes through precise AKI risk prediction.

SUMMARY

This brief review provides insights for current concepts for AKI prediction model development. In addition, by overviewing the recent AKI prediction models in various medical fields, future strategies to construct advanced AKI prediction models are suggested.

Biomarker Panels in Critical Care

Biomarker panels have the potential to advance the field of critical care medicine by stratifying patients according to prognosis and/or underlying pathophysiology. This article discusses the discovery and validation of biomarker panels, along with their translation to the clinical setting. The current literature on the use of biomarker panels in sepsis, acute respiratory distress syndrome, and acute kidney injury is reviewed.

Prognostic value of serum and urine kidney injury molecule-1 in infants with urinary tract infection

Introduction

Kidney injury molecule-1 (KIM-1) is an important diagnostic and prognostic marker in acute kidney injury and chronic kidney disease of various aetiologies. The aim of the study was to evaluate the usefulness of serum KIM-1 (sKIM-1) and urine KIM-1 (uKIM-1) for predicting febrile and non-febrile urinary tract infection (UTI) in infants.

Material and methods

A prospective study included 101 children divided into three groups: febrile UTI 49 children, non-febrile UTI 22 children, and healthy controls 30 children. The following laboratory tests were performed: sKIM-1, uKIM-1, white blood count (WBC), C-reactive protein (CRP), and procalcitonin (PCT).

Results

Median levels of sKIM-1 were significantly higher in the febrile and non-febrile UTI group compared to the healthy controls (both p < 0.05). Mean levels of uKIM-1 were significantly lower in the febrile UTI group compared to the non-febrile UTI group and healthy controls (p < 0.001 and p < 0.0001, respectively). Univariate logistic regression analysis has demonstrated a positive association of sKIM-1 with febrile and non-febrile UTI (both p < 0.05), and negative association uKIM-1 with febrile UTI (p < 0.0001). Receiver operating curve (ROC) analysis showed good diagnostic profiles of uKIM-1 with a best cut-off value of 2.4 ng/ml and sKIM-1 with a best cut-off value of 3.88 ng/ml for predicting febrile UTI (area under the curve [AUC] 0.82 and 0.67, sensitivity 73% and 63%, specificity 86% and 80%, respectively).

Conclusions

sKIM-1 can be useful for predicting febrile UTI. We do not recommended use of uKIM-1 as a marker of febrile UTI because of its negative association with febrile UTI. Both markers are not useful for predicting non-febrile UTI.

Kidney-based in vitro models for drug-induced toxicity testing

The kidney is frequently involved in adverse effects caused by exposure to foreign compounds, including drugs. An early prediction of those effects is crucial for allowing novel, safe drugs entering the market. Yet, in current pharmacotherapy, drug-induced nephrotoxicity accounts for up to 25% of the reported serious adverse effects, of which one-third is attributed to antimicrobials use. Adverse drug effects can be due to direct toxicity, for instance as a result of kidney-specific determinants, or indirectly by, e.g., vascular effects or crystals deposition. Currently used in vitro assays do not adequately predict in vivo observed effects, predominantly due to an inadequate preservation of the organs' microenvironment in the models applied. The kidney is highly complex, composed of a filter unit and a tubular segment, together containing over 20 different cell types. The tubular epithelium is highly polarized, and the maintenance of this polarity is critical for optimal functioning and response to environmental signals. Cell polarity is dependent on communication between cells, which includes paracrine and autocrine signals, as well as biomechanic and chemotactic processes. These processes all influence kidney cell proliferation, migration, and differentiation. For drug disposition studies, this microenvironment is essential for prediction of toxic responses. This review provides an overview of drug-induced injuries to the kidney, details on relevant and translational biomarkers, and advances in 3D cultures of human renal cells, including organoids and kidney-on-a-chip platforms.

Glycocalyx breakdown is increased in African children with cerebral and uncomplicated falciparum malaria

Cerebral malaria (CM) from Plasmodium falciparum infection is associated with endothelial dysfunction and parasite sequestration. The glycocalyx (GCX), a carbohydrate-rich layer lining the endothelium, is crucial in vascular homeostasis. To evaluate the role of its loss in the pathogenesis of pediatric CM, we measured GCX degradation in Tanzanian children with World Health Organization-defined CM (n = 55), uncomplicated malaria (UM; n = 20), and healthy controls (HCs; n = 25). Urine GCX breakdown products [glycosaminoglycans (GAGs)] were quantified using dimethylmethylene blue (DMMB) and liquid chromatography-tandem mass spectrometry assays. DMMB-GAG and mass spectrometry (MS)-GAG (g/mol creatinine) were increased in CM and UM compared with HCs (P < 0.001), with no differences in DMMB-GAG and MS-GAG between CM and UM children or between those with and without a fatal outcome. In CM survivors, urinary GCX DMMB-GAG normalized by d 3. After adjusting for disease severity, DMMB-GAG was significantly associated with parasitemia [partial correlation coefficient (P_corr) = 0.34; P = 0.01] and plasma TNF (P_corr = 0.26; P = 0.04) and inversely with plasma and urine NO oxidation products [P_corr = -0.31 (P = 0.01) and P_corr = -0.26 (P = 0.03), respectively]. GCX breakdown is increased in children with falciparum malaria, with similar elevations in CM and UM. Endothelial GCX degradation may impair endothelial NO production, exacerbate adhesion-molecule expression, exposure, and parasite sequestration, and contribute to malaria pathogenesis.-Yeo, T. W., Bush, P. A., Chen, Y., Young, S. P., Zhang, H., Millington, D. S., Granger, D. L., Mwaikambo, E. D., Anstey, N. M., Weinberg, J. B. Glycocalyx breakdown is increased in African children with cerebral and uncomplicated falciparum malaria.

Acute Kidney Injury and Septic Shock-Defined by Updated Sepsis-3 Criteria in Critically Ill Patients

Sepsis is commonly associated with acute kidney injury (AKI), particularly in those requiring dialysis (AKI-D). To date, Sepsis-3 criteria have not been applied to AKI-D patients. We investigated sepsis prevalence defined by Sepsis-3 criteria and evaluated the outcomes of septic-associated AKI-D among critically ill patients. Using the data collected from a prospective multi-center observational study, we applied the Sepsis-3 criteria to critically ill AKI-D patients treated in intensive care units (ICUs) in 30 hospitals between September 2014 and December 2015. We described the prevalence, outcomes, and characteristics of sepsis as defined by the screening Sepsis-3 criteria among AKI-D patients, and compared the outcomes of AKI-D patients with or without sepsis using the Sepsis-3 criteria. A total of 1078 patients (median 70 years; 673 (62.4%) men) with AKI-D were analyzed. The main etiology of AKI was sepsis (71.43%) and the most frequent indication for acute dialysis was oliguria (64.4%). A total of 577 (53.3% of 1078 patients) met the Sepsis-3 criteria, and 206 among the 577 patients (19.1%) had septic shock. Having sepsis and septic shock were independently associated with 90-day mortality among these ICU AKI-D patients (hazard ratio (HR) 1.23 (p = 0.027) and 1.39 (p = 0.004), respectively). Taking mortality as a competing risk factor, AKI-D patients with septic shock had a significantly reduced chance of weaning from dialysis at 90 days than those without sepsis (HR 0.65, p = 0.026). The combination of the Sepsis-3 criteria with the AKI risk score led to better performance in forecasting 90-day mortality. Sepsis affects more than 50% of ICU AKI patients requiring dialysis, and one-fifth of these patients had septic shock. In AKI-D patients, coexistent with or induced by sepsis (as screened by the Sepsis-3 criteria), there is a significantly higher mortality and reduced chance of recovering sufficient renal function, when compared to those without sepsis.

Hepcidin - Potential biomarker of contrast-induced acute kidney injury in patients undergoing percutaneous coronary interventions

PURPOSE

Contrast-induced acute kidney injury (CI-AKI) is a common and potentially serious complication of percutaneous coronary interventions (PCI). In this study, we tested the hypothesis whether serum and urinary hepcidin could represent early biomarkers of CI-AKI in patients with normal serum creatinine undergoing PCI. In addition, we assessed serum and urinary neutrophil gelatinase-associated lipocalin (NGAL), cystatin C, eGFR and serum creatinine in these patients.

METHODS

Serum and urinary hepcidin and NGAL, serum cystatin C, were evaluated before, and after 2, 4, 8, 24 and 48 h after PCI using commercially available kits. Serum creatinine was assessed before, 24 and 48 h after PCI.

RESULTS

We found a significant rise in serum hepcidin as early as after 4 and 8 h when compared to the baseline values. Serum NGAL increased after 2, 4 and 8 h, and in urinary NGAL after 4, 8 and 24 h after PCI. We found a significant fall in urinary hepcidin after 8 and 24 h after PCI. Serum cystatin C increased significantly 8 h after PCI, reaching peak 24 h after PCI and then decreased after 48 h. The prevalence of CI-AKI was 8%. Urine hepcidin was significantly lower 8 and 24 h after PCI in patients with CI-AKI, while serum and urine NGAL were significantly higher in patients with CI-AKI.

CONCLUSIONS

Our findings suggest that serum hepcidin might be an early predictive biomarker of ruling out CI-AKI after PCI, thereby contributing to early patient risk stratification. However, our data needs to be validated in large cohorts with various stages of CKD.

Diagnostic accuracy of urine neutrophil gelatinase-associated lipocalin and urine kidney injury molecule-1 as predictors of acute pyelonephritis in young children with febrile urinary tract infection

Introduction

We assessed whether two urinary biomarkers of acute kidney injury, neutrophil gelatinase associated lipocalin (uNGAL) and kidney injury molecule-1 (uKIM-1), can be useful for predicting acute pyelonephritis (APN) in children aged 1-24 months with the first febrile urinary tract infection (UTI).

Material and methods

A prospective study included 54 children divided into two groups (24 with APN, 30 with lower UTI), according to the dimercaptosuccinic acid (DMSA) renal scintigraphy results. Laboratory tests: uNGAL, uKIM-1, procalcitonin (PCT), C-reactive protein (CRP), white blood count (WBC) were performed.

Results

We did not find significant differences in normalized and non-normalized values of uNGAL and uKIM-1 in children with APN and lower UTI. Positive correlations were determined between uNGAL and pyuria (r = 0.28, p < 0.05) and between uNGAL/uCr and uKIM-1/uCr (r = 0.53, p < 0.001) in the all UTI groups. Univariate logistic regression analysis demonstrated that only PCT (p < 0.0001) and CRP (p < 0.05) were important diagnostic factors of APN. Receiver operating curve (ROC) analysis showed good diagnostic profiles of PCT with the best cut-off value of 1.66 ng/ml and of CRP with the best cut-off value of 4.3 mg/dl for predicting APN (area under the curve [AUC]: 0.894 and 0.719, sensitivity: 75% and 96%, specificity: 93% and 43%, respectively).

Conclusions

uNGAL and uKIM-1 are not effective diagnostic markers for APN in young children with febrile UTI and cannot be used in clinical practice to differentiate APN from lower UTI.

Effects of pulsatile minimal invasive extracorporeal circulation on fibrinolysis and organ protection in adult cardiac surgery-a prospective randomized trial

Background

Minimal invasive extracorporeal circulation (MiECC) reduces the impact of cardiopulmonary bypass during cardiac surgery on inflammation and hemostasis. Pulsatile perfusion may enhance organ perfusion and help to prevent renal and neuronal damage. The present study investigated the impact of pulsatile MiECC in low-risk coronary artery bypass grafting (CABG) patients.

Methods

CABG patients were prospectively randomized for non-pulsatile (np: n=19) and pulsatile (p: n=21) MiECC. Blood and urine samples were collected at several time points until 72 h post-operative and analyzed for biochemical markers of fibrinolytic capacity, renal damage, and neuronal damage.

Results

Although intraoperative tissue plasminogen activator (tPA) levels tended to be higher in the p group, none of the fibrinolysis markers including plasminogen activator inhibitor (PAI-1) and the PAI-1/tPA ratio were significantly affected by pulsation. Hemolysis and markers of renal and neuronal damage were comparable between groups. Intraoperative urinary excretion [np: 400 mL (355 to 680) vs. p: 530 mL (360 to 900)] and cumulative 24 h volume intake [np: 7,090 mL (5,492 to 7,544) vs. p: 7,155 mL (6,682 to 8,710)] were increased by pulsation whereas blood losses up to 12 h post-operative [np: 365 mL (270 to 515) vs. p: 310 mL (225 to 470)] and up to 24 h post-operative [np: 760 mL (555 to 870) vs. p: 520 mL (460 to 670)] were attenuated.

Conclusions

The present study did not find evidence for a beneficial effect of pulsation on markers of fibrinolysis, renal damage, and neuronal damage. However, pulsatile perfusion increased intraoperative urinary secretion and reduced post-operative blood losses.

Kidney Tubular Damage and Functional Biomarkers in Acute Kidney Injury Following Cardiac Surgery

Background

Cardiac 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.

Methods

Single-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.

Results

A 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).

Conclusions

Combining 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.