Urinary biomarkers and renal recovery in critically ill patients with renal support

A clinical score to predict recovery in end-stage kidney disease due to acute kidney injury

Background

Acute kidney injury (AKI) is a major contributor to end-stage kidney disease (ESKD). About one-third of patients with ESKD due to AKI recover kidney function. However, the inability to accurately predict recovery leads to improper triage of clinical monitoring and impacts the quality of care in ESKD.

Methods

Using data from the United States Renal Data System from 2005 to 2014 (n = 22 922), we developed a clinical score to predict kidney recovery within 90 days and within 12 months after dialysis initiation in patients with ESKD due to AKI. Multivariable logistic regressions were used to examine the effect of various covariates on the primary outcome of kidney recovery to develop the scoring system. The resulting logistic parameter estimates were transformed into integer point totals by doubling and rounding the estimates. Internal validation was performed.

Results

Twenty-four percent and 34% of patients with ESKD due to AKI recovered kidney function within 90 days and 12 months, respectively. Factors contributing to points in the two scoring systems were similar but not identical, and included age, race/ethnicity, body mass index, congestive heart failure, cancer, amputation, functional status, hemoglobin and prior nephrology care. Three score categories of increasing recovery were formed: low score (0-6), medium score (7-9) and high score (10-12), which exhibited 90-day recovery rates of 12%, 26% and 57%. For the 12-month scores, the low, medium and high groups consisted of scores 0-5, 6-8 and 9-11, with 12-month recovery rates of 16%, 33% and 62%, respectively. The internal validation assessment showed no overfitting of the models.

Conclusion

A clinical score derived from information available at incident dialysis predicts renal recovery at 90 days and 12 months in patients with presumed ESKD due to AKI. The score can help triage appropriate monitoring to facilitate recovery and begin planning long-term dialysis care for others.

When to discontinue renal replacement therapy. what do we know?

PURPOSE OF REVIEW

Acute kidney injury is common in intensive care patients. Supportive care involves the use of renal replacement therapies as organ support. Initiation of renal replacement therapy has been the subject of much interest over the last few years with several randomised controlled studies examining the optimal time to commence treatment. In contrast to this, little evidence has been generated regarding cessation of therapy. Given that this treatment is complex, not without risk and expensive it seems timely that efforts should be expended at examining this vexing issue.

RECENT FINDINGS

Although several studies have been reported examining the successful discontinuation of renal replacement therapies all studies reported to-date are observational in nature. Conventional biochemical criteria have been used as well as physiological parameters including urine output. More recently, more novel biomarkers of renal function have been studied. Although to-date no optimal variable nor threshold for discontinuation can be established.

SUMMARY

Several variables have been described which may have a role in determining which patients may be successfully weaned from renal replacement therapy. However, few have been exposed to vigorous examination and evidence is sparse in support of any potential approach although urine output currently is the most often described. More recently novel biomarkers have also been examined but again are limited by study design and heterogeneity. Further research is clearly needed focussing on proposed variables preferably in multivariate models to improve predictive ability and successful cessation of therapy.

Different Roles of Functional and Structural Renal Markers Measured at Discontinuation of Renal Replacement Therapy for Acute Kidney Injury

INTRODUCTION

Severe acute kidney injury (AKI) requiring renal replacement therapy (RRT) has been associated with an unacceptably high mortality of 50% or more. Successful discontinuation of RRT is thought to be linked to better outcomes. Although functional and structural renal markers have been evaluated in AKI, little is known about their roles in predicting outcomes at the time of RRT discontinuation.

METHODS

In this prospective single-center cohort study, we analyzed patients who received continuous RRT (CRRT) for AKI between August 2016 and March 2018 in the intensive care unit of the University of Tokyo Hospital (Tokyo, Japan). Clinical parameters and urine samples were obtained at CRRT discontinuation. Successful CRRT discontinuation was defined as neither resuming CRRT for 48 h nor receiving intermittent hemodialysis for 7 days from the CRRT termination. Major adverse kidney events (MAKEs) were defined as death, requirement for dialysis, or a decrease in the estimated glomerular filtration rate (eGFR) of more than 25% from the baseline at day 90.

RESULTS

Of 73 patients, who received CRRT for AKI, 59 successfully discontinued CRRT and 14 could not. Kinetic eGFR, urine volume, urinary neutrophil gelatinase-associated lipocalin (NGAL), and urinary L-type fatty acid binding protein were predictive for CRRT discontinuation. Of these factors, urine volume had the highest area under the curve (AUC) 0.91 with 95% confidence interval [0.80-0.96] for successful CRRT discontinuation. For predicting MAKEs at day 90, the urinary NGAL showed the highest AUC 0.76 [0.62-0.86], whereas kinetic eGFR and urine volume failed to show statistical significance (AUC 0.49 [0.35-0.63] and AUC 0.59 [0.44-0.73], respectively).

CONCLUSIONS

Our prospective study confirmed that urine volume, a functional renal marker, predicted successful discontinuation of RRT and that urinary NGAL, a structural renal marker, predicted long-term renal outcomes. These observations suggest that the functional and structural renal makers play different roles in predicting the outcomes of severe AKI requiring RRT.

Subgroups of Patients with Distinct Health Utility Profiles after AKI

Key Points

Health utility profiles can be identified at 60 days after AKI. Patient subgroups with distinct health utility profiles have different characteristics at index hospitalization and outcomes at 1 year. These profiles may be useful when considering resources to improve the physical and emotional health of patients after AKI.

Background

A large amount of interindividual variability exists in health-related quality of life outcomes after AKI. This study aimed to determine whether subgroups of early AKI survivors could be identified on the basis of distinct health utility impairment profiles ascertained at 60 days after AKI and whether these subgroups differed in clinical and biomarker characteristics at index hospitalization and outcomes at 1-year follow-up.

Methods

This retrospective analysis used data from the Biologic Markers of Renal Recovery for the Kidney study, an observational subcohort of the Acute Renal Failure Trial Network study. Of 402 patients who survived to 60 days after AKI, 338 completed the Health Utility Index 3 survey, which measures impairments in eight health attributes. Latent class analysis was used to identify subgroups of patients with distinct health utility profiles.

Results

Three subgroups with distinct health utility impairment profiles were identified: Low (28% of participants), Moderate (58%), and High (14%) with a median of one, four, and six impairments across the eight health attributes at 60 days after AKI, respectively. Patient subgroups differed in weight, history of cerebrovascular disease, intensity of dialysis, hospital length of stay, and dialysis dependence. Serum creatinine and blood urea nitrogen at index hospitalization did not differ among the three subgroups. The High impairment subgroup had higher levels of IL-6 and soluble TNF receptor 2 at study day 1. The three subgroups had different 1-year mortality rates: 5% in the Low, 21% in the Moderate, and 52% in the High impairment subgroup.

Conclusion

Patient subgroups with distinct health utility impairment profiles can be identified 60 days after AKI. These subgroups have different characteristics at index hospitalization. A higher level of impairment at 60 days was associated with decreased survival.

Evaluation of NAG, NGAL, and KIM-1 as Prognostic Markers of the Initial Evolution of Kidney Transplantation

Kidney transplantation is the best option for end-stage chronic kidney disease. Transplant viability is conditioned by drugs' nephrotoxicity, ischemia-reperfusion damage, or acute rejection. An approach to improve graft survival is the identification of post-transplant renal function prognostic biomarkers. Our objective was to study three early kidney damage biomarkers (N-acetyl-d-glucosaminidase, NAG; neutrophil gelatinase-associated lipocalin, NGAL; and kidney injury molecule-1, KIM-1) in the initial period after transplantation and to identify possible correlations with main complications. We analysed those biomarkers in urine samples from 70 kidney transplant patients. Samples were taken on days 1, 3, 5, and 7 after intervention, as well as on the day that renal function stabilised (based on serum creatinine). During the first week after transplant, renal function improved based on serum creatinine evolution. However, increasing levels of biomarkers at different times during that first week could indicate tubular damage or other renal pathology. A relationship was found between NGAL values in the first week after transplantation and delayed graft function. In addition, higher NAG and NGAL, and lower KIM-1 values predicted a longer renal function stabilisation time. Therefore, urinary NAG, NGAL, and KIM-1 could constitute a predictive tool for kidney transplant complications, contributing to improve graft survival rates.

Urinary neutrophil gelatinase-associated lipocalin and plasma IL-6 in discontinuation of continuous venovenous hemodiafiltration for severe acute kidney injury: a multicenter prospective observational study

BACKGROUND

Patients with severe acute kidney injury (AKI) who require continuous venovenous hemodiafiltration (CVVHDF) in intensive care unit (ICU) are at high mortality risk. Little is known about clinical biomarkers for risk prediction, optimal initiation, and optimal discontinuation of CVVHDF.

METHODS

This prospective observational study was conducted in seven university-affiliated ICUs. For urinary neutrophil gelatinase-associated lipocalin (NGAL) and plasma IL-6 measurements, samples were collected at initiation, 24 h, 48 h after, and CVVHDF discontinuation in adult patients with severe AKI. The outcomes were deaths during CVVHDF and CVVHDF dependence.

RESULTS

A total number of 133 patients were included. Twenty-eight patients died without CVVHDF discontinuation (CVVHDF nonsurvivors). Urinary NGAL and plasma IL-6 at the CVVHDF initiation were significantly higher in CVVHDF nonsurvivors than in survivors. Among 105 CVVHDF survivors, 70 patients were free from renal replacement therapy (RRT) or death in the next 7 days after discontinuation (success group), whereas 35 patients died or needed RRT again (failure group). Urinary NGAL at CVVHDF discontinuation was significantly lower in the success group (93.8 ng/ml vs. 999 ng/ml, p < 0.01), whereas no significant difference was observed in plasma IL-6 between the groups. Temporal elevations of urinary NGAL levels during the first 48 h since CVVHDF initiation were observed in CVVHDF nonsurvivors and those who failed in CVVHDF discontinuation.

CONCLUSIONS

Urinary NGAL at CVVHDF initiation and discontinuation was associated with mortality and RRT dependence, respectively. The serial changes of urinary NGAL might also help predict the prognosis of patients with AKI on CVVHDF.

Validated risk prediction models for outcomes of acute kidney injury: a systematic review

BACKGROUND

Acute Kidney Injury (AKI) is frequently seen in hospitalized and critically ill patients. Studies have shown that AKI is a risk factor for the development of acute kidney disease (AKD), chronic kidney disease (CKD), and mortality.

METHODS

A systematic review is performed on validated risk prediction models for developing poor renal outcomes after AKI scenarios. Medline, EMBASE, Cochrane, and Web of Science were searched for articles that developed or validated a prediction model. Moreover, studies that report prediction models for recovery after AKI also have been included. This review was registered with PROSPERO (CRD42022303197).

RESULT

We screened 25,812 potentially relevant abstracts. Among the 149 remaining articles in the first selection, eight met the inclusion criteria. All of the included models developed more than one prediction model with different variables. The models included between 3 and 28 independent variables and c-statistics ranged from 0.55 to 1.

CONCLUSION

Few validated risk prediction models targeting the development of renal insufficiency after experiencing AKI have been developed, most of which are based on simple statistical or machine learning models. While some of these models have been externally validated, none of these models are available in a way that can be used or evaluated in a clinical setting.

Clinical and Biochemical Profile Associated with Renal Recovery after Acute Kidney Injury in A Mexican Population: Retrospective Cohort Study

Background and Objectives: Our primary objective was to study the clinical and biochemical characteristics associated with acute kidney injury (AKI) remission in a group of Mexican patients. Materials and methods: We retrospectively enrolled 75 patients who were diagnosed with AKI and separated the sample into two groups: nonremitting patients (n = 27, 36%) vs. remitting patients (n = 48, 64%). Results: We found significant relationships between nonremitting AKI and previous diagnosis of chronic kidney disease (p = 0.009), higher serum creatinine (Cr) at admission (p < 0.0001), lower estimated glomerular filtration rate (eGFR) (p < 0.0001), maximum serum creatinine during hospitalization (p < 0.0001), higher fractional excretion of sodium (FENa) (p < 0.0003) and 24-h urine protein (p = 0.005), higher serum potassium on admission (p = 0.025), abnormal levels of procalcitonin (p = 0.006), and increased risk of death (p = 0.015). Conclusion: Chronic kidney disease (CKD), lower eGFR, higher levels of serum creatinine during hospitalization, higher FENa and 24-h urine protein, abnormal levels of procalcitonin, and higher serum potassium on admission were associated with nonremitting AKI. These findings may facilitate the rapid identification of patients at risk for nonremitting AKI based on clinical and biochemical characteristics. Furthermore, these findings may inform the design of timely strategies for the vigilance, prevention, and treatment of AKI.

Early effects of bone marrow-derived mononuclear cells on lung and kidney in experimental sepsis

BACKGROUND

In experimental sepsis, functional and morphological effects of bone marrow-derived mononuclear cell (BMDMC) administration in lung tissue have been evaluated 1 and 7 days after therapy. However, to date no study has evaluated the early effects of BMDMCs in both lung and kidney in experimental polymicrobial sepsis.

MATERIAL AND METHODS

Twenty-five female C57BL/6 mice were randomly divided into the following groups: 1) cecal ligation and puncture (CLP)-induced sepsis; and 2) Sham (surgical procedure without CLP). After 1 h, CLP animals received saline (NaCl 0.9%) (CLP-Saline) or 10⁶ BMDMCs (CLP-Cell) via the jugular vein. At 6, 12, and 24 h after saline or BMDMC administration, lungs and kidneys were removed for histology and molecular biology analysis.

RESULTS

In lungs, CLP-Saline, compared to Sham, was associated with increased lung injury score (LIS) and keratinocyte chemoattractant (KC) mRNA expression at 6, 12, and 24 h. BMDMCs were associated with reduced LIS and KC mRNA expression regardless of the time point of analysis. Interleukin (IL)- 10 mRNA content was higher in CLP-Cell than CLP-Saline at 6 and 24 h. In kidney tissue, CLP-Saline, compared to Sham, was associated with tubular cell injury and increased neutrophil gelatinase-associated lipocalin (NGAL) levels, which were reduced after BMDMC therapy at all time points. Surface high-mobility-group-box (HMGB)- 1 levels were higher in CLP-Saline than Sham at 6, 12, and 24 h, whereas nuclear HMGB-1 levels were increased only at 24 h. BMDMCs were associated with decreased surface HMGB-1 and increased nuclear HMGB-1 levels. Kidney injury molecule (KIM)- 1 and IL-18 gene expressions were reduced in CLP-Cell compared to CLP-Saline at 12 and 24 h.

CONCLUSION

In the present experimental polymicrobial sepsis, early intravenous therapy with BMDMCs was able to reduce lung and kidney damage in a time-dependent manner. BMDMCs thus represent a potential therapy in well-known scenarios of sepsis induction.

PURPOSE

To evaluate early bone marrow-derived mononuclear cell (BMDMC) therapy on lung and kidney in experimental polymicrobial sepsis.

METHODS

Twenty-five female C57BL/6 mice were randomly divided into the following groups: cecal ligation and puncture (CLP)-induced sepsis; and sham (surgical procedure without CLP). After 1 h, CLP animals received saline (CLP-saline) or 10⁶ BMDMCs (CLP-cell) via the jugular vein. Lungs and kidneys were evaluated for histology and molecular biology after 6, 12, and 24 h.

RESULTS

In lungs, BMDMCs reduced the lung injury score and keratinocyte chemoattractant mRNA expression regardless of the time point of analysis; interleukin-10 mRNA content was higher in CLP-cell than CLP-saline at 6 and 24 h. In kidneys, BMDMCs reduced neutrophil gelatinase-associated lipocalin levels at all time points. BMDMCs decreased surface high mobility group box (HMGB)- 1 but increased nuclear HMGB-1 levels.

CONCLUSION

Early BMDMC therapy reduced lung and kidney damage in a time-dependent manner.

Renal scintigraphy to predict persistent renal failure after acute kidney injury: an observational study

INTRODUCTION

Renal scintigraphy (RS) is occasionally performed to assess the risk of persistent renal failure (PRF) in patients with acute kidney disease (AKD). However, its diagnostic performance has never been assessed.

METHODS

We identified all patients with AKD for whom RS was performed in our institution between 2010 and 2017. PRF was defined as persistently low (< 33% of baseline) estimated glomerular filtration rates (eGFR), 1 year after RS. Nuclear medicine specialists reviewed RS data and rated, for each patient, the likelihood of PRF ("PRF score"). We evaluated the performance to predict PRF (area under the ROC curve (AUC)) of RS-derived parameters such as renal accumulation index, accumulation slope, and new parameters derived from serial kidney activity counts. We tested the ability of those parameters to improve a clinical model including hypertension, diabetes, AKI severity and baseline eGFR. Finally, we conducted sensitivity analyses using alternate PRF definitions.

RESULTS

Among 97 patients included, 57 (59%) fulfilled the criteria for PRF. The PRF score was able to predict PRF with an AUC of 0.63. Similarly, the accumulation index and accumulation slope respective AUCs were 0.64 and 0.63. None of these parameters were able to improve the performance of the clinical model. Among new parameters, the 3rd/2nd minute activity ratio and 3rd/2nd minute activity slope had fair diagnostic performance (AUC 0.72 and 0.74, respectively) and improved the performance of the clinical model. Results were confirmed in sensitivity analyses.

CONCLUSION

Conventional renal scintigraphy can identify patients at high risk of PRF with a high specificity but a low sensitivity. New parameters, with comparable diagnostic abilities can be obtained within three minutes of injection.

Development and validation of clinical prediction models for acute kidney injury recovery at hospital discharge in critically ill adults

PURPOSE

Acute kidney injury (AKI) recovery prediction remains challenging. The purpose of the present study is to develop and validate prediction models for AKI recovery at hospital discharge in critically ill patients with ICU-acquired AKI stage 3 (AKI-3).

METHODS

Models were developed and validated in a development cohort (n = 229) and a matched validation cohort (n = 244) from the multicenter EPaNIC database to create prediction models with the least absolute shrinkage and selection operator (Lasso) machine-learning algorithm. We evaluated the discrimination and calibration of the models and compared their performance with plasma neutrophil gelatinase-associated lipocalin (NGAL) measured on first AKI-3 day (NGAL_AKI3) and reference model that only based on age.

RESULTS

Complete recovery and complete or partial recovery occurred in 33.20% and 51.23% of the validation cohort patients respectively. The prediction model for complete recovery based on age, need for renal replacement therapy (RRT), diagnostic group (cardiac/surgical/trauma/others), and sepsis on admission had an area under the receiver operating characteristics curve (AUROC) of 0.53. The prediction model for complete or partial recovery based on age, need for RRT, platelet count, urea, and white blood cell count had an AUROC of 0.61. NGAL_AKI3 showed AUROCs of 0.55 and 0.53 respectively. In cardiac patients, the models had higher AUROCs of 0.60 and 0.71 than NGAL_AKI3's AUROCs of 0.52 and 0.54. The developed models demonstrated a better performance over the reference models (only based on age) for cardiac surgery patients, but not for patients with sepsis and for a general ICU population.

CONCLUSION

Models to predict AKI recovery upon hospital discharge in critically ill patients with AKI-3 showed poor performance in the general ICU population, similar to the biomarker NGAL. In cardiac surgery patients, discrimination was acceptable, and better than NGAL. These findings demonstrate the difficulty of predicting non-reversible AKI early.

The Nutritional Risk Index as a Predictor of 90-Day Dialysis Dependence After Acute Renal Failure: A Pilot Study

OBJECTIVE

Return of sufficient renal function to discontinue dialysis following acute renal failure is an important clinical and patient-oriented outcome. Our study sought to develop a model using the Nutritional Risk Index (NRI) to predict 90-day dialysis dependence.

METHODS

We retrospectively analyzed 77 patients with acute renal failure admitted to a single university medical center's intensive care units between January 2015 and January 2019 with the need for continuous renal replacement therapy. We assessed the predictive ability of the NRI for 90-day dialysis dependence using age, serum total protein, number of vasopressor days, baseline predialysis estimated glomerular filtration rate (eGFR), and Sequential Organ Failure Assessment (SOFA) score as covariates.

RESULTS

Of the analytic group, 20 (25.9%) had severe nutritional risk, and 16 (20.8%) recovered from acute renal failure at 90 days. The mean age was 57.1 years. The clinical model comprising the NRI, age, serum total protein, number of vasopressor days, SOFA score, and baseline predialysis eGFR had an area under the curve (AUC) of 0.89 (95% confidence interval [CI], 0.81-0.97), sensitivity 56.3%, and specificity 95%. Exclusion of baseline predialysis eGFR and SOFA score did not significantly decrease model discrimination, AUC 0.87 (95% CI, 0.78-0.97). The AUC was least when serum total protein was dropped from the final model, 0.79 (95% CI, 0.66-0.92).

CONCLUSIONS

The NRI when used together with other clinical parameters, including serum total protein, may improve the accuracy of predicting renal recovery and independence from dialysis at 90 days.

Predicting renal function recovery and short-term reversibility among acute kidney injury patients in the ICU: comparison of machine learning methods and conventional regression

BACKGROUND

Acute kidney injury (AKI) is one of the most frequent complications of critical illness. We aimed to explore the predictors of renal function recovery and the short-term reversibility after AKI by comparing logistic regression with four machine learning models.

METHODS

We reviewed patients who were diagnosed with AKI in the MIMIC-IV database between 2008 and 2019. Recovery from AKI within 72 h of the initiating event was typically recognized as the short-term reversal of AKI. Conventional logistic regression and four different machine algorithms (XGBoost algorithm model, Bayesian networks [BNs], random forest [RF] model, and support vector machine [SVM] model) were used to develop and validate prediction models. The performance measures were compared through the area under the receiver operating characteristic curve (AU-ROC), calibration curves, and 10-fold cross-validation.

RESULTS

A total of 12,321 critically ill adult AKI patients were included in our analysis cohort. The renal function recovery rate after AKI was 67.9%. The maximum and minimum serum creatinine (SCr) within 24 h of AKI diagnosis, the minimum SCr within 24 and 12 h, and antibiotics usage duration were independently associated with renal function recovery after AKI. Among the 8364 recovered patients, the maximum SCr within 24 h of AKI diagnosis, the minimum Glasgow Coma Scale (GCS) score, the maximum blood urea nitrogen (BUN) within 24 h, vasopressin and vancomycin usage, and the maximum lactate within 24 h were the top six predictors for short-term reversibility of AKI. The RF model presented the best performance for predicting both renal functional recovery (AU-ROC [0.8295 ± 0.01]) and early recovery (AU-ROC [0.7683 ± 0.03]) compared with the conventional logistic regression model.

CONCLUSIONS

The maximum SCr within 24 h of AKI diagnosis was a common independent predictor of renal function recovery and the short-term reversibility of AKI. The RF machine learning algorithms showed a superior ability to predict the prognosis of AKI patients in the ICU compared with the traditional regression models. These models may prove to be clinically helpful and can assist clinicians in providing timely interventions, potentially leading to improved prognoses.

The Growth Factors: Potential Biomarkers and Therapeutic Targets in Kidney Diseases

BACKGROUND

Kidney diseases are a prevalent health problem worldwide. Although substantial progress has been made in understanding the pathophysiology of kidney disease, currently there is no satisfactory clinical treatment available to prevent or treat kidney disease. Therefore, strategies to establish early diagnosis, identify the key molecules, and develop novel therapeutic interventions to slow the progression of kidney diseases and reduce their complications are encouraged.

SUMMARY

The growth factors play a crucial role in the development of kidney diseases. The altered levels of growth factors are usually detected in circulation and urine in the disease course. A growing body of studies has suggested that growth factors, receptors, and related regulators are promising biomarkers for the diagnosis and/or prognosis and potential therapeutic targets for the treatment of kidney diseases. In this review, we summarize recent advances in the potential applications of growth factors for diagnostic biomarkers and therapeutic targets in kidney diseases and highlight their performances in clinical trials.

KEY MESSAGES

Most diagnostic and therapeutic strategies targeting growth factors are still far from clinical implementation. The better understanding of growth factor-regulated pathophysiology and the progress of new intervention approaches are expected to facilitate the clinical translation of growth factor-based diagnosis and therapy of kidney diseases.

Serum myo-inositol oxygenase levels at hospital discharge predict progression to chronic kidney disease in community-acquired acute kidney injury

Acute kidney injury (AKI) increases the risk of morbidity, mortality, and progression to chronic kidney disease (CKD). There are few data on the risk of CKD following community-acquired AKI (CA-AKI) and its predictors from developing countries. We evaluated the association of a panel of serum and urine biomarkers at the time of hospital discharge with 4-month renal outcome in CA-AKI. Patients of either sex, aged between 18 and 70 years, with no underlying CKD, and with CA-AKI were recruited at the time of discharge from hospital in this prospective observational study. Levels of serum and urine biomarkers were analyzed and association between these markers and development of CKD, defined as eGFR < 60 ml/min/1.73 m2 or dialysis dependence at 4 month after discharge, were analyzed using multivariate logistic regression analysis and penalized least absolute shrinkage and selection operator logistic regression. Out of a total 126 patients followed up for 4 months, 25 developed CKD. Those who developed CKD were older (p = 0.008), had higher serum creatinine (p < 0.001) and lower serum albumin (p = 0.001) at discharge. Adjusted logistic regression showed that each 10% increase in standardized serum myo-inositol oxygenase (MIOX) level increased the odds of progression to CKD by 13.5%. With 10% increase in standardized urine Neutrophil gelatinase-associated lipocalin (NGAL), serum creatinine and urine protein creatinine ratio (uPCR), increase in the odds of progression to CKD was 10.5%, 9.6% and 8%, respectively. Multivariable logistic model including serum MIOX, discharge serum creatinine and discharge uPCR, was able to predict the progression of CKD [AUC ROC 0.88; (95% CI 0.81, 0.95)]. High level serum MIOX levels at the time of discharge from hospital are associated with progression to CKD in patients with CA-AKI.

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.

Going Micro in Leptospirosis Kidney Disease

Leptospirosis is a zoonotic and waterborne disease worldwide. It is a neglected infectious disease caused by Leptospira spp., as well as a reemerging disease and global public health problem with respect to morbidity and mortality both in humans and animals. Leptospirosis emerges as a leading cause of acute febrile illness along with hepatorenal injury in many countries, including Thailand. While most affected persons are symptomatic in acute disease, which is always difficult to differentiate from other tropical diseases, there is growing evidence of subtle manifestations that cause unrecognized chronic symptoms. The kidney is one of the common organs affected by Leptospires. Although acute kidney injury in the spectrum of interstitial nephritis is a well-described characteristic in severe leptospirosis, chronic kidney disease from leptospirosis is widely discussed. Early recognition of severe leptospirosis leads to reduce morbidity and mortality. Thus, in this review, we highlight the spectrum of characteristics involved in leptospirosis kidney disease and the use of serologic and molecular methods, as well as the treatments of severe leptospirosis.

The potential for artificial intelligence to predict clinical outcomes in patients who have acquired acute kidney injury during the perioperative period

Acute kidney injury (AKI) is a common medical problem in hospitalised patients worldwide that may result in negative physiological, social and economic consequences. Amongst patients admitted to ICU with AKI, over 40% have had either elective or emergency surgery prior to admission. Predicting outcomes after AKI is difficult and the decision on whom to initiate RRT with a goal of renal recovery or predict a long-term survival benefit still poses a challenge for acute care physicians. With the increasing use of electronic healthcare records, artificial intelligence may allow postoperative AKI prognostication and aid clinical management. Patients will benefit if the data can be readily accessed andregulatory, ethical and human factors challenges can be overcome.

Serum metabolite profiles predict outcomes in critically ill patients receiving renal replacement therapy

Acute kidney injury (AKI) requiring renal replacement therapy (RRT) is associated with increased incidence of dialysis dependence and portends high mortality in critically ill patients. At the early stage of RRT, serum metabolic biomarkers might differntiate patients with a high risk of mortality or permanent kidney injury from those who can recover. Serum samples from participants enrolled in the Veteran's Affairs/National Institutes of Health Acute Renal Failure Trial Network study were collected on day 1 (n = 97) and day 8 (n = 105) of randomized RRT. The samples were further evaluated using LC/MS-based metabolic profiling. A model predicting mortality by day 8 was built from samples collected on day 1 and based on four metabolites with an area under the curve (AUC) of 0.641. A model most predictive of mortality by day 28 was built from the levels of 11 serum metabolites from day 8 with an AUC of 0.789. Both day 1 and day 8 samples had lower serum levels of 1-arachidonoyl-lysoPC and 1-eicosatetraenoyl-lysoPC (involved in anti-inflammatory processes) in the critically ill patients who died by day 8 or day 28. Higher levels of amino acids and amino acid metabolites in the day 8 model predicting < day 28 mortality may be indicative of muscle wasting. A kidney recovery biomarker panel based on the serum levels of three metabolites from day 8 samples with an AUC of 0.70 was devised. Serum metabolic profiling of AKI critically ill patients requiring RRT revealed predictive models of mortality based on observed differences in four serum metabolites at day 1 and 11 metabolites at day 8 which were predictive of mortality. Significant changes in the levels of these metabolites suggest links to inflammatory processes and/or muscle wasting.

Serial urinary neutrophil gelatinase associated lipocalin in pediatric diabetic ketoacidosis with acute kidney injury

BACKGROUND

Acute kidney injury (AKI) due to Diabetic Ketoacidosis (DKA) is rather common. Novel biomarkers to diagnose AKI are being increasingly used in different settings. The use of urinary Neutrophil Gelatinase-Associated Lipocalin (uNGAL) in predicting persistent AKI in pediatric DKA cases is still not thoroughly investigated.

METHODS

This was a secondary analysis of Saline versus Plasma-Lyte in Ketoacidosis (SPinK) trial data; 66 children (> 1 month-12 years) with DKA, defined by the International Society for Pediatric and Adolescent Diabetes (ISPAD), were analyzed. Children with cerebral edema, chronic kidney disease and those who received pre-referral fluids and/or insulin were excluded. uNGAL and urine NGAL-creatinine ratio (uNCR) at 0 and 24 h were measured in all. Persistent AKI was defined as a composite outcome of continuance of AKI defined by the Kidney Disease Improving Global Outcomes (KDIGO) stage 2 or 3 beyond 48 h from AKI onset, progression of AKI from either KDIGO stage 0 or 1 to a worse stage, need of renal replacement therapy or death.

MAIN OUTCOMES

Thirty-five (53%) children had AKI at admission; 32 (91.4%) resolved within 48 h. uNGAL was significantly higher in the AKI group at admission [79.8 ± 27.2 vs 54.6 ± 22.0, p = 0.0002] and at 24 h [61.4 ± 28.3 vs 20.2 ± 14.5, p = 0.0003]. Similar trend was observed with uNCR at admission [6.7 ± 3.7 vs 4.1 ± 2.6, p = 0.002] and at 24 h [6.3 ± 2.5 vs 1.2 ± 1.0, p = 0.01]. Furthermore, uNGAL at admission showed a moderate positive linear correlation with serum creatinine. Additionally, elevated uNGAL at 0 and 24 h correlated with corresponding KDIGO stages. Admission uNGAL >88 ng/ml and uNCR of >11.3 ng/mg had a sensitivity of 66% and 67%, specificity of 76% and 95%, and Area under the receiver operating characteristic curve (AUC) of 0.78 and 0.89 respectively for predicting persistent AKI at 48 h.

CONCLUSIONS

Majority of AKI resolved with fluid therapy. While uNGAL and uNCR both correlated with serum creatinine and AKI stages, serial uNCR was a better predictor of persistent AKI than uNGAL alone. However, feasibility of routine uNGAL measurement to predict persistent AKI in DKA needs further elucidation.

TRIAL REGISTRATION

This was a secondary analysis of the data of SPinK trial [CTRI/2018/05/014042 ( ctri.nic.in )].

Cell spinpods are a simple inexpensive suspension culture device to deliver fluid shear stress to renal proximal tubular cells

Rotating forms of suspension culture allow cells to aggregate into spheroids, prevent the de-differentiating influence of 2D culture, and, perhaps most importantly of all, provide physiologically relevant, in vivo levels of shear stress. Rotating suspension culture technology has not been widely implemented, in large part because the vessels are prohibitively expensive, labor-intensive to use, and are difficult to scale for industrial applications. Our solution addresses each of these challenges in a new vessel called a cell spinpod. These small 3.5 mL capacity vessels are constructed from injection-molded thermoplastic polymer components. They contain self-sealing axial silicone rubber ports, and fluoropolymer, breathable membranes. Here we report the two-fluid modeling of the flow and stresses in cell spinpods. Cell spinpods were used to demonstrate the effect of fluid shear stress on renal cell gene expression and cellular functions, particularly membrane and xenobiotic transporters, mitochondrial function, and myeloma light chain, cisplatin and doxorubicin, toxicity. During exposure to myeloma immunoglobulin light chains, rotation increased release of clinically validated nephrotoxicity cytokine markers in a toxin-specific pattern. Addition of cisplatin or doxorubicin nephrotoxins reversed the enhanced glucose and albumin uptake induced by fluid shear stress in rotating cell spinpod cultures. Cell spinpods are a simple, inexpensive, easily automated culture device that enhances cellular functions for in vitro studies of nephrotoxicity.

Discovery of Novel Proteomic Biomarkers for the Prediction of Kidney Recovery from Dialysis-Dependent AKI Patients

BACKGROUND

AKI requiring dialysis (AKI-D) is associated with prolonged hospitalization, mortality, and progressive CKD among survivors. Previous studies have examined only select urine or serum biomarkers for predicting kidney recovery from AKI.

METHODS

Serum samples collected on day 8 of randomized RRT from 72 patients enrolled in the Veteran's Affairs/National Institutes of Health Acute Renal Failure Trial Network study were analyzed by the SOMAscan proteomic platform to profile 1305 proteins in each sample. Of these patients, 38 recovered kidney function and dialysis was discontinued, whereas another 34 patients remained on dialysis by day 28.

RESULTS

Differential serum levels of 119 proteins, with 53 higher and 66 lower, were detected in samples from patients who discontinued dialysis, compared with patients who remained on dialysis by day 28. Patients were classified into tertiles on the basis of SOMAscan protein measurements for the 25 proteins most differentially expressed. The association of serum levels of each protein with kidney recovery was further evaluated using logistic regression analysis. Higher serum levels of CXCL11, CXCL2/CXCL3, CD86, Wnt-7a, BTK, c-Myc, TIMP-3, CCL5, ghrelin, PDGF-C, survivin, CA2, IL-9, EGF, and neuregulin-1, and lower levels of soluble CXCL16, IL1RL1, stanniocalcin-1, IL-6, and FGF23 when classified in tertiles were significantly associated with better kidney recovery. This significant association persisted for each of these proteins after adjusting for potential confounding risk factors including age, sex, cardiovascular SOFA score, congestive heart failure, diabetes, modality of intensive dialysis treatment, cause of AKI, baseline serum creatinine, day 8 urine volume, and estimated 60-day mortality risk.

CONCLUSIONS

These results suggest concerted changes between survival-related proteins and immune-regulatory chemokines in regulating angiogenesis, endothelial and epithelial remodeling, and kidney cell regeneration, illustrating potential mechanisms of kidney recovery. Thus, this study identifies potential novel predictive biomarkers of kidney recovery in patients with AKI-D.

Nomenclature and diagnostic criteria for acute kidney injury - 2020 consensus of the Taiwan AKI-task force

Acute kidney injury (AKI) is a common syndrome that has a significant impact on prognosis in various clinical settings. To evaluate whether new evidence supports changing the current definition/classification/staging systems for AKI suggested by the Kidney Disease: Improving Global Outcomes (KDIGO) 2012 Clinical Practice Guideline, the Taiwan AKI-TASK Force, composed of 64 experts in various disciplines, systematically reviewed the literature and proposed recommendations about the current nomenclature and diagnostic criteria for AKI. The Taiwan Acute Kidney Injury (TW-AKI) Consensus 2020 was established following the principles of evidence-based medicine to investigate topics covered in AKI guidelines. The Taiwan AKI-TASK Force determined that patients with AKI have a higher risk of developing chronic kidney disease, end-stage renal disease, and death. After a comprehensive review, the TASK Force recommended using novel biomarkers, imaging examinations, renal biopsy, and body fluid assessment in the diagnosis of AKI. Clinical issues with regards to the definitions of baseline serum creatinine (sCr) level and renal recovery, as well as the use of biomarkers to predict renal recovery are also discussed in this consensus. Although the present classification systems using sCr and urine output for the diagnosis of AKI are not perfect, there is not enough evidence to change the current criteria in clinical practice. Future research should investigate and clarify the roles of the aforementioned tools in clinical practice for AKI.

Biomarkers in Acute Kidney Injury

Biomarkers have become a pillar of precision medicine in acute kidney injury (AKI). Traditional markers for diagnosis of AKI are insensitive and insufficient to provide comprehensive information for prognostication. Several emerging biomarkers have shown promising results in large-scale clinical studies. These novel markers likely will be beneficial for personalized AKI prevention and treatment.

Current knowledge about biomarkers of acute kidney injury in liver cirrhosis

Acute kidney injury (AKI) is common in advanced cirrhosis. Prerenal azotemia, hepatorenal syndrome, and acute tubular necrosis are the main causes of AKI in patients with cirrhosis. Evaluation of renal function and differentiation between functional and structural kidney injury are important issues in the management of cirrhosis. However, AKI in cirrhosis exists as a complex clinical spectrum rather than concrete clinical entity. Based on current evidence, changes in serum creatinine (Cr) levels remain the most appropriate standard for defining AKI in cirrhosis. However, serum Cr has a limited role in assessing renal function in this population. This review examines previous studies that investigated the ability of recent biomarkers for AKI in cirrhosis from the perspective of earlier and accurate diagnosis, classification of AKI phenotype, and prediction of clinical outcomes. Serum cystatin C and urine neutrophil gelatinase-associated lipocalin have been extensively studied in cirrhosis, and have facilitated improved diagnosis and prognosis prediction in patients with AKI. In addition, urine N-acetyl-β-D-glucosaminidase, interleukin 18, and kidney injury molecule 1 are other promising biomarkers for advanced cirrhosis. However, the clinical significance of these markers remains unclear because there are no cut-off values defining the normal range and differentiating phenotypes of AKI. In addition, AKI has been defined in terms of serum Cr, and renal biopsy-the gold standard-has not been carried out in most studies. Further discovery of innovate biomarkers and incorporation of various markers could improve the diagnosis and prognosis prediction of AKI, and will translate into meaningful improvements in patient outcomes.

Clinical and experimental approaches for imaging of acute kidney injury

Complex molecular cell dynamics in acute kidney injury and its heterogeneous etiologies in patient populations in clinical settings have revealed the potential advantages and disadvantages of emerging novel damage biomarkers. Imaging techniques have been developed over the past decade to further our understanding about diseased organs, including the kidneys. Understanding the compositional, structural, and functional changes in damaged kidneys via several imaging modalities would enable a more comprehensive analysis of acute kidney injury, including its risks, diagnosis, and prognosis. This review summarizes recent imaging studies for acute kidney injury and discusses their potential utility in clinical settings.

Prospective model for predicting renal recovery in cardiac surgery patients with acute kidney injury requiring renal replacement therapy

Aim

To develop a model for predicting renal recovery in cardiac surgery patients with acute kidney injury (AKI) requiring renal replacement therapy (RRT).

Methods

Data from a prospective randomized controlled trial, conducted in a tertiary hospital to compare the survival effect of two dosages of hemofiltration for continuous RRT in cardiac surgery patients between 20 March 2012 and 9 August 2015, were used to develop the model. The outcome was renal recovery defined as alive and dialysis‐free 90 days after RRT initiation. Multivariate logistic regression with a stepwise backward selection of variables based on Akaike Information Criterion was applied to develop the model, which was internally validated using bootstrapping. Model discrimination, calibration and clinical value were assessed using the concordance index (C‐Index), calibration plots and decision curve analysis, respectively.

Results

Totally, 211 patients with AKI requiring RRT (66.8% male) with median age of 57 years were included. The incidence of renal recovery was 33.2% (n = 70). The model included six variables: body mass index stratification, baseline estimated glomerular filtration rate, hypertension, sepsis, mean arterial pressure and mechanical ventilation. The C‐Index for this model was 0.807 (95% CI, 0.744–0.870). After correction by the bootstrap, the C‐Index was 0.780 (95% CI, 0.720–0.845). The calibration plots indicated good consistency between actual observations and model prediction of renal recovery. Decision curve analysis demonstrated the model was clinical usefulness.

Conclusion

We developed and validated a model to predict the chance of renal recovery in cardiac surgery patients with AKI requiring RRT.

This validated model based on prospective cohort data to predict the chance of renal recovery in cardiac surgery patients, especially after acute dialysis provides values to alert clinical decision and information for post AKI care.

Determinants of Outcomes of Acute Kidney Injury: Clinical Predictors and Beyond

Acute kidney injury (AKI) is a common clinical syndrome characterized by rapid impairment of kidney function. The incidence of AKI and its severe form AKI requiring dialysis (AKI-D) has been increasing over the years. AKI etiology may be multifactorial and is substantially associated with increased morbidity and mortality. The outcome of AKI-D can vary from partial or complete recovery to transitioning to chronic kidney disease, end stage kidney disease, or even death. Predicting outcomes of patients with AKI is crucial as it may allow clinicians to guide policy regarding adequate management of this problem and offer the best long-term options to their patients in advance. In this manuscript, we will review the current evidence regarding the determinants of AKI outcomes, focusing on AKI-D.

Risk factors and prognosis assessment for acute kidney injury: The 2020 consensus of the Taiwan AKI Task Force

Risk and prognostic factors for acute kidney injury (AKI) have been published in various studies across various populations. We aimed to explore recent advancements in and provide updated recommendations on AKI risk stratification and information about local AKI risk factors. The Taiwan Acute Kidney Injury Task Force reviewed relevant recently published literature and reached a consensus after group meetings. Systemic review and group discussion were performed. We conducted a meta-analysis according to the PRISMA statement for evaluating the diagnostic performance of the furosemide stress test. Several risk and susceptibility factors were identified through literature review. Contrast-associated AKI prediction models after coronary angiography were one of the most discussed prediction models we found. The basic approach and evaluation of patients with AKI was also discussed. Our meta-analysis found that the furosemide stress test can be used as a prognostic tool for AKI progression and to identify patients with AKI who are at low risk of renal replacement therapy. Factors associated with de novo chronic kidney injury or renal non-recovery after AKI were identified and summarized. Our review provided practical information about early identification of patients at high risk of AKI or disease progression for Taiwan local clinics.

Impact of sterile leukocyturia on outcome of critically ill patients with severe acute kidney injury

INTRODUCTION

The role of immunological mechanisms on renal regeneration and functional recovery after an episode of Acute Kidney Injury (AKI) is still understudied. We aim to evaluate the impact of sterile leukocyturia on outcomes of critically-ill AKI patients.

METHODS

A retrospective analysis of critically-ill patients with stage ≥2 AKI by KDIGO was performed. Patients with urinary tract infection, previous renal replacement therapy, chronic kidney disease stage >3 and kidney, urinary tract or prostatic cancer were excluded. Sterile leukocyturia was defined as a positive leukocyte esterase value.

RESULTS

108 patients with stage ≥2 AKI were included, 39.8% of which had sterile leukocyturia. AKI patients with sterile leukocyturia were older, had more cardiovascular disease and a lower baseline renal function (p < 0.05). They had a higher serum creatinine and leukocytosis at admission, were more frequently septic (p < 0.05) and had more persistent AKI by both KDIGO criteria at multivariable analysis (OR 6.130, 95% CI 2.007-18.747).

CONCLUSION

Sterile leukocyturia was associated with different patient baseline and AKI characteristics and more persistent AKI by both KDIGO criteria. Sterile leukocyturia may represent a surrogate marker of renal inflammation during AKI.

Long-term consequences of acute kidney injury: a narrative review

The incidence of acute kidney injury (AKI) has increased in the past decades. AKI complicates up to 15% of hospitalizations and can reach up to 50-60% in critically ill patients. Besides the short-term impact of AKI in patient outcomes, several studies report the association between AKI and adverse long-term outcomes, such as recurrent AKI episodes in 25-30% of cases, hospital re-admissions in up to 40% of patients, an increased risk of cardiovascular events, an increased risk of progression of chronic kidney disease (CKD) after AKI and a significantly increased long-term mortality. Despite the long-term impact of AKI, there are neither established guidelines on the follow-up care of AKI patients, nor treatment strategies to reduce the incidence of sequelae after AKI. Only a minority of patients have been referred to nephrology post-discharge care, despite the evidence of improved outcomes associated with nephrology referral by addressing cardiovascular risk and risk of progression to CKD. Indeed, AKI survivors should have specialized nephrology follow-up to assess kidney function after AKI, perform medication reconciliation, educate patients on nephrotoxic avoidance and implement strategies to prevent CKD progression. The authors provide a comprehensive review of the transition from AKI to CKD, analyse the current evidence on the long-term outcomes of AKI and describe predisposing risk factors, highlight the importance of follow-up care in these patients and describe the current therapeutic strategies which are being investigated on their impact in improving patient outcomes.

Urine neutrophil gelatinase-associated lipocalin and urine output as predictors of the successful discontinuation of continuous renal replacement therapy in critically ill patients with acute kidney injury

Background

Continuous renal replacement therapy (CCRT) is a frequently used modality for the support of intensive care patients with acute kidney injury (AKI). Nevertheless, there are no objective criteria for the discontinuation of CRRT. The purpose of this study was to investigate whether urine neutrophil gelatinase-associated lipocalin (uNGAL) alone or in combination with urine output could be used as a diagnostic test for renal function recovery in ICU patients on CRRT.

Methods

This was a single-centre prospective observational study including patients with acute kidney failure needing CRRT. Sixty-nine patients were enrolled, and 54 completed the study. Of the 54 patients, 22 recovered renal function (REC), defined as dialysis independency at 72 h from discontinuation, while 32 patients did not (NREC). Urine NGAL was measured at 0, 6, 12, and 24 h after CRRT discontinuation. The cumulated urine output was measured for 24 h prior to discontinuation and at 6, 12, and 24 h after discontinuation. Missing uNGAL values were calculated by interpolation. The Youden’s index was used to calculate cut-off values in order to define uNGAL and urine output single variable and 2-variable diagnostic tests with the optimum prediction of successful CRRT discontinuation.

Results

Baseline characteristics at CRRT initiation were similar between groups. Compared to the NREC group, the REC group had significantly higher urine output (p < 0.0001) and lower uNGAL (p < 0.001) at all time points, except for uNGAL at 24 h (p < 0.24). The best uNGAL predictor for successful CRRT discontinuation was uNGAL at 6 h after discontinuation (predictive value 80%). The best single predictor was cumulated urine output 24 h before discontinuation (predictive value 85%). The combinations of uNGAL at 6 h (cut-off 1650 μg/L) with cumulated urine output 24 h prior to discontinuation (cut-off 210 ml) proved to be the superior tests (using either “or” or “and”), with predictive values of 93% (successful CRRT discontinuation) and 92% (dialysis dependency).

Conclusions

With a predictive value of 93%, the combination of uNGAL at 6 h after and the cumulated urine output 24 h prior to CRRT cessation proved to be the best diagnostic test for successful CRRT discontinuation in ICU patients.

Clinical trial registration

N/A

Early Recognition of Persistent Acute Kidney Injury

Despite the vast amount of literature dedicated to acute kidney injury (AKI) and its clinical consequences, short-term renal recovery has been relatively neglected. Recent studies have suggested that timing of renal recovery is associated with longer-term risk of death, residual renal function, and end-stage renal failure risk. In addition, longer AKI duration is associated with an increased requirement for renal replacement therapy. Comorbidities, especially renal and cardiovascular, severity of AKI, criteria to reach AKI diagnosis, as well as severity of critical illness have been associated with longer AKI duration, and, more specifically, risk of persistent renal dysfunction. Because predicting short-term renal recovery is clinically relevant, several tests, imaging, and biomarkers have been tested in a way to predict the course of AKI and chances for early renal recovery. In this review, the definition of recovery, consequences of persistent AKI, and tools proposed to predict recovery are described. The performance of these tools and their limits are discussed.

Transient and Persistent AKI and Outcomes in Patients Undergoing Major Abdominal Surgery

INTRODUCTION

Acute kidney injury (AKI) is a frequent diagnosis in surgical patients which has a detrimental effect on short-term and long-term outcomes. The purpose of this study was to evaluate the incidence and predictive factors of transient and persistent postoperative AKI in patients submitted to major abdominal surgery and to characterize the impact of AKI on in-hospital mortality.

METHODS

This study was a cross-examination of a retrospective analysis of clinical data of 450 patients who underwent major abdominal surgery from January 2010 to February 2011. Only AKI developing in the first 48 h after surgery was considered. AKI was diagnosed using the Kidney Disease: Improving Global Outcome (KDIGO) classification based on both serum creatinine (SCr) and urine output criteria. Persistent and transient AKI were defined according to the Acute Disease Quality Initiative (ADQI) workgroup definitions.

RESULTS

In our study, 22.4% of patients developed AKI in the first 48 h post-surgery (n = 101), and 48% of patients had persistent AKI (n = 49), defined as postoperative AKI, with a duration of more than 48 h. Older age (adjusted odds ratio [OR] 1.06 [1.00-1.11], p = 0.039), hypertension (adjusted OR 4.60 [1.17-18.11], p = 0.029), and higher preoperative SCr (adjusted OR 22.67 [4.00-128.46], p < 0.001) were independent predictors of persistent AKI. The overall in-hospital mortality was 6.4% (n = 29). Persistent AKI was associated with higher mortality than transient AKI (51.9 vs. 20.7%; unadjusted OR 13.03 [5.78-29.36], p < 0.001; adjusted OR 4.20 [1.02-17.27], p = 0.047).

CONCLUSION

In this cohort of patients submitted to major abdominal surgery, persistent AKI was an independent predictor of in-hospital mortality in contrast to transient AKI.

Diagnostics, Risk Factors, Treatment and Outcomes of Acute Kidney Injury in a New Paradigm

Acute kidney injury (AKI) is a common clinical condition among patients admitted in the hospitals. The condition is associated with both increased short-term and long-term mortality. With the development of a standardized definition for AKI and the acknowledgment of the impact of AKI on patient outcomes, there has been increased recognition of AKI. Two advances from past decades, the usage of computer decision support and the discovery of AKI biomarkers, have the ability to advance the diagnostic method to and further management of AKI. The increasingly widespread use of electronic health records across hospitals has substantially increased the amount of data available to investigators and has shown promise in advancing AKI research. In addition, progress in the finding and validation of different forms of biomarkers of AKI within diversified clinical environments and has provided information and insight on testing, etiology and further prognosis of AKI, leading to future of precision and personalized approach to AKI management. In this this article, we discussed the changing paradigms in AKI: from mechanisms to diagnostics, risk factors, and management of AKI.

The Role of Biomarkers in Acute Kidney Injury

Several biomarkers have been developed to detect acute kidney injury (AKI) and predict outcomes. Most AKI biomarkers have been shown to be expressed before serum creatinine and to be more sensitive and specific than urine output. Only a few studies have examined how implementation can change clinical outcomes. A second generation of AKI biomarkers have been developed. These markers, including tissue inhibitor of metalloproteinases-2 (TIMP-2) and insulinlike growth factor-binding protein 7 (IGFBP7), have obtained regulatory approval in many countries based on large, rigorous clinical studies and small, single-centered trials and have begun to establish clinical utility.

Clinical predictors of renal non-recovery in acute respiratory distress syndrome

Background

Acute kidney injury (AKI) is the most common extra-pulmonary organ failure in acute respiratory distress syndrome (ARDS). Renal recovery after AKI is determined by several factors. The objective of this study was to determine the predictors of renal non-recovery in ARDS patients.

Methods

A single center retrospective cohort study of patients with AKI after onset of ARDS. Patients with preexisting chronic kidney disease or intensive care unit stay < 24 h were excluded. AKI staging was defined according to the Kidney Disease Improving Global Outcomes (KDIGO) 2012 guidelines. Renal non-recovery was defined as death, dialysis dependence, serum creatinine ≥1.5 times the baseline, or urine output < 0.5 mL/kg/h more than 6 h.

Results

Of the 244 patients that met study criteria, 60 (24.6%) had stage I AKI, 66 (27%) had stage II AKI, and 118 (48.4%) had stage III AKI. Of those, 148 (60.7%) patients had renal non-recovery. On multivariable analysis, factors associated with renal non-recovery were a higher stage of AKI (odds ratio [OR] stage II 5.71, 95% confidence interval [CI] 2.17–14.98; OR stage III 45.85, 95% CI 16.27–129.2), delay in the onset of AKI (OR 1.12, 95% CI 1.03–1.21), history of malignancy (OR 4.02, 95% CI 1.59–10.15), septic shock (OR 3.2, 95% CI 1.52–6.76), and a higher tidal volume on day 1–3 of ARDS (OR 1.41, 95% CI 1.05–1.90). Subgroup analysis of survival at day 28 of ARDS also found that higher severity of AKI (OR stage II 8.17, 95% CI 0.84–79.91; OR stage III 111.67, 95% CI 12.69–982.91), delayed onset of AKI (OR 1.12, 95% CI 1.02–1.23), and active malignancy (OR 6.55, 95% CI 1.34–32.04) were significant predictors of renal non-recovery.

Conclusions

A higher stage of AKI, delayed onset of AKI, a history of malignancy, septic shock, and a higher tidal volume on day 1–3 of ARDS predicted renal non-recovery in ARDS patients. Among survivors, a higher stage of AKI, delayed onset of AKI, and a history of malignancy were associated with renal non-recovery.

Electronic supplementary material

The online version of this article (10.1186/s12882-019-1439-2) contains supplementary material, which is available to authorized users.

WITHDRAWN: Death and Recovery of Kidney Function Among Patients Continued on Dialysis After Discharge From Hospital Stays Complicated by Acute Kidney Injury: A Cohort Study

This article has been withdrawn at the request of the authors and editors because after publication of the Article in Press, the authors discovered that there had been an error in the programming of the statistical analysis. Once the error was corrected, the conclusions of the article were no longer supported. The Publisher and authors apologize for any inconvenience this may cause. The full Elsevier Policy on Article Withdrawal can be found at https://www.elsevier.com/about/our-business/policies/article-withdrawal.

Plasma Biomarkers in Predicting Renal Recovery from Acute Kidney Injury in Critically Ill Patients

BACKGROUND

Numerous studies have suggested a possible role for acute kidney injury (AKI) biomarkers in predicting renal recovery both before and after renal replacement therapy (RRT). However, definitions for recovery and whether to include patients dying but free of RRT may influence results.

OBJECTIVES

To validate plasma neutrophil gelatinase-associated lipocalin (pNGAL) as a useful biomarker for predicting or improving the ability of clinical predictors alone to predict recovery following AKI, including in our model plasma B-type natriuretic peptide (pBNP) to account for cardiovascular events.

METHODS

We analyzed 69 patients enrolled in the Acute Renal Failure Trial Network study. pNGAL and pBNP were measured on days 2, 7, and 14. We analyzed their predictive ability for subsequent recovery, defined as alive and independent from dialysis in 60 days. In sensitivity analyses, we explored changes in results with alternative definitions of recovery.

RESULTS

Twenty-nine patients (42%) recovered from AKI. Neither pNGAL nor pBNP, alone or in combination, was accurate predictors of renal recovery-the best area under the receiver-operating characteristics curve (AUC) was for pNGAL using the largest relative change (AUC 0.59, 95% CI 0.45-0.74). The best clinical model achieved superior performance to biomarkers (AUC 0.69, 95% CI 0.56-0.81). The AUC was greatest (0.75, 95% CI 0.60-0.91) when pNGAL + pBNP on day 14 were added to the clinical model but this increase did not achieve statistical significance. However, integrated discrimination improvement analysis showed that the addition of pNGAL and pBNP on day 14 to the clinical model significantly improved the prediction of renal recovery (p = 0.008).

CONCLUSIONS

pNGAL and pBNP can improve the accuracy of clinical parameters in predicting AKI recovery and a full model using biomarkers together with age achieved adequate discrimination.

Predicting Renal Recovery After Dialysis-Requiring Acute Kidney Injury

INTRODUCTION

After dialysis-requiring acute kidney injury (AKI-D), recovery of sufficient kidney function to discontinue dialysis is an important clinical and patient-oriented outcome. Predicting the probability of recovery in individual patients is a common dilemma.

METHODS

This cohort study examined all adult members of Kaiser Permanente Northern California who experienced AKI-D between January 2009 and September 2015 and had predicted inpatient mortality of <20%. Candidate predictors included demographic characteristics, comorbidities, laboratory values, and medication use. We used logistic regression and classification and regression tree (CART) approaches to develop and cross-validate prediction models for recovery.

RESULTS

Among 2214 patients with AKI-D, mean age was 67.1 years, 40.8% were women, and 54.0% were white; 40.9% of patients recovered. Patients who recovered were younger, had higher baseline estimated glomerular filtration rates (eGFR) and preadmission hemoglobin levels, and were less likely to have prior heart failure or chronic liver disease. Stepwise logistic regression applied to bootstrapped samples identified baseline eGFR, preadmission hemoglobin level, chronic liver disease, and age as the predictors most commonly associated with coming off dialysis within 90 days. Our final logistic regression model including these predictors had a correlation coefficient between observed and predicted probabilities of 0.97, with a c-index of 0.64. An alternate CART approach did not outperform the logistic regression model (c-index 0.61).

CONCLUSION

We developed and cross-validated a parsimonious prediction model for recovery after AKI-D with excellent calibration using routinely available clinical data. However, the model's modest discrimination limits its clinical utility. Further research is needed to develop better prediction tools.

Proteomics and Metabolomics for AKI Diagnosis

Acute kidney injury (AKI) is a severe and frequent condition in hospitalized patients. Currently, no efficient therapy of AKI is available. Therefore, efforts focus on early prevention and potentially early initiation of renal replacement therapy to improve the outcome in AKI. The detection of AKI in hospitalized patients implies the need for early, accurate, robust, and easily accessible biomarkers of AKI evolution and outcome prediction because only a narrow window exists to implement the earlier-described measures. Even more challenging is the multifactorial origin of AKI and the fact that the changes of molecular expression induced by AKI are difficult to distinguish from those of the diseases associated or causing AKI as shock or sepsis. During the past decade, a considerable number of protein biomarkers for AKI have been described and we expect from recent advances in the field of omics technologies that this number will increase further in the future and be extended to other sorts of biomolecules, such as RNAs, lipids, and metabolites. However, most of these biomarkers are poorly defined by their AKI-associated molecular context. In this review, we describe the state-of-the-art tissue and biofluid proteomic and metabolomic technologies and new bioinformatics approaches for proteomic and metabolomic pathway and molecular interaction analysis. In the second part of the review, we focus on AKI-associated proteomic and metabolomic biomarkers and briefly outline their pathophysiological context in AKI.

Renal regeneration after acute kidney injury

Acute kidney injury is common and associated with negative renal and patient outcomes. The human kidney has a real but limited regeneration capacity. Understanding renal regeneration may allow us to manipulate this process and thus develop therapeutic weapons to improve patients' outcome. In the first part of this paper we discuss the clinical factors associated with renal recovery: baseline patient particularities, acute kidney injury characteristics and the medical approach taken in the short and long-term. In the second part, the cellular and molecular mechanisms underlying renal regeneration are explored. The immune system seems to have an important role, first promoting inflammation and then tissue healing. Other players, such as cellular senescence, mitochondrial dysfunction, renal haemodynamics and metabolic reprogramming also have a role in renal regeneration. We aim to develop a short review of renal regeneration, offering a holistic view of this process.

Continuous veno-venous hemofiltration yields better renal outcomes than intermittent hemodialysis among traumatic intracranial hemorrhage patients with acute kidney injury: A nationwide population-based retrospective study in Taiwan

OBJECT

Traumatic intracranial hemorrhage (TICH) patients with acute kidney injury (AKI) were reported to have a high mortality rate. Renal replacement therapy (RRT) is indicated for patients with a severe kidney injury. This study aimed to compare the effects of different RRT modalities regarding chronic dialysis rate among adult TICH patients with AKI.

METHODS

A retrospective search of computerized hospital records from 2000 to 2010 for patients with a discharge diagnosis of TICH was conducted to identify the index cases. We collected the data of TICH patients with increased intracranial pressure combined with severe AKI who received intermittent hemodialysis (IHD) or continuous veno-venous hemofiltration (CVVH) as RRT. The outcome was dialysis dependence between 2000 and 2010.

RESULTS

From a total of 310 patients who were enrolled in the study, 134 (43%) received CVVH and 176 (57%) received IHD. The risk of dialysis dependency was significantly lower in the CVVH group than in the IHD group (adjusted hazard ratio: 0.368, 95% CI, 0.158-0.858, P = 0.034). Diabetes mellitus and coronary artery disease were risk factors for dialysis dependency. CVVH compared with IHD modality was associated with lower dialysis dependency rate in TICH patients combined with AKI and diabetes mellitus and those with an injury severity score (ISS) ≥16.

CONCLUSION

CVVH may yield better renal outcomes than IHD among TICH patients with AKI, especially those with diabetes mellitus and an ISS ≥16. The beneficial impact of CVVH on TICH patients needs to be clarified in a large cohort study in future.

Soluble cMet levels in urine are a significant prognostic biomarker for diabetic nephropathy

Hepatocyte growth factor and its receptor cMet activate biological pathways necessary for repair and regeneration following kidney injury. Here, we evaluated the clinical role of urinary cMet as a prognostic biomarker in diabetic nephropathy (DN). A total of 218 patients with DN were enrolled in this study. We examined the association of urine cMet levels and long-term outcomes in patients with DN. The levels of urinary cMet were higher in patients with decreased renal function than in patients with relatively preserved renal function (5.25 ± 9.62 ng/ml versus 1.86 ± 4.77 ng/ml, P = 0.001). A fully adjusted model revealed that a urinary cMet cutoff of 2.9 ng/mL was associated with a hazard ratio for end-stage renal disease of 2.33 (95% confidence interval 1.19–4.57, P = 0.014). The addition of urinary cMet to serum creatinine and proteinuria provided the highest net reclassification improvement. We found that in primary cultured human glomerular endothelial cells, TGFβ treatment induced fibrosis, and the protein expression levels of collagen I, collagen IV, fibronectin, and αSMA were decreased after administration of an agonistic cMet antibody. In conclusion, elevated levels of urinary cMet at the time of initial diagnosis could predict renal outcomes in patients with DN.

Matrix metalloproteinases and tissue inhibitors of metalloproteinases in chronic kidney disease and acute kidney injury: a systematic review of the literature

INTRODUCTION

Matrix metalloproteinases (MMPs) are a family of zinc-dependent proteinases involved in remodeling the extracellular matrix. Tissue inhibitors of metalloproteinases (TIMPs) are a family of four proteins that act to limit the degradative actions of MMPs. Chronic kidney disease (CKD) and acute kidney injury (AKI) are public health problems worldwide, the prevalence of which has been increasing. Recent concept considers MMPs and TIMPs as critical factors before the onset of microalbuminuria, as well as accelerating factors associated with the breakdown of the glomerular basement membrane, renal scarring, and fibrosis during the progression of kidney diseases. Here we reviewed studies of the expression of MMPs and TIMPs in humans, using as clinical samples serum, plasma, and urine, with a focus on their potential role as molecular markers in CKD and AKI, as non-invasive markers.

MATERIAL AND METHODS

We used as data sources, studies at Medline database using combinations of the following keywords: CKD, AKI, MMP, TIMP, serum, plasma, and urine.

RESULTS

Evidence suggests that MMPs/TIMPs could be potential targets for therapeutic intervention in kidney diseases; future studies should attempt to improve the diagnostic or prognostic power of these families.

DISCUSSION

Considering published guides, such as biospecimen reporting for improved study quality (BRISQ), strengthening the reporting of observational studies in epidemiology (STROBE), an updated list of essential items for reporting diagnostic accuracy studies (STARD), transparent reporting of a multivariate prediction model for individual prognosis or diagnosis (TRIPOD), and on the studies reviewed here, we have adapted published recommendations and proposed other news in order to enhance the transparency and quality of MMPs/TIMPs research in CKD and AKI. This review reinforces the complexities of MMPs/TIMPs in the pathobiology of the kidney and the need for well-designed and transparent biomedical studies. HIPPOKRATIA 2018, 22(3): 99-104.