Acute Kidney Injury in Sepsis: Evidence From Asia

Predictive models of sepsis-associated acute kidney injury based on machine learning: a scoping review

BACKGROUND

With the development of artificial intelligence, the application of machine learning to develop predictive models for sepsis-associated acute kidney injury has made potential breakthroughs in early identification, grading, diagnosis, and prognosis determination.

METHODS

Here, we conducted a systematic search of the PubMed, Cochrane Library, Embase (Ovid), Web of Science, and Scopus databases on April 28, 2023, and screened relevant literature. Then, we comprehensively extracted relevant data related to machine learning algorithms, predictors, and predicted objectives. We subsequently performed a critical evaluation of research quality, data aggregation, and analyses.

RESULTS

We screened 25 studies on predictive models for sepsis-associated acute kidney injury from a total of originally identified 2898 studies. The most commonly used machine learning algorithm is traditional logistic regression, followed by eXtreme gradient boosting. We categorized these predictive models into early identification models (60%), prognostic prediction models (32%), and subtype identification models (8%) according to their predictive purpose. The five most commonly used predictors were serum creatinine levels, lactate levels, age, blood urea nitrogen concentration, and diabetes mellitus. In addition, a single data source, insufficient assessment of clinical utility, lack of model bias assessment, and hyperparameter adjustment may be the main reasons for the low quality of the current research.

CONCLUSIONS

However, studies on the nondeath prognostic outcomes, the long-term clinical outcomes, and the subtype identification models are insufficient. Additionally, the poor quality of the research and the insufficient practicality of the model are problems that need to be addressed urgently.

Acute kidney injury associated with thrombotic microangiopathy: Characterization, prevalence, and prognosis

Acute kidney injury (AKI) is an important feature of thrombotic microangiopathy (TMA). This present study aimed to describe and analyze the characterization, prevalence, and prognosis in TMA patients with AKI. This study was an observational, retrospective patient cohort study in which patients were classified as AKI and non-AKI groups. An analysis of the relationship between the risk factors and AKI and in-hospital mortality was conducted using logistic regression. Kaplan-Meier curves were adopted to obtain the link between AKI and in-hospital mortality. There were 27 and 51 patients in the AKI and non-AKI groups, respectively, and the morbidity and mortality of AKI were 34.62% and 40.74%, respectively. AKI was associated with an older age (P = .033) and higher infection rates (P < .001). In comparison with the non-AKI group, the AKI group had tremendously intrarenal manifestations: hematuria (P < .001), proteinuria (P < .001). The AKI group received all continuous renal replacement therapy treatment (P < .001), but fewer glucocorticoids were used (P = .045). In-hospital mortality (P = .045) were higher in the AKI group. The risk factors for AKI (P = .037) were age. In addition, higher total bilirubin (P = .011) and age (P = .022) were significantly correlated with increasing risk of in-hospital mortality. Survival analysis by Kaplan-Meier revealed a significantly poor prognosis predicted by the AKI group (P = .045). Acute kidney injury could be commonly seen in TMA pneumonia and was related to a higher mortality rate.

Tachycardia and Acute Kidney Injury among Critically Ill Patients with Sepsis: A Prospective Observational Study

INTRODUCTION

Tachycardia caused by sympathetic overactivity impairs myocardial function and raises septic patients' mortality. This study examined whether tachycardia is associated with acute kidney injury (AKI) period-prevalence among critically ill patients with and without sepsis.

METHODS

In 328 patients (119 sepsis and 209 non-sepsis) admitted to our intensive care unit (ICU), we assessed heart rate at ICU admission, plasma neutrophil gelatinase-associated lipocalin (NGAL) and N-terminal pro-B-type natriuretic peptide, and urinary L-type fatty acid-binding protein and N-acetyl-β-d-glucosaminidase (NAG) at 0 and 48 h after admission. Tachycardia was defined as a heart rate above 100 beats/min.

RESULTS

Tachycardia was independently correlated with AKI prevalence during the first week after ICU admission in the septic patients, but not in the non-septic patients. A dose-dependent increase in AKI period-prevalence was observed across ascending heart rate ranges. Furthermore, we discovered a dose-dependent increase in renal biomarker-positive patients regarding plasma NGAL and urinary NAG over increasing heart rate ranges 48 h after admission.

CONCLUSION

The findings revealed an independent relationship between tachycardia and AKI prevalence during the first week of ICU in septic patients. Heart rate was found to have a dose-dependent effect on AKI prevalence and renal insult monitored by biomarkers.

Erythropoietin promotes energy metabolism to improve LPS-induced injury in HK-2 cells via SIRT1/PGC1-α pathway

Acute kidney injury (AKI) is one of frequent complications of sepsis with high mortality. Mitochondria is the center of energy metabolism participating in the pathogenesis of sepsis-associated AKI, and SIRT1/PGC1-α signaling pathway plays a crucial role in the modulation of energy metabolism. Erythropoietin (EPO) exerts protective functions on chronic kidney disease. We aimed to assess the effects of EPO on cell damage and energy metabolism in a cell model of septic AKI. Renal tubular epithelial cells HK-2 were treated with LPS and human recombinant erythropoietin (rhEPO). Cell viability was detected by CCK-8 and mitochondrial membrane potential was determined using JC-1 fluorescent probe. Then the content of ATP, ADP and NADPH, as well as lactic acid, were measured for the assessment of energy metabolism. Oxidative stress was evaluated by detecting the levels of ROS, MDA, SOD and GSH. Pro-inflammatory cytokines, including TNF-α, IL-6, and IL-1β, were measured with ELISA. Moreover, qRT-PCR and western blot were performed to detect mRNA and protein expressions. shSIRT1 was used to knockdown SIRT1, while EX527 and SR-18292 were applied to inhibit SIRT1 and PGC1-α, respectively, to investigate the regulatory mechanism of rhEPO on inflammatory injury and energy metabolism. In LPS-exposed HK-2 cells, rhEPO attenuated cell damage, inflammation and abnormal energy metabolism, as indicated by the elevated cell viability, the inhibited oxidative stress, cell apoptosis and inflammation, as well as the increased mitochondrial membrane potential and energy metabolism. However, these protective effects induced by rhEPO were reversed after SIRT1 or PGC1-α inhibition. EPO activated SIRT1/PGC1-α pathway to alleviate LPS-induced abnormal energy metabolism and cell damage in HK-2 cells. Our study suggested that rhEPO played a renoprotective role through SIRT1/PGC1-α pathway, which supported its therapeutic potential in septic AKI.

Spectrum, Outcomes, and Mortality Predictors of Acute Kidney Injury among Non-COVID-19 Patients during COVID-19 Pandemic: Data from Four Intensive Care Units

Introduction

The data of acute kidney injury (AKI), that is, community-acquired AKI (CA-AKI) and hospital-acquired AKI (HA-AKI) among non-COVID patients from intensive care units (ICU) during the coronavirus disease-2019 (COVID-19) pandemic are scarce. We planned to study the change in the profile of such patients compared to the pre-pandemic era.

Materials and methods

This prospective observational study was conducted at four ICUs dealing with non-COVID patients at a government hospital in North India, and was aimed at assessing outcomes, and mortality predictors of AKI among non-COVID patients during the COVID-19 pandemic. Renal and patient survival at ICU transfer-out and hospital discharge, ICU and hospital stay duration, mortality predictors, and dialysis requirement at discharge were evaluated. The current or previous COVID-19 infection, previous AKI or chronic kidney disease (CKD), organ donors, and organ transplant patients were excluded.

Results

Among the 200 non-COVID-19 AKI patients, diabetes mellitus (DM), primary hypertension, and cardiovascular diseases were the predominant comorbidities in descending order. The commonest cause of AKI was severe sepsis, followed by systemic infections and post-surgery patients. Dialysis requirements at ICU admission during ICU stay and above 30 days were seen in 20.5, 47.5, and 6.5% of patients, respectively. Incidence of CA-AKI and HA-AKI was 1.24:1, whereas dialysis requirement above 30 days was 0.85:1, respectively. The 30-day mortality was 42%. Hepatic dysfunction [hazard ratio (HR): 3.471], septicemia (HR: 3.342), age above 60 years (HR: 4.000), higher sequential organ failure assessment (SOFA) score (HR: 1.107; p = 0.001), anemia (p = 0.003), and low serum iron (p = 0.001) were important mortality predictors in AKI.

Conclusion

Compared to the pre-COVID era, CA-AKI was more common than HA-AKI due to restricted elective surgeries during the COVID-19 pandemic. Acute kidney injury with multiorgan involvement and hepatic dysfunction, elderly age with higher SOFA score and sepsis were predictors of adverse renal and patient outcomes.

How to cite this article

Singh B, Dogra PM, Sood V, Singh V, Katyal A, Dhawan M, et al. Spectrum, Outcomes, and Mortality Predictors of Acute Kidney Injury among Non-COVID-19 Patients during COVID-19 Pandemic: Data from Four Intensive Care Units. Indian J Crit Care Med 2023;27(2):119-126.

The Potential of miR-370-3p and miR-495-3p Serving as Biomarkers for Sepsis-Associated Acute Kidney Injury

Objective

This study is aimed at evaluating the miR-370-3p and miR-495-3p expression in the urine of patients with sepsis-associated acute kidney injury (SA-AKI) and exploring its diagnosis value in for SA-AKI.

Methods

184 sepsis invalids were collected and divided two groups (non-AKI group or AKI group) according to whether they had acute kidney injury. RT-qPCR was utilized to measure miR-370-3p and miR-495-3p expressions. ROC curve was performed to evaluate the diagnostic value of miR-370-3p and miR-495-3p for SA-AKI. Patients diagnosed with SA-AKI were followed up for 28 days to record survival time. The prognostic performance of miR-370-3p and miR-495-3p for SA-AKI was evaluated by survival curves.

Results

Compared with non-AKI invalids, miR-370-3p and miR-495-3p expressions were obviously lower in the urine of AKI invalids. miR-370-3p and miR-495-3p expressions were markedly negatively correlated with biomarkers of renal injury. Furthermore, the area under the curve (AUC) of miR-370-3p and miR-495-3p for diagnosing sepsis SA-AKI was 0.896 and 0.814, respectively. The higher 28 days-survival rate was observed in patients with high miR-370-3p and miR-495-3p expressions.

Conclusions

A novel biomarker for the early diagnosis of SA-AKI may be miR-370-3p and miR-495-3p, which was clearly reduced in the urine of SA-AKI patients.