Limiting Acute Kidney Injury Progression In Sepsis: Study Protocol and Trial Simulation

lncRNA NORAD alleviates dysfunction of renal proximal tubular epithelial cells during the sepsis-associated acute kidney injury by modulating the miR-155-5p-PDK1 axis

The sepsis-associated acute kidney injury (Sa-AKI) is closely related to high mortality rates worldwide. Injury to the renal proximal tubular epithelial cells (RPTECs), caused by pathological conditions, is a major cause of acute kidney injury (AKI). The lncRNA NORAD has been reported to be positively associated with kidney cancers. However, the biological roles and underlying mechanisms of NORAD in RPTECs during AKI are still unclear. In this study, we found that NORAD was significantly downregulated in RPTECs from AKI tissues. Overexpression of NORAD alleviated RPTECs injury induced by lipopolysaccharide (LPS). Additionally, glucose metabolism was significantly impaired during AKI, and LPS treatment inhibited glucose metabolism in RPTECs. We demonstrated that NORAD rescued the LPS-induced inhibition of glucose metabolism in RPTECs. Furthermore, miRNA-155-5p was significantly upregulated in RPTECs from AKI. Through bioinformatics analysis, RNA pull-down, RNA IP, and luciferase assays, we showed that NORAD directly associated with miR-155-5p to downregulate its expression. Moreover, overexpression of miR-155-5p inhibited glucose metabolism by directly targeting the 3'UTR of the glucose metabolism enzyme, pyruvate dehydrogenase kinase 1 (PDK1). Finally, rescue experiments validated that NORAD's protective effect on RPTECs injury was mediated through modulation of the miR-155-5p-PDK1-glucose metabolism pathway. In summary, these results reveal that lncRNA NORAD can alleviate RPTECs dysfunction by targeting the miR-155-5p-PDK1 axis, suggesting that NORAD has the potential to contribute to the development of therapeutic approaches against Sa-AKI.

Distribution of Acute and Chronic Kidney Disease Across Clinical Phenotypes for Sepsis

BACKGROUND

Sepsis is the most common cause of acute kidney injury (AKI) in critically ill patients. Four phenotypes (α, β, γ, δ) for sepsis, which have different outcomes and responses to treatment, were described using routine clinical data in the electronic health record.

RESEARCH QUESTION

Do the frequencies of AKI, acute kidney disease (AKD), chronic kidney disease (CKD), and AKI on CKD differ by sepsis phenotype?

STUDY DESIGN AND METHODS

This was a secondary analysis of a randomized clinical trial of early resuscitation, including patients with septic shock at 31 sites. After excluding patients with end-stage kidney disease and missing data, we determined frequencies of the following clinical outcomes: AKI (defined within 24 h as Kidney Disease: Improving Global Outcomes stages 2 or 3 or stage 1 with tissue inhibitor of metalloproteinases-2 × insulin-like growth factor binding protein 7 value of > 2.0), CKD, and AKD (persistence of AKI at any stage on day 7 after enrollment) across four phenotypes. We performed multivariable logistic regression to assess the risk-adjusted association between development of AKI and AKD and phenotype.

RESULTS

Among 1,090 eligible patients, 543 patients (50%) had AKI. Across phenotypes, the frequencies of AKI varied, being highest in the δ and β phenotypes (78% and 71%, respectively) and the lowest in the α phenotype (26%; P < .001). AKD occurred most often in the δ phenotype (41%) and least often in the α phenotype (8%; P < .001). The highest frequencies of CKD and of AKI on CKD were found in the β phenotype (53% and 38% respectively; P < .001 for both). In the multivariable logistic regression models (α phenotype as reference), δ phenotype showed the strongest association with AKI (OR, 12.33; 95% CI, 7.81-19.47; P < .001) and AKD (OR, 9.18; 95% CI, 5.44-15.51; P < .001).

INTERPRETATION

The rates of AKI and AKD differed across clinical sepsis phenotypes and are more common among patients with phenotypes β and δ. Phenotype β showed a higher level of underlying CKD that predisposed patients to new AKI. The α and γ phenotypes showed lower frequencies of AKI and less progression to AKD.

Unsupervised clustering identifies sub-phenotypes and reveals novel outcome predictors in patients with dialysis-requiring sepsis-associated acute kidney injury

INTRODUCTION

Heterogeneity exists in sepsis-associated acute kidney injury (SA-AKI). This study aimed to perform unsupervised consensus clustering in critically ill patients with dialysis-requiring SA-AKI.

PATIENTS AND METHODS

This prospective observational cohort study included all septic patients, defined by the Sepsis-3 criteria, with dialysis-requiring SA-AKI in surgical intensive care units in Taiwan between 2009 and 2018. We employed unsupervised consensus clustering based on 23 clinical variables upon initializing renal replacement therapy. Multivariate-adjusted Cox regression models and Fine-Gray sub-distribution hazard models were built to test associations between cluster memberships with mortality and being free of dialysis at 90 days after hospital discharge, respectively.

RESULTS

Consensus clustering among 999 enrolled patients identified three sub-phenotypes characterized with distinct clinical manifestations upon renal replacement therapy initiation (n = 352, 396 and 251 in cluster 1, 2 and 3, respectively). They were followed for a median of 48 (interquartile range 9.5-128.5) days. Phenotypic cluster 1, featured by younger age, lower Charlson Comorbidity Index, higher baseline estimated glomerular filtration rate but with higher severity of acute illness was associated with an increased risk of death (adjusted hazard ratio of 3.05 [95% CI, 2.35-3.97]) and less probability to become free of dialysis (adjusted sub-distribution hazard ratio of 0.55 [95% CI, 0.38-0.8]) than cluster 3. By examining distinct features of the sub-phenotypes, we discovered that pre-dialysis hyperlactatemia ≥3.3 mmol/L was an independent outcome predictor. A clinical model developed to determine high-risk sub-phenotype 1 in this cohort (C-static 0.99) can identify a sub-phenotype with high in-hospital mortality risk (adjusted hazard ratio of 1.48 [95% CI, 1.25-1.74]) in another independent multi-centre SA-AKI cohort.

CONCLUSIONS

Our data-driven approach suggests sub-phenotypes with clinical relevance in dialysis-requiring SA-AKI and serves an outcome predictor. This strategy represents further development toward precision medicine in the definition of high-risk sub-phenotype in patients with SA-AKI.Key messagesUnsupervised consensus clustering can identify sub-phenotypes of patients with SA-AKI and provide a risk prediction.Examining the features of patient heterogeneity contributes to the discovery of serum lactate levels ≥ 3.3 mmol/L upon initializing RRT as an independent outcome predictor.This data-driven approach can be useful for prognostication and lead to a better understanding of therapeutic strategies in heterogeneous clinical syndromes.

A Combined Biomarker That Includes Plasma Fibroblast Growth Factor 23, Erythropoietin, and Klotho Predicts Short- and Long-Term Morbimortality and Development of Chronic Kidney Disease in Critical Care Patients with Sepsis: A Prospective Cohort

Acute Kidney Injury (AKI) is a frequent complication in intensive care unit (ICU) patients that increases mortality and chronic kidney disease (CKD) development. AKI is associated with elevated plasma fibroblast growth factor 23 (FGF23), which can be modulated by erythropoietin (EPO) and Klotho. We aimed to evaluate whether a combined biomarker that includes these molecules predicted short-/long-term outcomes. We performed a prospective cohort of ICU patients with sepsis and previously normal renal function. They were followed during their inpatient stay and for one year after admission. We measured plasma FGF23, EPO, and Klotho levels at admission and calculated a combined biomarker (FEK). A total of 164 patients were recruited. Of these, 50 (30.5%) had AKI at admission, and 55 (33.5%) developed AKI within 48 h. Patients with AKI at admission and those who developed AKI within 48 h had 12- and 5-fold higher FEK values than non-AKI patients, respectively. Additionally, patients with higher FEK values had increased 1-year mortality (41.9% vs. 18.6%, p = 0.003) and CKD progression (26.2% vs. 8.3%, p = 0.023). Our data suggest that the FEK indicator predicts the risk of AKI, short-/long-term mortality, and CKD progression in ICU patients with sepsis. This new indicator can improve clinical outcome prediction and guide early therapeutic strategies.

Feasibility Assessment of a Biomarker-Guided Kidney-Sparing Sepsis Bundle: The Limiting Acute Kidney Injury Progression In Sepsis Trial

OBJECTIVES

To determine the feasibility, safety, and efficacy of a biomarker-guided implementation of a kidney-sparing sepsis bundle (KSSB) of care in comparison with standard of care (SOC) on clinical outcomes in patients with sepsis.

DESIGN

Adaptive, multicenter, randomized clinical trial.

SETTING

Five University Hospitals in Europe and North America.

PATIENTS

Adult patients, admitted to the ICU with an indwelling urinary catheter and diagnosis of sepsis or septic shock, without acute kidney injury (acute kidney injury) stage 2 or 3 or chronic kidney disease.

INTERVENTIONS

A three-level KSSB based on Kidney Disease: Improving Global Outcomes (KDIGOs) recommendations guided by serial measurements of urinary tissue inhibitor of metalloproteinases-2 and insulin-like growth factor-binding protein 7 used as a combined biomarker [TIMP2]•[IGFBP7].

MEASUREMENTS AND MAIN RESULTS

The trial was stopped for low enrollment related to the COVID-19 pandemic. Nineteen patients enrolled in five sites over 12 months were randomized to the SOC (n = 8, 42.0%) or intervention (n = 11, 58.0%). The primary outcome was feasibility, and key secondary outcomes were safety and efficacy. Adherence to protocol in patients assigned to the first two levels of KSSB was 15 of 19 (81.8%) and 19 of 19 (100%) but was 1 of 4 (25%) for level 3 KSSB. Serious adverse events were more frequent in the intervention arm (4/11, 36.4%) than in the control arm (1/8, 12.5%), but none were related to study interventions. The secondary efficacy outcome was a composite of death, dialysis, or progression of greater than or equal to 2 stages of acute kidney injury within 72 hours after enrollment and was reached by 3 of 8 (37.5%) patients in the control arm, and 0 of 11 (0%) patients in the intervention arm. In the control arm, two patients experienced progression of acute kidney injury, and one patient died.

CONCLUSIONS

Although the COVID-19 pandemic impeded recruitment, the actual implementation of a therapeutic strategy that deploys a KDIGO-based KSSB of care guided by risk stratification using urinary [TIMP2]•[IGFBP7] seems feasible and appears to be safe in patients with sepsis.

Non-Neuronal Acetylcholinesterase Activity Shows Limited Utility for Early Detection of Sepsis

(1) Background: Sepsis is a severe systemic inflammatory condition characterized by rapid clinical deterioration and organ dysfunction. The cholinergic system has been implicated in modulating the inflammatory response. Acetylcholinesterase (AChE), an enzyme primarily responsible for the hydrolysis of acetylcholine, has been proposed as a potential early indicator of sepsis onset. However, the exact role of non-neuronal AChE activity in sepsis and its correlation with disease severity and patient outcomes remain unclear. This study aimed to investigate the involvement of AChE activity in sepsis and evaluate its association with disease severity and clinical outcomes. (2) Methods: A prospective study included 43 septic patients. AChE activity was measured at sepsis detection, as well as 7 and 28 days later. Inflammatory biomarkers, disease severity scores, and patient outcomes were evaluated. (3) Results: AChE activity remained stable for 7 days and decreased at 28 days. However, there was no correlation between initial AChE activity and inflammatory biomarkers, disease severity scores, ICU stay, or hospital stay. (4) Conclusions: Non-neuronal AChE activity may not reliably indicate early sepsis or predict disease severity.

Utility of Biomarkers for Sepsis-Associated Acute Kidney Injury Staging

Importance

The 23rd Acute Disease Quality Initiative (ADQI-23) consensus conference proposed a framework to integrate biomarkers into the staging of acute kidney injury (AKI). It is unknown whether tissue inhibitor of metalloproteinases 2 (TIMP-2) and insulinlike growth factor binding protein 7 (IGFBP7) could be used for staging.

Objective

To test whether higher levels of urinary [TIMP-2] × [IGFBP7] are associated with lower survival among patients with the same functional stage of AKI.

Design, Setting, and Participants

This cohort study was performed using data from the Protocolized Care for Early Septic Shock (ProCESS) trial, which enrolled critically ill patients with septic shock who presented at academic and community emergency departments and intensive care units in the US from March 2008 to May 2013. Patients with end-stage kidney disease, a reference serum creatinine level of 4 mg/dL or greater (to convert to μmol/L, multiply by 76.25), or missing data on serum creatinine levels or urinary levels of [TIMP-2] × [IGFBP7] were excluded. Data were analyzed from October 2020 to October 2021.

Exposures

The presence of AKI, assessed using Kidney Disease: Improving Global Outcomes criteria within 24 hours after enrollment and the highest AKI stage as well as urinary [TIMP-2] × [IGFBP7] level at 6 hours after enrollment. A previously reported high-specificity cutoff level for [TIMP-2] × [IGFBP7] of 2.0 (ng/mL)2/1000 was used to categorize patients (including those without functional criteria of AKI) according to the new staging system proposed by the ADQI-23 as biomarker negative (urinary [TIMP-2] × [IGFBP7] level ≤2.0 [ng/mL]2/1000) or biomarker positive ([TIMP-2] × [IGFBP7] >2.0 [ng/mL]2/1000).

Main Outcomes and Measures

Survival (assessed using Kaplan-Meier plots and the log-rank test) and mortality (assessed using relative risk [RR] 30 days after enrollment).

Results

The analysis included 999 patients with a median age of 61 years (IQR, 50-73 years); 554 (55.5%) were male. Biomarker-positive patients had lower survival and higher mortality at 30 days in the groups with AKI stage 1 (RR, 2.20; 95% CI, 1.02-4.72), stage 2 (RR, 1.53; 95% CI, 1.04-2.27), and stage 3 (RR, 1.61; 95% CI, 1.00-2.60). The associations were specific to patients with AKI. No difference in 30-day survival was found between biomarker-positive and biomarker-negative patients in the absence of functional criteria for AKI (RR, 1.16; 95% CI, 0.45-3.01).

Conclusions and Relevance

The findings suggest that assessment of the cell-cycle arrest biomarkers TIMP-2 and IGFBP7 may augment AKI staging for patients with functional criteria for AKI.

Are Baseline Levels of Gas6 and Soluble Mer Predictors of Mortality and Organ Damage in Patients with Sepsis? The Need-Speed Trial Database

Soluble tyrosine kinase receptor Mer (sMer) and its ligand Growth arrest-specific protein 6 (Gas6) are predictors of mortality in patients with sepsis. Our aim is to clarify whether their measurement at emergency department (ED) presentation is useful in risk stratification. We re-analyzed data from the Need-Speed trial, evaluating mortality and the presence of organ damage according to baseline levels of sMer and Gas6. 890 patients were eligible; no association with 7- and 30-day mortality was observed for both biomarkers (p > 0.05). sMer and Gas6 levels were significantly higher in acute kidney injury (AKI) patients compared to non-AKI ones (9.8 [4.1–17.8] vs. 7.9 [3.8–12.9] ng/mL and 34.8 [26.4–47.5] vs. 29.8 [22.1–41.6] ng/mL, respectively, for sMer and Gas6), and Gas6 also emerged as an independent AKI predictor (odds ratio (OR) 1.01 [1.00–1.02]). Both sMer and Gas6 independently predicted thrombocytopenia in sepsis patients not treated with anticoagulants (OR 1.01 [1.00–1.02] and 1.04 [1.02–1.06], respectively). Moreover, sMer was an independent predictor of both prothrombin time-international normalized ratio (PT-INR) > 1.4 (OR 1.03 [1.00–1.05]) and sepsis-induced coagulopathy (SIC) (OR 1.05 [1.02–1.07]). An early measurement of the sMer and Gas6 plasma concentration could not predict mortality. However, the biomarkers were associated with AKI, thrombocytopenia, PT-INR derangement and SIC, suggesting a role in predicting sepsis-related organ damage.