Mortality and host response aberrations associated with transient and persistent acute kidney injury in critically ill patients with sepsis: a prospective cohort study

The combination of kidney function variables with cell cycle arrest biomarkers identifies distinct subphenotypes of sepsis-associated acute kidney injury: a post-hoc analysis (the PHENAKI study)

BACKGROUND

The severity and course of sepsis-associated acute kidney injury (SA-AKI) are correlated with the mortality rate. Early detection of SA-AKI subphenotypes might facilitate the rapid provision of individualized care.

PATIENTS AND METHODS

In this post-hoc analysis of a multicenter prospective study, we combined conventional kidney function variables with serial measurements of urine (tissue inhibitor of metalloproteinase-2 [TIMP-2])* (insulin-like growth factor-binding protein [IGFBP7]) at 0, 6, 12, and 24 h) and then using an unsupervised hierarchical clustering of principal components (HCPC) approach to identify different phenotypes of SA-AKI. We then compared the subphenotypes with regard to a composite outcome of in-hospital death or the initiation of renal replacement therapy (RRT).

RESULTS

We included 184 patients presenting SA-AKI within 6 h of the initiation of catecholamines. Three distinct subphenotypes were identified: subphenotype A (99 patients) was characterized by a normal urine output (UO), a low SCr and a low [TIMP-2]*[IGFBP7] level; subphenotype B (74 patients) was characterized by existing chronic kidney disease (CKD), a higher SCr, a low UO, and an intermediate [TIMP-2]*[IGFBP7] level; and subphenotype C was characterized by very low UO, a very high [TIMP-2]*[IGFBP7] level, and an intermediate SCr level. With subphenotype A as the reference, the adjusted hazard ratio (aHR) [95%CI] for the composite outcome was 3.77 [1.92-7.42] (p < 0.001) for subphenotype B and 4.80 [1.67-13.82] (p = 0.004) for subphenotype C.

CONCLUSIONS

Combining conventional kidney function variables with urine measurements of [TIMP-2]*[IGFBP7] might help to identify distinct SA-AKI subphenotypes with different short-term courses and survival rates.

High versus low chloride load in adult hyperglycemic emergencies with acute kidney injury: a multicenter retrospective cohort study

Hyperglycemic emergencies frequently lead to acute kidney injury (AKI) and require treatment with large amount of intravenous fluids. However, the effects of chloride loading on this population have not yet been investigated. We conducted a multicenter, retrospective, cohort study in 21 acute-care hospitals in Japan. The study included hospitalized adult patients with diabetic ketoacidosis (DKA) and hyperosmolar hyperglycemic syndrome (HHS) who had AKI upon arrival. The patients were classified into high and low chloride groups based on the amount of chloride administered within the first 48 h of their arrival. The primary outcome was recovery from AKI; secondary outcome was major adverse kidney events within 30 days (MAKE30), including mortality and prolonged renal failure. A total of 390 patients with AKI, including 268 (69%) with DKA and 122 (31%) with HHS, were included in the study. Using the criteria of Kidney Disease Improving Global Outcomes, the severity of AKI in the patients was Stage 1 (n = 159, 41%), Stage 2 (n = 121, 31%), and Stage 3 (n = 110, 28%). The analysis showed no significant difference between the two groups in recovery from AKI (adjusted hazard ratio, 0.96; 95% CI 0.72-1.28; P = 0.78) and in MAKE30 (adjusted odds ratio, 0.91; 95% CI 0.45-1.76; P = 0.80). Chloride loading with fluid administration had no significant impact on recovery from AKI in patients with hyperglycemic emergencies.Trial Registration This study was registered in the UMIN clinical trial registration system (UMIN000025393, registered December 23, 2016).

The role of thromboinflammation in acute kidney injury among patients with septic coagulopathy

Inflammation and coagulation are critical self-defense mechanisms for mitigating infection that can nonetheless induce tissue injury and organ dysfunction. In severe cases, like sepsis, a dysregulated thromboinflammatory response may result in multiorgan dysfunction. Sepsis-associated acute kidney injury (AKI) is a significant contributor to patient morbidity and mortality. The connection between AKI and thromboinflammation is largely due to unique aspects of the renal vasculature. Specifically, the interaction between blood cells with the endothelial, glomerular, and peritubular capillary systems during thromboinflammation reduces oxygen supply to tubular epithelial cells. Previous studies have focused on tubular epithelial cell damage due to hypoxia, oxidative stress, and nephrotoxins. Although these factors are pivotal in acute tubular injury or necrosis, recent studies have demonstrated that AKI in sepsis encompasses a mixture of tubular and glomerular damage subtypes. In cases of sepsis-induced coagulopathy, thromboinflammation within the glomerulus and peritubular capillaries is an important pathogenic mechanism for AKI. Unfortunately, and despite the use of renal replacement therapy, the development of AKI in sepsis continues to be associated with high morbidity, mortality, and clinical challenges requiring alternative approaches. This review introduces the important role of thromboinflammation in AKI pathogenesis and details innovative vascular-targeting therapeutic strategies.

Incidence, risk factors and outcome of postoperative acute kidney injury in China

BACKGROUND

Postoperative acute kidney injury (AKI) is a common condition after surgery, however, the available data about nationwide epidemiology of postoperative AKI in China from large and high-quality studies are limited. This study aimed to determine the incidence, risk factors and outcomes of postoperative AKI among patients undergoing surgery in China.

METHODS

This was a large, multicentre, retrospective study performed in 16 tertiary medical centres in China. Adult patients (≥18 years of age) who underwent surgical procedures from 1 January 2013 to 31 December 2019 were included. Postoperative AKI was defined by the Kidney Disease: Improving Global Outcomes creatinine criteria. The associations of AKI and in-hospital outcomes were investigated using logistic regression models adjusted for potential confounders.

RESULTS

Among 520 707 patients included in our study, 25 830 (5.0%) patients developed postoperative AKI. The incidence of postoperative AKI varied by surgery type, which was highest in cardiac (34.6%), urologic (8.7%) and general (4.2%) surgeries. A total of 89.2% of postoperative AKI cases were detected in the first 2 postoperative days. However, only 584 (2.3%) patients with postoperative AKI were diagnosed with AKI on discharge. Risk factors for postoperative AKI included older age, male sex, lower baseline kidney function, pre-surgery hospital stay ≤3 days or >7 days, hypertension, diabetes mellitus and use of proton pump inhibitors or diuretics. The risk of in-hospital death increased with the stage of AKI. In addition, patients with postoperative AKI had longer lengths of hospital stay (12 versus 19 days) and were more likely to require intensive care unit care (13.1% versus 45.0%) and renal replacement therapy (0.4% versus 7.7%).

CONCLUSIONS

Postoperative AKI was common across surgery type in China, particularly for patients undergoing cardiac surgery. Implementation and evaluation of an alarm system is important for the battle against postoperative AKI.

Fractional excretion of sodium and potassium and urinary strong ion difference in the evaluation of persistent AKI in sepsis

OBJECTIVE

To evaluate the diagnostic performance of FENa (Fractional excretion of sodium), FEK (fractional excretion of potassium) and uSID (urinary strong ion difference) in predicting pAKI in sepsis and septic shock.

DESIGN

Retrospective cohort study.

SETTING

Two intensive care units in Argentina.

PATIENTS

Adult patients with a confirmed diagnosis of sepsis or septic shock and AKI, and had a urinary biochemistry within 24h of the AKI diagnosis.

INTERVENTIONS

None.

MAIN VARIABLES OF INTEREST

We evaluated the diagnostic accuracy of FENa, FEK and uSID through a ROC (Receiver Operating Characteristic) curve analysis.

RESULTS

80 patients were included. 40 patients presented pAKI. pAKI group had higher APACHE, SOFA score, and mortality rate. In the ROC curve analysis, uSID had no diagnostic utility (AUC=0.52, p=0.69). FENa presented moderate accuracy showing an AUC of 0.71 (95% CI 0.60-0.83; p=0.001), while FEK presented low accuracy with an AUC of 0.69 (95% CI 0.57-0.80; p=0.04). The optimal Youden point for identifying pAKI was at a FENa higher than 0.51 % with a specificity of 72.5% and a sensitivity of 65.0%. In the case of FEK, a value higher than 21.9 % presented the best relation, with a specificity of 67.5% and a sensitivity of 65.0%.

CONCLUSIONS

urine biochemistry interpretation in septic patients must be revised. FENa and FEK are related to the severity of AKI and could be helpful complementary tools for diagnosing pAKI.

The effects of timing onset and progression of AKI on the clinical outcomes in AKI patients with sepsis: a prospective multicenter cohort study

BACKGROUND

Limited studies are available concerning on the earlier identification of AKI with sepsis. The aim of the study was to identify the risk factors of AKI early which depended on the timing onset and progression of AKI and investigate the effects of timing onset and progression of AKI on clinical outcomes.

METHODS

Patients who developed sepsis during their first 48-h admission to ICU were included. The primary outcome was major adverse kidney events (MAKE) consisted of all-cause mortality, RRT-dependence, or an inability to recover to 1.5 times of the baseline creatinine value up to 30 days. We determined MAKE and in-hospital mortality by multivariable logistic regression and explored the risk factors of early persistent-AKI. C statistics were used to evaluate model fit.

RESULTS

58.7% sepsis patients developed AKI. According to the timing onset and progression of AKI, Early transient-AKI, early persistent-AKI, late transient-AKI, late persistent-AKI were identified. Clinical outcomes were quite different among subgroups. Early persistent-AKI had 3.0-fold (OR 3.04, 95% CI 1.61 - 4.62) risk of MAKE and 2.6-fold (OR 2.60, 95%CI 1.72 - 3.76) risk of in-hospital mortality increased compared with the late transients-AKI. Older age, underweight, obese, faster heart rate, lower MAP, platelet, hematocrit, pH and energy intake during the first 24 h on ICU admission could well predict the early persistent-AKI in patients with sepsis.

CONCLUSION

Four AKI subphenotypes were identified based on the timing onset and progression of AKI. Early persistent-AKI showed higher risk of major adverse kidney events and in-hospital mortality.

TRIAL REGISTRATION

This study was registered in the Chinese Clinical Trials Registry (www.chictr.org/cn) under registration number ChiCTR-ECH-13003934.

Organotypic heterogeneity in microvascular endothelial cell responses in sepsis-a molecular treasure trove and pharmacological Gordian knot

In the last decades, it has become evident that endothelial cells (ECs) in the microvasculature play an important role in the pathophysiology of sepsis-associated multiple organ dysfunction syndrome (MODS). Studies on how ECs orchestrate leukocyte recruitment, control microvascular integrity and permeability, and regulate the haemostatic balance have provided a wealth of knowledge and potential molecular targets that could be considered for pharmacological intervention in sepsis. Yet, this information has not been translated into effective treatments. As MODS affects specific vascular beds, (organotypic) endothelial heterogeneity may be an important contributing factor to this lack of success. On the other hand, given the involvement of ECs in sepsis, this heterogeneity could also be leveraged for therapeutic gain to target specific sites of the vasculature given its full accessibility to drugs. In this review, we describe current knowledge that defines heterogeneity of organ-specific microvascular ECs at the molecular level and elaborate on studies that have reported EC responses across organ systems in sepsis patients and animal models of sepsis. We discuss hypothesis-driven, single-molecule studies that have formed the basis of our understanding of endothelial cell engagement in sepsis pathophysiology, and include recent studies employing high-throughput technologies. The latter deliver comprehensive data sets to describe molecular signatures for organotypic ECs that could lead to new hypotheses and form the foundation for rational pharmacological intervention and biomarker panel development. Particularly results from single cell RNA sequencing and spatial transcriptomics studies are eagerly awaited as they are expected to unveil the full spatiotemporal signature of EC responses to sepsis. With increasing awareness of the existence of distinct sepsis subphenotypes, and the need to develop new drug regimen and companion diagnostics, a better understanding of the molecular pathways exploited by ECs in sepsis pathophysiology will be a cornerstone to halt the detrimental processes that lead to MODS.

Sepsis-associated acute kidney injury: consensus report of the 28th Acute Disease Quality Initiative workgroup

Sepsis-associated acute kidney injury (SA-AKI) is common in critically ill patients and is strongly associated with adverse outcomes, including an increased risk of chronic kidney disease, cardiovascular events and death. The pathophysiology of SA-AKI remains elusive, although microcirculatory dysfunction, cellular metabolic reprogramming and dysregulated inflammatory responses have been implicated in preclinical studies. SA-AKI is best defined as the occurrence of AKI within 7 days of sepsis onset (diagnosed according to Kidney Disease Improving Global Outcome criteria and Sepsis 3 criteria, respectively). Improving outcomes in SA-AKI is challenging, as patients can present with either clinical or subclinical AKI. Early identification of patients at risk of AKI, or at risk of progressing to severe and/or persistent AKI, is crucial to the timely initiation of adequate supportive measures, including limiting further insults to the kidney. Accordingly, the discovery of biomarkers associated with AKI that can aid in early diagnosis is an area of intensive investigation. Additionally, high-quality evidence on best-practice care of patients with AKI, sepsis and SA-AKI has continued to accrue. Although specific therapeutic options are limited, several clinical trials have evaluated the use of care bundles and extracorporeal techniques as potential therapeutic approaches. Here we provide graded recommendations for managing SA-AKI and highlight priorities for future research.

Gene signature for the prediction of the trajectories of sepsis-induced acute kidney injury

BACKGROUND

Acute kidney injury (AKI) is a common complication in sepsis. However, the trajectories of sepsis-induced AKI and their transcriptional profiles are not well characterized.

METHODS

Sepsis patients admitted to centres participating in Chinese Multi-omics Advances In Sepsis (CMAISE) from November 2020 to December 2021 were enrolled, and gene expression in peripheral blood mononuclear cells was measured on Day 1. The renal function trajectory was measured by the renal component of the SOFA score (SOFA_renal) on Days 1 and 3. Transcriptional profiles on Day 1 were compared between these renal function trajectories, and a support vector machine (SVM) was developed to distinguish transient from persistent AKI.

RESULTS

A total of 172 sepsis patients were enrolled during the study period. The renal function trajectory was classified into four types: non-AKI (SOFA_renal = 0 on Days 1 and 3, n = 50), persistent AKI (SOFA_renal > 0 on Days 1 and 3, n = 62), transient AKI (SOFA_renal > 0 on Day 1 and SOFA_renal = 0 on Day 3, n = 50) and worsening AKI (SOFA_renal = 0 on Days 1 and SOFA_renal > 0 on Day 3, n = 10). The persistent AKI group showed severe organ dysfunction and prolonged requirements for organ support. The worsening AKI group showed the least organ dysfunction on day 1 but had higher serum lactate and prolonged use of vasopressors than the non-AKI and transient AKI groups. There were 2091 upregulated and 1,902 downregulated genes (adjusted p < 0.05) between the persistent and transient AKI groups, with enrichment in the plasma membrane complex, receptor complex, and T-cell receptor complex. A 43-gene SVM model was developed using the genetic algorithm, which showed significantly greater performance predicting persistent AKI than the model based on clinical variables in a holdout subset (AUC: 0.948 [0.912, 0.984] vs. 0.739 [0.648, 0.830]; p < 0.01 for Delong's test).

CONCLUSIONS

Our study identified four subtypes of sepsis-induced AKI based on kidney injury trajectories. The landscape of host response aberrations across these subtypes was characterized. An SVM model based on a gene signature was developed to predict renal function trajectories, and showed better performance than the clinical variable-based model. Future studies are warranted to validate the gene model in distinguishing persistent from transient AKI.

Development and Validation of Machine Learning Models for Real-Time Mortality Prediction in Critically Ill Patients With Sepsis-Associated Acute Kidney Injury

Background

Sepsis-associated acute kidney injury (SA-AKI) is common in critically ill patients, which is associated with significantly increased mortality. Existing mortality prediction tools showed insufficient predictive power or failed to reflect patients' dynamic clinical evolution. Therefore, the study aimed to develop and validate machine learning-based models for real-time mortality prediction in critically ill patients with SA-AKI.

Methods

The multi-center retrospective study included patients from two distinct databases. A total of 12,132 SA-AKI patients from the Medical Information Mart for Intensive Care IV (MIMIC-IV) were randomly allocated to the training, validation, and internal test sets. An additional 3,741 patients from the eICU Collaborative Research Database (eICU-CRD) served as an external test set. For every 12 h during the ICU stays, the state-of-the-art eXtreme Gradient Boosting (XGBoost) algorithm was used to predict the risk of in-hospital death in the following 48, 72, and 120 h and in the first 28 days after ICU admission. Area under the receiver operating characteristic curves (AUCs) were calculated to evaluate the models' performance.

Results

The XGBoost models, based on routine clinical variables updated every 12 h, showed better performance in mortality prediction than the SOFA score and SAPS-II. The AUCs of the XGBoost models for mortality over different time periods ranged from 0.848 to 0.804 in the internal test set and from 0.818 to 0.748 in the external test set. The shapley additive explanation method provided interpretability for the XGBoost models, which improved the understanding of the association between the predictor variables and future mortality.

Conclusions

The interpretable machine learning XGBoost models showed promising performance in real-time mortality prediction in critically ill patients with SA-AKI, which are useful tools for early identification of high-risk patients and timely clinical interventions.

Early recovery status and outcomes after sepsis-associated acute kidney injury in critically ill patients

OBJECTIVES

Acute kidney injury (AKI) is one of the common complications in critically ill septic patients, which is associated with increased risks of death, cardiovascular events, and chronic renal dysfunction. The duration of AKI and the renal function recovery status after AKI onset can affect the patient prognosis. Nevertheless, it remains controversial whether early recovery status after AKI is closely related to the prognosis in patients with sepsis-associated AKI (SA-AKI). In addition, early prediction of renal function recovery after AKI is beneficial to individualized treatment decision-making and prevention of severe complications, thus improving the prognosis. At present, there is limited clinical information on how to identify SA-AKI patients at high risk of unrecovered renal function at an early stage. The study aims to investigate the association between early recovery status after SA-AKI, identify risk factors for unrecovered renal function, and to improve patients' quality of life.

METHODS

We retrospectively analyzed clinical data of septic patients who were admitted to the intensive care unit (ICU) and developed AKI within the first 48 hours after ICU admission in the Second Xiangya Hospital and the Third Xiangya Hospital of Central South University from January 2015 to March 2017. Sepsis was defined based on the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). AKI was diagnosed and staged according to the 2012 Kidney Disease: Improving Global Outcomes (KDIGO) guideline. SA-AKI patients were assigned into 3 groups including a complete recovery group, a partial recovery group, and an unrecovered group based on recovery status at Day 7 after the diagnosis of AKI. Patients' baseline characteristics were collected, including demographics, comorbidities, clinical and laboratory examination information at ICU admission, and treatment within the first 24 hours. The primary outcome of the study was the composite of death and chronic dialysis at 90 days, and secondary outcomes included length of stay in the ICU, length of stay in the hospital, and persistent renal dysfunction. Multivariate regression analysis was performed to evaluate the prognostic value of early recovery status after AKI and to determine the risk factors for unrecovered renal function after AKI. Sensitivity analysis was conducted in patients who still stayed in hospital on Day 7 after AKI diagnosis, patients without premorbid chronic kidney disease, and patients with AKI Stage 2 to 3.

RESULTS

A total of 553 SA-AKI patients were enrolled, of whom 251 (45.4%), 73 (13.2%), and 229 (41.4%) were categorized as the complete recovery group, the partial recovery group, and the unrecovered group, respectively. Compared with the complete or partial recovery group, the unrecovered group had a higher incidence of 90-day mortality (unrecovered vs partial recovery or complete recovery: 64.2% vs 26.0% or 22.7%; P<0.001) and 90-day composite outcome (unrecovered vs partial recovery or complete recovery: 65.1% vs 27.4% or 22.7%; P<0.001). The unrecovered group also had a shorter length of stay in the hospital and a larger proportion of progression into persistent renal dysfunction than the other 2 groups. After adjustment for potential confounders, patients in the unrecovered group were at an increased risk of 90-day mortality (HR=3.50, 95% CI 2.47 to 4.96, P<0.001) and 90-day composite outcome (OR=5.55, 95% CI 3.43 to 8.98, P<0.001) when compared with patients in the complete recovery group, but patients in the partial recovery group had no significant difference (P>0.05). Male sex, congestive heart failure, pneumonia, respiratory rate >20 beats per minute, anemia, hyperbilirubinemia, need for mechanical ventilation, and AKI Stage 3 were identified as independent risk factors for unrecovered renal function after AKI. The sensitivity analysis further supported that unrecovered renal function after AKI remained an independent predictor for 90-day mortality and composite outcome in the subgroups.

CONCLUSIONS

The early recovery status after AKI is closely associated with poor prognosis in critically ill patients with SA-AKI. Unrecovered renal function within the first 7 days after AKI diagnosis is an independent predictor for 90-day mortality and composite outcome. Male sex, congestive heart failure, pneumonia, tachypnea, anemia, hyperbilirubinemia, respiratory failure, and severe AKI are risk factors for unrecovered renal function after AKI. Therefore, timely assessment for the renal function in the early phase after AKI diagnosis is essential for SA-AKI patients. Furthermore, patients with unrecovered renal function after AKI need additional management in the hospital, including rigorous monitoring, avoidance of nephrotoxin, and continuous assessment for the renal function, and after discharge, including more frequent follow-up, regular outpatient consultation, and prevention of long-term adverse events.

Effect of erythromycin on mortality and the host response in critically ill patients with sepsis: a target trial emulation

BACKGROUND

Immunomodulatory therapies that improve the outcome of sepsis are not available. We sought to determine whether treatment of critically ill patients with sepsis with low-dose erythromycin-a macrolide antibiotic with broad immunomodulatory effects-decreased mortality and ameliorated underlying disease pathophysiology.

METHODS

We conducted a target trial emulation, comparing patients with sepsis admitted to two intensive care units (ICU) in the Netherlands for at least 72 h, who were either exposed or not exposed during this period to treatment with low-dose erythromycin (up to 600 mg per day, administered as a prokinetic agent) but no other macrolides. We used two common propensity score methods (matching and inverse probability of treatment weighting) to deal with confounding by indication and subsequently used Cox regression models to estimate the treatment effect on the primary outcome of mortality rate up to day 90. Secondary clinical outcomes included change in SOFA, duration of mechanical ventilation and the incidence of ICU-acquired infections. We used linear mixed models to assess differences in 15 host response biomarkers reflective of key pathophysiological processes from admission to day 4.

RESULTS

In total, 235 patients started low-dose erythromycin treatment, 470 patients served as controls. Treatment started at a median of 38 [IQR 25-52] hours after ICU admission for a median of 5 [IQR 3-8] total doses in the first course. Matching and weighting resulted in populations well balanced for proposed confounders. We found no differences between patients treated with low-dose erythromycin and control subjects in mortality rate up to day 90: matching HR 0.89 (95% CI 0.64-1.24), weighting HR 0.95 (95% CI 0.66-1.36). There were no differences in secondary clinical outcomes. The change in host response biomarker levels from admission to day 4 was similar between erythromycin-treated and control subjects.

CONCLUSION

In this target trial emulation in critically ill patients with sepsis, we could not demonstrate an effect of treatment with low-dose erythromycin on mortality, secondary clinical outcomes or host response biomarkers.

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.

Acute kidney injury-attributable mortality in critically ill patients with sepsis

Background

To assess whether acute kidney injury (AKI) is independently associated with hospital mortality in ICU patients with sepsis, and estimate the excess AKI-related mortality attributable to AKI.

Methods

We analyzed adult patients from two distinct retrospective critically ill cohorts: (1) Medical Information Mart for Intensive Care IV (MIMIC IV; n = 15,610) cohort and (2) Wenzhou (n = 1,341) cohort. AKI was defined by Kidney Disease: Improving Global Outcomes (KDIGO) criteria. We applied multivariate logistic and linear regression models to assess the hospital and ICU mortality, hospital length-of-stay (LOS), and ICU LOS. The excess attributable mortality for AKI in ICU patients with sepsis was further evaluated.

Results

AKI occurred in 5,225 subjects in the MIMIC IV cohort (33.5%) and 494 in the Wenzhou cohort (36.8%). Each stage of AKI was an independent risk factor for hospital mortality in multivariate logistic regression after adjusting for baseline illness severity. The excess attributable mortality for AKI was 58.6% (95% CI [46.8%-70.3%]) in MIMIC IV and 44.6% (95% CI [12.7%-76.4%]) in Wenzhou. Additionally, AKI was independently associated with increased ICU mortality, hospital LOS, and ICU LOS.

Conclusion

Acute kidney injury is an independent risk factor for hospital and ICU mortality, as well as hospital and ICU LOS in critically ill patients with sepsis. Thus, AKI is associated with excess attributable mortality.

Renal microvascular endothelial cell responses in sepsis-induced acute kidney injury

Microvascular endothelial cells in the kidney have been a neglected cell type in sepsis-induced acute kidney injury (sepsis-AKI) research; yet, they offer tremendous potential as pharmacological targets. As endothelial cells in distinct cortical microvascular segments are highly heterogeneous, this Review focuses on endothelial cells in their anatomical niche. In animal models of sepsis-AKI, reduced glomerular blood flow has been attributed to inhibition of endothelial nitric oxide synthase activation in arterioles and glomeruli, whereas decreased cortex peritubular capillary perfusion is associated with epithelial redox stress. Elevated systemic levels of vascular endothelial growth factor, reduced levels of circulating sphingosine 1-phosphate and loss of components of the glycocalyx from glomerular endothelial cells lead to increased microvascular permeability. Although coagulation disbalance occurs in all microvascular segments, the molecules involved differ between segments. Induction of the expression of adhesion molecules and leukocyte recruitment also occurs in a heterogeneous manner. Evidence of similar endothelial cell responses has been found in kidney and blood samples from patients with sepsis. Comprehensive studies are needed to investigate the relationships between segment-specific changes in the microvasculature and kidney function loss in sepsis-AKI. The application of omics technologies to kidney tissues from animals and patients will be key in identifying these relationships and in developing novel therapeutics for sepsis.

Non-linear and Interaction Analyses of Biomarkers for Organ Dysfunctions as Predictive Markers for Sepsis: A Nationwide Retrospective Study

The Sequential Organ Failure Assessment (SOFA) score is predominantly used to assess the severity of organ dysfunction in sepsis. However, differences in prognostic value between SOFA subscores have not been sufficiently evaluated. This retrospective observational study used a large-scale database containing about 30 million patients. Among them, we included 38,869 adult patients with sepsis from 2006 to 2019. The cardiovascular and neurological subscores were calculated by a modified method. Associations between the biomarkers of the SOFA components and mortality were examined using restricted cubic spline analyses, which showed that an increase in the total modified SOFA score was linearly associated with increased mortality. However, the prognostic association of subscores varied widely: platelet count showed a J-shaped association, creatinine showed an inverted J-shaped association, and bilirubin showed only a weak association. We also evaluated interaction effects on mortality between an increase of one subscore and another. The joint odds ratios on mortality of two modified SOFA subscores were synergistically increased compared to the sum of the single odds ratios, especially in cardiovascular-neurological, coagulation-hepatic, and renal-hepatic combinations. In conclusion, total modified SOFA score was associated with increased mortality despite the varied prognostic associations of the subscores, possibly because interactions between subscores synergistically enhanced prognostic accuracy.

Predictors and Assessment of Hospice Use for End-Stage Renal Disease Patients in Taiwan

OBJECTIVES

Hospice and early palliative care are generally considered as an alternative and supportive care to offer symptoms relief and optimize the quality of life among end-stage renal disease (ESRD) patients, but hospice care remains underutilized. This study aimed to examine patient and health system characteristics and develop a patient assessment scale to evaluate ESRD patients for hospice care after the implementation of non-cancer hospice care reimbursement policy in 2009 in Taiwan.

METHOD

We conducted a retrospective cohort study using nationwide population-based datasets. Adult long-term dialysis patients between 2009 and 2012 were included. Multivariable logistic regression and the Firth penalized likelihood estimation were used to estimate the likelihood of receiving hospice care. A receiver operating characteristic curve (ROC) analysis and C-statistic were calculated to determine the optimal models for a patient assessment of hospice use.

RESULTS

Patients who were older, comorbid with anemia (odds ratio [OR] 3.53, 95% CI 1.43-8.70) or sepsis (OR 1.62, 95% CI 1.08-2.44), with longer dialysis durations, more hospitalizations (OR 4.68, 95% CI 2.56-8.55), or primary provider care with hospice (OR 5.15, 95% CI 2.80-9.45) were more likely to receive hospice care. The total score of the patient assessment scale of hospice care was 0-28 with a cut-off value of 19 based on the results of the receiver operating characteristic curve.

CONCLUSION

Given the "Patient Right to Autonomy Act" implemented in Taiwan in 2019 to promote the concept of a "good quality of death", this patient assessment scale may help health professionals target ESRD patients for hospice care and engage in shared decision making and the advance care planning process.

Machine learning for early discrimination between transient and persistent acute kidney injury in critically ill patients with sepsis

Acute kidney injury (AKI) is commonly present in critically ill patients with sepsis. Early prediction of short-term reversibility of AKI is beneficial to risk stratification and clinical treatment decision. The study sought to use machine learning methods to discriminate between transient and persistent sepsis-associated AKI. Septic patients who developed AKI within the first 48 h after ICU admission were identified from the Medical Information Mart for Intensive Care III database. AKI was classified as transient or persistent according to the Acute Disease Quality Initiative workgroup consensus. Five prediction models using logistic regression, random forest, support vector machine, artificial neural network and extreme gradient boosting were constructed, and their performance was evaluated by out-of-sample testing. A simplified risk prediction model was also derived based on logistic regression and features selected by machine learning algorithms. A total of 5984 septic patients with AKI were included, 3805 (63.6%) of whom developed persistent AKI. The artificial neural network and logistic regression models achieved the highest area under the receiver operating characteristic curve (AUC) among the five machine learning models (0.76, 95% confidence interval [CI] 0.74-0.78). The simplified 14-variable model showed adequate discrimination, with the AUC being 0.76 (95% CI 0.73-0.78). At the optimal cutoff of 0.63, the sensitivity and specificity of the simplified model were 63% and 76% respectively. In conclusion, a machine learning-based simplified prediction model including routine clinical variables could be used to differentiate between transient and persistent AKI in critically ill septic patients. An easy-to-use risk calculator can promote its widespread application in daily clinical practice.

Potential Value of TNF-α (-376 G/A) Polymorphism and Cystatin C (CysC) in the Diagnosis of Sepsis Associated Acute Kidney Injury (S-AK I) and Prediction of Mortality in Critically Ill patients

Sepsis Associated Kidney Injury represents a major health concern as it is frequently associated with increased risk of mortality and morbidity. We aimed to evaluate the potential value of TNF-α (-376 G/A) and cystatin C in the diagnosis of S-AKI and prediction of mortality in critically ill patients. This study included 200 critically ill patients and 200 healthy controls. Patients were categorized into 116 with acute septic shock and 84 with sepsis, from which 142 (71%) developed S-AKI. Genotyping of TNF-α (-376 G/A) was performed by RT-PCR and serum CysC was assessed by Enzyme Linked Immunosorbent Assay. Our results showed a highly significant difference in the genotype frequencies of TNF-α (-376 G/A) SNP between S-AKI and non-AKI patients (p < 0.001). Additionally, sCysC levels were significantly higher in the S-AKI group (p = 0.011). The combination of both sCysC and TNF-α (-376 G/A) together had a better diagnostic ability for S-AKI than sCysC alone (AUC = 0.610, 0.838, respectively). Both GA and AA genotypes were independent predictors of S-AKI (p= < 0.001, p = 0.002 respectively). Additionally, sCysC was significantly associated with the risk of S-AKI development (Odds Ratio = 1.111). Both genotypes and sCysC were significant predictors of non-survival (p < 0.001), suggesting their potential role in the diagnosis of S-AKI and prediction of mortality.

Kinetic changes in serum procalcitonin predict persistent acute kidney injury in critical patients

PURPOSE

Persistent acute kidney injury (AKI) has been shown to be closely associated with poor prognosis in critical patients. Recent studies have shown that procalcitonin (PCT) is valuable for the early prediction of AKI in critically patients. Our aim was to determine whether PCT and its kinetic changes could predict the occurrence of persistent AKI in critical patients.

METHODS

This is a prospective observational study. The definition of AKI was based on the Kidney Disease: Improving Global Outcomes criteria. Persistent AKI was defined as renal function that does not return to baseline serum creatinine levels within 48 h. Blood samples were obtained at the onset of AKI and two subsequent days of hospital stay. 24-h PCT change (ΔPCT-24 h) was defined as 24 h PCT minus baseline PCT (day 0).

RESULTS

A total of 91 critical patients with AKI were included in this study. The persistent AKI group had a stepwise increase in PCT concentration. ΔPCT-24 h was higher in the persistent AKI group (p < .01). Logistic regression analysis showed that ΔPCT-24 h (p = .04) was independent predictors of persistent AKI. The receiver operating characteristic curves showed that area under the curve of ΔPCT-24 h was 0.84 (p < .01), and the cut-off value for PCT to predict persistent AKI was 0.56 ng/ml.

CONCLUSION

Our study showed that the observation of kinetic changes in PCT is more significant for the early prediction of persistent AKI than the index of PCT at a single time point. ΔPCT-24 h is a good predictor of persistent AKI in critical patients.

Risk factors, clinical features and outcome of new-onset acute kidney injury among critically ill patients: a database analysis based on prospective cohort study

Background

Acute kidney injury (AKI) newly-emerged in intensive care unit (ICU), has not been thoroughly studied in previous researches, is likely to differ from AKI developed before ICU admission. This study aimed to evaluate the incidence, risk factors, clinical features and outcome of new-onset AKI in critically ill patients.

Methods

The data of present study derived from a multicenter, prospective cohort study in17 Chinese ICUs (January 2014 - August 2015). The incidence, risk factors, clinical features and survival analysis of new-onset AKI were assessed.

Results

A total of 3374 adult critically ill patients were eligible. The incidence of new-onset AKI was 30.0 % (n = 1012). Factors associated with a higher risk of new-onset AKI included coronary heart disease, hypertension, chronic liver disease, use of nephrotoxic drugs, sepsis, SOFA score, APACHEII score and use of vasopressors. The new-onset AKI was an independent risk factor for 28-day mortality (adjusted hazard ratio, 1.643; 95 % CI, 1.370–1.948; P < 0.001). 220 (21.7 %) patients received renal replacement therapy (RRT), 71 (32.3 %) of them were successfully weaning from RRT. More than half of the new-onset AKI were transient AKI (renal recovery within 48 h). There was no statistical relationship between transient AKI and 28-day mortality (hazard ratio, 1.406; 95 % CI, 0.840–1.304; P = 0.686), while persistent AKI (non-renal recovery within 48 h) was strongly associated with 28-day mortality (adjusted hazard ratio, 1.486; 95 % CI, 1.137–1.943; P < 0.001).

Conclusions

New-onset AKI is common in ICU patients and is associated with significantly higher 28-day mortality. Only persistent AKI, but not transient AKI is associated with significantly higher 28-day mortality.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12882-021-02503-x.

Acute Kidney Injury Recovery Patterns in Critically Ill Patients: Results of a Retrospective Cohort Study

OBJECTIVES

Acute kidney injury, acute kidney injury severity, and acute kidney injury duration are associated with both short- and long-term outcomes. Despite recent definitions, only few studies assessed pattern of renal recovery and time-dependent competing risks are usually disregarded. Our objective was to describe pattern of acute kidney injury recovery, change of transition probability over time and their risk factors.

DESIGN

Monocenter retrospective cohort study. Acute kidney injury was defined according to Kidney Disease Improving Global Outcomes definition. Renal recovery was defined as normalization of both serum creatinine and urine output criteria. Competing risk analysis, time-inhomogeneous Markov model, and group-based trajectory modeling were performed.

SETTING

Monocenter study.

PATIENTS

Consecutive patients admitted in ICU from July 2018 to December 2018 were included.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Three-hundred fifty patients were included. Acute kidney injury occurred in 166 patients at ICU admission, including 64 patients (38.6%) classified as acute kidney disease according to Acute Disease Quality Initiative definition and 44 patients (26.5%) who could not be classified. Cumulative incidence of recovery was 25 % at day 2 (95% CI, 18-32%) and 35% at day 7 (95% CI, 28-42%). After adjustment, need for mechanical ventilation (subdistribution hazard ratio, 0.42; 95% CI, 0.23-0.74) and severity of the acute kidney injury (stage 3 vs stage 1 subdistribution hazard ratio, 0.11; 95% CI, 0.03-0.35) were associated with lack of recovery. Group-based trajectory modeling identified three clusters of temporal changes in this setting, associated with both acute kidney injury recovery and patients' outcomes.

CONCLUSIONS

In this study, we demonstrate Acute Disease Quality Initiative to allow recovery pattern classification in 75% of critically ill patients. Our study underlines the need to take into account competing risk factors when assessing recovery pattern in critically ill patients.

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.

Prognostic classification based on P/F and PEEP in invasively ventilated ICU patients with hypoxemia-insights from the MARS study

Background

Outcome prediction in patients with acute respiratory distress syndrome (ARDS) greatly improves when patients are reclassified based on predefined arterial oxygen partial pressure to fractional inspired oxygen ratios (PaO₂/FiO₂) and positive end–expiratory pressure (PEEP) cutoffs 24 h after the initial ARDS diagnosis. The aim of this study was to test whether outcome prediction improves when patients are reclassified based on predefined PaO₂/FiO₂ and PEEP cutoffs 24 h after development of mild hypoxemia while not having ARDS.

Methods

Post hoc analysis of a large prospective, multicenter, observational study that ran in the ICUs of two academic hospitals in the Netherlands between January 2011 and December 2013. Patients were classified into four groups using predefined cutoffs for PaO₂/FiO₂ (250 mmHg) and PEEP (5 cm H₂O), both at onset of hypoxemia and after 24 h: PaO₂/FiO₂ ≥ 250 mmHg and PEEP < 6 cm H₂O (group I), PaO₂/FiO₂ ≥ 250 mmHg and PEEP ≥ 6 cm H₂O (group II), PaO₂/FiO₂ < 250 mmHg and PEEP < 6 cm H₂O (group III), and PaO₂/FiO₂ < 250 mmHg and PEEP ≥ 6 cm H₂O (group IV), to look for trend association with all-cause in-hospital mortality, the primary outcome. Secondary outcome were ICU- and 90-day mortality, and the number of ventilator-free days or ICU-free days and alive at day 28.

Results

The analysis included 689 consecutive patients. All-cause in-hospital mortality was 35%. There was minimal variation in mortality between the four groups at onset of hypoxemia (33, 36, 38, and 34% in groups I to IV, respectively; P = 0.65). Reclassification after 24 h resulted in a strong trend with increasing mortality from group I to group IV (31, 31, 37, and 48% in groups I to IV, respectively; P < 0.01). Similar trends were found for the secondary endpoints.

Conclusions

Reclassification using PaO₂/FiO₂ and PEEP cutoffs after 24 h improved classification for outcome in invasively ventilated ICU patients with hypoxemia not explained by ARDS, compared to classification at onset of hypoxemia.

Trial registration

ClinicalTrials.gov identifier: NCT01905033. Registered on July 11, 2013. Retrospectively registered.

Estimation of Missing Baseline Serum Creatinine for Acute Kidney Injury Diagnosis in Hospitalized Patients

INTRODUCTION

In hospitalized patients, information on preadmission kidney function is often missing, impeding timely and accurate acute kidney injury (AKI) detection and affecting results of AKI-related studies.

OBJECTIVE

In this study, we provided estimates of preadmission serum creatinine (SCr), based on a multivariate linear regression (Model 1) and random forest model (Model 2) built with different parametrizations. Their accuracy for AKI diagnosis was compared with the accuracy of commonly used surrogate methods: (i) SCr at hospital admission (first SCr) and (ii) SCr back-calculated from the assumed estimated glomerular filtration rate of 75 mL/min/1.73 m2 (eGFR 75).

METHODS

From 44,670 unique adult admissions to a tertiary referral centre between 2013 and 2015, we analysed 8,540 patients with preadmission SCr available. To control for differences in characteristics of patients with and without SCr, we used an inverse probability weighting technique.

RESULTS

Estimates of SCr were likely to be higher than true preadmission SCr in a low Cr concentration and undervalued in high concentrations although for Model 2 Complete-SCr these differences were smallest. The true cumulative incidence of AKI was 14.8%. Model 2 Complete-SCr had the best agreement for AKI diagnosis (kappa 0.811, 95% CI 0.787-0.835), while surrogate methods resulted in the lowest agreement: (kappa 0.553, 0.516-0.590) and (0.648, 0.620-0.676) for first SCr and eGFR 75, respectively.

CONCLUSIONS

Multivariable imputation of preadmission SCr, taking into account elementary admission data, improved accuracy in AKI diagnosis over commonly used surrogate methods. Random forest-based models can serve as an effective tool in research.