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

ABSTRACT: PURPOSE:Sepsis is the most frequent cause of acute kidney injury (AKI). The "Acute Disease Quality Initiative Workgroup" recently proposed new definitions for AKI, classifying it as transient or persistent. We investigated the incidence, mortality, and host response aberrations associated with transient and persistent AKI in sepsis patients. METHODS:A total of 1545 patients admitted with sepsis to 2 intensive care units in the Netherlands were stratified according to the presence (defined by any urine or creatinine RIFLE criterion within the first 48 h) and evolution of AKI (with persistent defined as remaining > 48 h). We determined 30-day mortality by logistic regression adjusting for confounding variables and analyzed 16 plasma biomarkers reflecting pathways involved in sepsis pathogenesis (n = 866) and blood leukocyte transcriptomes (n = 392). RESULTS:AKI occurred in 37.7% of patients, of which 18.4% was transient and 81.6% persistent. On admission, patients with persistent AKI had higher disease severity scores and more frequently had severe (injury or failure) RIFLE AKI stages than transient AKI patients. Persistent AKI, but not transient AKI, was associated with increased mortality by day 30 and up to 1 year. Persistent AKI was associated with enhanced and sustained inflammatory and procoagulant responses during the first 4 days, and a more severe loss of vascular integrity compared with transient AKI. Baseline blood gene expression showed minimal differences with respect to the presence or evolution of AKI. CONCLUSION:Persistent AKI is independently associated with sepsis mortality, as well as with sustained inflammatory and procoagulant responses, and loss of vascular integrity as compared with transient AKI.

SUBMITTER: Uhel F

PROVIDER: S-EPMC7381452 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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

Uhel Fabrice F Peters-Sengers Hessel H Falahi Fahimeh F Scicluna Brendon P BP van Vught Lonneke A LA Bonten Marc J MJ Cremer Olaf L OL Schultz Marcus J MJ van der Poll Tom T

Intensive care medicine 20200608 8

<h4>Purpose</h4>Sepsis is the most frequent cause of acute kidney injury (AKI). The "Acute Disease Quality Initiative Workgroup" recently proposed new definitions for AKI, classifying it as transient or persistent. We investigated the incidence, mortality, and host response aberrations associated with transient and persistent AKI in sepsis patients.<h4>Methods</h4>A total of 1545 patients admitted with sepsis to 2 intensive care units in the Netherlands were stratified according to the presence ...[more]

PMID: 32514599

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Project description:Background: Systemic inflammation is a whole body reaction that can have an infection-positive (i.e. sepsis) or infection-negative origin. It is important to distinguish between septic and non-septic presentations early and reliably, because this has significant therapeutic implications for critically ill patients. We hypothesized that a molecular classifier based on a small number of RNAs expressed in peripheral blood could be discovered that would: 1) determine which patients with systemic inflammation had sepsis; 2) be robust across independent patient cohorts; 3) be insensitive to disease severity; and 4) provide diagnostic utility. The overall goal of this study was to identify and validate such a molecular classifier. Methods and Findings: We conducted an observational, non-interventional study of adult patients recruited from tertiary intensive care units (ICU). Biomarker discovery was conducted with an Australian cohort (n = 105) consisting of sepsis patients and post -surgical patients with infection-negative systemic inflammation. Using this cohort, a four-gene classifier consisting of a combination of CEACAM4, LAMP1, PLA2G7 and PLAC8 RNA biomarkers was identified. This classifier, designated SeptiCyteÂ® Lab, was externally validated using RT-qPCR and receiver operating characteristic (ROC) curve analysis in five cohorts (n = 345) from the Netherlands. Cohort 1 (n=59) consisted of unambiguous septic cases and infection-negative systemic inflammation controls; SeptiCyteÂ® Lab gave an area under curve (AUC) of 0.96 (95% CI: 0.91-1.00). ROC analysis of a more heterogeneous group of patients (Cohorts 2-5; 249 patients after excluding 37 patients with infection likelihood possible) gave an AUC of 0.89 (95% CI: 0.85-0.93). Disease severity, as measured by Sequential Organ Failure Assessment (SOFA) score or the Acute Physiology and Chronic Health Evaluation (APACHE) IV score, was not a significant confounding variable. The diagnostic utility o f SeptiCyteÂ® Lab was evaluated by comparison to various clinical and laboratory parameters that would be available to a clinician within 24 hours of ICU admission. SeptiCyteÂ® Lab was significantly better at differentiating sepsis from infection-negative systemic inflammation than all tested parameters, both singly and in various logistic combinations. SeptiCyteÂ® Lab more than halved the diagnostic error rate compared to PCT in all tested cohorts or cohort combinations. Conclusions: SeptiCyteÂ® Lab is a rapid molecular assay that may be clinically useful in the management of ICU patients with systemic inflammation. SIRS and Sepsis ICU patients, admission samples Retrospective, mutli-site sutdy using retrospective physician adjudication as a comparator

Project description:Objective: It is unclear whether the host response of gram-positive sepsis differs from gram-negative sepsis at a transcriptome level. Using microarray technology, we compared the gene-expression profiles of gram-positive sepsis and gram-negative sepsis in critically ill patients. Design: A prospective cross-sectional study. Setting: A 20-bed general intensive care unit of a tertiary referral hospital. Patients: Seventy-two patients admitted to the intensive care unit. Interventions: Intravenous blood was collected for leukocyte separation and RNA extraction. Microarray experiements were then performed examing the expression level of 19,232 genes in each sample. Measurements and Main Results: There was no difference in the expression profile between gram-positive and gram-negative sepsis. The finding remained unchanged even when genes with lower expression level were included or after statistical stringency was lowered. There were, however, ninety-four genes differentially expressed between sepsis and control patients. These genes included those involved in immune regulation, inflammation and mitochondrial function. Hierarchical cluster analysis confirmed that the difference in gene expression profile existed between sepsis and control patients, but not between gram-positive and gram-negative patients. Conclusion: Gram-positive and gram-negative sepsis share a common host response at a transcriptome level. These findings support the hypothesis that the septic response is non-specific and is designed to provide a more general response that can be elicited by a wide range of different micro-organisms. The study included seventy-two critically ill patients admitted to the intensive care unit (ICU) of Nepean Hospital, Sydney, Australia. Of these, fifty-five patients were diagnosed to have sepsis, as confirmed by microbiological culture. The remaining seventeen patients did not have sepsis and were therefore used as controls. The study was approved by the hospital ethics committee and informed consent was obtained from all patients or their relatives. Patient Samples. Whole blood was taken from each patient on admission to ICU. Neutrophils were separated from whole blood using density-gradient separation with Ficoll-PaqueP P(Amersham). Subsequent neutrophil RNA extraction was performed using guanidinium thiocyanate (Ambion). Microarray Experiment. The neutrophil RNA was converted to cDNA, fluorescently labeled and hybridized to its complimentary sequences on the microarray (Invitrogen). The fluorescent signals on each micrroarray were captured using the GenePix 4000B laser scanner (Axon Instruments). Expression level of each gene was represented by the intensity of its fluorescent signal. Data Extraction. All signal intensity values were processed using background-subtraction method. Prior to analysis, all values were log-transformed and normalized by fitting a print-tip group Lowess curve. Normalization minimizes bias due to dye chemistry, signal intensity or location of a gene on the array. It ensures the detection of genes that are truly differentially expressed, instead of those caused by experimental artifacts or variation in the hybridization process. After normalization, genes that had more than 50% of data missing were removed. We then selected genes that had at least 80% of the data showing two-fold changes from the geneâs median values. After filtering, 1617 genes were available for further analysis.

Project description:BackgroundSepsis and acute kidney injury (AKI) are common severe diseases in the intensive care unit (ICU). This study aimed to estimate the attributable mortality of AKI among critically ill patients with sepsis and to assess whether AKI was an independent risk factor for 30-day mortality.MethodsThe information we used was derived from a multicenter prospective cohort study conducted in 18 Chinese ICUs, focusing on septic patients post ICU admission. The patients were categorized into two groups: those who developed AKI (AKI group) within seven days following a sepsis diagnosis and those who did not develop AKI (non-AKI group). Using propensity score matching (PSM), patients were matched 1:1 as AKI and non-AKI groups. We then calculated the mortality rate attributable to AKI in septic patients. Furthermore, a survival analysis was conducted comparing the matched AKI and non-AKI septic patients. The primary outcome of interest was the 30-day mortality rate following the diagnosis of sepsis.ResultsOut of the 2175 eligible septic patients, 61.7% developed AKI. After the application of PSM, a total of 784 septic patients who developed AKI were matched in a 1:1 ratio with 784 septic patients who did not develop AKI. The overall 30-day attributable mortality of AKI was 6.6% (95% CI 2.3 ∼ 10.9%, p = 0.002). A subgroup analysis revealed that the 30-day attributable mortality rates for stage 1, stage 2, and stage 3 AKI were 0.6% (95% CI -5.9 ∼ 7.2%, p = 0.846), 4.7% (95% CI -3.1 ∼ 12.4%, p = 0.221) and 16.8% (95% CI 8.1 ∼ 25.2%, p < 0.001), respectively. Particularly noteworthy was that stage 3 AKI emerged as an independent risk factor for 30-day mortality, possessing an adjusted hazard ratio of 1.80 (95% CI 1.31 ∼ 2.47, p < 0.001).ConclusionsThe overall 30-day attributable mortality of AKI among critically ill patients with sepsis was 6.6%. Stage 3 AKI had the most significant contribution to 30-day mortality, while stage 1 and stage 2 AKI did not increase excess mortality.

Project description:Background: Systemic inflammation is a whole body reaction that can have an infection-positive (i.e. sepsis) or infection-negative origin. It is important to distinguish between septic and non-septic presentations early and reliably, because this has significant therapeutic implications for critically ill patients. We hypothesized that a molecular classifier based on a small number of RNAs expressed in peripheral blood could be discovered that would: 1) determine which patients with systemic inflammation had sepsis; 2) be robust across independent patient cohorts; 3) be insensitive to disease severity; and 4) provide diagnostic utility. The overall goal of this study was to identify and validate such a molecular classifier. Methods and Findings: We conducted an observational, non-interventional study of adult patients recruited from tertiary intensive care units (ICU). Biomarker discovery was conducted with an Australian cohort (n = 105) consisting of sepsis patients and post -surgical patients with infection-negative systemic inflammation. Using this cohort, a four-gene classifier consisting of a combination of CEACAM4, LAMP1, PLA2G7 and PLAC8 RNA biomarkers was identified. This classifier, designated SeptiCyte® Lab, was externally validated using RT-qPCR and receiver operating characteristic (ROC) curve analysis in five cohorts (n = 345) from the Netherlands. Cohort 1 (n=59) consisted of unambiguous septic cases and infection-negative systemic inflammation controls; SeptiCyte® Lab gave an area under curve (AUC) of 0.96 (95% CI: 0.91-1.00). ROC analysis of a more heterogeneous group of patients (Cohorts 2-5; 249 patients after excluding 37 patients with infection likelihood possible) gave an AUC of 0.89 (95% CI: 0.85-0.93). Disease severity, as measured by Sequential Organ Failure Assessment (SOFA) score or the Acute Physiology and Chronic Health Evaluation (APACHE) IV score, was not a significant confounding variable. The diagnostic utility o f SeptiCyte® Lab was evaluated by comparison to various clinical and laboratory parameters that would be available to a clinician within 24 hours of ICU admission. SeptiCyte® Lab was significantly better at differentiating sepsis from infection-negative systemic inflammation than all tested parameters, both singly and in various logistic combinations. SeptiCyte® Lab more than halved the diagnostic error rate compared to PCT in all tested cohorts or cohort combinations. Conclusions: SeptiCyte® Lab is a rapid molecular assay that may be clinically useful in the management of ICU patients with systemic inflammation. SIRS and Sepsis ICU patients, admission samples

Dataset Information

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

Publications

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

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