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Derivation of urine output thresholds that identify a very high risk of AKI in patients with septic shock.

ABSTRACT: BACKGROUND AND OBJECTIVES: To promote early detection of AKI, recently proposed pretest probability models combine sub-Kidney Disease Improving Global Outcomes (KDIGO) AKI criteria with baseline AKI risk. The primary objective of this study was to determine sub-KDIGO thresholds that identify patients with septic shock at highest risk for AKI. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: This was a retrospective analysis of 390 adult patients admitted to the medical intensive care unit (ICU) of a tertiary, academic medical center with septic shock between January 2008 and December 2010. Hourly urine output was collected from the time of septic shock recognition (hour 0) to hour 96, urine catheter removal, or ICU discharge (whichever occurred first). All available serum creatinine (SCr) measurements were collected until hour 96. The AKI pretest probability model was assessed during the first 12 hours of resuscitation and included the initial episode of oliguria, increase from baseline to peak SCr level, and Acute Physiology and Chronic Health Evaluation (APACHE) III score in a multivariable receiver-operator characteristic (ROC) analysis. The primary outcome was the incidence of stage II or III (stage II+) AKI defined by KDIGO criteria. Secondary outcomes included the need for RRT and 28-day mortality. RESULTS: Ninety-eight (25%) patients developed stage II+ AKI after septic shock recognition. APACHE III score and increase in SCr level in the first 12 hours were not statistically associated with stage II+ AKI in multivariable ROC analysis. Consecutive oliguria for 3 hours had fair predictive ability for achieving stage II+ AKI criteria (area under ROC curve, 0.73; 95% confidence interval [95% CI], 0.68 to 0.78), and oliguria for 5 hours demonstrated optimal accuracy (82%; 95% CI, 79% to 86%). CONCLUSIONS: Three to 5 hours of consecutive oliguria in patients with septic shock may provide a valuable measure of AKI risk. Further validation to support this finding is needed.

SUBMITTER: Leedahl DD

PROVIDER: S-EPMC4078959 | biostudies-literature | 2014 Jul

REPOSITORIES: biostudies-literature

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Derivation of urine output thresholds that identify a very high risk of AKI in patients with septic shock.

Leedahl David D DD Frazee Erin N EN Schramm Garrett E GE Dierkhising Ross A RA Bergstralh Eric J EJ Chawla Lakhmir S LS Kashani Kianoush B KB

Clinical journal of the American Society of Nephrology : CJASN 20140501 7

<h4>Background and objectives</h4>To promote early detection of AKI, recently proposed pretest probability models combine sub-Kidney Disease Improving Global Outcomes (KDIGO) AKI criteria with baseline AKI risk. The primary objective of this study was to determine sub-KDIGO thresholds that identify patients with septic shock at highest risk for AKI.<h4>Design, setting, participants, & measurements</h4>This was a retrospective analysis of 390 adult patients admitted to the medical intensive care ...[more]

PMID: 24789551

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Project description:IntroductionThe current definition of acute kidney injury (AKI) includes increased serum creatinine (sCr) concentration and decreased urinary output (UO). Recent studies suggest that the standard UO threshold of 0.5 ml/kg/h may be suboptimal. This study aimed to develop and validate a novel UO-based AKI classification system that improves mortality prediction and patient stratification.MethodsData were obtained from the MIMIC-IV and eICU databases. The development process included (1) evaluating UO as a continuous variable over 3-, 6-, 12-, and 24-h periods; (2) identifying 3 optimal UO cutoff points for each time window (stages 1, 2, and 3); (3) comparing sensitivity and specificity to develop a unified staging system; (4) assessing average versus persistent reduced UO hourly; (5) comparing the new UO-AKI system to the KDIGO UO-AKI system; (6) integrating sCr criteria with both systems and comparing them; and (7) validating the new classification with an independent cohort. In all these steps, the outcome was hospital mortality. Another analyzed outcome was 90-day mortality. The analyses included ROC curve analysis, net reclassification improvement (NRI), integrated discrimination improvement (IDI), and logistic and Cox regression analyses.ResultsFrom the MIMIC-IV database, 35,845 patients were included in the development cohort. After comparing the sensitivity and specificity of 12 different lowest UO thresholds across four time frames, 3 cutoff points were selected to compose the proposed UO-AKI classification: stage 1 (0.2-0.3 mL/kg/h), stage 2 (0.1-0.2 mL/kg/h), and stage 3 (< 0.1 mL/kg/h) over 6 h. The proposed classification had better discrimination when the average was used than when the persistent method was used. The adjusted odds ratio demonstrated a significant stepwise increase in hospital mortality with advancing UO-AKI stage. The proposed classification combined or not with the sCr criterion outperformed the KDIGO criteria in terms of predictive accuracy-AUC-ROC 0.75 (0.74-0.76) vs. 0.69 (0.68-0.70); NRI: 25.4% (95% CI: 23.3-27.6); and IDI: 4.0% (95% CI: 3.6-4.5). External validation with the eICU database confirmed the superior performance of the new classification system.ConclusionThe proposed UO-AKI classification enhances mortality prediction and patient stratification in critically ill patients, offering a more accurate and practical approach than the current KDIGO criteria.

Project description:Background: Septic shock is a heterogeneous syndrome within which probably exist several biological subclasses. Discovery and identification of septic shock subclasses could provide the foundation for the design of more specifically targeted therapies. Herein we tested the hypothesis that pediatric septic shock subclasses can be discovered through genome-wide expression profiling. Methods: Genome-wide expression profiling was conducted using whole blood-derived RNA from 98 children with septic shock, followed by a series of bioinformatic approaches targeted at subclass discovery and characterization. Results: Three putative subclasses (subclasses A, B, and C) were initially identified based on an empiric, discovery-oriented expression filter and unsupervised hierarchical clustering. Statistical comparison of the 3 putative subclasses (ANOVA, Bonferonni correction, p < 0.05) identified 6,934 differentially regulated genes. K means clustering of these 6,934 genes generated 10 coordinately regulated gene clusters corresponding to multiple signaling and metabolic pathways, all of which were differentially regulated across the 3 subclasses. Leave one out cross validation procedures indentified 100 genes having the strongest predictive values for subclass identification. Forty-four of these 100 genes corresponded to signaling pathways relevant to the adaptive immune system and glucocorticoid receptor signaling, the majority of which were repressed in subclass A patients. Subclass A patients were also characterized by repression of genes corresponding to zinc-related biology. Phenotypic analyses revealed that subclass A patients were younger, had a higher illness severity, and a higher mortality rate than patients in subclasses B and C. Conclusions: Genome-wide expression profiling can identify pediatric septic shock subclasses having clinically relevant phenotypes. Expression data from 98 children with septic shock and 32 normal controls were generated using whole blood-derived RNA samples representing the first 24 hours of admission to the pediatric intensive care unit. The controls were used for normalization. Subsequently, we used the expression data to derive expression-based subclasses of patients using discovery oriented expression and statistical filters, followed by unsupervised hierarchical clustering.

Project description:Septic shock is the leading cause of cardiovascular failure in the intensive care unit (ICU). Cardiac output is a primary component of global oxygen delivery to organs and a sensitive parameter of cardiovascular failure. Any mismatch between oxygen delivery and rapidly varying metabolic demand may result in tissue dysoxia, hence organ dysfunction. Since the intricate alterations of both vascular and cardiac function may rapidly and widely change over time, cardiac output should be measured repeatedly to characterize the type of shock, select the appropriate therapeutic intervention, and evaluate patient's response to therapy. Among the numerous techniques commercially available for measuring cardiac output, transpulmonary thermodilution (TPT) provides a continuous monitoring with external calibration capability, whereas critical care echocardiography (CCE) offers serial hemodynamic assessments. CCE allows early identification of potential sources of inaccuracy of TPT, including right ventricular failure, severe tricuspid or left-sided regurgitations, intracardiac shunt, very low flow states, or dynamic left ventricular outflow tract obstruction. In addition, CCE has the unique advantage of depicting the distinct components generating left ventricular stroke volume (large cavity size vs. preserved contractility), providing information on left ventricular diastolic properties and filling pressures, and assessing pulmonary artery pressure. Since inotropes may have deleterious effects if misused, their initiation should be based on the documentation of a cardiac dysfunction at the origin of the low flow state by CCE. Experts widely advocate using CCE as a first-line modality to initially evaluate the hemodynamic profile associated with shock, as opposed to more invasive techniques. Repeated assessments of both the efficacy (amplitude of the positive response) and tolerance (absence of side-effect) of therapeutic interventions are required to best guide patient management. Overall, TPT allowing continuous tracking of cardiac output variations and CCE appear complementary rather than mutually exclusive in patients with septic shock who require advanced hemodynamic monitoring.

Project description:BackgroundExtracorporeal cytokine adsorption is an option in septic shock as an additional measure to treat a pathological immune response. Purpose of this study was to investigate the effects of extracorporeal cytokine adsorption on hemodynamic parameters in patients with acute kidney injury (AKI) on continuous renal replacement therapy (CRRT) and septic shock after cardiac surgery.MethodsIn this retrospective study, a total of 98 patients were evaluated. Hemoadsorption was performed by the CytoSorb® adsorber. In all patients cytokine adsorption was applied for at least 15 hours and at least one adsorber was used per patient. To compare cumulative inotrope need in order to maintain a mean arterial pressure (MAP) of ≥ 65 mmHg, we applied vasoactive score (VAS) for each patient before and after cytokine adsorption. A paired t-test has been performed to determine statistical significance.ResultsBefore cytokine adsorption the mean VAS was 56.7 points. This was statistically significant decreased after cytokine adsorption (27.7 points, p< 0.0001). Before cytokine adsorption, the mean noradrenalin dose to reach a MAP of ≥ 65 mmHg was 0.49 μg/kg bw/min, the mean adrenalin dose was 0.12 μg/kg bw/min. After cytokine adsorption, significantly reduced catecholamine doses were necessary to maintain a MAP of ≥ 65 mmHg (0.24 μg/kg bw/min noradrenalin; p< 0.0001 and 0.07 μg/kg bw/min adrenalin; p < 0.0001). Moreover, there was a significant reduction of serum lactate levels after treatment (p< 0.0001). The mean SOFA-score for these patients with septic shock and AKI before cytokine adsorption was 16.7 points, the mean APACHE II-score was 30.2 points. The mean predicted in-hospital mortality rate based on this SOFA-score of 16.7 points was 77,0%, respectively 73,0% on APACHE II-score, while the all-cause in-hospital mortality rate of the patients in this study was 59.2%.ConclusionIn patients with septic shock and AKI undergoing cardiac surgery, extracorporeal cytokine adsorption could significantly lower the need for postoperative inotropes. Additionally, observed versus SOFA- and APACHE II-score predicted in-hospital mortality rate was decreased.

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Derivation of urine output thresholds that identify a very high risk of AKI in patients with septic shock.

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Derivation of urine output thresholds that identify a very high risk of AKI in patients with septic shock.

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