Assessment of a modified renal angina index for AKI prediction in critically ill adults.
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ABSTRACT: Background
The renal angina index (RAI) is a useful tool for risk stratification of acute kidney injury (AKI) in critically ill children. We evaluated the performance of a modified adult RAI (mRAI) for the risk stratification of AKI in critically ill adults.Methods
We used two independent intensive care unit (ICU) cohorts: 13 965 adult patients from the University of Kentucky (UKY) and 4789 from University of Texas Southwestern (UTSW). The mRAI included: diabetes, presence of sepsis, mechanical ventilation, pressor/inotrope use, percentage change in serum creatinine (SCr) in reference to admission SCr (ΔSCr) and fluid overload percentage within the first day of ICU admission. The primary outcome was AKI Stage ≥2 at Days 2-7. Performance and reclassification metrics were determined for the mRAI score compared with ΔSCr alone.Results
The mRAI score outperformed ΔSCr and readjusted probabilities to predict AKI Stage ≥2 at Days 2-7: C-statistic: UKY 0.781 versus 0.708 [integrated discrimination improvement (IDI) 2.2%] and UTSW 0.766 versus 0.696 (IDI 1.8%) (P < 0.001 for both). In the UKY cohort, only 3.3% of patients with mRAI score <10 had the AKI event, while 16.4% of patients with mRAI score of ≥10 had the AKI event (negative predictive value 96.8%). Similar findings were observed in the UTSW cohort as part of external validation.Conclusions
In critically ill adults, the adult mRAI score determined within the first day of ICU admission outperformed changes in SCr for the prediction of AKI Stage ≥2 at Days 2-7 of ICU stay. The mRAI is a feasible tool for AKI risk stratification in adult patients in the ICU.
SUBMITTER: Ortiz-Soriano V
PROVIDER: S-EPMC9272422 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Background and objectivesNovel AKI biomarkers carry variable performance for prediction of AKI in patients with heterogeneous illness. Until utility is demonstrated in critically ill patients outside of the cardiopulmonary bypass population, AKI biomarkers are unlikely to gain widespread implementation. Operationalization of an AKI risk stratification methodology, termed renal angina, was recently reported to enhance prediction at the time of intensive care unit admission for persistent severe AKI. The renal angina index (RAI) was developed to provide the clinical context to direct AKI biomarker testing. This study tested the hypothesis that incorporation of AKI biomarkers in patients fulfilling renal angina improves the prediction of persistent severe AKI.Design, setting, participants, & measurementsIn a multicenter study of 214 patients admitted to the pediatric intensive care unit with sepsis, the discrimination of plasma neutrophil gelatinase-associated lipocalin (NGAL), matrix metalloproteinase-8 (MMP-8), and neutrophil elastase-2 (Ela-2) were determined individually and in combination with the RAI for severe AKI. Net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were calculated.ResultsIndividual biomarkers demonstrated marginal discrimination for severe AKI (area under curve [AUC]: NGAL, 0.72; MMP-8, 0.68; Ela-2, 0.72), inferior to prediction by the clinical model of the RAI (AUC=0.80). Incorporation of each biomarker significantly added to the renal angina model AKI prediction (AUC=0.80, increased to 0.84-0.88; P<0.05 for each). The inclusion of each biomarker with the RAI demonstrated NRI (0.512, 0.428, and 0.545 for NGAL, MMP-8, and Ela-2, respectively; all P<0.03) and IDI (0.075 for Ela-2). The inclusion of both Ela-2 and NGAL with RAI demonstrated an NRI of 0.871 (P<0.001) and an IDI of 0.1 (P=0.01).ConclusionsThis study shows that incorporation of AKI biomarkers into the RAI improves discrimination for severe AKI. The RAI optimizes the utility of AKI biomarkers in a heterogeneous, critically ill patient population.
| S-EPMC3974366 | biostudies-literature
Project description:Background:Acute kidney injury (AKI) occurs in one in four children admitted to the intensive care unit (ICU) and AKI severity is independently associated with increased patient morbidity and mortality. Early prediction of AKI has the potential to improve outcomes. In smaller, single center populations, we have previously derived and validated the performance of the renal angina index (RAI), a context driven risk stratification system, to predict severe AKI. Methods:A prospective, observational study (AWARE1, January-December 2014) was conducted in intensive care units from 32 centers in 9 countries. The primary outcome was the presence of severe AKI ("AKIS"; Stage 2-3 AKI KDIGO guidelines) on the third day after ICU admission (). We compared the performance of the RAI to changes in serum creatinine relative to baseline (SCr/Base) for prediction of the primary outcome and secondary outcomes of interest. A RAI ? 8 defined fulfillment of renal angina (RA+); RA+ was compared to SCr increased relative to baseline ("SCr>Base"; using maximum SCr in first 12 hours of ICU admission). Findings:The 1590 patients studied were 55% male and had median age of 54.5 months. 286 patients (17.9%) were RA+. AKIS occurred in 121 (42.3%) RA+ vs. 247 (18.9%) RA-patients (relative risk (RR) 2.23; 95% confidence interval (CI): 1.87-2.66, p<0.001). 368 (23.1%) patients with AKIS had increased renal replacement therapy utilization (10.9% vs. 1.5%, p<0.001) and increased mortality (7.6% vs. 4.3%, p=0.01) compared to patients without AKIS. RA+ demonstrated better prediction for AKIS than SCr>Base (RR: 1.61; (1.33-1.93), p<0.001) which was maintained on multivariate regression (independent odds ratio (OR): RA+ 3.21; 95% CI (2.20-4.67) vs. SCr>Base 0.68; 95% CI (0.49-4.94)). Interpretation:Earlier, better prediction of severe AKI has the potential to improve AKI associated patient outcomes. Compared to isolated, context-free changes in SCr, renal angina risk assessment improved accuracy for prediction of severe AKI in critically ill children and young adults.
| S-EPMC6053052 | biostudies-literature
Project description:BackgroundFluid overload and acute kidney injury are common and associated with poor outcomes among critically ill children. The prodrome of renal angina stratifies patients by risk for severe acute kidney injury, but the predictive discrimination for fluid overload is unknown.MethodsPost-hoc analysis of patients admitted to a tertiary care pediatric intensive care unit (PICU). The primary outcome was the performance of renal angina fulfillment on day of ICU admission to predict fluid overload ≥15% on Day 3.Results77/139 children (55%) fulfilled renal angina (RA+). After adjusting for covariates, RA+ was associated with increased odds of fluid overload on Day 3 (adjusted odds ratio (aOR) 5.1, 95% CI 1.23-21.2, p = 0.025, versus RA-). RA- resulted in a 90% negative predictive value for fluid overload on Day 3. Median fluid overload was significantly higher in RA+ patients with severe acute kidney injury compared to RA+ patients without severe acute kidney injury (% fluid overload on Day 3: 8.8% vs. 0.73%, p = 0.002).ConclusionAmong critically ill children, fulfillment of renal angina was associated with increased odds of fluid overload versus the absence of renal angina and a higher fluid overload among patients who developed acute kidney injury. Renal angina directed risk classification may identify patients at highest risk for fluid accumulation. Expanded study in larger populations is warranted.
| S-EPMC8502791 | biostudies-literature
Project description:Reliable prediction of severe acute kidney injury (AKI) has the potential to optimize treatment. Here we operationalized the empiric concept of renal angina with a renal angina index (RAI) and determined the predictive performance of RAI. This was assessed on admission to the pediatric intensive care unit, for subsequent severe AKI (over 200% rise in serum creatinine) 72?h later (Day-3 AKI). In a multicenter four cohort appraisal (one derivation and three validation), incidence rates for a Day 0 RAI of 8 or more were 15-68% and Day-3 AKI was 13-21%. In all cohorts, Day-3 AKI rates were higher in patients with an RAI of 8 or more with the area under the curve of RAI for predicting Day-3 AKI of 0.74-0.81. An RAI under 8 had high negative predictive values (92-99%) for Day-3 AKI. RAI outperformed traditional markers of pediatric severity of illness (Pediatric Risk of Mortality-II) and AKI risk factors alone for prediction of Day-3 AKI. Additionally, the RAI outperformed all KDIGO stages for prediction of Day-3 AKI. Thus, we operationalized the renal angina concept by deriving and validating the RAI for prediction of subsequent severe AKI. The RAI provides a clinically feasible and applicable methodology to identify critically ill children at risk of severe AKI lasting beyond functional injury. The RAI may potentially reduce capricious AKI biomarker use by identifying patients in whom further testing would be most beneficial.
| S-EPMC4659420 | biostudies-literature
Project description:BackgroundAKI is a common sequela of coronavirus disease 2019 (COVID-19). However, few studies have focused on AKI treated with RRT (AKI-RRT).MethodsWe conducted a multicenter cohort study of 3099 critically ill adults with COVID-19 admitted to intensive care units (ICUs) at 67 hospitals across the United States. We used multivariable logistic regression to identify patient-and hospital-level risk factors for AKI-RRT and to examine risk factors for 28-day mortality among such patients.ResultsA total of 637 of 3099 patients (20.6%) developed AKI-RRT within 14 days of ICU admission, 350 of whom (54.9%) died within 28 days of ICU admission. Patient-level risk factors for AKI-RRT included CKD, men, non-White race, hypertension, diabetes mellitus, higher body mass index, higher d-dimer, and greater severity of hypoxemia on ICU admission. Predictors of 28-day mortality in patients with AKI-RRT were older age, severe oliguria, and admission to a hospital with fewer ICU beds or one with greater regional density of COVID-19. At the end of a median follow-up of 17 days (range, 1-123 days), 403 of the 637 patients (63.3%) with AKI-RRT had died, 216 (33.9%) were discharged, and 18 (2.8%) remained hospitalized. Of the 216 patients discharged, 73 (33.8%) remained RRT dependent at discharge, and 39 (18.1%) remained RRT dependent 60 days after ICU admission.ConclusionsAKI-RRT is common among critically ill patients with COVID-19 and is associated with a hospital mortality rate of >60%. Among those who survive to discharge, one in three still depends on RRT at discharge, and one in six remains RRT dependent 60 days after ICU admission.
| S-EPMC7894677 | biostudies-literature
Project description:BackgroundThe inconsistent ability of novel biomarkers to predict acute kidney injury (AKI) across heterogeneous patients and illnesses limits integration into routine practice. We previously retrospectively validated the ability of the renal angina index (RAI) to risk-stratify patients and provide context for confirmatory serum biomarker testing for the prediction of severe AKI.MethodsWe conducted this first prospective study of renal angina to determine whether the RAI on the day of admission (Day0) risk-stratified critically ill children for 'persistent, severe AKI' on Day 3 (Day3-AKI: KDIGO Stage 2-3) and whether incorporation of urinary biomarkers in the RAI model optimized AKI prediction.ResultsA total of 184 consecutive patients (52.7% male) were included. Day0 renal angina was present (RAI ?8) in 60 (32.6%) patients and was associated with longer duration of mechanical ventilation (P = 0.04), higher number of organ failure days (P = 0.003) and increased mortality (P < 0.001) than in patients with absence of renal angina. Day3-AKI was present in 15/156 (9.6%) patients; 12/15 (80%) fulfilled Day0 renal angina. Incorporation of urinary biomarkers into the RAI model increased the specificity and positive likelihood, and demonstrated net reclassification improvement (P < 0.001) for the prediction of Day3-AKI. Inclusion of urinary neutrophil gelatinase-associated lipocalin increased the area under the curve receiver-operating characteristic of RAI for Day3-AKI from 0.80 [95% confidence interval (CI): 0.58, 1.00] to 0.97 (95% CI: 0.93, 1.00).ConclusionsWe have now prospectively validated the RAI as a functional risk stratification methodology in a heterogeneous group of critically ill patients, providing context to direct measurement of novel urinary biomarkers and improving the prediction of severe persistent AKI.
| S-EPMC6281075 | biostudies-literature
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 Retrospective, mutli-site sutdy using retrospective physician adjudication as a comparator
2015-10-24 | E-GEOD-74224 | biostudies-arrayexpress
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
2015-10-24 | GSE74224 | GEO
Project description:Acute kidney injury (AKI) is associated with poor outcome in critically ill children. While data extracted from retrospective study of pediatric populations demonstrate a high incidence of AKI, the literature lacks focused and comprehensive multicenter studies describing AKI risk factors, epidemiology, and outcome. Additionally, very few pediatric studies have examined novel urinary biomarkers outside of the cardiopulmonary bypass population.This is a prospective observational study. We anticipate collecting data on over 5000 critically ill children admitted to 31 pediatric intensive care units (PICUs) across the world during the calendar year of 2014. Data will be collected for seven days on all children older than 90 days and younger than 25 years without baseline stage 5 chronic kidney disease, chronic renal replacement therapy, and outside of 90 days of a kidney transplant or from surgical correction of congenital heart disease. Data to be collected includes demographic information, admission diagnoses and co-morbidities, and details on fluid and vasoactive resuscitation used. The renal angina index will be calculated integrating risk factors and early changes in serum creatinine and fluid overload. On days 2-7, all hemodynamic and pertinent laboratory values will be captured focusing on AKI pertinent values. Daily calculated values will include % fluid overload, fluid corrected creatinine, and KDIGO AKI stage. Urine will be captured twice daily for biomarker analysis on Days 0-3 of admission. Biomarkers to be measured include neutrophil gelatinase lipocalin (NGAL), kidney injury molecule-1 (KIM-1), liver-type fatty acid binding protein (l-FABP), and interleukin-18 (IL-18). The primary outcome to be quantified is incidence rate of severe AKI on Day 3 (Day 3-AKI). Prediction of Day 3-AKI by the RAI and after incorporation of biomarkers with RAI will be analyzed.The Assessment of Worldwide Acute Kidney Injury, Renal Angina and Epidemiology (AWARE) study, creates the first prospective international pediatric all cause AKI data warehouse and biologic sample repository, providing a broad and invaluable resource for critical care nephrologists seeking to study risk factors, prediction, identification, and treatment options for a disease syndrome with high associated morbidity affecting a significant proportion of hospitalized children.ClinicalTrials.gov: NCT01987921.
| S-EPMC4355130 | biostudies-literature
Project description:BACKGROUND:Acute kidney injury (AKI) is associated with poor outcomes in critically ill children. Recent international consensus panels recommend standardized classification systems to improve the precision of AKI diagnosis, but there is a paucity of data to enable this refinement, particularly in pediatric critical care. METHODS/DESIGN:This is a prospective observational study. We anticipate collecting data from more than 5500 critically ill children admitted to 32 pediatric intensive care units (PICUs) across the world, during the calendar year of 2014. Data will be collected continuously for three months at each center on all children older than 90 days and younger than 25 years admitted to the ICU. Demographic, resuscitative, and daily physiological and lab data will be captured at individual centers using MediData Rave™, a commercial system designed to manage and report clinical research data. Kidney specific measured variables include changes in serum creatinine and urine output, cumulative fluid overload (%), serum creatinine corrected for fluid balance, and KDIGO AKI stage. Urinary AKI biomarkers to be measured include: urinary neutrophil gelatinase lipocalin (NGAL), kidney injury molecule-1 (KIM-1), liver-type fatty acid binding protein (l-FABP), and interleukin-18 (IL-18). Biomarker combinations will be created from different pairs and triplets of urinary biomarkers. The primary analysis will compare the discrimination of these panels versus changes in creatinine for prediction of severe AKI by Day 7 of ICU admission. Secondary analysis will investigate the prediction of biomarkers for injury 'time based phenotypes': duration (>2 days), severity (KDIGO stage, use of renal replacement therapy), reversibility (time to return of serum creatinine to baseline), association with fluid overload > 10%, and disease association (sepsis, hypovolemia, hypoxemia, or nephrotoxic). DISCUSSION:The Assessment of Worldwide Acute Kidney Injury, Renal Angina and Epidemiology (AWARE) study will be the largest ever prospective study of any disease process in pediatric critical care. Data from AWARE will enable refinement of AKI classification. AWARE creates the largest ever all-cause pediatric AKI data warehouse and biologic sample repository, providing a broad and invaluable resource for critical care nephrologists seeking to study risk factors, prediction, identification, and treatment options for a disease syndrome with high associated morbidity affecting a significant proportion of hospitalized children. Improving the precision of AKI diagnosis using biomarker combinations provides a foundation for targeted, personalized therapy for different injury phenotypes. TRIAL REGISTRATION NUMBER:NCT01987921.
| S-EPMC4692459 | biostudies-literature