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Derivation and validation of the renal angina index to improve the prediction of acute kidney injury in critically ill children.

ABSTRACT: 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.

SUBMITTER: Basu RK

PROVIDER: S-EPMC4659420 | biostudies-literature | 2014 Mar

REPOSITORIES: biostudies-literature

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Derivation and validation of the renal angina index to improve the prediction of acute kidney injury in critically ill children.

Basu Rajit K RK Zappitelli Michael M Brunner Lori L Wang Yu Y Wong Hector R HR Chawla Lakhmir S LS Wheeler Derek S DS Goldstein Stuart L SL

Kidney international 20130918 3

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 ...[more]

PMID: 24048379

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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.

Project description:BackgroundThe renal angina index (RAI) is a tool that has been validated by several studies in the pediatric population to predict the development of severe acute kidney injury (AKI). The aims of this study were to evaluate the efficacy of the RAI in predicting severe AKI in critically ill patients with COVID-19 and to propose a modified RAI (mRAI) for this population.MethodsThis was a prospective cohort analysis of all COVID-19 patients receiving invasive mechanical ventilation (IMV) who were admitted to the intensive care unit (ICU) of a third-level hospital in Mexico City from 03/2020 to 01/2021. AKI was defined according to KDIGO guidelines. The RAI score was calculated for all enrolled patients using the method of Matsuura. Since all patients had the highest score for the condition (due to receiving IMV), the score corresponded to the delta creatinine (ΔSCr) value. The main outcome was severe AKI (stage 2 or 3) at 24 and 72 h after ICU admission. A logistic regression analysis was applied to search for factors associated with the development of severe AKI, and the data were applied to develop a mRAI and compare it vis-à-vis the efficacy of both scores (RAI and mRAI).ResultsOf the 452 patients studied, 30% developed severe AKI. The original RAI score was associated with AUCs of 0.67 and 0.73 at 24 h and 72 h, respectively, with a cutoff of 10 points to predict severe AKI. In the multivariate analysis adjusted for age and sex, a BMI ≥30 kg/m2, a SOFA score ≥6, and Charlson score were identified as risk factors for the development of severe AKI. In the new proposed score (mRAI), the conditions were summed and multiplied by the ΔSCr value. With these modifications, the AUC improved to 0.72 and 0.75 at 24 h and 72 h, respectively, with a cutoff of 8 points.ConclusionsThe original RAI is a limited tool for patients with critical COVID-19 receiving IMV. The mRAI, with the parameters proposed in the present study, improves predictive performance and risk stratification in critically ill patients receiving IMV.

Project description:BackgroundAcute 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.MethodsA 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).FindingsThe 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)).InterpretationEarlier, 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.

Project description: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. 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). 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. NCT01987921.

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:OBJECTIVES:To derive and validate a score that correlates with an objective measurement of a child's effort of breathing. DESIGN:Secondary analysis of a previously conducted observational study. SETTING:The pediatric and cardiothoracic ICUs of a quaternary-care children's hospital. PATIENTS:Patients more than 37 weeks gestational age to age 18 years who were undergoing extubation. INTERVENTIONS:Effort of breathing was measured in patients following extubation using esophageal manometry to calculate pressure rate product. Simultaneously, members of a multidisciplinary team (nurse, physician, and respiratory therapist) assessed respiratory function using a previously validated tool. Elements of the tool that were significantly associated with pressure rate product in univariate analysis were identified and included in a multivariate model. An Effort of Breathing score was derived from the results of the model using data from half of the subjects (derivation cohort) and then validated using data from the remaining subjects (validation cohort) by calculating the area under the receiver operator characteristic curve for pressure rate product greater than 90th percentile and for the need for reintubation. MEASUREMENTS AND MAIN RESULTS:Among 409 subjects, the median age was 5 months, and nearly half were cardiac surgery patients (49.1%). Retractions, stridor, and pulsus paradoxus were included in the Simple Score. Area under the receiver operator characteristic curve for pressure rate product greater than 90th percentile was 0.8359 (95% CI, 0.7996-0.8722) in the derivation cohort and 0.7930 (0.7524-0.8337) in the validation cohort. Area under the receiver operator characteristic curve for reintubation was 0.7280 (0.6807-0.7752) when all scores were analyzed individually and was 0.7548 (0.6644-0.8452) if scores from three clinicians from different disciplines were summated. Results were similar regardless of provider discipline or training. CONCLUSIONS:A scoring system was derived and validated, performed acceptably to predict increased effort of breathing or need for advanced respiratory support and may function best when used by a team.

Dataset Information

Derivation and validation of the renal angina index to improve the prediction of acute kidney injury in critically ill children.

Publications

Derivation and validation of the renal angina index to improve the prediction of acute kidney injury in critically ill children.

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