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

Basu, Rajit K.; Zappitelli, Michael; Brunner, Lori; Wang, Yu; Wong, Hector R.; Chawla, Lakhmir S.; Wheeler, Derek S.; Goldstein, Stuart L.

doi:10.1038/ki.2013.349

Cited by 297Acute Kidney Injury ResearchChronic Kidney Disease and DiabetesSepsis Diagnosis and Treatment

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

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Basu, Rajit K., Zappitelli, Michael, Brunner, Lori, Wang, Yu, Wong, Hector R., Chawla, Lakhmir S., Wheeler, Derek S., Goldstein, Stuart L.·2014·Kidney International

DOI 10.1038/ki.2013.349PMC PMC4659420

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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.

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Stem cell transplantation information, originally used in RAI but not in the model, may have contributed to the higher performance of previously reported RAI compared to those computed here.
“In addition, stem cell transplantation information, originally used in RAI [17] but not in the model, may have contributed to the higher performance of previously reported RAI compared to those computed here”
From Machine learning model for early prediction of acute kidney injury (AKI) in pediatric critical care (2021) · cites this paper as [17]
The baseline comparator RAI, using mainly creatinine to predict AKI, performed worse than the model.
“The baseline comparator RAI, using mainly creatinine to predict AKI [17], performed worse than the model”
From Machine learning model for early prediction of acute kidney injury (AKI) in pediatric critical care (2021) · cites this paper as [17]
The model outperforms the RAI.
“The model outperforms a more simple comparator, the RAI, shown to be predictive of AKI in critically ill children [17].”
From Machine learning model for early prediction of acute kidney injury (AKI) in pediatric critical care (2021) · cites this paper as [17]

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Fatal Outcomes of COVID-19 in Patients with Severe Acute Kidney Injury
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Epidemiology of acute kidney injury in children worldwide, including developing countries
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Renal angina: concept and development of pretest probability assessment in acute kidney injury
Chawla, L. S., Goldstein, S. L., Kellum, J. A., & Ronco, C. (2015) · Critical Care · doi:10.1186/s13054-015-0779-y · Cited by 70
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PPAR αcontributes to protection against metabolic and inflammatory derangements associated with acute kidney injury in experimental sepsis
Iwaki, T., Bennion, B. G., Stenson, E. K., Lynn, J. C., Otinga, C., Djukovic, D., Raftery, D., Fei, L., Wong, H. R., Liles, W. C., et al. (2019) · Physiological Reports · doi:10.14814/phy2.14078 · Cited by 70
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Syndecan-1 improves severe acute kidney injury prediction after pediatric cardiac surgery
Cavalcante, C. T. D. M. B., Branco, K. M. P. C., Júnior, V. C. P., Meneses, G. C., Neves, F. M. D. O., de Souza, N. M. G., Penaforte, K. L., Martins, A. M. C., & Libório, A. B. (2016) · Journal of Thoracic and Cardiovascular Surgery · doi:10.1016/j.jtcvs.2016.03.079 · Cited by 68
Kinetics of the cell cycle arrest biomarkers (TIMP-2*IGFBP-7) for prediction of acute kidney injury in infants after cardiac surgery
Gist, K. M., Goldstein, S. L., Wrona, J., Alten, J. A., Basu, R. K., Cooper, D. S., Soranno, D. E., Duplantis, J., Altmann, C. J., Gao, Z., et al. (2017) · Pediatric Nephrology · doi:10.1007/s00467-017-3655-y · Cited by 69
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Acute kidney injury epidemiology, risk factors, and outcomes in critically ill patients 16–25 years of age treated in an adult intensive care unit
Fuhrman, D. Y., Kane‐Gill, S. L., Goldstein, S. L., Priyanka, P., & Kellum, J. A. (2018) · Annals of Intensive Care · doi:10.1186/s13613-018-0373-y · Cited by 67
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Derivation of Urine Output Thresholds That Identify a Very High Risk of AKI in Patients with Septic Shock
Leedahl, D. D., Frazee, E. N., Schramm, G. E., Dierkhising, R., Bergstralh, E. J., Chawla, L. S., & KASHANI, K. B. (2014) · Clinical Journal of the American Society of Nephrology · doi:10.2215/cjn.09360913 · Cited by 64
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Pediatric acute kidney injury: new advances in the last decade
Sethi, S. K., Bunchman, T. E., Chakraborty, R., & Raina, R. (2021) · Kidney Research and Clinical Practice · doi:10.23876/j.krcp.20.074 · Cited by 70
Integration of urinary neutrophil gelatinase-associated lipocalin with serum creatinine delineates acute kidney injury phenotypes in critically ill children
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Cardiac Biomarkers and Acute Kidney Injury After Cardiac Surgery
Bucholz, E. M., Whitlock, R. P., Zappitelli, M., Devarajan, P., Eikelboom, J. W., Garg, A. X., Thiessen‐Philbrook, H., Devereaux, P. J., Krawczeski, C. D., Kavsak, P. A., et al. (2015) · PEDIATRICS · doi:10.1542/peds.2014-2949 · Cited by 59
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Use of the Renal Angina Index in Determining Acute Kidney Injury
Matsuura, R., Srisawat, N., Granado, R. C., Doi, K., Yoshida, T., Nangaku, M., & Noiri, E. (2018) · Kidney International Reports · doi:10.1016/j.ekir.2018.01.013 · Cited by 59
Fluid assessment, fluid balance, and fluid overload in sick children: a report from the Pediatric Acute Disease Quality Initiative (ADQI) conference
Selewski, D. T., Barhight, M. F., Bjornstad, E. C., Ricci, Z., Tavares, M. D. S., Akcan‐Arikan, A., Goldstein, S. L., Basu, R. K., Bagshaw, S. M., Alobaidi, R., et al. (2023) · Pediatric Nephrology · doi:10.1007/s00467-023-06156-w · Cited by 62
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Real-Time Clinical Decision Support Based on Recurrent Neural Networks for In-Hospital Acute Kidney Injury: External Validation and Model Interpretation
Kim, K., Yang, H., Yi, J., Son, H. E., Ryu, J. Y., Kim, Y. C., Jeong, J. C., Chin, H. J., Na, K. Y., Chae, D., et al. (2021) · Journal of Medical Internet Research · doi:10.2196/24120 · Cited by 57
Continuous Kidney Replacement Therapy Practices in Pediatric Intensive Care Units Across Europe
Daverio, M., Cortina, G., Jones, A., Ricci, Z., Demirkol, D., Raymakers-Janssen, P. A. M. A., Lion, F., Camilo, C., Stojanovic, V. D., Grazioli, S., et al. (2022) · JAMA Network Open · doi:10.1001/jamanetworkopen.2022.46901 · Cited by 55
Hypoalbuminemia: a risk factor for acute kidney injury development and progression to chronic kidney disease in critically ill patients
Shao, M., Wang, S., & Parameswaran, P. K. (2016) · International Urology and Nephrology · doi:10.1007/s11255-016-1453-2 · Cited by 54
Development of a Prediction Model of Early Acute Kidney Injury in Critically Ill Children Using Electronic Health Record Data
Sanchez-Pinto, L. N., & Khemani, R. G. (2016) · Pediatric Critical Care Medicine · doi:10.1097/pcc.0000000000000750 · Cited by 52
Utilization of Small Changes in Serum Creatinine with Clinical Risk Factors to Assess the Risk of AKI in Critically lll Adults
Cruz, D. N., Ferrer‐Nadal, A., Piccinni, P., Goldstein, S. L., Chawla, L. S., Alessandri, E., Anello, C. B., Bohannon, W., Bove, T., Brienza, N., et al. (2014) · Clinical Journal of the American Society of Nephrology · doi:10.2215/cjn.05190513 · Cited by 52
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Acute Kidney Injury Epidemiology in pediatrics
Cleto-Yamane, T. L., Gomes, C. L. R., Suassuna, J. H. R., & Nogueira, P. C. K. (2018) · Brazilian Journal of Nephrology · doi:10.1590/2175-8239-jbn-2018-0127 · Cited by 56
Continuous renal replacement therapy in neonates and children: what does the pediatrician need to know? An overview from the Critical Care Nephrology Section of the European Society of Paediatric and Neonatal Intensive Care (ESPNIC)
Cortina, G., Daverio, M., Demirkol, D., Chanchlani, R., & Deep, A. (2023) · European Journal of Pediatrics · doi:10.1007/s00431-023-05318-0 · Cited by 53
Current Status of Novel Biomarkers for the Diagnosis of Acute Kidney Injury: A Historical Perspective
Griffin, B. R., Gist, K. M., & Faubel, S. G. (2019) · Journal of Intensive Care Medicine · doi:10.1177/0885066618824531 · Cited by 50
Pediatric acute kidney injury: prevalence, impact and management challenges
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A Time-Updated, Parsimonious Model to Predict AKI in Hospitalized Children
Sandokji, I. A., Yamamoto, Y., Biswas, A., Arora, T., Ugwuowo, U. C., Simonov, M., Saran, I., Martin, M. C., Testani, J. M., Mansour, S. G., et al. (2020) · Journal of the American Society of Nephrology · doi:10.1681/asn.2019070745 · Cited by 52
Acute Kidney Injury Risk Assessment: Differences and Similarities Between Resource-Limited and Resource-Rich Countries
KASHANI, K. B., Macedo, E. M., Burdmann, E. A., Hooi, L. S., Khullar, D., Bagga, A., Chakravarthi, R. M., & Mehta, R. L. (2017) · Kidney International Reports · doi:10.1016/j.ekir.2017.03.014 · Cited by 48
Acute Kidney Injury
Menon, S., Symons, J. M., & Selewski, D. T. (2023) · Pediatrics in Review · doi:10.1542/pir.2021-005438 · Cited by 47
Neonatal multiple organ failure after perinatal asphyxia
Iribarren, I., Hilario, E., Alvarez, A. A., & Alconada, D. A. (2022) · Anales de Pediatría (English Edition) · doi:10.1016/j.anpede.2022.08.010 · Cited by 46
Acute Kidney Injury in Pediatric Inflammatory Multisystem Syndrome Temporally Associated With Severe Acute Respiratory Syndrome Coronavirus-2 Pandemic: Experience From PICUs Across United Kingdom*
Deep, A., Upadhyay, G., du Pré, P., Lillie, J., Pan, D., Mudalige, N. L., Kanthimathinathan, H. K., Johnson, M. K. A., Riphagen, S. D., Dwarakanathan, B., et al. (2020) · Critical Care Medicine · doi:10.1097/ccm.0000000000004662 · Cited by 46
Definitions, phenotypes, and subphenotypes in acute kidney injury—Moving towards precision medicine
Rodrigues, C. E., & Endre, Z. H. (2022) · Nephrology · doi:10.1111/nep.14132 · Cited by 44
Explainable Machine Learning Model for Predicting Persistent Sepsis-Associated Acute Kidney Injury: Development and Validation Study
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Kidney disease in children: latest advances and remaining challenges
Bertram, J. F., Goldstein, S. L., Pape, L., Schaefer, F. S., Shroff, R. C., & Warady, B. A. (2016) · Nature Reviews Nephrology · doi:10.1038/nrneph.2015.219 · Cited by 43
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Biomarkers for prediction of acute kidney injury in pediatric patients: a systematic review and meta-analysis of diagnostic test accuracy studies
Meena, J. K., Thomas, C. C., Kumar, J., Mathew, G., & Bagga, A. (2023) · Pediatric Nephrology · doi:10.1007/s00467-023-05891-4 · Cited by 45
Predicting acute kidney injury in critically ill patients using comorbid conditions utilizing machine learning
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Fluid Overload and Renal Angina Index at Admission Are Associated With Worse Outcomes in Critically Ill Children
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Predictive factors of mortality in pediatric patients with acute renal injury associated with sepsis
Riyuzo, M. C., Silveira, L. V. D. A., de Macedo, C. S., & Fioretto, J. R. (2016) · Jornal de Pediatria · doi:10.1016/j.jped.2016.04.006 · Cited by 36
The impact of biomarkers of acute kidney injury on individual patient care
Koyner, J. L., Zarbock, A., Basu, R. K., & Ronco, C. (2019) · Nephrology Dialysis Transplantation · doi:10.1093/ndt/gfz188 · Cited by 36
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Risk Stratification for Acute Kidney Injury: Are Biomarkers Enough?
McMahon, B. A., & Koyner, J. L. (2016) · Advances in Chronic Kidney Disease · doi:10.1053/j.ackd.2016.03.001 · Cited by 35
Use of the Selective Cytopheretic Device in Critically Ill Children
Goldstein, S. L., Askenazi, D. J., Basu, R. K., Selewski, D. T., Paden, M. L., Krallman, K. A., Kirby, C. L., Mottes, T. A., Terrell, T. C., & Humes, H. D. (2020) · Kidney International Reports · doi:10.1016/j.ekir.2020.12.010 · Cited by 36
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Quality improvement goals for pediatric acute kidney injury: pediatric applications of the 22nd Acute Disease Quality Initiative (ADQI) conference
Selewski, D. T., Askenazi, D. J., KASHANI, K. B., Basu, R. K., Gist, K. M., Harer, M. W., Jetton, J. G., Sutherland, S. M., Zappitelli, M., Ronco, C., et al. (2021) · Pediatric Nephrology · doi:10.1007/s00467-020-04828-5 · Cited by 37
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Failure of renal biomarkers to predict worsening renal function in high-risk patients presenting with oliguria
Legrand, M. M., Jacquemod, A., Gayat, É., Collet, C., Giraudeaux, V., Launay, J., & Payen, D. M. (2014) · Intensive Care Medicine · doi:10.1007/s00134-014-3566-3 · Cited by 33
Biomarkers of acute kidney injury after pediatric cardiac surgery: a meta-analysis of diagnostic test accuracy
den Eynde, J. V., Schuermans, A., Verbakel, J. Y. J., Gewillig, M. H. M. L., Kutty, S., Allegaert, K., & Mekahli, D. (2022) · European Journal of Pediatrics · doi:10.1007/s00431-022-04380-4 · Cited by 35
Integration of the Renal Angina Index and Urine Neutrophil Gelatinase-Associated Lipocalin Improves Severe Acute Kidney Injury Prediction in Critically Ill Children and Young Adults
Goldstein, S. L., Krallman, K. A., Kirby, C. L., Roy, J., Collins, M., Fox, K., Schmerge, A., Wilder, S., Gerhardt, B., Chima, R. S., et al. (2022) · Kidney International Reports · doi:10.1016/j.ekir.2022.05.021 · Cited by 34
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Acute kidney injury in pediatric patients
Kwiatkowski, D. M., & Sutherland, S. M. (2017) · Best practice & research. Clinical anaesthesiology · doi:10.1016/j.bpa.2017.08.007 · Cited by 34
Derivation and Validation of an Optimal Neutrophil Gelatinase-Associated Lipocalin Cutoff to Predict Stage 2/3 Acute Kidney Injury (AKI) in Critically Ill Children
Goldstein, S. L., Akcan‐Arikan, A., Afonso, N. S., Askenazi, D. J., Basalely, A. M., Basu, R. K., Beng, H. M., Fitzgerald, J. C., Gist, K. M., Kizilbash, S. J., et al. (2024) · Kidney International Reports · doi:10.1016/j.ekir.2024.05.010 · Cited by 34
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Neonatal acute kidney injury risk stratification score: STARZ study
Wazir, S., Sethi, S. K., Agarwal, G., Tibrewal, A. O., Dhir, R., Bajaj, N., Gupta, N. P., Mirgunde, S., Sahoo, J. P., Balachandran, B., et al. (2021) · Pediatric Research · doi:10.1038/s41390-021-01573-9 · Cited by 31
Pediatric Acute Kidney Injury: Focusing on Diagnosis and Management
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Advances in pediatric acute kidney injury
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The role of sex and gender in acute kidney injury—consensus statements from the 33rd Acute Disease Quality Initiative
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Acute Kidney Injury in Real Time: Prediction, Alerts, and Clinical Decision Support
Wilson, F. P., & Greenberg, J. H. (2018) · The Nephron journals/Nephron journals · doi:10.1159/000492064 · Cited by 30
Renal Dysfunction Criteria in Critically Ill Children: The PODIUM Consensus Conference
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Biology of sepsis: Its relevance to pediatric nephrology
Blatt, N. B., Srinivasan, S., Mottes, T., Shanley, M. M., & Shanley, T. P. (2014) · Pediatric Nephrology · doi:10.1007/s00467-013-2677-3 · Cited by 29
Use of height-independent baseline creatinine imputation method with renal angina index
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Utilization of the renal angina index in PICU of a developing country for prediction of subsequent severe acute kidney injury
Kaur, R., Dhooria, G. S., Pooni, P. A., Bhat, D., Bhargava, S., Kakkar, S., Arora, K., & Bansal, N. (2018) · Pediatric Nephrology · doi:10.1007/s00467-018-4001-8 · Cited by 30
Prediction of Severe Acute Kidney Injury using Renal Angina Index in a Pediatric Intensive Care Unit
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Assessment of a modified renal angina index for AKI prediction in critically ill adults
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Evolution of Acute Kidney Injury and Its Association With Systemic Hemodynamics in Children With Fluid-Refractory Septic Shock
Deep, A., Sagar, H., Goonasekera, C. D. A., Karthikeyan, P., Brierley, J., & Douiri, A. (2018) · Critical Care Medicine · doi:10.1097/ccm.0000000000003156 · Cited by 27
Recalibration of the Renal Angina Index for Pediatric Septic Shock
Stanski, N. L., Wong, H. R., Basu, R. K., Cvijanovich, N. Z., Fitzgerald, J. C., Weiss, S. L., Bigham, M. T., Jain, P., Schwarz, A. J., Lutfi, R., et al. (2021) · Kidney International Reports · doi:10.1016/j.ekir.2021.04.022 · Cited by 29
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A proposed framework for advancing acute kidney injury risk stratification and diagnosis in children: a report from the 26th Acute Disease Quality Initiative (ADQI) conference
Fuhrman, D. Y., Stanski, N. L., Krawczeski, C. D., Greenberg, J. H., Akcan‐Arikan, A., Basu, R. K., Goldstein, S. L., Gist, K. M., workgroup, T. A. 2., Alobaidi, R., et al. (2023) · Pediatric Nephrology · doi:10.1007/s00467-023-06133-3 · Cited by 29
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Early Recognition of Persistent Acute Kidney Injury
Darmon, M., Truche, A., Abdel-Nabey, M., Schnell, D., & Souweine, B. (2019) · Seminars in Nephrology · doi:10.1016/j.semnephrol.2019.06.003 · Cited by 28
Artificial intelligence in early detection and prediction of pediatric/neonatal acute kidney injury: current status and future directions
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Automated/integrated real-time clinical decision support in acute kidney injury
Goldstein, S. L. (2015) · Current Opinion in Critical Care · doi:10.1097/mcc.0000000000000250 · Cited by 25
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Assessment of Worldwide Acute Kidney Injury, Renal Angina and Epidemiology in Critically Ill Children (AWARE): A Prospective Study to Improve Diagnostic Precision
Basu, R. K. (2015) · Journal of Clinical Trials · doi:10.4172/2167-0870.1000222 · Cited by 25
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Risk Factors for Acute Kidney Injury in Hospitalized Non–Critically Ill Patients: A Population-Based Study
Safadi, S., Hommos, M. S., Enders, F., Lieske, J. C., & KASHANI, K. B. (2020) · Mayo Clinic Proceedings · doi:10.1016/j.mayocp.2019.06.011 · Cited by 24
Diagnostic accuracy of renal angina index alone or in combination with biomarkers for predicting acute kidney injury in children
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Improving acute kidney injury diagnostic precision using biomarkers
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Validation of the STARZ neonatal acute kidney injury risk stratification score
Sethi, S. K., Raina, R., Rana, A., Agrawal, G. G., Tibrewal, A. O., Bajaj, N., Gupta, N. P., Mirgunde, S., Sahoo, J. P., Balachandran, B., et al. (2022) · Pediatric Nephrology · doi:10.1007/s00467-021-05369-1 · Cited by 23
Renal Dysfunction Criteria in Critically Ill Children: The PODIUM Consensus Conference
Fitzgerald, J. C., Basu, R. K., Fuhrman, D. Y., Gorga, S. M., Hassinger, A. B., Sanchez-Pinto, L. N., Selewski, D. T., Sutherland, S. M., & Akcan‐Arikan, A. (2022) · Zurich Open Repository and Archive (University of Zurich) · doi:10.5167/uzh-227092 · Cited by 23
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Early recognition and prevention of acute kidney injury in hospitalised children
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Clinical significance of urinary L-FABP in the emergency department
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The role of continuous renal replacement therapy in the management of acute kidney injury associated with sinusoidal obstruction syndrome following hematopoietic cell transplantation
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The complement system in pediatric acute kidney injury
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An update on the role of fluid overload in the prediction of outcome in acute kidney injury
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Acute Kidney Injury Electronic Alert for Nephrologist: Reactive versus Proactive?
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Risk of nonsteroidal anti-inflammatory drug-associated renal dysfunction among neonates diagnosed with patent ductus arteriosus and treated with gentamicin
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Identifying critically ill children at high risk of acute kidney injury and renal replacement therapy
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Validation of renal angina index to improve prediction of acute kidney injury in critically Ill children- A prospective observational cohort study
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Validation of Renal Angina Index (RAI) to improve the prediction of Acute Kidney Injury (AKI) in critically ill children admitted to paediatric intensive care unit (PICU)
Jakanattane, V., Sivakumar, E., Rajkumar, D., & Kulandaivel, M. (2017) · International Journal of Contemporary Pediatrics · doi:10.18203/2349-3291.ijcp20174749 · Cited by 3
Exploring the Renal Angina Index in Pediatric Intensive Care: Correlations and Clinical Outcomes
Agarwal, P., Maurya, D. R., Shukla, A., & Singh, A. (2026) · Annals of African Medicine · doi:10.4103/aam.aam_410_26
Renal angina index in critically ill children as an applicable and reliable tool in the prediction of severe acute kidney injury: Two tertiary centers’ prospective observational study from the Middle East
Soliman, A. S. A., Al-Ghamdi, H. S., Abukhatwah, M. W., Kamal, N. M., Dabour, S. A. Y., Elgendy, S. A., Alfaifi, J. A., Abukhatwah, O. M. W., Abosabie, S. A., Abosabie, S. A., et al. (2023) · Medicine · doi:10.1097/md.0000000000036713 · Cited by 11
Assessment of the renal angina index for the prediction of acute kidney injury in patients admitted to a European pediatric intensive care unit
Ribeiro‐Mourão, F., Vaz, A. D. C., Azevedo, A. C., Pinto, H., Silva, M. J., Jardim, J., & Ribeiro, A. (2021) · Pediatric Nephrology · doi:10.1007/s00467-021-05116-6 · Cited by 10

Authors: Basu, R. K., Zappitelli, M., Brunner, L., Wang, Y., Wong, H. R., Chawla, L. S., Wheeler, D. S., & Goldstein, S. L.
Affiliations: Cincinnati Children's Hospital Medical Center (US)
Montreal Children's Hospital (CA)
George Washington University (US)
Corresponding author: Basu, Rajit K.
ORCID: Basu, Rajit K.
Zappitelli, Michael
Wang, Yu
Wong, Hector R.
Chawla, Lakhmir S.
Wheeler, Derek S.
Goldstein, Stuart L.
Venue: Kidney International
Publisher: Elsevier BV
Published: 2014-03
Volume: 85
Issue: 3
Pages: 659-667
ISSN: 0085-2538 (ISSN-L)
DOI: 10.1038/ki.2013.349
PMC: PMC4659420
OpenAlex: W2007813089
Cited by: 297
References: 49
Citations by year: 2026: 22 · 2025: 34 · 2024: 21 · 2023: 28 · 2022: 31 · 2021: 27 · 2020: 18 · 2019: 22 · 2018: 28 · 2017: 15 · 2016: 21 · 2015: 16 · 2014: 12
FWCI: 12.63
Type: journal article
Language: en
Open access: bronze
doi.org
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/open-access/userlicense/1.0/ (vor, 1461 d)
Locations: Kidney International (publishedVersion)
PubMed (publishedVersion)
Europe PMC (PubMed Central) (acceptedVersion)
PubMed Central (acceptedVersion)
Funders: National Institutes of Health (5ul1rr026314-03, 5rc1hl100474-02, UL1TR000077)
National Heart, Lung, and Blood Institute (RC1-HL100474)
National Institute of General Medical Sciences (R01GM064619, R01GM108025, R01GM099773)
National Institute of Diabetes and Digestive and Kidney Diseases (P50DK096418)
National Center for Research Resources (UL1-RR026314, UL1RR02631401)
National Center for Advancing Translational Sciences
Topics: Health Sciences › Medicine › Nephrology › Acute Kidney Injury Research
Health Sciences › Medicine › Nephrology › Chronic Kidney Disease and Diabetes
Health Sciences › Medicine › Critical Care and Intensive Care Medicine › Sepsis Diagnosis and Treatment
Keywords: renal angina index, acute kidney injury, pediatric intensive care, critically ill children, AKI prediction, risk stratification, serum creatinine, KDIGO staging, kidney injury biomarkers, negative predictive value
MeSH terms: Child, Child, Preschool, Creatinine, Female, Humans, Infant, Male, Severity of Illness Index, Biomarkers, Critical Illness, Acute Kidney Injury

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

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