Christian Albert1, Antonia Zapf2, Michael Haase3, Christian Röver4, John W Pickering5, Annemarie Albert6, Rinaldo Bellomo7, Tobias Breidthardt8, Fabrice Camou9, Zhongquing Chen10, Sidney Chocron11, Dinna Cruz12, Hilde R H de Geus13, Prasad Devarajan14, Salvatore Di Somma15, Kent Doi16, Zoltan H Endre17, Mercedes Garcia-Alvarez18, Peter B Hjortrup19, Mina Hur20, Georgios Karaolanis21, Cemil Kavalci22, Hanah Kim20, Paolo Lentini23, Christoph Liebetrau24, Miklós Lipcsey25, Johan Mårtensson26, Christian Müller8, Serafim Nanas27, Thomas L Nickolas28, Chrysoula Pipili27, Claudio Ronco29, Guillermo J Rosa-Diez30, Azrina Ralib31, Karina Soto32, Rüdiger C Braun-Dullaeus33, Judith Heinz4, Anja Haase-Fielitz34. 1. University Clinic for Cardiology and Angiology, Medical Faculty, Otto-von-Guericke University, Magdeburg, Germany; Diaverum Renal Services Germany, Potsdam, Germany. Electronic address: christian.albert@diaverum.com. 2. Department of Medical Biometry and Epidemiology, University Medical Center Hamburg-Eppendorf, Hamburg-Eppendorf, Germany. 3. Faculty of Medicine, Otto-von-Guericke University, Magdeburg, Germany; Diaverum Renal Services Germany, Potsdam, Germany. 4. Department of Medical Statistics, University Medical Center Göttingen, Göttingen, Germany. 5. Department of Medicine, University of Otago Christchurch; Emergency Department, Christchurch Hospital, Christchurch, New Zealand. 6. Diaverum Renal Services Germany, Potsdam, Germany; Department for Nephrology and Endocrinology, Klinikum Ernst von Bergmann, Potsdam, Germany. 7. Department of Intensive Care, The Austin Hospital, Melbourne, Australia; Centre for Integrated Critical Care, The University of Melbourne, Melbourne, Australia. 8. Department of Internal Medicine, University Hospital Basel, Basel, Switzerland; Department of Nephrology, University Hospital Basel, Basel, Switzerland; Department of Cardiology, University Hospital Basel, Basel, Switzerland. 9. Service de réanimation médicale, hôpital Saint-André, CHU de Bordeaux, France. 10. Department of Critical Care Medicine, Nanfang Hospital, Southern Medical University, Guangdong, China. 11. Department of Thoracic and Cardio-Vascular Surgery, University Hospital Jean Minjoz, Besançon, France. 12. Division of Nephrology-Hypertension, University of California, San Diego, CA. 13. Department of Intensive Care, Erasmus University Medical Center, Rotterdam, the Netherlands. 14. Division of Nephrology and Hypertension, Cincinnati Children's Hospital, University of Cincinnati, Cincinnati, OH. 15. Emergency Medicine, Department of Medical-Surgery Sciences and Translational Medicine, Sapienza' University of Rome S. Andrea Hospital, Rome, Italy. 16. Department of Emergency and Critical Care Medicine, The University of Tokyo, Tokyo, Japan. 17. Department of Nephrology, Prince of Wales Hospital and Clinical School, University of New South Wales, Sydney, Australia. 18. Department of Anesthesiology, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain. 19. Department of Intensive Care, Copenhagen University Hospital, Copenhagen, Denmark. 20. Department of Laboratory Medicine, Konkuk University School of Medicine, Seoul, Republic of Korea. 21. Vascular Unit, First Department of Surgery, "Laiko" General Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece. 22. Emergency Department, Baskent University Faculty of Medicine, Ankara, Turkey. 23. Department of Nephrology and Dialysis, San Bassiano Hospital, Bassano del Grappa, Italy. 24. Department of Cardiology, Kerckhoff Clinic, Bad Nauheim, Germany. 25. CIRRUS, Hedenstierna laboratory, Anaesthesiology and Intensive care, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden. 26. Section of Anaesthesia and Intensive Care Medicine, Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden. 27. First Critical Care Department, 'Evangelismos' General Hospital, National and Kapodistrian University of Athens, Athens, Greece. 28. Columbia University Vagelos College of Physicians and Surgeons, New York, NY. 29. Department of Nephrology, Dialysis & Transplantation, University of Padova, Vicenza, Italy; International Renal Research Institute, San Bortolo Hospital, Vicenza, Italy. 30. Department of Nephrology, Dialysis and Transplantation, Hospital Italiano de Buenos Aires, Buenos Aires, Argentina. 31. Department of Anaesthesiology and Intensive Care, International Islamic University Malaysia, Pahang, Malaysia. 32. Department of Nephrology, Hospital Fernando Fonseca, Lisbon, Portugal; CEAUL, Centro de Estatística e Aplicações da Universidade de Lisboa, Lisbon, Portugal. 33. University Clinic for Cardiology and Angiology, Medical Faculty, Otto-von-Guericke University, Magdeburg, Germany. 34. Department of Cardiology, Immanuel Diakonie Bernau, Heart Center Brandenburg, Brandenburg Medical School Theodor Fontane, Faculty of Health Sciences, University of Potsdam, Potsdam, Germany.
Abstract
RATIONALE & OBJECTIVE: The usefulness of measures of neutrophil gelatinase-associated lipocalin (NGAL) in urine or plasma obtained on clinical laboratory platforms for predicting acute kidney injury (AKI) and AKI requiring dialysis (AKI-D) has not been fully evaluated. We sought to quantitatively summarize published data to evaluate the value of urinary and plasma NGAL for kidney risk prediction. STUDY DESIGN: Literature-based meta-analysis and individual-study-data meta-analysis of diagnostic studies following PRISMA-IPD guidelines. SETTING & STUDY POPULATIONS: Studies of adults investigating AKI, severe AKI, and AKI-D in the setting of cardiac surgery, intensive care, or emergency department care using either urinary or plasma NGAL measured on clinical laboratory platforms. SELECTION CRITERIA FOR STUDIES: PubMed, Web of Science, Cochrane Library, Scopus, and congress abstracts ever published through February 2020 reporting diagnostic test studies of NGAL measured on clinical laboratory platforms to predict AKI. DATA EXTRACTION: Individual-study-data meta-analysis was accomplished by giving authors data specifications tailored to their studies and requesting standardized patient-level data analysis. ANALYTICAL APPROACH: Individual-study-data meta-analysis used a bivariate time-to-event model for interval-censored data from which discriminative ability (AUC) was characterized. NGAL cutoff concentrations at 95% sensitivity, 95% specificity, and optimal sensitivity and specificity were also estimated. Models incorporated as confounders the clinical setting and use versus nonuse of urine output as a criterion for AKI. A literature-based meta-analysis was also performed for all published studies including those for which the authors were unable to provide individual-study data analyses. RESULTS: We included 52 observational studies involving 13,040 patients. We analyzed 30 data sets for the individual-study-data meta-analysis. For AKI, severe AKI, and AKI-D, numbers of events were 837, 304, and 103 for analyses of urinary NGAL, respectively; these values were 705, 271, and 178 for analyses of plasma NGAL. Discriminative performance was similar in both meta-analyses. Individual-study-data meta-analysis AUCs for urinary NGAL were 0.75 (95% CI, 0.73-0.76) and 0.80 (95% CI, 0.79-0.81) for severe AKI and AKI-D, respectively; for plasma NGAL, the corresponding AUCs were 0.80 (95% CI, 0.79-0.81) and 0.86 (95% CI, 0.84-0.86). Cutoff concentrations at 95% specificity for urinary NGAL were>580ng/mL with 27% sensitivity for severe AKI and>589ng/mL with 24% sensitivity for AKI-D. Corresponding cutoffs for plasma NGAL were>364ng/mL with 44% sensitivity and>546ng/mL with 26% sensitivity, respectively. LIMITATIONS: Practice variability in initiation of dialysis. Imperfect harmonization of data across studies. CONCLUSIONS: Urinary and plasma NGAL concentrations may identify patients at high risk for AKI in clinical research and practice. The cutoff concentrations reported in this study require prospective evaluation.
RATIONALE & OBJECTIVE: The usefulness of measures of neutrophil gelatinase-associated lipocalin (NGAL) in urine or plasma obtained on clinical laboratory platforms for predicting acute kidney injury (AKI) and AKI requiring dialysis (AKI-D) has not been fully evaluated. We sought to quantitatively summarize published data to evaluate the value of urinary and plasma NGAL for kidney risk prediction. STUDY DESIGN: Literature-based meta-analysis and individual-study-data meta-analysis of diagnostic studies following PRISMA-IPD guidelines. SETTING & STUDY POPULATIONS: Studies of adults investigating AKI, severe AKI, and AKI-D in the setting of cardiac surgery, intensive care, or emergency department care using either urinary or plasma NGAL measured on clinical laboratory platforms. SELECTION CRITERIA FOR STUDIES: PubMed, Web of Science, Cochrane Library, Scopus, and congress abstracts ever published through February 2020 reporting diagnostic test studies of NGAL measured on clinical laboratory platforms to predict AKI. DATA EXTRACTION: Individual-study-data meta-analysis was accomplished by giving authors data specifications tailored to their studies and requesting standardized patient-level data analysis. ANALYTICAL APPROACH: Individual-study-data meta-analysis used a bivariate time-to-event model for interval-censored data from which discriminative ability (AUC) was characterized. NGAL cutoff concentrations at 95% sensitivity, 95% specificity, and optimal sensitivity and specificity were also estimated. Models incorporated as confounders the clinical setting and use versus nonuse of urine output as a criterion for AKI. A literature-based meta-analysis was also performed for all published studies including those for which the authors were unable to provide individual-study data analyses. RESULTS: We included 52 observational studies involving 13,040 patients. We analyzed 30 data sets for the individual-study-data meta-analysis. For AKI, severe AKI, and AKI-D, numbers of events were 837, 304, and 103 for analyses of urinary NGAL, respectively; these values were 705, 271, and 178 for analyses of plasma NGAL. Discriminative performance was similar in both meta-analyses. Individual-study-data meta-analysis AUCs for urinary NGAL were 0.75 (95% CI, 0.73-0.76) and 0.80 (95% CI, 0.79-0.81) for severe AKI and AKI-D, respectively; for plasma NGAL, the corresponding AUCs were 0.80 (95% CI, 0.79-0.81) and 0.86 (95% CI, 0.84-0.86). Cutoff concentrations at 95% specificity for urinary NGAL were>580ng/mL with 27% sensitivity for severe AKI and>589ng/mL with 24% sensitivity for AKI-D. Corresponding cutoffs for plasma NGAL were>364ng/mL with 44% sensitivity and>546ng/mL with 26% sensitivity, respectively. LIMITATIONS: Practice variability in initiation of dialysis. Imperfect harmonization of data across studies. CONCLUSIONS: Urinary and plasma NGAL concentrations may identify patients at high risk for AKI in clinical research and practice. The cutoff concentrations reported in this study require prospective evaluation.
Authors: Andrew S Allegretti; Xavier Vela Parada; Paul Endres; Sophia Zhao; Scott Krinsky; Shelsea A St Hillien; Sahir Kalim; Sagar U Nigwekar; James G Flood; Andrea Nixon; Douglas A Simonetto; Luis A Juncos; Nithin Karakala; Hani M Wadei; Kevin R Regner; Justin M Belcher; Mitra K Nadim; Guadalupe Garcia-Tsao; Juan Carlos Q Velez; Samir M Parikh; Raymond T Chung Journal: Clin Transl Gastroenterol Date: 2021-05-11 Impact factor: 4.396
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