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Reidy KJ, Guillet R, Selewski DT, Defreitas M, Stone S, Starr MC, Harer MW, Todurkar N, Vuong KT, Gogcu S, Askenazi D, Tipple TE, Charlton JR. Advocating for the inclusion of kidney health outcomes in neonatal research: best practice recommendations by the Neonatal Kidney Collaborative. J Perinatol 2024:10.1038/s41372-024-02030-1. [PMID: 38969825 DOI: 10.1038/s41372-024-02030-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/15/2024] [Revised: 05/21/2024] [Accepted: 06/06/2024] [Indexed: 07/07/2024]
Abstract
Acute kidney injury (AKI) occurs in nearly 30% of sick neonates. Chronic kidney disease (CKD) can be detected in certain populations of sick neonates as early as 2 years. AKI is often part of a multisystem syndrome that negatively impacts developing organs resulting in short- and long-term pulmonary, neurodevelopmental, and cardiovascular morbidities. It is critical to incorporate kidney-related data into neonatal clinical trials in a uniform manner to better understand how neonatal AKI or CKD could affect an outcome of interest. Here, we provide expert opinion recommendations and rationales to support the inclusion of short- and long-term neonatal kidney outcomes using a tiered approach based on study design: (1) observational studies (prospective or retrospective) limited to data available within a center's standard practice, (2) observational studies involving prospective data collection where prespecified kidney outcomes are included in the design, (3) interventional studies with non-nephrotoxic agents, and (4) interventional studies with known nephrotoxic agents. We also provide recommendations for biospecimen collection to facilitate ancillary kidney specific research initiatives. This approach balances the costs of AKI and CKD ascertainment with knowledge gained. We advocate that kidney outcomes be included routinely in neonatal clinical study design. Consistent incorporation of kidney outcomes across studies will increase our knowledge of neonatal morbidity.
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Affiliation(s)
- Kimberly J Reidy
- Division of Nephrology, Department of Pediatrics, Children's Hospital at Montefiore/Albert Einstein College of Medicine, Bronx, NY, 10467, USA
| | - Ronnie Guillet
- Division of Neonatology, Golisano Children's Hospital, University of Rochester, Rochester, NY, USA
| | - David T Selewski
- Division of Nephrology, Department of Pediatrics, Medical University of South Carolina, Charleston, SC, USA
| | - Marissa Defreitas
- Division of Nephrology, Department of Pediatrics, University of Miami/Holtz Children's Hospital, Miami, FL, USA
| | - Sadie Stone
- Department of Pharmacy, Children's of Alabama, Birmingham, AL, UK
| | - Michelle C Starr
- Division of Pediatric Nephrology, Division of Child Health Service Research, Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Matthew W Harer
- Division of Neonatology, Department of Pediatrics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Namrata Todurkar
- Division of Neonatal Perinatal Medicine, Department of Pediatrics, University of British Columbia, Vancouver, BC, Canada
| | - Kim T Vuong
- Division of Pediatric Nephrology, Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
| | - Semsa Gogcu
- Section of Neonatal-Perinatal Medicine, Department of Pediatrics, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - David Askenazi
- Division of Nephrology, Department of Pediatrics, University of Alabama at Birmingham, Birmingham, AL, UK
| | - Trent E Tipple
- Section of Neonatal-Perinatal Medicine, Department of Pediatrics, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Jennifer R Charlton
- Division of Nephrology, Department of Pediatrics, University of Virginia, Box 800386, Charlottesville, VA, 22903, USA.
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Klaus R, Barth TK, Imhof A, Thalmeier F, Lange-Sperandio B. Comparison of clean catch and bag urine using LC-MS/MS proteomics in infants. Pediatr Nephrol 2024; 39:203-212. [PMID: 37523035 PMCID: PMC10673958 DOI: 10.1007/s00467-023-06098-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Revised: 07/12/2023] [Accepted: 07/12/2023] [Indexed: 08/01/2023]
Abstract
BACKGROUND Urinary proteomics identifies the totality of urinary proteins and can therefore help in getting an early and precise diagnosis of various pathological processes in the kidneys. In infants, non-invasive urine collection is most commonly accomplished with a urine bag or clean catch. The influence of those two collection methods on urinary proteomics was assessed in this study. METHODS Thirty-two urine samples were collected in infants using urine bag and clean catch within 24 h. Nine boys and seven girls with a mean age of 4.3 ± 2.9 months were included (5 × post-pyelonephritis, 10 × non-kidney disease, 1 × chronic kidney disease (CKD)). Liquid chromatography-mass spectrometry (LC-MS/MS) was performed in data-independent acquisition (DIA) mode. Protein identification and quantification were achieved using Spectronaut. RESULTS A total of 1454 urinary proteins were detected. Albumin and α-1-microglobulin were detected the most. The 18 top-abundant proteins accounted for 50% of total abundance. The number of proteins was slightly, but insignificantly higher in clean catch (957 ± 245) than in bag urine (876 ± 255). The median intensity was 1.2 × higher in the clean catch. Overall, differential detection of proteins was 29% between the collection methods; however, it diminished to 3% in the 96 top-abundant proteins. Pearson's correlation coefficient was 0.81 ± 0.11, demonstrating a high intraindividual correlation. A principal component analysis and a heat map showed clustering according to diagnoses and patients rather than to the collection method. CONCLUSION Urinary proteomics shows a high correlation with minor variation in low-abundant proteins between the two urine collection methods. The biological characteristics overrule this variation. Graphical abstract A higher resolution version of the Graphical abstract is available as Supplementary information.
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Affiliation(s)
- Richard Klaus
- Division of Pediatric Nephrology, Department of Pediatrics, Dr. V. Hauner Children's Hospital, Ludwig-Maximilians University, Lindwurmstraße 4, 80337, Munich, Germany
| | - Teresa K Barth
- Faculty of Medicine, Biomedical Center, Protein Analysis Unit, Ludwig-Maximilians University, Planegg-Martinsried, Munich, Germany
| | - Axel Imhof
- Faculty of Medicine, Biomedical Center, Protein Analysis Unit, Ludwig-Maximilians University, Planegg-Martinsried, Munich, Germany
| | - Franziska Thalmeier
- Division of Pediatric Nephrology, Department of Pediatrics, Dr. V. Hauner Children's Hospital, Ludwig-Maximilians University, Lindwurmstraße 4, 80337, Munich, Germany
| | - Bärbel Lange-Sperandio
- Division of Pediatric Nephrology, Department of Pediatrics, Dr. V. Hauner Children's Hospital, Ludwig-Maximilians University, Lindwurmstraße 4, 80337, Munich, Germany.
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Downes KJ, Zuppa AF, Sharova A, Neely MN. Optimizing Vancomycin Therapy in Critically Ill Children: A Population Pharmacokinetics Study to Inform Vancomycin Area under the Curve Estimation Using Novel Biomarkers. Pharmaceutics 2023; 15:1336. [PMID: 37242578 PMCID: PMC10220925 DOI: 10.3390/pharmaceutics15051336] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 04/20/2023] [Accepted: 04/21/2023] [Indexed: 05/28/2023] Open
Abstract
Area under the curve (AUC)-directed vancomycin therapy is recommended, but Bayesian AUC estimation in critically ill children is difficult due to inadequate methods for estimating kidney function. We prospectively enrolled 50 critically ill children receiving IV vancomycin for suspected infection and divided them into model training (n = 30) and testing (n = 20) groups. We performed nonparametric population PK modeling in the training group using Pmetrics, evaluating novel urinary and plasma kidney biomarkers as covariates on vancomycin clearance. In this group, a two-compartment model best described the data. During covariate testing, cystatin C-based estimated glomerular filtration rate (eGFR) and urinary neutrophil gelatinase-associated lipocalin (NGAL; full model) improved model likelihood when included as covariates on clearance. We then used multiple-model optimization to define the optimal sampling times to estimate AUC24 for each subject in the model testing group and compared the Bayesian posterior AUC24 to AUC24 calculated using noncompartmental analysis from all measured concentrations for each subject. Our full model provided accurate and precise estimates of vancomycin AUC (bias 2.3%, imprecision 6.2%). However, AUC prediction was similar when using reduced models with only cystatin C-based eGFR (bias 1.8%, imprecision 7.0%) or creatinine-based eGFR (bias -2.4%, imprecision 6.2%) as covariates on clearance. All three model(s) facilitated accurate and precise estimation of vancomycin AUC in critically ill children.
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Affiliation(s)
- Kevin J. Downes
- The Center for Clinical Pharmacology, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Clinical Futures, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Division of Infectious Diseases, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Athena F. Zuppa
- The Center for Clinical Pharmacology, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Anna Sharova
- The Center for Clinical Pharmacology, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Clinical Futures, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Michael N. Neely
- Children’s Hospital Los Angeles, Los Angeles, CA 90027, USA
- Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
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Hari Gopal S, Garcia-Prats JA, Fernandes CJ. Cotton Balls for Urine Sample Collection-Is Negative Bias Truly Negative? J Pediatr 2023; 255:259. [PMID: 36402432 DOI: 10.1016/j.jpeds.2022.10.040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Accepted: 10/27/2022] [Indexed: 11/18/2022]
Affiliation(s)
- Srirupa Hari Gopal
- Section of Neonatology Department of Pediatrics Baylor College of Medicine Houston, TX
| | - Joseph A Garcia-Prats
- Section of Neonatology Department of Pediatrics Baylor College of Medicine Houston, TX
| | - Caraciolo J Fernandes
- Section of Neonatology Department of Pediatrics Baylor College of Medicine Houston, TX
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