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Avoiding insufficient therapies and overdosing with co-reporting eGFRs (estimated glomerular filtration rate) for personalized drug therapy and improved outcomes – a simulation of the financial benefits

Patients with impaired renal function are at high risk for morbidity and mortality. Chronic kidney disease (CKD) even in the early stages can be associated with significant side effects of drug therapy, longer length of stay, and high costs. Correct assessment of renal function in the hospital is im...

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Autores principales: Hoenle, Adrian, Haase, Karin Johanna, Maus, Sebastian, Hofmann, Manfred, Orth, Matthias
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Communications and Publications Division (CPD) of the IFCC 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7941064/
https://www.ncbi.nlm.nih.gov/pubmed/33753973
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author Hoenle, Adrian
Haase, Karin Johanna
Maus, Sebastian
Hofmann, Manfred
Orth, Matthias
author_facet Hoenle, Adrian
Haase, Karin Johanna
Maus, Sebastian
Hofmann, Manfred
Orth, Matthias
author_sort Hoenle, Adrian
collection PubMed
description Patients with impaired renal function are at high risk for morbidity and mortality. Chronic kidney disease (CKD) even in the early stages can be associated with significant side effects of drug therapy, longer length of stay, and high costs. Correct assessment of renal function in the hospital is important to detect CKD, to avoid further damage to the kidneys, and to optimize pharmacological therapy. Current protocols for renal function testing in drug dosing are only creatinine based, are not robust enough, and can wrongly classify certain patients. Goal of our simulation study is to optimize noninvasive renal function estimates and to allow for optimal dosing of pharmacological treatment without further renal damage. Co-reporting of creatinine- and of cystatin C-derived estimated glomerular filtration rates (eGFR) allows a personalized approach for patients with large discrepancies in eGFR and it enabled us in detecting patients at high risk for side effects due to incorrect drug dosing. This approach might be highly effective for patients as well as for clinicians. In addition, we simulated the efficiency by estimating savings for the hospital administration and the payor with a benefit cost ratio of 58 to 1.
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spelling pubmed-79410642021-03-21 Avoiding insufficient therapies and overdosing with co-reporting eGFRs (estimated glomerular filtration rate) for personalized drug therapy and improved outcomes – a simulation of the financial benefits Hoenle, Adrian Haase, Karin Johanna Maus, Sebastian Hofmann, Manfred Orth, Matthias EJIFCC Research Article Patients with impaired renal function are at high risk for morbidity and mortality. Chronic kidney disease (CKD) even in the early stages can be associated with significant side effects of drug therapy, longer length of stay, and high costs. Correct assessment of renal function in the hospital is important to detect CKD, to avoid further damage to the kidneys, and to optimize pharmacological therapy. Current protocols for renal function testing in drug dosing are only creatinine based, are not robust enough, and can wrongly classify certain patients. Goal of our simulation study is to optimize noninvasive renal function estimates and to allow for optimal dosing of pharmacological treatment without further renal damage. Co-reporting of creatinine- and of cystatin C-derived estimated glomerular filtration rates (eGFR) allows a personalized approach for patients with large discrepancies in eGFR and it enabled us in detecting patients at high risk for side effects due to incorrect drug dosing. This approach might be highly effective for patients as well as for clinicians. In addition, we simulated the efficiency by estimating savings for the hospital administration and the payor with a benefit cost ratio of 58 to 1. The Communications and Publications Division (CPD) of the IFCC 2021-02-28 /pmc/articles/PMC7941064/ /pubmed/33753973 Text en Copyright © 2021 International Federation of Clinical Chemistry and Laboratory Medicine (IFCC). All rights reserved. http://creativecommons.org/licenses/by-nc/4.0/ This is a Platinum Open Access Journal distributed under the terms of the Creative Commons Attribution Non-Commercial License which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Hoenle, Adrian
Haase, Karin Johanna
Maus, Sebastian
Hofmann, Manfred
Orth, Matthias
Avoiding insufficient therapies and overdosing with co-reporting eGFRs (estimated glomerular filtration rate) for personalized drug therapy and improved outcomes – a simulation of the financial benefits
title Avoiding insufficient therapies and overdosing with co-reporting eGFRs (estimated glomerular filtration rate) for personalized drug therapy and improved outcomes – a simulation of the financial benefits
title_full Avoiding insufficient therapies and overdosing with co-reporting eGFRs (estimated glomerular filtration rate) for personalized drug therapy and improved outcomes – a simulation of the financial benefits
title_fullStr Avoiding insufficient therapies and overdosing with co-reporting eGFRs (estimated glomerular filtration rate) for personalized drug therapy and improved outcomes – a simulation of the financial benefits
title_full_unstemmed Avoiding insufficient therapies and overdosing with co-reporting eGFRs (estimated glomerular filtration rate) for personalized drug therapy and improved outcomes – a simulation of the financial benefits
title_short Avoiding insufficient therapies and overdosing with co-reporting eGFRs (estimated glomerular filtration rate) for personalized drug therapy and improved outcomes – a simulation of the financial benefits
title_sort avoiding insufficient therapies and overdosing with co-reporting egfrs (estimated glomerular filtration rate) for personalized drug therapy and improved outcomes – a simulation of the financial benefits
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7941064/
https://www.ncbi.nlm.nih.gov/pubmed/33753973
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