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Personalized screening intervals for kidney function in patients with chronic heart failure: a modeling study

BACKGROUND: High mortality and rehospitalization rates demonstrate that improving risk assessment in heart failure patients remains challenging. Individual temporal evolution of kidney biomarkers is associated with poor clinical outcome in these patients and hence may carry the potential to move tow...

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Autores principales: Schuurman, Anne-Sophie, Tomer, Anirudh, Akkerhuis, K. Martijn, Hoorn, Ewout J., Brugts, Jasper J., Manintveld, Olivier C., van Ramshorst, Jan, Umans, Victor A., Boersma, Eric, Rizopoulos, Dimitris, Kardys, Isabella
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8494722/
https://www.ncbi.nlm.nih.gov/pubmed/33738779
http://dx.doi.org/10.1007/s40620-021-01014-0
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author Schuurman, Anne-Sophie
Tomer, Anirudh
Akkerhuis, K. Martijn
Hoorn, Ewout J.
Brugts, Jasper J.
Manintveld, Olivier C.
van Ramshorst, Jan
Umans, Victor A.
Boersma, Eric
Rizopoulos, Dimitris
Kardys, Isabella
author_facet Schuurman, Anne-Sophie
Tomer, Anirudh
Akkerhuis, K. Martijn
Hoorn, Ewout J.
Brugts, Jasper J.
Manintveld, Olivier C.
van Ramshorst, Jan
Umans, Victor A.
Boersma, Eric
Rizopoulos, Dimitris
Kardys, Isabella
author_sort Schuurman, Anne-Sophie
collection PubMed
description BACKGROUND: High mortality and rehospitalization rates demonstrate that improving risk assessment in heart failure patients remains challenging. Individual temporal evolution of kidney biomarkers is associated with poor clinical outcome in these patients and hence may carry the potential to move towards a personalized screening approach. METHODS: In 263 chronic heart failure patients included in the prospective Bio-SHiFT cohort study, glomerular and tubular biomarker measurements were serially obtained according to a pre-scheduled, fixed trimonthly scheme. The primary endpoint (PE) comprised cardiac death, cardiac transplantation, left ventricular assist device implantation or heart failure hospitalization. Personalized scheduling of glomerular and tubular biomarker measurements was compared to fixed scheduling in individual patients by means of a simulation study, based on clinical characteristics of the Bio-SHiFT study. For this purpose, repeated biomarker measurements and the PE were jointly modeled. For personalized scheduling, using this fitted joint model, we determined the optimal time point of the next measurement based on the patient’s individual risk profile as estimated by the joint model and the maximum information gain on the patient’s prognosis. We compared the schedule’s capability of enabling timely intervention before the occurrence of the PE and number of measurements needed. RESULTS: As compared to a pre-defined trimonthly scheduling approach, personalized scheduling of glomerular and tubular biomarker measurements showed similar performance with regard to prognostication, but required a median of 0.4–2.7 fewer measurements per year. CONCLUSION: Personalized scheduling is expected to reduce the number of patient visits and healthcare costs. Thus, it may contribute to efficient monitoring of chronic heart failure patients and could provide novel opportunities for timely adaptation of treatment. GRAPHIC ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40620-021-01014-0.
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spelling pubmed-84947222021-10-19 Personalized screening intervals for kidney function in patients with chronic heart failure: a modeling study Schuurman, Anne-Sophie Tomer, Anirudh Akkerhuis, K. Martijn Hoorn, Ewout J. Brugts, Jasper J. Manintveld, Olivier C. van Ramshorst, Jan Umans, Victor A. Boersma, Eric Rizopoulos, Dimitris Kardys, Isabella J Nephrol Technical Note BACKGROUND: High mortality and rehospitalization rates demonstrate that improving risk assessment in heart failure patients remains challenging. Individual temporal evolution of kidney biomarkers is associated with poor clinical outcome in these patients and hence may carry the potential to move towards a personalized screening approach. METHODS: In 263 chronic heart failure patients included in the prospective Bio-SHiFT cohort study, glomerular and tubular biomarker measurements were serially obtained according to a pre-scheduled, fixed trimonthly scheme. The primary endpoint (PE) comprised cardiac death, cardiac transplantation, left ventricular assist device implantation or heart failure hospitalization. Personalized scheduling of glomerular and tubular biomarker measurements was compared to fixed scheduling in individual patients by means of a simulation study, based on clinical characteristics of the Bio-SHiFT study. For this purpose, repeated biomarker measurements and the PE were jointly modeled. For personalized scheduling, using this fitted joint model, we determined the optimal time point of the next measurement based on the patient’s individual risk profile as estimated by the joint model and the maximum information gain on the patient’s prognosis. We compared the schedule’s capability of enabling timely intervention before the occurrence of the PE and number of measurements needed. RESULTS: As compared to a pre-defined trimonthly scheduling approach, personalized scheduling of glomerular and tubular biomarker measurements showed similar performance with regard to prognostication, but required a median of 0.4–2.7 fewer measurements per year. CONCLUSION: Personalized scheduling is expected to reduce the number of patient visits and healthcare costs. Thus, it may contribute to efficient monitoring of chronic heart failure patients and could provide novel opportunities for timely adaptation of treatment. GRAPHIC ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40620-021-01014-0. Springer International Publishing 2021-03-18 2021 /pmc/articles/PMC8494722/ /pubmed/33738779 http://dx.doi.org/10.1007/s40620-021-01014-0 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Technical Note
Schuurman, Anne-Sophie
Tomer, Anirudh
Akkerhuis, K. Martijn
Hoorn, Ewout J.
Brugts, Jasper J.
Manintveld, Olivier C.
van Ramshorst, Jan
Umans, Victor A.
Boersma, Eric
Rizopoulos, Dimitris
Kardys, Isabella
Personalized screening intervals for kidney function in patients with chronic heart failure: a modeling study
title Personalized screening intervals for kidney function in patients with chronic heart failure: a modeling study
title_full Personalized screening intervals for kidney function in patients with chronic heart failure: a modeling study
title_fullStr Personalized screening intervals for kidney function in patients with chronic heart failure: a modeling study
title_full_unstemmed Personalized screening intervals for kidney function in patients with chronic heart failure: a modeling study
title_short Personalized screening intervals for kidney function in patients with chronic heart failure: a modeling study
title_sort personalized screening intervals for kidney function in patients with chronic heart failure: a modeling study
topic Technical Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8494722/
https://www.ncbi.nlm.nih.gov/pubmed/33738779
http://dx.doi.org/10.1007/s40620-021-01014-0
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