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Using CUSUM in real time to signal clinically relevant decreases in estimated glomerular filtration rate

BACKGROUND: The electronic health record (EHR), utilized to apply statistical methodology, assists provider decision-making, including during the care of chronic kidney disease (CKD) patients. When estimated glomerular filtration (eGFR) decreases, the rate of that change adds meaning to a patient’s...

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Autores principales: Zafarnejad, Reyhaneh, Dumbauld, Steven, Dumbauld, Diane, Adibuzzaman, Mohammad, Griffin, Paul, Rutsky, Edwin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9389810/
https://www.ncbi.nlm.nih.gov/pubmed/35982411
http://dx.doi.org/10.1186/s12882-022-02910-8
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author Zafarnejad, Reyhaneh
Dumbauld, Steven
Dumbauld, Diane
Adibuzzaman, Mohammad
Griffin, Paul
Rutsky, Edwin
author_facet Zafarnejad, Reyhaneh
Dumbauld, Steven
Dumbauld, Diane
Adibuzzaman, Mohammad
Griffin, Paul
Rutsky, Edwin
author_sort Zafarnejad, Reyhaneh
collection PubMed
description BACKGROUND: The electronic health record (EHR), utilized to apply statistical methodology, assists provider decision-making, including during the care of chronic kidney disease (CKD) patients. When estimated glomerular filtration (eGFR) decreases, the rate of that change adds meaning to a patient’s single eGFR and may represent severity of renal injury. Since the cumulative sum chart technique (CUSUM), often used in quality control and surveillance, continuously checks for change in a series of measurements, we selected this statistical tool to detect clinically relevant eGFR decreases and developed CUSUM(GFR). METHODS: In a retrospective analysis we applied an age adjusted CUSUM(GFR), to signal identification of eventual ESKD patients prior to diagnosis date. When the patient signaled by reaching a specified threshold value, days from CUSUM signal date to ESKD diagnosis date (earliness days) were measured, along with the corresponding eGFR measurement at the signal. RESULTS: Signaling occurred by CUSUM(GFR) on average 791 days (se = 12 days) prior to ESKD diagnosis date with sensitivity = 0.897, specificity = 0.877, and accuracy = .878. Mean days prior to ESKD diagnosis were significantly greater in Black patients (905 days) and patients with hypertension (852 days), diabetes (940 days), cardiovascular disease (1027 days), and hypercholesterolemia (971 days). Sensitivity and specificity did not vary by sociodemographic and clinical risk factors. CONCLUSIONS: CUSUM(GFR) correctly identified 30.6% of CKD patients destined for ESKD when eGFR was > 60 ml/min/1.73 m(2) and signaled 12.3% of patients that did not go on to ESKD (though almost all went on to later-stage CKD). If utilized in an EHR, signaling patients could focus providers’ efforts to slow or prevent progression to later stage CKD and ESKD. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12882-022-02910-8.
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spelling pubmed-93898102022-08-20 Using CUSUM in real time to signal clinically relevant decreases in estimated glomerular filtration rate Zafarnejad, Reyhaneh Dumbauld, Steven Dumbauld, Diane Adibuzzaman, Mohammad Griffin, Paul Rutsky, Edwin BMC Nephrol Research BACKGROUND: The electronic health record (EHR), utilized to apply statistical methodology, assists provider decision-making, including during the care of chronic kidney disease (CKD) patients. When estimated glomerular filtration (eGFR) decreases, the rate of that change adds meaning to a patient’s single eGFR and may represent severity of renal injury. Since the cumulative sum chart technique (CUSUM), often used in quality control and surveillance, continuously checks for change in a series of measurements, we selected this statistical tool to detect clinically relevant eGFR decreases and developed CUSUM(GFR). METHODS: In a retrospective analysis we applied an age adjusted CUSUM(GFR), to signal identification of eventual ESKD patients prior to diagnosis date. When the patient signaled by reaching a specified threshold value, days from CUSUM signal date to ESKD diagnosis date (earliness days) were measured, along with the corresponding eGFR measurement at the signal. RESULTS: Signaling occurred by CUSUM(GFR) on average 791 days (se = 12 days) prior to ESKD diagnosis date with sensitivity = 0.897, specificity = 0.877, and accuracy = .878. Mean days prior to ESKD diagnosis were significantly greater in Black patients (905 days) and patients with hypertension (852 days), diabetes (940 days), cardiovascular disease (1027 days), and hypercholesterolemia (971 days). Sensitivity and specificity did not vary by sociodemographic and clinical risk factors. CONCLUSIONS: CUSUM(GFR) correctly identified 30.6% of CKD patients destined for ESKD when eGFR was > 60 ml/min/1.73 m(2) and signaled 12.3% of patients that did not go on to ESKD (though almost all went on to later-stage CKD). If utilized in an EHR, signaling patients could focus providers’ efforts to slow or prevent progression to later stage CKD and ESKD. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12882-022-02910-8. BioMed Central 2022-08-18 /pmc/articles/PMC9389810/ /pubmed/35982411 http://dx.doi.org/10.1186/s12882-022-02910-8 Text en © The Author(s) 2022 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/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Zafarnejad, Reyhaneh
Dumbauld, Steven
Dumbauld, Diane
Adibuzzaman, Mohammad
Griffin, Paul
Rutsky, Edwin
Using CUSUM in real time to signal clinically relevant decreases in estimated glomerular filtration rate
title Using CUSUM in real time to signal clinically relevant decreases in estimated glomerular filtration rate
title_full Using CUSUM in real time to signal clinically relevant decreases in estimated glomerular filtration rate
title_fullStr Using CUSUM in real time to signal clinically relevant decreases in estimated glomerular filtration rate
title_full_unstemmed Using CUSUM in real time to signal clinically relevant decreases in estimated glomerular filtration rate
title_short Using CUSUM in real time to signal clinically relevant decreases in estimated glomerular filtration rate
title_sort using cusum in real time to signal clinically relevant decreases in estimated glomerular filtration rate
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9389810/
https://www.ncbi.nlm.nih.gov/pubmed/35982411
http://dx.doi.org/10.1186/s12882-022-02910-8
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