Prediction of serum digoxin concentration using estimated glomerular filtration rate in Thai population

© 2019 Sae-lim et al. Purpose: Serum digoxin concentration (SDC) monitoring may be unavailable in some healthcare settings. Predicted SDC comes into play in the efficacy and toxicity monitoring of digoxin. Renal function is the important parameter for predicting SDC. This study was conducted to comp...

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Main Authors: Orawan Sae-Lim, Thitima Doungngern, Siriluk Jaisue, Sirichai Cheewatanakornkul, Poukwan Arunmanakul, Sirirat Anutrakulchai, Rungsrit Kanjanavanit, Wibul Wongpoowarak
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Published: 2020
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http://cmuir.cmu.ac.th/jspui/handle/6653943832/68014
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spelling th-cmuir.6653943832-680142020-04-02T15:15:53Z Prediction of serum digoxin concentration using estimated glomerular filtration rate in Thai population Orawan Sae-Lim Thitima Doungngern Siriluk Jaisue Sirichai Cheewatanakornkul Poukwan Arunmanakul Sirirat Anutrakulchai Rungsrit Kanjanavanit Wibul Wongpoowarak Medicine © 2019 Sae-lim et al. Purpose: Serum digoxin concentration (SDC) monitoring may be unavailable in some healthcare settings. Predicted SDC comes into play in the efficacy and toxicity monitoring of digoxin. Renal function is the important parameter for predicting SDC. This study was conducted to compare measured and predicted SDC when using creatinine clearance (CrCl) from Cockcroft–Gault (CG) equation and estimated glomerular filtration rate (eGFR) calculated from CKD-Epidemiology Collaboration (CKD-EPI), re-expressed Modification of Diet in Renal Disease (Re-MDRD4), Thai-MDRD4, and Thai-eGFR equations in Sheiner’s and Konishi’s pharmacokinetic models. Patients and methods: In this retrospective study, patients with cardiovascular disease with a steady-state of SDC within 0.5–2.0 mcg/L were enrolled. CrCl and studied eGFR adjusted for body surface area (BSA) were used in the models to determine the predicted SDC. The discrepancies of the measured and the predicted SDC were analyzed and compared. Results: One hundred and twenty-four patients ranging in age from 22 to 88 years (median 60 years, IQR 50.2, 69.2) were studied. Their serum creatinine ranged from 0.40 to 1.80 mg/dL (median 0.90 mg/dL, IQR 0.79, 1.10). The mean±SD of measured SDC was 1.12±0.34 mcg/L. In the Sheiner’s model, the mean predicted SDC was calculated by using the CG and the BSA adjusted CKD-EPI equations and was not different when compared with the measured levels (1.10±0.36 mcg/L (p=0.669) and 1.08±0.42 mcg/L (p=0.374), respectively). The CG, CKD-EPI, and Re-MDRD4 equations were a better fit for patients with creatinine ≥0.9 mg/dL for prediction with minimal errors. In the Konishi’s model, the predicted SDC using the CG and the studied eGFR equation was lower than the measured SDC (p<0.05). Conclusion: In Sheiner’s model, the CG and the BSA adjusted CKD-EPI equations should be used for predicting SDC, especially in patients with serum creatinine ≥0.9 mg/dL. The other studied eGFRs underestimated SDC in both Sheiner’s and Konishi’s model. 2020-04-02T15:15:53Z 2020-04-02T15:15:53Z 2019-01-01 Journal 11787074 2-s2.0-85076224031 10.2147/IJGM.S218393 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85076224031&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/68014
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
topic Medicine
spellingShingle Medicine
Orawan Sae-Lim
Thitima Doungngern
Siriluk Jaisue
Sirichai Cheewatanakornkul
Poukwan Arunmanakul
Sirirat Anutrakulchai
Rungsrit Kanjanavanit
Wibul Wongpoowarak
Prediction of serum digoxin concentration using estimated glomerular filtration rate in Thai population
description © 2019 Sae-lim et al. Purpose: Serum digoxin concentration (SDC) monitoring may be unavailable in some healthcare settings. Predicted SDC comes into play in the efficacy and toxicity monitoring of digoxin. Renal function is the important parameter for predicting SDC. This study was conducted to compare measured and predicted SDC when using creatinine clearance (CrCl) from Cockcroft–Gault (CG) equation and estimated glomerular filtration rate (eGFR) calculated from CKD-Epidemiology Collaboration (CKD-EPI), re-expressed Modification of Diet in Renal Disease (Re-MDRD4), Thai-MDRD4, and Thai-eGFR equations in Sheiner’s and Konishi’s pharmacokinetic models. Patients and methods: In this retrospective study, patients with cardiovascular disease with a steady-state of SDC within 0.5–2.0 mcg/L were enrolled. CrCl and studied eGFR adjusted for body surface area (BSA) were used in the models to determine the predicted SDC. The discrepancies of the measured and the predicted SDC were analyzed and compared. Results: One hundred and twenty-four patients ranging in age from 22 to 88 years (median 60 years, IQR 50.2, 69.2) were studied. Their serum creatinine ranged from 0.40 to 1.80 mg/dL (median 0.90 mg/dL, IQR 0.79, 1.10). The mean±SD of measured SDC was 1.12±0.34 mcg/L. In the Sheiner’s model, the mean predicted SDC was calculated by using the CG and the BSA adjusted CKD-EPI equations and was not different when compared with the measured levels (1.10±0.36 mcg/L (p=0.669) and 1.08±0.42 mcg/L (p=0.374), respectively). The CG, CKD-EPI, and Re-MDRD4 equations were a better fit for patients with creatinine ≥0.9 mg/dL for prediction with minimal errors. In the Konishi’s model, the predicted SDC using the CG and the studied eGFR equation was lower than the measured SDC (p<0.05). Conclusion: In Sheiner’s model, the CG and the BSA adjusted CKD-EPI equations should be used for predicting SDC, especially in patients with serum creatinine ≥0.9 mg/dL. The other studied eGFRs underestimated SDC in both Sheiner’s and Konishi’s model.
format Journal
author Orawan Sae-Lim
Thitima Doungngern
Siriluk Jaisue
Sirichai Cheewatanakornkul
Poukwan Arunmanakul
Sirirat Anutrakulchai
Rungsrit Kanjanavanit
Wibul Wongpoowarak
author_facet Orawan Sae-Lim
Thitima Doungngern
Siriluk Jaisue
Sirichai Cheewatanakornkul
Poukwan Arunmanakul
Sirirat Anutrakulchai
Rungsrit Kanjanavanit
Wibul Wongpoowarak
author_sort Orawan Sae-Lim
title Prediction of serum digoxin concentration using estimated glomerular filtration rate in Thai population
title_short Prediction of serum digoxin concentration using estimated glomerular filtration rate in Thai population
title_full Prediction of serum digoxin concentration using estimated glomerular filtration rate in Thai population
title_fullStr Prediction of serum digoxin concentration using estimated glomerular filtration rate in Thai population
title_full_unstemmed Prediction of serum digoxin concentration using estimated glomerular filtration rate in Thai population
title_sort prediction of serum digoxin concentration using estimated glomerular filtration rate in thai population
publishDate 2020
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85076224031&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/68014
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