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DC Field | Value | Language |
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dc.contributor.author | Orawan Sae-Lim | en_US |
dc.contributor.author | Thitima Doungngern | en_US |
dc.contributor.author | Siriluk Jaisue | en_US |
dc.contributor.author | Sirichai Cheewatanakornkul | en_US |
dc.contributor.author | Poukwan Arunmanakul | en_US |
dc.contributor.author | Sirirat Anutrakulchai | en_US |
dc.contributor.author | Rungsrit Kanjanavanit | en_US |
dc.contributor.author | Wibul Wongpoowarak | en_US |
dc.date.accessioned | 2020-04-02T15:15:53Z | - |
dc.date.available | 2020-04-02T15:15:53Z | - |
dc.date.issued | 2019-01-01 | en_US |
dc.identifier.issn | 11787074 | en_US |
dc.identifier.other | 2-s2.0-85076224031 | en_US |
dc.identifier.other | 10.2147/IJGM.S218393 | en_US |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85076224031&origin=inward | en_US |
dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/68014 | - |
dc.description.abstract | © 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. | en_US |
dc.subject | Medicine | en_US |
dc.title | Prediction of serum digoxin concentration using estimated glomerular filtration rate in Thai population | en_US |
dc.type | Journal | en_US |
article.title.sourcetitle | International Journal of General Medicine | en_US |
article.volume | 12 | en_US |
article.stream.affiliations | Faculty of Medicine, Khon Kaen University | en_US |
article.stream.affiliations | Faculty of Medicine, Prince of Songkia University | en_US |
article.stream.affiliations | Khon Kaen University | en_US |
article.stream.affiliations | Prince of Songkla University | en_US |
article.stream.affiliations | Chiang Mai University | en_US |
Appears in Collections: | CMUL: Journal Articles |
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