Implementation of a Prototype Glomerular Filtration Rate Application To Monitor Creatinine Kinetic Dynamics in Critically Ill Patients
It has always been desirable for clinicians to ascertain whether glomerular filtration rate has recovered or still depressed at the bedside as increase in serum creatinine often indicates acute kidney injury to a clinician. In recent years, several clinical studies have developed mathematical models...
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ump-161482018-11-30T02:03:54Z http://umpir.ump.edu.my/id/eprint/16148/ Implementation of a Prototype Glomerular Filtration Rate Application To Monitor Creatinine Kinetic Dynamics in Critically Ill Patients Fatimah, Dzaharudin Azrina, Md Ralib Mohd Basri, Mat Nor Ummu Kulthum, Jamaludin Q Science (General) QA75 Electronic computers. Computer science R Medicine (General) RM Therapeutics. Pharmacology It has always been desirable for clinicians to ascertain whether glomerular filtration rate has recovered or still depressed at the bedside as increase in serum creatinine often indicates acute kidney injury to a clinician. In recent years, several clinical studies have developed mathematical models to simulate the creatinine response to changes in glomerular filtration rate which includes the estimated glomerular filtration rate Chronic Kidney Disease Epidemiology Collaboration, the Chen-kinetic estimated GFR model and the modified Chen-Pianta-Endre-Pickering-Bukley-Pecke kinetic estimated GFR model. Another study also showed that the ratio of creatinine excretion rates to creatinine production rates may predict changes in plasma concentration. The aim of this study is to allow clinicians to gauge the performance of glomerular filtration rate estimation using the aforementioned equations and models to predict worsening of renal function, indicated by a low kinetic estimated glomerular filtration rate or creatinine production rates less than unity, or recovery of kidney function, indicated by high kinetic estimated glomerular filtration rate. In order to achieve this a mobile software is developed to aid data collection and calculation for the clinical study based on the aforementioned models. This paper summarises the implementation details of the native application development and presents the graphical user interface of the system in practice. 2017 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/16148/1/bare_conf.pdf application/pdf en http://umpir.ump.edu.my/id/eprint/16148/7/implementation%20of%20a%20prototype1.pdf Fatimah, Dzaharudin and Azrina, Md Ralib and Mohd Basri, Mat Nor and Ummu Kulthum, Jamaludin (2017) Implementation of a Prototype Glomerular Filtration Rate Application To Monitor Creatinine Kinetic Dynamics in Critically Ill Patients. In: IEEE-EMBS Conference on Biomedical Engineering and Sciences, 4-8 December 2016 , Kuala Lumpur, Malaysia. pp. 1-5.. |
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Q Science (General) QA75 Electronic computers. Computer science R Medicine (General) RM Therapeutics. Pharmacology Fatimah, Dzaharudin Azrina, Md Ralib Mohd Basri, Mat Nor Ummu Kulthum, Jamaludin Implementation of a Prototype Glomerular Filtration Rate Application To Monitor Creatinine Kinetic Dynamics in Critically Ill Patients |
description |
It has always been desirable for clinicians to ascertain whether glomerular filtration rate has recovered or still depressed at the bedside as increase in serum creatinine often indicates acute kidney injury to a clinician. In recent years, several clinical studies have developed mathematical models to simulate the creatinine response to changes in glomerular filtration rate which includes the estimated glomerular filtration rate Chronic Kidney Disease Epidemiology Collaboration, the Chen-kinetic estimated GFR model and the modified Chen-Pianta-Endre-Pickering-Bukley-Pecke kinetic estimated GFR model. Another study also showed that the ratio of creatinine excretion rates to creatinine production rates may predict changes in plasma concentration. The aim of this study is to allow clinicians to gauge the performance of glomerular filtration rate estimation using the aforementioned equations and models to predict worsening of renal function, indicated by a low kinetic estimated glomerular filtration rate or creatinine production rates less than unity, or recovery of kidney function, indicated by high kinetic estimated glomerular filtration rate. In order to achieve this a mobile software is developed to aid data collection and calculation for the clinical study based on the aforementioned models. This paper summarises the implementation details of the native application development and presents the graphical user interface of the system in practice. |
format |
Conference or Workshop Item |
author |
Fatimah, Dzaharudin Azrina, Md Ralib Mohd Basri, Mat Nor Ummu Kulthum, Jamaludin |
author_facet |
Fatimah, Dzaharudin Azrina, Md Ralib Mohd Basri, Mat Nor Ummu Kulthum, Jamaludin |
author_sort |
Fatimah, Dzaharudin |
title |
Implementation of a Prototype Glomerular Filtration Rate Application To Monitor Creatinine Kinetic Dynamics in Critically Ill Patients |
title_short |
Implementation of a Prototype Glomerular Filtration Rate Application To Monitor Creatinine Kinetic Dynamics in Critically Ill Patients |
title_full |
Implementation of a Prototype Glomerular Filtration Rate Application To Monitor Creatinine Kinetic Dynamics in Critically Ill Patients |
title_fullStr |
Implementation of a Prototype Glomerular Filtration Rate Application To Monitor Creatinine Kinetic Dynamics in Critically Ill Patients |
title_full_unstemmed |
Implementation of a Prototype Glomerular Filtration Rate Application To Monitor Creatinine Kinetic Dynamics in Critically Ill Patients |
title_sort |
implementation of a prototype glomerular filtration rate application to monitor creatinine kinetic dynamics in critically ill patients |
publishDate |
2017 |
url |
http://umpir.ump.edu.my/id/eprint/16148/ http://umpir.ump.edu.my/id/eprint/16148/1/bare_conf.pdf http://umpir.ump.edu.my/id/eprint/16148/7/implementation%20of%20a%20prototype1.pdf |
first_indexed |
2023-09-18T22:21:33Z |
last_indexed |
2023-09-18T22:21:33Z |
_version_ |
1777415690282598400 |