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Glucose monitoring devices = measuring blood glucose to manage and control diabetes /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Glucose monitoring devices/ edited by Chiara Fabris, Boris Kovatchev.
其他題名:	measuring blood glucose to manage and control diabetes /
出版者:	London, United Kingdom ;Elsevier Academic Press, : 2020.,
面頁冊數:	1 online resource.
內容註:	Front Cover -- Glucose Monitoring Devices -- Glucose Monitoring Devices: Measuring Blood Glucose to Manage and Control Diabetes -- Copyright -- Contents -- Contributors -- About the Authors -- 1 -- Self-monitoring of blood glucose (SMBG) devices -- 1 -- Introduction to SMBG -- Historical perspective and principles of blood glucose control -- The evidence base for SMBG in type 1 diabetes -- The evidence base for SMBG in type 2 diabetes -- Guidelines for SMBG -- The shortcomings of SMBG and future perspective -- References -- 2 -- Analytical performance of SMBG systems -- Introduction
內容註:	The process for premarket approval of SMBG devices -- Analytical performance according to ISO 15197 -- Precision -- Interference evaluation -- Accuracy -- Analytical performance according to FDA -- Postmarket analytical performance -- Advances in analytical performance of SMBG devices -- Conclusion -- List of authors -- References -- 3 -- Clinical evaluation of SMBG systems -- References -- 4 -- Consequences of SMBG systems inaccuracy -- Introduction -- Quantifying the effect of inaccurate BGM systems -- A complex system -- Patient behavior is the main driver -- Effects spread over time and space
內容註:	Clinical outcomes -- Short term -- Long term -- Quality of life -- Financial outcomes -- Long term -- Requirements -- Physiological variability -- Behavioral variability -- Device and lot variability -- Therapy modes -- Time span -- Accuracy and its consequences -- Modeling and simulation -- Metabolic models and simulators (metabolic variability) -- Behavioral modeling and simulation (behavioral variability and therapy modes) -- Integrated metabolic/behavioral simulation -- Modeling glucose monitoring devices (device and lot variability) -- In silico accuracy studies
內容註:	From in silico results to short-term clinical outcomes -- Long-term health and complications -- From in silico results to long-term complications -- From clinical performance to financial outcomes -- An extended illustration -- The in silico study -- Meter models -- Behavioral models -- Clinical and financial outcomes -- Results: clinical outcomes -- Accuracy and clinical outcomes: a regression model -- Determining financial impact -- Cost compared to an ideal -- Worst-case costing -- Observations from the illustrative example -- Limitations -- Conclusions and future work -- References
內容註:	5 -- Modeling the SMBG measurement error -- SMBG measurement error -- Why modeling the SMBG measurement error? -- Literature models of SMBG measurement error -- The state-of-the-art modeling method by Vettoretti et al. -- Definition of training and test sets -- Constant-SD zones identification -- Maximum-likelihood fitting -- Model validation -- Derivation of a model of SMBG error distribution for two commercial devices -- Case study 1: modeling the One Touch Ultra 2 measurement error -- Dataset -- Preprocessing of YSI and SMBG-YSI matching -- Model development -- Model validation
標題:	Medical instruments and apparatus. -
電子資源:	https://www.sciencedirect.com/science/book/9780128167144
ISBN:	9780128168844 (electronic bk.)

Glucose monitoring devices = measuring blood glucose to manage and control diabetes /
Glucose monitoring devicesmeasuring blood glucose to manage and control diabetes /[electronic resource] :edited by Chiara Fabris, Boris Kovatchev. - London, United Kingdom ;Elsevier Academic Press,2020. - 1 online resource.

Front Cover -- Glucose Monitoring Devices -- Glucose Monitoring Devices: Measuring Blood Glucose to Manage and Control Diabetes -- Copyright -- Contents -- Contributors -- About the Authors -- 1 -- Self-monitoring of blood glucose (SMBG) devices -- 1 -- Introduction to SMBG -- Historical perspective and principles of blood glucose control -- The evidence base for SMBG in type 1 diabetes -- The evidence base for SMBG in type 2 diabetes -- Guidelines for SMBG -- The shortcomings of SMBG and future perspective -- References -- 2 -- Analytical performance of SMBG systems -- Introduction

ISBN: 9780128168844 (electronic bk.)Subjects--Topical Terms:

672534
Medical instruments and apparatus.
Index Terms--Genre/Form:

542853
Electronic books.

LC Class. No.: R856 / .G58 2020

Dewey Class. No.: 610.284

Glucose monitoring devices = measuring blood glucose to manage and control diabetes /
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505 8 $a The process for premarket approval of SMBG devices -- Analytical performance according to ISO 15197 -- Precision -- Interference evaluation -- Accuracy -- Analytical performance according to FDA -- Postmarket analytical performance -- Advances in analytical performance of SMBG devices -- Conclusion -- List of authors -- References -- 3 -- Clinical evaluation of SMBG systems -- References -- 4 -- Consequences of SMBG systems inaccuracy -- Introduction -- Quantifying the effect of inaccurate BGM systems -- A complex system -- Patient behavior is the main driver -- Effects spread over time and space
505 8 $a Clinical outcomes -- Short term -- Long term -- Quality of life -- Financial outcomes -- Long term -- Requirements -- Physiological variability -- Behavioral variability -- Device and lot variability -- Therapy modes -- Time span -- Accuracy and its consequences -- Modeling and simulation -- Metabolic models and simulators (metabolic variability) -- Behavioral modeling and simulation (behavioral variability and therapy modes) -- Integrated metabolic/behavioral simulation -- Modeling glucose monitoring devices (device and lot variability) -- In silico accuracy studies
505 8 $a From in silico results to short-term clinical outcomes -- Long-term health and complications -- From in silico results to long-term complications -- From clinical performance to financial outcomes -- An extended illustration -- The in silico study -- Meter models -- Behavioral models -- Clinical and financial outcomes -- Results: clinical outcomes -- Accuracy and clinical outcomes: a regression model -- Determining financial impact -- Cost compared to an ideal -- Worst-case costing -- Observations from the illustrative example -- Limitations -- Conclusions and future work -- References
505 8 $a 5 -- Modeling the SMBG measurement error -- SMBG measurement error -- Why modeling the SMBG measurement error? -- Literature models of SMBG measurement error -- The state-of-the-art modeling method by Vettoretti et al. -- Definition of training and test sets -- Constant-SD zones identification -- Maximum-likelihood fitting -- Model validation -- Derivation of a model of SMBG error distribution for two commercial devices -- Case study 1: modeling the One Touch Ultra 2 measurement error -- Dataset -- Preprocessing of YSI and SMBG-YSI matching -- Model development -- Model validation
650 0 $a Medical instruments and apparatus. $3 672534
650 0 $a Blood sugar monitoring. $3 2041609
650 0 $a Diabetes $x Treatment. $3 841790
650 7 $a Blood sugar monitoring $2 fast $3 3508746
650 7 $a Diabetes $x Treatment $v Handbooks, manuals, etc. $3 2015956
650 7 $a Medical instruments and apparatus $2 fast $3 3508747
655 4 $a Electronic books. $2 lcsh $3 542853
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