Glucose Monitoring Devices: Measuring Blood Glucose to Manage and Control Diabetes

359 Pages·2020·12.748 MB·English

by  Chiara Fabris (editor), Boris Kovatchev (editor)

Glucose Monitoring
Devices
Measuring Blood Glucose to
Manage and Control Diabetes
Edited by
Chiara Fabris, PhD
Assistant Professor
Center for Diabetes Technology
Department of Psychiatry and Neurobehavioral Sciences
University of Virginia
Charlottesville, Virginia
United States
Boris Kovatchev, PhD
Professor and Director
Center for Diabetes Technology
Department of Psychiatry and Neurobehavioral Sciences
University of Virginia
Charlottesville, Virginia
United States
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Contributors
Giada Acciaroli, PhD
Department ofInformation Engineering, University of Padova, Padova, Italy
David Ahn,MD
ProgramDirector, Mary &Dick Allen DiabetesCenter,Hoag Memorial Hospital
Presbyterian, NewportBeach,CA, United States
Tadej Battelino, MD, PhD
Department ofEndocrinology,Diabetes and Metabolism, University children’s
hospitalUniversity Medical CentreLjubljana, Ljubljana,Slovenia; Faculty of
Medicine, University ofLjubljana, Ljubljana,Slovenia
Rachel Brandt, BSc
Illinois Institute ofTechnology,Biomedical Engineering, Chicago,IL, United
States
Marc D. Breton, PhD
AssistantProfessor,Center for DiabetesTechnology,Department of Psychiatry
andNeurobehavioralSciences,UniversityofVirginia,Charlottesville,VA,United
States
Enrique Campos-Na´n˜ez, PhD
Principal Algorithm Engineer,Research& Development, DexcomInc,
Charlottesville,VA,UnitedStates
Ali Cinar, PhD
Professor,Chemical and BiologicalEngineeringDepartment,Illinois Instituteof
Technology,Chicago,IL, United States
William L. Clarke,MD
Profesor, EmeritusofPediatric Endocrinology,Department ofPediatrics,
University ofVirginia, Charlottesville, VA, United States
Claudio Cobelli,PhD
Department ofInformation Engineering, University of Padova, Padova, Italy
Andrew DeHennis, PhD
Sr.Director ofEngineering, R&D, Product Development Senseonics
Incorporated, Germantown, MD, UnitedStates
Simone Del Favero, PhD
AssistantProfessor,Department ofInformation Engineering, Padova, Italy
Laya Ekhlaspour,MD
Instructor,PediatricEndocrinology,StanfordUniversity,PaloAlto, CA, United
States
xiii
xiv Contributors
Chiara Fabris, PhD
AssistantProfessor,Center for DiabetesTechnology,Department ofPsychiatry
andNeurobehavioralSciences,UniversityofVirginia,Charlottesville,VA,United
States
Andrea Facchinetti,PhD
Department ofInformation Engineering, University ofPadova, Padova, Italy
Gregory P.Forlenza, MD
AssistantProfessor,BarbaraDavisCenter,UniversityofColoradoDenver,Aurora,
CO, United States
Kurt Fortwaengler,PMP
Disease Modeling, Global MarketAccess, Roche Diabetes Care, Mannheim,
Germany
Satish Garg, MD
Professor of Pediatrics and Medicine, Barbara Davis Center for Diabetes Adult
Clinic, University of Colorado Anschutz Medical Center,Aurora,CO, United
States
Iman Hajizadeh,MSc
Research Assistantand PhD Student,Chemical and BiologicalEngineering,
Illinois InstituteofTechnology,Chicago,IL, United States
Nicole Hobbs, BSc
Graduate Research Assistant,Department ofBiomedicalEngineering, Illinois
Instituteof Technology, Chicago,IL, United States
David Klonoff,MD, FACP,FRCP (Edin), Fellow AIMBE
Medical Director,DiabetesResearch Institute,Mills-Peninsula Medical Center,
San Mateo, CA,United States
Boris Kovatchev,PhD
Professor and Director,Center for Diabetes Technology,Department of
PsychiatryandNeurobehavioral Sciences, University of Virginia, Charlottesville,
Virginia, United States
Mark Mortellaro, PhD
DirectorofChemistry,SenseonicsIncorporated,Germantown,MD,UnitedStates
Laura M. Nally,MD
AssociateProfessor,PediatricEndocrinology,YaleChildren’sDiabetesProgram,
Yale University School ofMedicine, New Haven, CT, United States
Nick Oliver,FRCP
Wynn Professor ofHuman Metabolism, Consultant in Endocrinology, Diabetes
and Internal Medicine, ImperialCollege London,St. Mary’s Hospital Medical
School Building, London,UnitedKingdom
Contributors xv
Mudassir Rashid, PhD,BEng
SeniorResearchAssociate,DepartmentofChemicalandBiologicalEngineering,
Illinois Institute ofTechnology,Chicago, IL,UnitedStates
Monika Reddy,MBChB, MRCP (UK), PhD
Honorary Senior Clinical Lecturer,Consultant in Endocrinology, Diabetes and
Internal Medicine,Imperial College London,St. Mary’s Hospital Medical School
Building,London,United Kingdom
Amanda Rewers, MD
ResearchAssistant,BarbaraDavisCenterforDiabetesAdultClinic,Aurora,CO,
United States
Sediqeh Samadi,MSc
IllinoisInstituteofTechnology,ChemicalandBiologicalEngineering,Chicago,IL,
United States
Mert Sevil, MSc
ResearchAssistantandPhDStudent,BiomedicalEngineering,IllinoisInstituteof
Technology,Chicago,IL, United States
ViralN.Shah,MD
AssistantProfessor ofPediatrics and Medicine,BarbaraDavis Center for
DiabetesAdultClinic, University of Colorado Anschutz Medical Center,Aurora,
CO, United States
JenniferL. Sherr,MD, PhD
Instructor,PediatricEndocrinology,Yale Children’sDiabetes Program, Yale
University School ofMedicine, New Haven, CT, United States
DarjaSmigocSchweiger,MD, PhD
Department ofEndocrinology,Diabetes and Metabolism, University children’s
hospitalUniversity Medical CentreLjubljana, Ljubljana,Slovenia; Faculty of
Medicine, University ofLjubljana, Ljubljana,Slovenia
GiovanniSparacino,PhD
Department ofInformation Engineering, University of Padova, Padova, Italy
Chukwuma Uduku,MBBS, BSc,MRCP
ClinicalResearchFellowandSpecialistRegistrarinEndocrinology,Diabetesand
Internal Medicine,Imperial College London,St. Mary’s Hospital Medical School
Building,London,United Kingdom
Martina Vettoretti, PhD
Department ofInformation Engineering, University of Padova, Padova, Italy
About the Authors
Dr.ChiaraFabrisisAssistantProfessorattheUniversityofVirginiaSchoolofMed-
icineandmemberofthefacultyattheCenterforDiabetesTechnology.Sheholdsa
Master’s and a Doctoral Degree in Bioengineering from the University of Padova
(Padova, Italy) and has significant experience in mathematical modeling and
simulationdespeciallyregarding theglucose/insulin regulationsystemdand algo-
rithmdevelopment.Overthepast4years,Dr.FabrishasbeenawardedanAdvanced
PostdoctoralFellowshipandaCareerDevelopmentAwardbytheJuvenileDiabetes
ResearchFoundation,whichsupportedthedevelopmentandclinicaltestingofdeci-
sionsupportsystemstohelppeoplewithdiabetesmanagetheirdisease.Dr.Fabrisis
involvedinseveralprojectsfocusedonoptimizationoftreatmentsfordiabetesand
diabetesdata science.
Dr. Boris Kovatchev is Professor at the University of Virginia School of Medicine
and School of Engineering and founding director of the Center for Diabetes Tech-
nology. He has a 30-year track record in mathematical modeling, biosimulation,
and algorithm development. Currently, he is Principal Investigator of several pro-
jectsdedicatedtoDiabetesDataScienceandthedevelopmentofartificialpancreas
anddecisionsupportsystems,includingthelarge-scaleNIHInternationalDiabetes
Closed-LoopTrialandtheUVAStrategicInvestmentFundproject“PrecisionIndi-
vidualized Medicine for Diabetes”. Dr. Kovatchev is author of over 200
peer-reviewed publications andholds 85patents.
xvii
CHAPTER
1
Introduction to SMBG
Darja Smigoc Schweiger, MD, PhD,Tadej Battelino, MD, PhD
DepartmentofEndocrinology,DiabetesandMetabolism,Universitychildren’shospitalUniversity
MedicalCentreLjubljana,Ljubljana,Slovenia;FacultyofMedicine,UniversityofLjubljana,
Ljubljana,Slovenia
Historical perspective and principles of blood glucose
control
AsBenedictdevelopedacopperreagentforurineglucose,urineglucosetestinghas
beenthemainmethodfordiabetesmonitoringfor50years[1].Later,amoreconve-
nient and specific “dip-and-read” urineglucose oxidase-based reagent strip (Clini-
stix) was introduced [2]. However, urine tests had several well-recognized
limitations. High glucose levels were detected only when the renal threshold for
glucosewas exceeded over a period of several hours and the results were affected
byfluidintakeandurineconcentration.Moreover,thetestdidnotdetectlowglucose
levels [3]. In the 1960s, first blood glucose (BG) test strips (Dextrostix) were
developed. The exposure to blood resulted in a colorimetric reaction proportional
to blood glucose concentration. The color change that occurred was compared to
a color chart providing a semiquantitative assessment of blood glucose levels [4].
The first blood glucose meter, the Ames Reflectance Meter, was introduced in
1970. The meter exhibited quantitative blood glucose results based on Dextrostix
teststripsandreflectancephotometry,thuseliminatingvisualreadingerrors.There-
sultsweredisplayedbyamovingpointeronthreeanalogscales[5].Thedevicewas
only available for testing in a doctor’s office and hospital emergency departments
[6]. Although the meter was heavy, expensive, and cumbersome to use, it ushered
the development in an era of blood glucose monitoring systems. In 1972, more
convenient Eyetone glucometer using Dextrostix test strips was developed, which
wasmoreprecise,lighter,andeasiertooperate[7].In1974,BoehringerMannheim
launchedReflomat,areflectancemeterwithmodifiedreagentteststrips(Reflotest),
equippedtoacceptsmallervolumesofblood,whichwasremovedmoreeasilyand
thus more suitable for at-home self-monitoring of blood glucose (SMBG) [6].
Dextrometer and Glucochek launched, in 1980, were the first glucometers with
digitaldisplay[8].Technologicaladvancesduring1980smadeglucometerssmaller
and easier to use with built-in software to store and retrieve results [6]. The One
Touch meter introduced in 1987 was regarded as the first second-generation blood
glucose meter because it utilized an improved sampling procedure that eliminated
3
GlucoseMonitoringDevices.https://doi.org/10.1016/B978-0-12-816714-4.00001-6
Copyright©2020ElsevierInc.Allrightsreserved.
4 CHAPTER 1 Introduction to SMBG
bloodremovalstepandtheneedfortimereactions[9].Towardtheendofthe1980s,
test strips changed dramaticallywhenelectrochemicalprinciples tomeasure blood
glucosewereintroduced.Furthermore,theintroductionofelectrochemicaltechnol-
ogy led to the development of the third generation of glucose monitoring systems
[10]. The landmark in glucose self-monitoring was the release of the first electro-
chemical blood glucose monitor, ExacTech by Medisense, in 1987. The device
used an enzyme electrode strip containing glucose oxidase and ferrocene as an
electron transfer mediator. A current generated at the electrode was detected by
anamperometricsensor[11].
Today, most glucometersare electrochemical,using commercial screen-printed
stripsbasedonthesameprinciple.Theyrequireasmallerbloodsampleandprovide
resultsinafewseconds.Glucoseoxidaseandglucosedehydrogenasearetwotypes
ofenzymesthathavebeenusedforcommercialelectrochemicalbloodglucosetest
strips. Test strips using glucose oxidase technology are susceptible to dissolved
oxygenconcentrationsandcanonlybeusedwithcapillarybloodinanormalrange
of oxygen levels. Glucose dehydrogenase-based test strips are not sensitive to
oxygen[12].However,coenzymepyrroloquinolinequinoneandglucosedehydroge-
nase containing test strips lack specificity as they cross-react with maltose,
galactose, and xylose. Therefore they must not be used by patients on peritoneal
dialysis [13]. The most common electrochemical detection methods for glucose
measurement are amperometry and coulometry [12]. Coulometric strips have
demonstrated to operate over the wider ranges of hematocrit values and with the
minimized effect of temperature, high concentrations of paracetamol, uric acid,
and vitamin C [14]. The performance of glucometers has further improved with
simplified sampling and testing procedures to minimize user interaction errors.
Meters using no-coding technology are precalibrated to report whole blood or
plasmaequivalentresults[15].Mostcurrentmetersareplasmacalibratedandauto-
matically convertresults into plasma equivalentresults [16].Modern electrochem-
ical blood glucose test strips use the capillary gap to automatically draw blood
into the test surface, which requires only a small volume of blood (just about
0.3mL) and has automatic fill detection ensuring that sufficient volume of blood
is provided to the strip. The average test time has been reduced to just less than
5s [17]. In addition, lower blood volume requirements allow alternative sites for
blood glucose testing such as arm or thigh that are likely to be less painful and
providesimilarresultstothefingertip[18].However,whenbloodglucoseischang-
ingrapidly,significantdifferencesinbloodglucoseresultscanbeanticipateddueto
thetimelagofupto20minatalternativesites[19].Thereforetestingatalternative
sitesisnotrecommendedwithintheearlypostmealperiod,immediatelyafterexer-
cise or when blood glucose is suspected to be low [20]. Some fully automated
devices have integral lacing device and extract blood by drawing a vacuum over a
lanced site [21].Newermetersofferdata-storagesoftware thatcan bedownloaded
and used by diabetes management systems for the graphical display of trends,
statistics,andsharingofreports[22].Downloadinginformationfrombloodglucose
meters enables the analysis of large amounts of data that reveal glycemic patterns
The evidence base for SMBG in type 1 diabetes 5
andsupportpersonswithdiabetesandhealthcareprofessionalstomakeappropriate
management strategies [23]. Data retrieval has further improved with wireless
connectivity to smartphone apps [24]. The analytical quality of personal blood
glucosemetersusedforat-homemonitoringisimportantasappropriatetherapeutic
decisionsrelyonaccurateglucosereadings.Standardizedqualityamongmanufac-
turers is required by the regulatory recommendations and analytical performance
criteria. In 2003, the International Organization for Standardization (ISO) criteria
for glucose meters were introduced. The ISO 15197: 2003 standard recommended
an allowable error of (cid:1)15mg/dL for blood glucose levels <75mg/dL and (cid:1)20%
for blood glucose levels (cid:3)75mg/dL [25]. These criteria were updated in ISO
15197:2013 standard, which required an allowable error of (cid:1)15mg/dL for BG
concentrations <100mg/dL and (cid:1)15% for BG concentrations (cid:3)100mg/dL [26].
In the United States, the Food and Drug Administration (FDA) standard finalized
in 2016 recommended that at least 95% of measurement results shall fall within
(cid:1)15% of the reference value at blood glucose concentrations <100mg/dL and
(cid:1)15% at (cid:3)100mg/dL, thus requiring greater hypoglycemia accuracy than the
ISO 15197:2013 [27].
The evidence base for SMBG in type 1 diabetes
RichardBernsteinwasthefirstreportedpersonwithtype1diabetes(T1D)toadopta
glucometerforpersonaluse.Withfrequentglucosemonitoring,hewasabletorefine
insulin doses and diet regimen to maintain essentiallynormal blood glucose levels
and prevent hypoglycemia. However, he failed to publish his personal experience
usingSMBGuntil heearneda medicaldegreeinthe early 1980s [28].In the mid-
1970s, peoplewith diabetes for the first time started using reflectance glucometers
Eyetone and Reflomat at home for SMBG. In 1978, first experiences in teaching
peoplewithinsulin-dependentdiabetestomeasuretheirownbloodglucoseconcen-
trations were published [29e34]. Direct measurement of blood glucose by people
with diabetes at home provided sufficiently accurate results for easier and more
predictable adjustment of insulin doses over the urine-glucose analysis [35].
Frequent SMBG as a guide to multiple injections of insulin has considerably
improved metabolic control and could guard against undue hypoglycemia [36];
it was well accepted by persons with diabetes and improved their understanding
of diabetes and motivation to become more involved in their own care [37]. Due
to the growing evidence in the late 1970s that chronic complications of diabetes
can be minimized with glycemic control, daily SMBG gained wider acceptance
[38]. In addition, improved glycemic control could objectively be assessed by the
measurement of glycated hemoglobin levels [39]. Over the next decade, SMBG
proved tobe one ofthe major technological advances inaddition tomultiple daily
insulininjectionsandthenewlydevelopedinsulinpumpsthatestablishedintensive
insulin therapy, a therapeutic strategy that has become increasingly used in an
attempt to achieve near-normal glycemia [40,41]. In the 1980s, smaller, more