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Towards Defence In Depth In Diabetes Glucose Self-Management

Ståhl, Fredrik LU (2015) In PhD Theses TFRT-1111.
Abstract (Swedish)
Popular Abstract in Swedish

Personer med insulinbehandlad diabetes saknar, eller har kraftigt försämrad, kroppsegen förmåga att reglera blodsockernivån genom utsöndring av hormonet insulin, och måste därför ta flera injektioner insulin dagligen. De flesta injektioner tas i samband med måltid, och individen bestämmer normalt sina måltidsdoser utifrån aktuell blodsocker- och hälsostatus i kombination med ackumulerad självkännedom om hur måltider, insulin och andra faktorer kan förväntas påverka blodsockernivån. Terapin diskuteras och utvärderas i samråd med läkare och diabetessjuksköterska vid periodiska behandlingstillfällen, men däremellan måste patienten själv besluta om lämpliga doser. Många patienter har svårt att... (More)
Popular Abstract in Swedish

Personer med insulinbehandlad diabetes saknar, eller har kraftigt försämrad, kroppsegen förmåga att reglera blodsockernivån genom utsöndring av hormonet insulin, och måste därför ta flera injektioner insulin dagligen. De flesta injektioner tas i samband med måltid, och individen bestämmer normalt sina måltidsdoser utifrån aktuell blodsocker- och hälsostatus i kombination med ackumulerad självkännedom om hur måltider, insulin och andra faktorer kan förväntas påverka blodsockernivån. Terapin diskuteras och utvärderas i samråd med läkare och diabetessjuksköterska vid periodiska behandlingstillfällen, men däremellan måste patienten själv besluta om lämpliga doser. Många patienter har svårt att bestämma korrekt insulindos, och tar därför ofta både för lite och för mycket insulin med variende risker som följd.



I denna avhandling presenteras metoder som på olika sätt kan ingå i utformningen av egenvården av insulinbehandlad diabetes utifrån ett djupförsvarsperspektiv. Djupförsvar innebär att flera olika skyddsmekanismer arbetar tillsammans för att förebygga potentiellt farliga händelser, och kan bestå av tekniska lösningar, men även omfatta exempelvis riktlinjer, normer och rekommendationer. I detta sammanhang handlar det om att förbättra blodsockerkontrollen och reducera risken för de kort- och långsiktiga komplikationer som kan uppkomma till följd av avvikande blodsockervärden. Sådana skyddssystem kan exempelvis vara en rådgivningsfunktion avseende insulindosering i en insulinpump eller varningsfunktion för låga och höga blodsockervärden i en kontinuerlig glukossensor. Underlag till avhandlingsarbetet har utgjorts av datamaterial från två studier där bl.a. blodsockermätningar, insulindoser och information om måltidsintag har insamlats från patienter med insulinberoende diabetes.



För att kunna bestämma väl avvägda insulindoser krävs kunskap och förståelse för hur olika insulintyper påverkar blodsockret. Dessa effekter skiljer sig åt mellan olika insulinpreparat, men även mellan olika individer. Skillnaderna avser både magnituden på den totala blodsockersänkande effekten och hur snabbt och hur länge denna effekt verkar efter en dosering. En metod för att skatta modeller som beskriver dessa effekter på individbasis för snabbverkande insulin har utabarbetats. Resultaten visar att insulinet verkar under längre tid än vad som normalt brukar antas. Ett annat intressant resultat bekräftar en tidigare studie där man med en annan metod visat att insulinets förmåga att sänka blodsockret varierar beroende på blod-sockernivån. En hög blodsockernivå sänker insulinets effekt, medan ett lågt blodsocker istället ökar densamma.



Nattliga blodsockerfall är ett särskilt svårt och återkommande problem för många individer med insulinbehandlad diabetes. Med hjälp av insulinmodellerna kan sannolikheten för att hamna i låga blodsockervärden (hypoglykemi) förutses. Insulinpumpar finns i dag som kan stänga av insulintillförseln vid förväntad hypoglykemi. Simulering på insamlat data av denna avstängningsfunktion tillsammans med insulinmodellen visar att många av dessa hypoglykemier kan upptäckas och avvärjas i förväg. Andelen falsklarm var tillfredställande låg. Ett alternativt förfarande är att varna användaren redan inför sänggående. Även detta scenario simulerades med goda resultat.



Liksom effekten av insulin är nödvändig att förstå, är kunskap om den glukoshöjande effekten av olika måltider essentiell för att kunna välja rätt måltidsdos och undvika höga blodsockervärden efter måltid, dvs. i den postprandiala fasen. Med hjälp av det insamlade datamaterialet kunde modeller av denna effekt bestämmas för ett antal olika rätter. Utvärderingen visar att modellerna kan reproducera det postprandiala blodsockret med acceptabel noggrannhet. Modellerna användes därefter för att utvärdera kliniska riktlinjer avseende postprandialt {blod-socker}. Slutsatsen var att riktlinjerna kan vara för snäva för vissa patienter och måltider. För att ytterligare stärka möjligheten att förutse blodsockernivån utarbetades en metod för att låta flera olika specialiserade prediktiva modeller samverka. Test av metoden på både simulerade och verkliga dataserier visade att robustheten i den prediktiva förmågan ökade. Slutligen addresserades problematiken med fördröjning av mätvärdet i en kontinuerlig glukossensor i förhållande till kapillära blod-sockermätningar, och med hjälp av en skattningsalgoritm kunde tidsfördröjningen reduceras. (Less)
Abstract
Diabetes is a disease characterized by insufficient capacity to regulate the blood glucose level. In insulin-dependent diabetes, multiple daily injections of insulin have to be administered. In-between scheduled visits to the care provider, the patient has to manage the glucose control independently. Insulin dosing is a non-trivial task and many patients find it difficult. This is reflected in the health statistics, that indicate that a majority of patients with diabetes have poor metabolic control with associate risks of several short and long term complications.



In this thesis, building blocks of a defence-in-depth approach to glucose self-management in insulin-dependent diabetes are investigated. Defence-in-depth is... (More)
Diabetes is a disease characterized by insufficient capacity to regulate the blood glucose level. In insulin-dependent diabetes, multiple daily injections of insulin have to be administered. In-between scheduled visits to the care provider, the patient has to manage the glucose control independently. Insulin dosing is a non-trivial task and many patients find it difficult. This is reflected in the health statistics, that indicate that a majority of patients with diabetes have poor metabolic control with associate risks of several short and long term complications.



In this thesis, building blocks of a defence-in-depth approach to glucose self-management in insulin-dependent diabetes are investigated. Defence-in-depth is a concept where technical and administrative systems work in cohort to divert potentially dangerous conditions and events. In the context of insulin-dependent diabetes this amounts to avoiding low (hypoglycemia) and high (hyperglycemia) glucose values. Data from the European DIADvisor project and from a local trial conducted with patients from Skåne University Hospital were used in the thesis.



A basis for improved glucose control is understanding and knowledge of the glucose-lowering effect of insulin, the insulin action, and the corresponding glucose-elevating effect produced by meal intake. Individualized models of these impacts, and methods to improve the predictive capacity of these models, were developed. Interesting properties, such as, time-variability and nonlinear effects, were found. The models allow for the glucose level to be predicted and different meal and bolus scenarios to be simulated. Using the models, the possibility to foresee and prevent nocturnal hypoglycemia was validated with good performance in a retrospective analysis on the collected data.



Recent advances in sensor technology have allowed for commercial systems where the glucose level is measured with a high sampling rate in the interstitial fluid. However, a known deficiency with this approach is the measurement lag introduced by equilibrium dynamics between the blood and interstitial compartments. A Kalman filter based approach to resolving this issue was developed and successfully validated in a case study.



Diabetes glucose dynamics is known to comprise both short and more long term time-variability. Merging different diversified models may prove to be a successful approach, as a means to improve performance and robustness under such conditions. A novel merging algorithm based in a Bayesian setting was developed. The suggested method admits for soft switching and interpolation between the different models based on an evaluation of the different predictors' recent performance, using a sliding data window, and by looking for data features identified to be correlated to switching. Different aspects of the merging approach were investigated, using a simulated dataset, and the concept was thereafter successfully validated, showing improved robustness to the prediction performance in comparison to relying on the individual prediction models.



Meal impact models were estimated for 56 different meal types, and a clustering analysis showed that a majority of these models could be represented by three base models. Cross-validation confirmed good predictive capacity. The insulin action and meal impact models were further used to assess whether clinical recommendations on postprandial glucose levels, issued by international patient and professional organizations, are realistic and achievable. An important finding was that the postprandial excursion of meals with rapid postprandial response may be impossible to restrain within the recommended boundaries for even moderate meal sizes. This difficulty is exaggerated for persons with slower than normal insulin action.



The above methods and models could contribute to improving already available technology in diabetes self-management such as, e.g., bolus dose guides in insulin pumps, warning systems in continuous glucose monitoring systems or in interpretation and implementation of postprandial recommendations.

%A Bayesian method to allow several specialized prediction models to work in cohort was also developed. Validation on both simulated and real-world data confirmed that the prediction robustness increased. Finally,

%Among these, the insulin model reconfirmed a previous result that the insulin action is heterogeneous across the glucose range, with elevated magnitude at low glucose values and reduced at high glucose values. (Less)
Please use this url to cite or link to this publication:
author
supervisor
opponent
  • Dr Hovorka, Roman, Cambridge University
organization
publishing date
type
Thesis
publication status
published
subject
keywords
Diabetes, model, insulin action, postprandial glucose
in
PhD Theses
volume
TFRT-1111
pages
194 pages
publisher
Department of Automatic Control, Lund Institute of Technology, Lund University
defense location
Lecture hall B, building M, Ole Römers väg 1, Lund University, Faculty of Engineering LTH, LUnd
defense date
2015-12-11 10:15
ISSN
0280-5316
ISBN
978-91-7623-575-1 (print)
978-91-7623-576-8 (web)
project
LCCC
language
English
LU publication?
yes
id
b1a9adca-9ed9-4a7b-8d32-9851b254259a (old id 8171278)
date added to LUP
2015-11-17 11:07:04
date last changed
2016-09-19 08:44:50
@phdthesis{b1a9adca-9ed9-4a7b-8d32-9851b254259a,
  abstract     = {Diabetes is a disease characterized by insufficient capacity to regulate the blood glucose level. In insulin-dependent diabetes, multiple daily injections of insulin have to be administered. In-between scheduled visits to the care provider, the patient has to manage the glucose control independently. Insulin dosing is a non-trivial task and many patients find it difficult. This is reflected in the health statistics, that indicate that a majority of patients with diabetes have poor metabolic control with associate risks of several short and long term complications. <br/><br>
<br/><br>
In this thesis, building blocks of a defence-in-depth approach to glucose self-management in insulin-dependent diabetes are investigated. Defence-in-depth is a concept where technical and administrative systems work in cohort to divert potentially dangerous conditions and events. In the context of insulin-dependent diabetes this amounts to avoiding low (hypoglycemia) and high (hyperglycemia) glucose values. Data from the European DIADvisor project and from a local trial conducted with patients from Skåne University Hospital were used in the thesis. <br/><br>
<br/><br>
A basis for improved glucose control is understanding and knowledge of the glucose-lowering effect of insulin, the insulin action, and the corresponding glucose-elevating effect produced by meal intake. Individualized models of these impacts, and methods to improve the predictive capacity of these models, were developed. Interesting properties, such as, time-variability and nonlinear effects, were found. The models allow for the glucose level to be predicted and different meal and bolus scenarios to be simulated. Using the models, the possibility to foresee and prevent nocturnal hypoglycemia was validated with good performance in a retrospective analysis on the collected data.<br/><br>
<br/><br>
Recent advances in sensor technology have allowed for commercial systems where the glucose level is measured with a high sampling rate in the interstitial fluid. However, a known deficiency with this approach is the measurement lag introduced by equilibrium dynamics between the blood and interstitial compartments. A Kalman filter based approach to resolving this issue was developed and successfully validated in a case study. <br/><br>
<br/><br>
Diabetes glucose dynamics is known to comprise both short and more long term time-variability. Merging different diversified models may prove to be a successful approach, as a means to improve performance and robustness under such conditions. A novel merging algorithm based in a Bayesian setting was developed. The suggested method admits for soft switching and interpolation between the different models based on an evaluation of the different predictors' recent performance, using a sliding data window, and by looking for data features identified to be correlated to switching. Different aspects of the merging approach were investigated, using a simulated dataset, and the concept was thereafter successfully validated, showing improved robustness to the prediction performance in comparison to relying on the individual prediction models.<br/><br>
<br/><br>
Meal impact models were estimated for 56 different meal types, and a clustering analysis showed that a majority of these models could be represented by three base models. Cross-validation confirmed good predictive capacity. The insulin action and meal impact models were further used to assess whether clinical recommendations on postprandial glucose levels, issued by international patient and professional organizations, are realistic and achievable. An important finding was that the postprandial excursion of meals with rapid postprandial response may be impossible to restrain within the recommended boundaries for even moderate meal sizes. This difficulty is exaggerated for persons with slower than normal insulin action. <br/><br>
<br/><br>
The above methods and models could contribute to improving already available technology in diabetes self-management such as, e.g., bolus dose guides in insulin pumps, warning systems in continuous glucose monitoring systems or in interpretation and implementation of postprandial recommendations. <br/><br>
%A Bayesian method to allow several specialized prediction models to work in cohort was also developed. Validation on both simulated and real-world data confirmed that the prediction robustness increased. Finally, <br/><br>
%Among these, the insulin model reconfirmed a previous result that the insulin action is heterogeneous across the glucose range, with elevated magnitude at low glucose values and reduced at high glucose values.},
  author       = {Ståhl, Fredrik},
  isbn         = {978-91-7623-575-1 (print)},
  issn         = {0280-5316},
  keyword      = {Diabetes,model,insulin action,postprandial glucose},
  language     = {eng},
  pages        = {194},
  publisher    = {Department of Automatic Control, Lund Institute of Technology, Lund University},
  school       = {Lund University},
  series       = {PhD Theses},
  title        = {Towards Defence In Depth In Diabetes Glucose Self-Management},
  volume       = {TFRT-1111},
  year         = {2015},
}