المؤلفون: Faggionato, Edoardo, Schiavon, Michele, Ekhlaspour, Laya, Buckingham, Bruce, Dalla Man, Chiara

المصدر: IEEE Transactions on Biomedical Engineering, vol 71, iss 3

مصطلحات موضوعية: Humans, Adult, Middle Aged, Glucose, Diabetes Mellitus, Type 1, Insulin Resistance, Blood Glucose, Blood Glucose Self-Monitoring, Bayes Theorem, Insulin, Hypoglycemic Agents

الوصف: OBJECTIVE: Modeling the effect of meal composition on glucose excursion would help in designing decision support systems (DSS) for type 1 diabetes (T1D) management. In fact, macronutrients differently affect post-prandial gastric retention (GR), rate of appearance (R[Formula: see text]), and insulin sensitivity (S[Formula: see text]). Such variables can be estimated, in inpatient settings, from plasma glucose (G) and insulin (I) data using the Oral glucose Minimal Model (OMM) coupled with a physiological model of glucose transit through the gastrointestinal tract (reference OMM, R-OMM). Here, we present a model able to estimate those quantities in daily-life conditions, using minimally-invasive (MI) technologies, and validate it against the R-OMM. METHODS: Forty-seven individuals with T1D (weight =78±13 kg, age =42±10 yr) underwent three 23-hour visits, during which G and I were frequently sampled while wearing continuous glucose monitoring (CGM) and insulin pump (IP). Using a Bayesian Maximum A Posteriori estimator, R-OMM was identified from plasma G and I measurements, and MI-OMM was identified from CGM and IP data. RESULTS: The MI-OMM fitted the CGM data well and provided precise parameter estimates. GR and R[Formula: see text] model parameters were not significantly different using the MI-OMM and R-OMM (p 0.05) and the correlation between the two S[Formula: see text] was satisfactory ( ρ =0.77). CONCLUSION: The MI-OMM is usable to estimate GR, R[Formula: see text], and S[Formula: see text] from data collected in real-life conditions with minimally-invasive technologies. SIGNIFICANCE: Applying MI-OMM to datasets where meal compositions are available will allow modeling the effect of each macronutrient on GR, R[Formula: see text], and S[Formula: see text]. DSS could finally exploit this information to improve diabetes management.

وصف الملف: application/pdf

العلاقة: qt4zm3c05s; https://escholarship.org/uc/item/4zm3c05sTest

الإتاحة: https://escholarship.org/uc/item/4zm3c05sTest

المؤلفون: Faggionato, Edoardo, Schiavon, Michele, Ekhlaspour, Laya, Buckingham, Bruce A., Dalla Man, Chiara

المساهمون: MIUR

المصدر: IEEE Transactions on Biomedical Engineering ; volume 71, issue 3, page 977-986 ; ISSN 0018-9294 1558-2531

مصطلحات موضوعية: Biomedical Engineering

الإتاحة: https://doi.org/10.1109/tbme.2023.3324206Test
http://xplorestaging.ieee.org/ielx7/10/10445140/10286275.pdf?arnumber=10286275Test

المؤلفون: Faggionato, Edoardo, Laurenti, Marcello C., Vella, Adrian, Man, Chiara Dalla

المساهمون: MIUR, Departments of Excellence”, University of Padova, SID-Networking Project 2019, US National Institutes of Health, Mayo Clinic General Clinical Research Center, University of Padova Research

المصدر: IEEE Transactions on Biomedical Engineering ; volume 70, issue 9, page 2733-2740 ; ISSN 0018-9294 1558-2531

الإتاحة: https://doi.org/10.1109/tbme.2023.3262974Test
http://xplorestaging.ieee.org/ielx7/10/10235284/10086655.pdf?arnumber=10086655Test

المؤلفون: Faggionato, Edoardo, Guazzo, Alessandro, Pegolo, Elena, Carli, Ruggero, Bruschetta, Mattia, Favero, Simone Del

المساهمون: MIUR, Italian Minister for Education, Dipartimenti di Eccellenza

المصدر: IEEE Transactions on Biomedical Engineering ; volume 70, issue 9, page 2667-2678 ; ISSN 0018-9294 1558-2531

مصطلحات موضوعية: Biomedical Engineering

الإتاحة: https://doi.org/10.1109/tbme.2023.3261962Test
http://xplorestaging.ieee.org/ielx7/10/10235284/10081506.pdf?arnumber=10081506Test

المؤلفون: Faggionato, Edoardo, Schiavon, Michele, Man, Chiara Dalla

المصدر: 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)

الإتاحة: https://doi.org/10.1109/embc46164.2021.9629554Test
http://xplorestaging.ieee.org/ielx7/9629355/9629471/09629554.pdf?arnumber=9629554Test

المؤلفون: CASIRAGHI, MARTINA

المساهمون: DALLA MAN, CHIARA, FAGGIONATO, EDOARDO

مصطلحات موضوعية: pharmacokinetics, piperacillin, mathematical model, population analysis, personalized medicin

الوصف: open ; Un trattamento antibiotico mirato ed efficace è di vitale importanza per i pazienti ricoverati in terapia intensiva. Le loro gravi condizioni cliniche, spesso in rapida evoluzione, possono compromettere il successo terapeutico della terapia antibiotica. In questo elaborato vengono presentati dei modelli non lineari ad effetti misti della piperacillina, antibiotico comunemente somministrato per il trattamento delle infezioni nei pazienti critici. I modelli mirano a predire l’andamento della concentrazione del farmaco nel tempo, con il fine ultimo di identificare il dosaggio ottimale per questi pazienti. L’obiettivo di questa tesi consiste nell’identificazione dei parametri clinici che influenzano la cinetica della piperacillina e nello studio dell’effetto delle tecniche di depurazione extracorporea sull’eliminazione di questo antibiotico.

وصف الملف: application/pdf

العلاقة: Dipartimento di Ingegneria dell'Informazione - DEI; BIOINGEGNERIA Laurea Magistrale (D.M. 270/2004); 2023; https://hdl.handle.net/20.500.12608/65968Test

الإتاحة: https://doi.org/20.500.12608/65968Test
https://hdl.handle.net/20.500.12608/65968Test