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1.
Artigo em Inglês | MEDLINE | ID: mdl-32324063

RESUMO

Background: In silico trials in type 2 diabetes (T2D) would be useful for testing diabetes treatments and accelerating the development of new antidiabetic drugs. In this study, we present a T2D simulator able to reproduce the variability observed in a T2D population. The simulator also allows to safely experiment on virtual subjects with severe (and possibly rare) pathological conditions. Methods: A meal simulation model of glucose, insulin, and C-peptide systems, made of 15 differential equations and 39 parameters, has been identified using a system decomposition and forcing function Bayesian strategy on data of 51 T2D subjects undergoing a single triple-tracer mixed meal. One hundred T2D in silico subjects have been generated from the joint distribution of estimated model parameters. A case study is presented to illustrate the simulator use for testing a virtual drug (improving insulin action and secretion) in a subpopulation of rare, extremely impaired, T2D subjects. Results: The model well fitted T2D data and parameters were estimated with precision. Simulated plasma glucose, insulin, and C-peptide well matched the data (e.g., median [25th-75th percentile] glucose area under the curves of 6.9 [6.1-8.5] 104 mg/dL·min in silico vs. 7.0 [5.6-8.2] 104 mg/dL·min in vivo). The potential use of the simulator was shown in a case study, in which the (virtual) antidiabetic drug dose was optimized for very insulin-resistant T2D subjects. Conclusions: We have developed a T2D simulator that captures the behavior of T2D population during a meal, both in terms of average and intersubject variability. The simulator represents a cost-effective way to test new antidiabetic drugs, before moving to human trials.

2.
JCI Insight ; 5(7)2020 Apr 09.
Artigo em Inglês | MEDLINE | ID: mdl-32182220

RESUMO

BACKGROUNDMetabolic disorders such as type 2 diabetes have been associated with a decrease in insulin pulse frequency and amplitude. We hypothesized that the T allele at rs7903146 in TCF7L2, previously associated with ß cell dysfunction, would be associated with changes in these insulin pulse characteristics.METHODSTwenty-nine nondiabetic subjects (age 46 ± 2, BMI 28 ± 1 kg/m2) participated in this study. Of these, 16 were homozygous for the C allele at rs7903146 and 13 were homozygous for the T allele. Deconvolution of peripheral C-peptide concentrations allowed the reconstruction of portal insulin secretion over time. These data were used for subsequent analyses. Pulse orderliness was assessed by approximate entropy (ApEn), and the dispersion of insulin pulses was measured by a frequency dispersion index (FDI) after a Fast Fourier Transform (FFT) of individual insulin secretion rates.RESULTSDuring fasting conditions, the CC genotype group exhibited decreased pulse disorderliness compared with the TT genotype group (1.10 ± 0.03 vs. 1.19 ± 0.04, P = 0.03). FDI decreased in response to hyperglycemia in the CC genotype group, perhaps reflecting less entrainment of insulin secretion during fasting.CONCLUSIONDiabetes-associated variation in TCF7L2 is associated with decreased orderliness and pulse dispersion, unchanged by hyperglycemia. Quantification of ApEn and FDI could represent novel markers of ß cell health.FUNDINGThis work was funded by US NIH (DK78646, DK116231), University of Padova research grant CPDA145405, and Mayo Clinic General Clinical Research Center (UL1 TR000135).

3.
Artigo em Inglês | MEDLINE | ID: mdl-32125178

RESUMO

Background: Second-generation long-acting insulin glargine 300 U/mL (Gla-300) and degludec 100 U/mL (Deg-100) provide novel basal insulin therapies for the treatment of type 1 diabetes (T1D). Both offer a flatter pharmacokinetic (PK) profile than the previous generation of long-acting insulins, thus improving glycemic control while reducing hypoglycemic events. This work describes an in silico head-to-head comparison of the two basal insulins on 24-h glucose profiles and was used to guide the design of a clinical trial. Materials and Methods: The Universities of Virginia (UVA)/Padova T1D simulator describes the intra-/interday variability of glucose-insulin dynamics and thus provides a robust bench-test for assessing glucose control for basal insulin therapies. A PK model describing subcutaneous absorption of Deg-100, in addition to the one already available for Gla-300, has been developed based on T1D clinical data and incorporated into the simulator. One hundred in silico T1D subjects received a basal insulin dose (Gla-300 or Deg-100) for 12 weeks (8 weeks uptitration, 4 weeks stable dosing) by morning or evening administration in a basal/bolus regimen. The virtual patients were uptitrated to their individual doses with two different titration rules. Results: The last 2-week simulated continuous glucose monitoring data were used to calculate various outcome metrics for both basal insulin treatments, with primary outcome being the percent time in glucose target (70-140 mg/dL). The simulations show no statistically significant difference for Gla-300 versus Deg-100 in the main endpoints. Conclusions: This work suggests comparable glucose control using either Gla-300 or Deg-100 and was used to guide the design of a clinical trial intended to compare second-generation long-acting insulin analogues.

4.
Metabolism ; 105: 154175, 2020 04.
Artigo em Inglês | MEDLINE | ID: mdl-32045582

RESUMO

PURPOSE: Abnormal glucagon concentrations are a feature of prediabetes but it is uncertain if α-cell dysfunction contributes to a longitudinal decline in ß-cell function. We therefore sought to determine if a decline in ß-cell function is associated with a higher nadir glucagon in the postprandial period or with higher fasting glucagon. METHODS: This was a longitudinal study in which 73 non-diabetic subjects were studied on 2 occasions 6.6 ±â€¯0.3 years apart using a 2-hour, 7-sample oral glucose tolerance test. Disposition Index (DI) was calculated using the oral minimal model applied to the measurements of glucose, insulin, C-peptide concentrations during the studies. We subsequently examined the relationship of glucagon concentrations at baseline with change in DI (used as a measure of ß-cell function) after adjusting for changes in weight and the baseline value of DI. RESULTS: After adjusting for covariates, nadir postprandial glucagon concentrations were not associated with changes in ß-cell function as quantified by DI. On the other hand, fasting glucagon concentrations during the baseline study were inversely correlated with longitudinal changes in DI. CONCLUSIONS: Defects in α-cell function, manifest as elevated fasting glucagon, are associated with a subsequent decline in ß-cell function. It remains to be ascertained if abnormal α-cell function contributes directly to loss of ß-cell secretory capacity in the pathogenesis of type 2 diabetes.


Assuntos
Glucagon/sangue , Células Secretoras de Insulina/fisiologia , Adulto , Glicemia/análise , Peptídeo C/sangue , Jejum , Feminino , Teste de Tolerância a Glucose , Humanos , Insulina/sangue , Estudos Longitudinais , Masculino , Pessoa de Meia-Idade , Pâncreas/citologia , Pâncreas/crescimento & desenvolvimento , Período Pós-Prandial , Estado Pré-Diabético/metabolismo
5.
J Clin Endocrinol Metab ; 105(2)2020 Feb 01.
Artigo em Inglês | MEDLINE | ID: mdl-31972003

RESUMO

CONTEXT: The time-to-glucose-peak following the oral glucose tolerance test (OGTT) is a highly reproducible marker for diabetes risk. In obese youths, we lack evidence for the mechanisms underlying the effects of the TCF7L2 rs7903146 variant on glucose peak. METHODS: We analyzed the metabolic phenotype and the genotype for the TCF7L2 rs7903146 in 630 obese youths with normal (NGT) and impaired (IGT) glucose tolerance. Participants underwent a 3-hour, 9-point OGTT to estimate, using the oral minimal model, the disposition index (DI), the static (φstatic) and dynamic (φdynamic) components ß-cell responsiveness and insulin sensitivity (SI). In a subgroup (n = 241) longitudinally followed for 2 years, we estimated the effect of time-to-glucose-peak on glucose tolerance change. RESULTS: Participants were grouped into early (<30 minutes) and late (≥30 minutes) glucose peakers. A delayed glucose peak was featured by a decline in φstatic (P < .001) in the absence of a difference in φdynamic. The prevalence of T-risk allele for TCF7L2 rs7903146 variant significantly increased in the late peak group. A lower DI was correlated with higher glucose concentration at 1 and 2 hours, whereas SI was inversely associated with 1-hour glucose. Glucose peak <30 minutes was protective toward worsening of glucose tolerance overtime (odds ratio 0.35 [0.15-0.82]; P = .015), with no subjects progressing to NGT or persisting IGT, in contrast to the 40% of progressor in those with late glucose peak. CONCLUSION: The prevalence of T-risk allele for the TCF7L2 rs7903146 prevailed in the late time-to-glucose peak group, which in turn is associated with impaired ß-cell responsiveness to glucose (φ), thereby predisposing to prediabetes and diabetes in obese youths.

6.
IEEE Trans Biomed Eng ; 67(2): 624-631, 2020 02.
Artigo em Inglês | MEDLINE | ID: mdl-31150327

RESUMO

OBJECTIVE: Subcutaneous (sc) administration of long-acting insulin analogs is often employed in multiple daily injection (MDI) therapy of type 1 diabetes (T1D) to cover patient's basal insulin needs. Among these, insulin glargine 100 U/mL (Gla-100) and 300 U/mL (Gla-300) are formulations indicated for once daily sc administration in MDI therapy of T1D. A few semi-mechanistic models of sc absorption of insulin glargine have been proposed in the literature, but were not quantitatively assessed on a large dataset. The aim of this paper is to propose a model of sc absorption of insulin glargine able to describe the data and provide precise model parameters estimates with a clear physiological interpretation. METHODS: Three candidate models were identified on a total of 47 and 77 insulin profiles of T1D subjects receiving a single or repeated sc administration of Gla-100 or Gla-300, respectively. Model comparison and selection were performed on the basis of their ability to describe the data and numerical identifiability. RESULTS: The most parsimonious model is linear two-compartment and accounts for the insulin distribution between the two compartments after sc administration through parameter k. Between the two formulations, we report a lower fraction of insulin in the first versus second compartment (k = 86% versus 94% in Gla-100 versus Gla-300, p < 0.05), a lower dissolution rate from the first to the second compartment ([Formula: see text] versus 0.0008 min-1 in Gla-100 versus Gla-300, p << 0.001), and a similar rate of insulin absorption from the second compartment to plasma ([Formula: see text] versus 0.0016 min-1 in Gla-100 versus Gla-300, p = NS), in accordance with the mechanisms of insulin glargine protraction. CONCLUSIONS: The proposed model is able to both accurately describe plasma insulin data after sc administration and precisely estimate physiologically plausible parameters. SIGNIFICANCE: The model can be incorporated in simulation platforms potentially usable for optimizing basal insulin treatment strategies.

7.
Diabetes Technol Ther ; 22(2): 112-120, 2020 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-31769699

RESUMO

Objective: Safety data on Do-It-Yourself Artificial Pancreas Systems are missing. The most widespread in Europe is the AndroidAPS implementation of the OpenAPS algorithm. We used the UVA/Padova Type 1 Diabetes Simulator to in silico test safety and efficacy of this algorithm in different scenarios. Methods: We tested five configurations of the AndroidAPS algorithm differing in aggressiveness and patient's interaction with the system. All configurations were tested with insulin sensitivity variation of ±30%. The most promising configurations were tested in real-life scenarios: over- and underestimated bolus by 50%, bolus delivered 15 min before meal, and late bolus delivered 15 min after meal. Continuous Glucose Monitoring (CGM) time in ranges (TIRs) metrics were used to assess the glycemic control. Results: In silico testing showed that open-source closed-loop system AndroidAPS works effectively and safely. The best results were reached if AndroidAPS algorithm worked with microboluses and when half of calculated bolus was issued (mean glycemia 131 mg/dL, SD 27 mg/dL, TIR 91%, time between 54 and 70 mg/dL <1%, and low blood glucose index even <1). The meal bolus over- and underestimation as well as late bolus did not affect the TIR and, importantly, the time between 54 and 70 mg/dL. Conclusion: In silico testing proved that AndroidAPS implementation of the OpenAPS algorithm is safe and effective, and it showed a great potential to be tested in prospective home setting study.

8.
Diabetes Obes Metab ; 2019 Dec 05.
Artigo em Inglês | MEDLINE | ID: mdl-31808298

RESUMO

AIM: To evaluate the change in insulin sensitivity, ß-cell function and glucose absorption after 28 days of treatment with high and low doses of SAR425899, a novel dual glucagon-like peptide-1 receptor/glucagon receptor agonist, versus placebo. MATERIALS AND METHODS: Thirty-six overweight to obese subjects with type 2 diabetes were randomized to receive daily subcutaneous administrations of low-dose SAR425899 (0.03, 0.06 and 0.09 mg) and high-dose SAR425899 (0.06, 0.12 and 0.18 mg) or placebo for 28 days; dose escalation occurred after days 7 and 14. Mixed meal tolerance tests were conducted before treatment (day -1) and on days 1 and 28. Oral glucose and C-peptide minimal models were used to quantify metabolic indices of insulin sensitivity, ß-cell responsiveness and glucose absorption. RESULTS: With low-dose SAR425899, high-dose SAR425899 and placebo, ß-cell function from day -1 to day 28 increased by 163%, 95% and 23%, respectively. The change in area under the curve for the rate of meal glucose appearance between 0 and 120 minutes was -32%, -20% and 8%, respectively. CONCLUSIONS: After 28 days of treatment, SAR425899 improved postprandial glucose control by significantly enhancing ß-cell function and slowing glucose absorption rate.

9.
J Diabetes Sci Technol ; 13(6): 1008-1016, 2019 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-31645119

RESUMO

BACKGROUND: The objective of this research is to show the effectiveness of individualized hypoglycemia predictive alerts (IHPAs) based on patient-tailored glucose-insulin models (PTMs) for different subjects. Interpatient variability calls for PTMs that have been identified from data collected in free-living conditions during a one-month trial. METHODS: A new impulse-response (IR) identification technique has been applied to free-living data in order to identify PTMs that are able to predict the future glucose trends and prevent hypoglycemia events. Impulse response has been applied to seven patients with type 1 diabetes (T1D) of the University of Amsterdam Medical Centre. Individualized hypoglycemia predictive alert has been designed for each patient thanks to the good prediction capabilities of PTMs. RESULTS: The PTMs performance is evaluated in terms of index of fitting (FIT), coefficient of determination, and Pearson's correlation coefficient with a population FIT of 63.74%. The IHPAs are evaluated on seven patients with T1D with the aim of predicting in advance (between 45 and 10 minutes) the unavoidable hypoglycemia events; these systems show better performance in terms of sensitivity, precision, and accuracy with respect to previously published results. CONCLUSION: The proposed work shows the successful results obtained applying the IR to an entire set of patients, participants of a one-month trial. Individualized hypoglycemia predictive alerts are evaluated in terms of hypoglycemia prevention: the use of a PTM allows to detect 84.67% of the hypoglycemia events occurred during a one-month trial on average with less than 0.4% of false alarms. The promising prediction capabilities of PTMs can be a key ingredient for new generations of individualized model predictive control for artificial pancreas.

10.
BMC Med Inform Decis Mak ; 19(1): 163, 2019 08 16.
Artigo em Inglês | MEDLINE | ID: mdl-31419982

RESUMO

BACKGROUND: To understand user needs, system requirements and organizational conditions towards successful design and adoption of Clinical Decision Support Systems for Type 2 Diabetes (T2D) care built on top of computerized risk models. METHODS: The holistic and evidence-based CEHRES Roadmap, used to create eHealth solutions through participatory development approach, persuasive design techniques and business modelling, was adopted in the MOSAIC project to define the sequence of multidisciplinary methods organized in three phases, user needs, implementation and evaluation. The research was qualitative, the total number of participants was ninety, about five-seventeen involved in each round of experiment. RESULTS: Prediction models for the onset of T2D are built on clinical studies, while for T2D care are derived from healthcare registries. Accordingly, two set of DSSs were defined: the first, T2D Screening, introduces a novel routine; in the second case, T2D Care, DSSs can support managers at population level, and daily practitioners at individual level. In the user needs phase, T2D Screening and solution T2D Care at population level share similar priorities, as both deal with risk-stratification. End-users of T2D Screening and solution T2D Care at individual level prioritize easiness of use and satisfaction, while managers prefer the tools to be available every time and everywhere. In the implementation phase, three Use Cases were defined for T2D Screening, adapting the tool to different settings and granularity of information. Two Use Cases were defined around solutions T2D Care at population and T2D Care at individual, to be used in primary or secondary care. Suitable filtering options were equipped with "attractive" visual analytics to focus the attention of end-users on specific parameters and events. In the evaluation phase, good levels of user experience versus bad level of usability suggest that end-users of T2D Screening perceived the potential, but they are worried about complexity. Usability and user experience were above acceptable thresholds for T2D Care at population and T2D Care at individual. CONCLUSIONS: By using a holistic approach, we have been able to understand user needs, behaviours and interactions and give new insights in the definition of effective Decision Support Systems to deal with the complexity of T2D care.


Assuntos
Sistemas de Apoio a Decisões Clínicas , Diabetes Mellitus Tipo 2/diagnóstico , Diabetes Mellitus Tipo 2/etiologia , Adulto , Idoso , Simulação por Computador , Feminino , Humanos , Masculino , Programas de Rastreamento , Pessoa de Meia-Idade , Medição de Risco , Software , Telemedicina
11.
Am J Physiol Endocrinol Metab ; 317(3): E483-E493, 2019 Sep 01.
Artigo em Inglês | MEDLINE | ID: mdl-31265327

RESUMO

While the triple tracer isotope dilution method has enabled accurate estimation of carbohydrate turnover after a mixed meal, use of the simple carbohydrate glucose as the carbohydrate source limits its translational applicability to everyday meals that typically contain complex carbohydrates. Hence, utilizing the natural enrichment of [13C]polysaccharide in commercially available grains, we devised a novel tracer method to measure postprandial complex carbohydrate turnover and indices of insulin action and ß-cell function and compared the parameters to those obtained after a simple carbohydrate containing mixed meal. We studied healthy volunteers after either rice (n = 8) or sorghum (n = 8) and glucose (n = 16) containing mixed meals and modified the triple tracer technique to calculate carbohydrate turnover. All meals were matched for calories and macronutrient composition. Rates of meal glucose appearance (2,658 ± 736 vs. 4,487 ± 909 µM·kg-1·2 h-1), endogenous glucose production (-835 ± 283 vs. -1,123 ± 323 µM·kg-1·2 h-1) and glucose disappearance (1,829 ± 807 vs. 3,606 ± 839 µM·kg-1·2 h-1) differed (P < 0.01) between complex and simple carbohydrate containing meals, respectively. Interestingly, there were significant increase in indices of insulin sensitivity (32.5 ± 3.5 vs. 25.6 ± 3.2 10-5 (dl·kg-1·min-2)/pM, P = 0.006) and ß-cell responsivity (disposition index: 1,817 ± 234 vs. 1,236 ± 159 10-14 (dl·kg-1·min-2)/pM, P < 0.005) with complex than simple carbohydrate meals. We present a novel triple tracer approach to estimate postprandial turnover of complex carbohydrate containing mixed meals. We also report higher insulin sensitivity and ß-cell responsivity with complex than with simple carbohydrates in mixed meals of identical calorie and macronutrient compositions in healthy adults.

12.
Diabetes Care ; 42(8): 1593-1603, 2019 08.
Artigo em Inglês | MEDLINE | ID: mdl-31177185

RESUMO

Improvements in sensor accuracy, greater convenience and ease of use, and expanding reimbursement have led to growing adoption of continuous glucose monitoring (CGM). However, successful utilization of CGM technology in routine clinical practice remains relatively low. This may be due in part to the lack of clear and agreed-upon glycemic targets that both diabetes teams and people with diabetes can work toward. Although unified recommendations for use of key CGM metrics have been established in three separate peer-reviewed articles, formal adoption by diabetes professional organizations and guidance in the practical application of these metrics in clinical practice have been lacking. In February 2019, the Advanced Technologies & Treatments for Diabetes (ATTD) Congress convened an international panel of physicians, researchers, and individuals with diabetes who are expert in CGM technologies to address this issue. This article summarizes the ATTD consensus recommendations for relevant aspects of CGM data utilization and reporting among the various diabetes populations.

14.
Diabetes Technol Ther ; 21(3): 146-153, 2019 03.
Artigo em Inglês | MEDLINE | ID: mdl-30835533

RESUMO

OBJECTIVE: To develop and validate a new risk score for intraventricular hemorrhage (IVH) in preterm neonates based on continuous glucose monitoring (CGM). STUDY DESIGN: We retrospectively analyzed CGM traces obtained from 50 very preterm neonates, grouped into two sub-cohorts started on CGM within 12 and 48 h of birth, respectively. A CGM linked to an Artificial Intelligence Risk (CLAIR) index was developed to quantify glucose variability during the first 72 h of life in neonates with and without IVH. Brain-US was performed at least twice a day for the first 5 days of birth. An integrated remote monitoring platform was developed to capture major clinical events in real time and gather data for the risk index. The new score performance was further compared with other measures of glucose variability (coefficient of variation [CV] and standard deviation [SD]) and with a clinical risk index for babies II (CRIB-II) as a predictor of IVH event. The two cohorts were analyzed separately for internal validation of the method. RESULTS: The primary cohort consisted of 26 neonates (gestational age 30 [28, 31] weeks; BW1275 g[1090, 1750]). Controls (n = 23) exhibited higher CLAIR index than cases (P = 0.004). A cut-off of 0.69 for the new CLAIR index allowed a 100% sensitivity and an 83% specificity for IVH prediction. The CLAIR index was the sole significant predictor for IVH (P = 0.003) when compared with clinical variables, CV, SD, and CRIB-II. In a subgroup analysis in very low-birth-weight infants, the CLAIR index was the sole variable significantly associated with IVH (P = 0.009). Analysis on the secondary cohort (five cases and 16 controls) confirmed a higher CLAIR index in the controls (P = 0.008), in the absence of a difference for CV, SD, and CRIB-II between the two groups. CONCLUSION: CGM, combined with the AI-algorithm, provides a high-sensitivity index for risk detection of IVH that reflects the glycemic impairment preceding IVH.


Assuntos
Inteligência Artificial , Automonitorização da Glicemia/estatística & dados numéricos , Hemorragia Cerebral/diagnóstico , Recém-Nascido Prematuro/sangue , Medição de Risco/métodos , Feminino , Idade Gestacional , Humanos , Recém-Nascido , Masculino , Estudos Retrospectivos , Fatores de Risco
15.
Artigo em Inglês | MEDLINE | ID: mdl-30735983

RESUMO

OBJECTIVE: Glargine 100U/mL (Gla-100) and 300U/mL (Gla-300) are long-acting insulin analogs providing basal insulin supply in multiple daily injection (MDI) therapy of type 1 diabetes (T1D). Both insulins require extensive testing to arrive at the optimal dosing regimen, e.g. timing and amount. Here we aim at a simulation tool for evaluating benefits/risks of different dosing schemes and up-titration rules for both Gla-100 and Gla-300 before clinical testing. METHODS: A new pharmacokinetic (PK) model of both Gla-100 and Gla-300 was incorporated into the FDA-accepted UVA/Padova T1D simulator: specifically, a joint parameter distribution, built from PK parameter estimates, was used to generate individual PK parametrizations for each in silico subject. A virtual trial comparing Gla-100 vs. Gla-300 was performed and assessed against a clinical study to validate the glargine simulator. RESULTS: Like in vivo, in silico both insulins performed similarly with respect to glucose control: percent time of glucose between [80-140] mg/dL with Gla-100 vs. Gla-300 (primary endpoint) were 41.5±1.1% vs. 39.0±1.2% (P=0.11) in silico, 31.0±1.6% vs. 31.8±1.5% (P=0.73) in vivo. CONCLUSIONS: The glargine simulator reproduced the main findings of the clinical trial, proving its validity for testing MDI therapies. SIGNIFICANCE: In silico testing of MDI therapies can help designing clinical trials. Due to the more standardized settings in silico (e.g. standardized meals and strict adherence to titration rule), any potential treatment effect is reaching statistical significance in simulation vs. clinical trial.

16.
Am J Physiol Endocrinol Metab ; 316(5): E687-E694, 2019 05 01.
Artigo em Inglês | MEDLINE | ID: mdl-30807214

RESUMO

The characteristics of pulsatile insulin secretion are important determinants of type 2 diabetes pathophysiology, but they are understudied due to the difficulties in measuring pulsatile insulin secretion noninvasively. Deconvolution of either peripheral C-peptide or insulin concentrations offers an appealing alternative to hepatic vein catheterization. However, to do so, there are a series of methodological challenges to overcome. C-peptide has a relatively long half-life and accumulates in the circulation. On the other hand, peripheral insulin concentrations reflect relatively fast clearance and hepatic extraction as it leaves the portal circulation to enter the systemic circulation. We propose a method based on nonparametric stochastic deconvolution of C-peptide concentrations, using individually determined C-peptide kinetics, to overcome these limitations. The use of C-peptide (instead of insulin) concentrations allows estimation of portal (and not post-hepatic) insulin pulses, whereas nonparametric stochastic deconvolution allows evaluation of pulsatile signals without any a priori assumptions of pulse shape and occurrence. The only assumption required is the degree of smoothness of the (unknown) secretion rate. We tested this method first on simulated data and then on 29 nondiabetic subjects studied during euglycemia and hyperglycemia and compared our estimates with the profiles obtained from hepatic vein insulin concentrations. This method produced satisfactory results both in the ability to fit the data and in providing reliable estimates of pulsatile secretion, in agreement with hepatic vein measurements. In conclusion, the proposed method enables reliable and noninvasive measurement of pulsatile insulin secretion. Future studies will be needed to validate this method in people with type 2 diabetes.


Assuntos
Peptídeo C/sangue , Hiperglicemia/sangue , Secreção de Insulina/fisiologia , Insulina/sangue , Adulto , Peptídeo C/metabolismo , Simulação por Computador , Diabetes Mellitus Tipo 2/metabolismo , Feminino , Glucose/metabolismo , Voluntários Saudáveis , Veias Hepáticas , Humanos , Hiperglicemia/metabolismo , Insulina/metabolismo , Cinética , Masculino , Pessoa de Meia-Idade , Estatísticas não Paramétricas
17.
Diabetes Technol Ther ; 21(2): 73-80, 2019 02.
Artigo em Inglês | MEDLINE | ID: mdl-30649925

RESUMO

BACKGROUND: Use of artificial pancreas (AP) requires seamless interaction of device components, such as continuous glucose monitor (CGM), insulin pump, and control algorithm. Mobile AP configurations also include a smartphone as computational hub and gateway to cloud applications (e.g., remote monitoring and data review and analysis). This International Diabetes Closed-Loop study was designed to demonstrate and evaluate the operation of the inControl AP using different CGMs and pump modalities without changes to the user interface, user experience, and underlying controller. METHODS: Forty-three patients with type 1 diabetes (T1D) were enrolled at 10 clinical centers (7 United States, 3 Europe) and 41 were included in the analyses (39% female, >95% non-Hispanic white, median T1D duration 16 years, median HbA1c 7.4%). Two CGMs and two insulin pumps were tested by different study participants/sites using the same system hub (a smartphone) during 2 weeks of in-home use. RESULTS: The major difference between the system components was the stability of their wireless connections with the smartphone. The two sensors achieved similar rates of connectivity as measured by percentage time in closed loop (75% and 75%); however, the two pumps had markedly different closed-loop adherence (66% vs. 87%). When connected, all system configurations achieved similar glycemic outcomes on AP control (73% [mean] time in range: 70-180 mg/dL, and 1.7% [median] time <70 mg/dL). CONCLUSIONS: CGMs and insulin pumps can be interchangeable in the same Mobile AP system, as long as these devices achieve certain levels of reliability and wireless connection stability.


Assuntos
Glicemia/análise , Diabetes Mellitus Tipo 1/tratamento farmacológico , Hipoglicemiantes/administração & dosagem , Sistemas de Infusão de Insulina , Insulina/administração & dosagem , Pâncreas Artificial , Adolescente , Adulto , Idoso , Algoritmos , Automonitorização da Glicemia , Diabetes Mellitus Tipo 1/sangue , Feminino , Humanos , Hipoglicemiantes/uso terapêutico , Insulina/uso terapêutico , Masculino , Pessoa de Meia-Idade , Reprodutibilidade dos Testes , Smartphone , Resultado do Tratamento , Adulto Jovem
18.
Diabetes Obes Metab ; 21(2): 424-428, 2019 02.
Artigo em Inglês | MEDLINE | ID: mdl-30203536

RESUMO

The hypothalamic neuropeptide oxytocin not only modulates psychosocial function, but also contributes to metabolic regulation. We have recently shown that intranasal oxytocin acutely improves beta-cell responsivity and glucose tolerance in normal-weight men. In the present experiment, we investigated the acute glucoregulatory impact of oxytocin in obese men with impaired insulin sensitivity. Fifteen obese healthy men with an average body mass index of 35 kg/m2 and an average body fat content of 33% received a single intranasal dose (24 IU) of oxytocin before undergoing an oral glucose tolerance test. Results were analysed according to the oral minimal model and compared with our findings in normal-weight participants. In contrast to the results in normal-weight subjects, oxytocin did not blunt postprandial glucose and insulin excursions in obese men, and moreover failed to enhance beta-cell responsivity and glucose tolerance. These results indicate that pronounced obesity may be associated with a certain degree of resistance to the glucoregulatory impact of exogenous oxytocin, and underlines the need for further investigations into the potential of oxytocin to improve glucose homeostasis in the clinical context.


Assuntos
Glicemia/efeitos dos fármacos , Obesidade/tratamento farmacológico , Obesidade/metabolismo , Ocitocina/administração & dosagem , Administração Intranasal , Adolescente , Adulto , Glicemia/metabolismo , Índice de Massa Corporal , Estudos Cross-Over , Método Duplo-Cego , Intolerância à Glucose/tratamento farmacológico , Intolerância à Glucose/metabolismo , Intolerância à Glucose/patologia , Teste de Tolerância a Glucose , Humanos , Resistência à Insulina , Masculino , Obesidade/patologia , Ocitocina/farmacocinética , Falha de Tratamento , Adulto Jovem
19.
Comput Methods Programs Biomed ; 171: 133-140, 2019 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-27424482

RESUMO

BACKGROUND AND OBJECTIVE: The inter-subject variability characterizing the patients affected by type 1 diabetes mellitus makes automatic blood glucose control very challenging. Different patients have different insulin responses, and a control law based on a non-individualized model could be ineffective. The definition of an individualized control law in the context of artificial pancreas is currently an open research topic. In this work we consider two novel identification approaches that can be used for individualizing linear glucose-insulin models to a specific patient. METHODS: The first approach belongs to the class of black-box identification and is based on a novel kernel-based nonparametric approach, whereas the second is a gray-box identification technique which relies on a constrained optimization and requires to postulate a model structure as prior knowledge. The latter is derived from the linearization of the average nonlinear adult virtual patient of the UVA/Padova simulator. Model identification and validation are based on in silico data collected during simulations of clinical protocols designed to produce a sufficient signal excitation without compromising patient safety. The identified models are evaluated in terms of prediction performance by means of the coefficient of determination, fit, positive and negative max errors, and root mean square error. RESULTS: Both identification approaches were used to identify a linear individualized glucose-insulin model for each adult virtual patient of the UVA/Padova simulator. The resulting model simulation performance is significantly improved with respect to the performance achieved by a linear average model. CONCLUSIONS: The approaches proposed in this work have shown a good potential to identify glucose-insulin models for designing individualized control laws for artificial pancreas.


Assuntos
Insulina/administração & dosagem , Pâncreas Artificial/normas , Algoritmos , Diabetes Mellitus Tipo 1/tratamento farmacológico , Humanos
20.
Mol Psychiatry ; 24(10): 1513-1522, 2019 10.
Artigo em Inglês | MEDLINE | ID: mdl-29523870

RESUMO

Patients with psychotic disorders are at high risk for type 2 diabetes mellitus, and there is increasing evidence that patients display glucose metabolism abnormalities before significant antipsychotic medication exposure. In the present study, we examined insulin action by quantifying insulin sensitivity in first-episode psychosis (FEP) patients and unaffected siblings, compared to healthy individuals, using a physiological-based model and comprehensive assessment battery. Twenty-two unaffected siblings, 18 FEP patients, and 15 healthy unrelated controls were evaluated using a 2-h oral glucose tolerance test (OGTT), with 7 samples of plasma glucose and serum insulin concentration measurements. Insulin sensitivity was quantified using the oral minimal model method. Lipid, leptin, free fatty acids, and inflammatory marker levels were also measured. Anthropometric, nutrient, and activity assessments were conducted; total body composition and fat distribution were determined using whole-body dual-energy X-ray absorptiometry. Insulin sensitivity significantly differed among groups (F = 6.01 and 0.004), with patients and siblings showing lower insulin sensitivity, compared to controls (P = 0.006 and 0.002, respectively). Body mass index, visceral adipose tissue area (cm2), lipids, leptin, free fatty acids, inflammatory markers, and activity ratings were not significantly different among groups. There was a significant difference in nutrient intake with lower total kilocalories/kilogram body weight in patients, compared to siblings and controls. Overall, the findings suggest that familial abnormal glucose metabolism or a primary insulin signaling pathway abnormality is related to risk for psychosis, independent of disease expression and treatment effects. Future studies should examine underlying biological mechanisms of insulin signaling abnormalities in psychotic disorders.

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