Artificial pancreas development in type 1 diabetic patients

Introduction and background: In type 1 diabetic patients good glycaemic control is associated with complication reduction. Nevertheless a minority of patients, also treated with insulin pumps and continuous glucose monitoring (SAP therapy) achieve a satisfactory metabolic control. Several researchers are developing automatic systems, called artificial pancreas (AP) or Closed Loop Control (CLC). This system are composed by an insulin pump, a continuous glucose monitoring device and a control algorithm which modifies insulin infusion from data derived by continuous glucose monitoring. Several AP models exist, composed by different insulin pumps, different continuous glucose monitoring system and by different control algorithms that determine the precision of glucose control. Method: we evaluated our AP model efficacy and safety at patients home compared to SAP therapy. In our AP model, the Algorithm is installed in a smartphone (DiAS, Diabetes Assistant) that communicate with pump and CGM thought blue tooth connection. We developed 5 studies that tested the system in free life condition, first during evening and night, than for 24 hours and for longer period (6 months). We finally evaluated this system in pediatric population. Results: In a randomized cross over study of 2 month AP use during evening and night vs SAP therapy, system usage improved time in target (70-180 mg/dl) from 58.1% to 66.7% ( P < 0.0001), reduce mean glucose concentration (162 mg/dl vs 167 mg/dl, P=0.0053) and time spent in hypoglycemia (<70 mg/dl) from 3.0% to 1.7% (P < 0.0001) and lead to reduction in HbA1c values. Extension of this study for a month using AP 24 hours/day demonstrated an improvement of time in target vs SAP (64.7 ± 7.6% vs. 59.7 ± 9.6%, P = 0.01), reduction of time below the target (1.9 ± 1.1% vs. 3.2 ± 1.8%, P = 0.001). A third trial evaluated a different algorithm for 2 weeks during overnight e for 2 weeks for 24 hours, comparing these period with 2 weeks of SAP therapy. In overnight period AP improved glucose metric vs SAP: time spent in hypoglycaemia dropped from 3.0% to 1.1% (P < 0.001), time in target increased from 61% to 75% (P < 0.001) , time spent above 180 mg/dl dropped from 37% to 24% (P < 0.001), the mean glucose concentration dropped from 163 to 150 mg/dL (P = 0.002). Similarly, metrics of glucose control in the 24-hour AP usage vs SAP demonstrated reduction of the time below target from 4.1% to 1.7% (P < 0.001), increase of time in target from 65% to 73% (P < 0.001), decrease of time above target from 32% to 25% (P = 0.001). Comparing the overnight and 24 hours CLC, a reduction in time spent in hypoglycaemia was observed when AP was used for 24 hours. A subgroup of patients extended AP use for other 5 months, confirming AP efficacy (time in target:77% vs. 66%, P<0.001, time in hypoglycaemia: 4.1% vs 1.3%, P < 0.001, time above target 31% vs 22%, P = 0.01). Finally we tested the system in paediatric population, enrolling in a summer camp 30 subject 5-9 years old. During the night AP reduced time in hypoglycaemia (P < 0.002), with no difference in time in target. During 24 hours we observed reduction of the time in hypoglycaemia, from 6.7% to 2.0% (P < 0.001), but an increase of mean glucose (147 mg/dL vs. 169 mg/dL, P < 0.001) and a decrease of time spent in target (63.1% vs. 56.8%, P = 0.022) Conclusions: These results demonstrated our model safety and efficacy. Some improvements are necessary to ameliorate glycaemiec control on pediatric population and during day time

Artificial pancreas development in type 1 diabetic patients

Introduction and background: In type 1 diabetic patients good glycaemic control is associated with complication reduction. Nevertheless a minority of patients, also treated with insulin pumps and continuous glucose monitoring (SAP therapy) achieve a satisfactory metabolic control. Several researchers are developing automatic systems, called artificial pancreas (AP) or Closed Loop Control (CLC). This system are composed by an insulin pump, a continuous glucose monitoring device and a control algorithm which modifies insulin infusion from data derived by continuous glucose monitoring. Several AP models exist, composed by different insulin pumps, different continuous glucose monitoring system and by different control algorithms that determine the precision of glucose control. Method: we evaluated our AP model efficacy and safety at patients home compared to SAP therapy. In our AP model, the Algorithm is installed in a smartphone (DiAS, Diabetes Assistant) that communicate with pump and CGM thought blue tooth connection. We developed 5 studies that tested the system in free life condition, first during evening and night, than for 24 hours and for longer period (6 months). We finally evaluated this system in pediatric population. Results: In a randomized cross over study of 2 month AP use during evening and night vs SAP therapy, system usage improved time in target (70-180 mg/dl) from 58.1% to 66.7% ( P < 0.0001), reduce mean glucose concentration (162 mg/dl vs 167 mg/dl, P=0.0053) and time spent in hypoglycemia (<70 mg/dl) from 3.0% to 1.7% (P < 0.0001) and lead to reduction in HbA1c values. Extension of this study for a month using AP 24 hours/day demonstrated an improvement of time in target vs SAP (64.7 ± 7.6% vs. 59.7 ± 9.6%, P = 0.01), reduction of time below the target (1.9 ± 1.1% vs. 3.2 ± 1.8%, P = 0.001). A third trial evaluated a different algorithm for 2 weeks during overnight e for 2 weeks for 24 hours, comparing these period with 2 weeks of SAP therapy. In overnight period AP improved glucose metric vs SAP: time spent in hypoglycaemia dropped from 3.0% to 1.1% (P < 0.001), time in target increased from 61% to 75% (P < 0.001) , time spent above 180 mg/dl dropped from 37% to 24% (P < 0.001), the mean glucose concentration dropped from 163 to 150 mg/dL (P = 0.002). Similarly, metrics of glucose control in the 24-hour AP usage vs SAP demonstrated reduction of the time below target from 4.1% to 1.7% (P < 0.001), increase of time in target from 65% to 73% (P < 0.001), decrease of time above target from 32% to 25% (P = 0.001). Comparing the overnight and 24 hours CLC, a reduction in time spent in hypoglycaemia was observed when AP was used for 24 hours. A subgroup of patients extended AP use for other 5 months, confirming AP efficacy (time in target:77% vs. 66%, P<0.001, time in hypoglycaemia: 4.1% vs 1.3%, P < 0.001, time above target 31% vs 22%, P = 0.01). Finally we tested the system in paediatric population, enrolling in a summer camp 30 subject 5-9 years old. During the night AP reduced time in hypoglycaemia (P < 0.002), with no difference in time in target. During 24 hours we observed reduction of the time in hypoglycaemia, from 6.7% to 2.0% (P < 0.001), but an increase of mean glucose (147 mg/dL vs. 169 mg/dL, P < 0.001) and a decrease of time spent in target (63.1% vs. 56.8%, P = 0.022) Conclusions: These results demonstrated our model safety and efficacy. Some improvements are necessary to ameliorate glycaemiec control on pediatric population and during day time.Introduzione: Nei pazienti affetti da diabete mellito di tipo 1, il buon controllo glicemico si associa con la riduzione delle complicanze. Tuttavia solo una parte di questi pazienti, anche se trattati con sistemi per il monitoraggio in continuo della glicemia e con microinfusori per la somministrazione in continuo di insulina (SAP therapy), raggiungono un controllo metabolico soddisfacente. Diversi gruppi di studio stanno sviluppando sistemi automatici, chiamati pancreas artificiale o sistemi ad ansa chiusa (CLC, closed loop control). Tale sistema è costituito da una pompa insulinica (microinfusore), da un sistema per il monitoraggio in continuo della glicemia e da un algoritmo di controllo in grado di modificare la velocità di infusione di insulina in maniera automatica, sulla base dei valori registrati dal sensore glicemico. Materiali e metodi: abbiamo valutato l'efficacia e la sicurezza del nostro modello di Pancreas Artificiale nei confronti della SAP therapy. Nel nostro modello di pancreas artificiale l'algoritmo di controllo è installato all'interno di uno smartphone (DiAS, Diabetes Assistant), in grado di comunicare via bluetooth con il sistema di monitoraggio in continuo della glicemia e con il microinfusore. Abbiamo portato a termine 5 studi, che saranno oggetto di questa tesi, nei quali abbiamo testato il sistema a domicilio del paziente, dapprima durante la notte, in seguito per l'intera giornata e per periodi progressivamente piu lunghi fino ad arrivare a 6 mesi di utilizzo. Abbiamo quindi testato il sistema in ambito pediatrico. Risultati: in un trial cross over randomizzato della durata di 2 mesi in cui si utilizzava il pancreas artificiale durante la sera e la notte, confrontato a SAP Therapy, l'utilizzo del sistema portava ad un incremento del tempo trascorso in target (70-180 mg/dl), dal 58.1% al 66.7% ( P < 0.0001), ad una riduzione della glicemia media, (162 mg/dl vs 167 mg/dl, P=0.0053) e del tempo trascorso in ipoglicemia (<70 mg/dl) dal 3.0% al 1.7% (P < 0.0001) e a una riduzione dei valori di emoglobina glicata. Il proseguimento di tale studio prevedeva l'utilizzo del pancreas artificiale per l'intera giornata per un mese, dimostrando nei confronti della SAP therapy, un miglioramento del tempo trascorso in target (64.7 ± 7.6% vs. 59.7 ± 9.6%, P = 0.01) e una riduzione del tempo trascorso in ipoglicemia (1.9 ± 1.1% vs. 3.2 ± 1.8%, P = 0.001). In un terzo trial abbiamo valutato un differente algoritmo di controllo per 2 settimane durante il periodo notturno e per 2 settimane durante l'intera giornata, paragonando tali periodi a settimane di SAP therapy. Durante il periodo notturno il pancreas artificiale ha ridotto il tempo trascorso in ipoglicemia dal 3.0% al 1.1% (P < 0.001), incrementato il tempo in target dal 61% al 75% (P < 0.001) ridotto la glicemia media da 163 a 150 mg/dL (P = 0.002). Allo stesso modo il pancreas artificiale ha migliorato il controllo glicemico anche nelle 24 ore, riducendo il tempo trascorso in ipoglicemia dal 4.1% al 1.7% (P < 0.001), incrementando il tempo trascorso nel target dal 65% al 73% (P < 0.001), riducendo il tempo trascorso in iperglicemia dal 32% al 25% (P = 0.001). Confrontando l'utilizzo notturno del pancreas artificiale con l'utilizzo nelle 24 ore si è osservata un ulteriore riduzione del tempo trascorso in ipoglicemia con l'utilizzo del sistema per l'intera giornata. Un sottogruppo di pazienti ha proseguito l'utilizzo del pancreas artificiale per ulteriori 5 mesi, confermando l'efficacia del sistema (tempo in target:77% vs. 66%, P<0.001, tempo in ipoglicemia: 4.1% vs 1.3%, P < 0.001, tempo in iperglicemia 31% vs 22%, P = 0.01). Infine abbiamo testato il sistema in una popolazione pediatrica durante un campo scuola estivo, arruolando pazienti diabetici di età compresa tra i 5 e i 9 anni. Durante il periodo notturno il pancreas artificiale ha portato ad una riduzione delle ipoglicemie (P < 0.002), senza differenze riguardo il tempo trascorso nel target. Durante le 24 ore si osservava una riduzione del tempo trascorso in ipoglicemia, dal 6.7% al 2.0% (P < 0.001), ma un incremento della glicemia media (147 mg/dL vs. 169 mg/dL, P < 0.001) e una riduzione dle tempo trascorso nel target (63.1% vs. 56.8%, P = 0.022). Conclusioni: questi risultati hanno dimostrato la sicurezza e l'efficacia del nostro modello di pancreas artificiale. Sono ovviamente necessari alcuni miglioramenti per portare ad ottimizzare il controllo in ambito pediatrico e durante le ore diurne

Glycaemic Control Among People with Type 1 Diabetes During Lockdown for the SARS-CoV-2 Outbreak in Italy

In late February 2020, due to the spread of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the Italian Government closed down all educational and sport activities. In March, it introduced further measures to stop the spread of coronavirus disease (COVID-19), placing the country in a state of almost complete lockdown. We report the impact of these restrictions on glucose control among people with type 1 diabetes (T1D)

Effectiveness of adding alarms to flash glucose monitoring in adults with type 1 diabetes under routine care

none6noAim: Whether glucose sensor alarms improve metabolic control and are accepted by individuals with diabetes is unclear. Here, we investigated whether switching from a standard flash glucose monitoring system (FGM1)&nbsp;to a system&nbsp;equipped with hypo- and hyperglycemia alarms (FGM2) improves glycemic control and psychological outcomes in adults with type 1 diabetes (T1D). Methods: Subjects with T1D and &gt; 4% of time in hypoglycemia or &gt; 40% of time in hyperglycemia were studied while wearing FGM1 (4&nbsp;weeks) and after switching to FGM2 for 8&nbsp;weeks. The primary endpoint was&nbsp;the change in time in range (TIR 70–180&nbsp;mg/dl [3.9–10.0&nbsp;mmol/L])&nbsp;after&nbsp;4 weeks of FGM2 use. Time below range (TBR), time above range (TAR), mean glucose, coefficient of variation (CV), sensor scans, treatment satisfaction, and hypoglycemia fear were secondary outcomes. Results: We included 38 subjects aged 33.7 ± 12.6&nbsp;year. During 4&nbsp;weeks of FGM2 use, TIR increased from 52.8 to 57.0% (p = 0.001), TBR decreased from 6.2 to 3.4% (p &lt; 0.0001) as did time &lt; 54&nbsp;mg/dl (from 1.4 to 0.3%, p &lt; 0.0001) and CV (from 39.6% to 36.1%, p &lt; 0.0001). These changes were confirmed after 8&nbsp;weeks of FGM2 use. Treatment satisfaction improved and fear of hypoglycemia decreased. Subjects who had &gt; 4% of time in hypoglycemia at baseline showed the greatest improvements in glucose control and treatment satisfaction. Conclusion: Switching from FGM1 to FGM2 improved TIR and treatment satisfaction and reduced fear of hypoglycemia. Participants who benefited most from switching from FGM1 to FGM2 were those prone to hypoglycemia.Boscari F.; Ferretto S.; Cavallin F.; Fadini G.P.; Avogaro A.; Bruttomesso D.Boscari, F.; Ferretto, S.; Cavallin, F.; Fadini, G. P.; Avogaro, A.; Bruttomesso, D

Effects of Hypoglycemia on Circulating Stem and Progenitor Cells in Diabetic Patients

Iatrogenic hypoglycemia is the most common acute diabetic complication, and it significantly increases morbidity. In people with diabetes, reduction in the levels of circulating stem and progenitor cells predicts adverse outcomes

Development of the metabolic syndrome and electrocardiographic features of left ventricular hypertrophy in middle-aged working subjects.

Background and aims. The metabolic syndrome (MS) leads to excess cardiovascular disease, including heart failure. Left ventricular hypertrophy (LVH) is common in MS patients, but it is unknown whether onsets of the MS and LVH coincide. Herein, we tested the association between development of the MS and of electrocardiographic LVH in a cohort of middle-aged individuals. Methods. We included 303 working subjects (mean age 43.0\ub16.2; 41% males), followed-up for 4.3\ub10.8 years. ATP-III MS components were determined. Electrocardiographic LVH features were assessed by the Sokolow and Cornell voltage indexes and the Rohmilt-Estes score. Results. At baseline, the Cornell index was significantly higher in subjects with (n=55; 18.2%) than in those without MS (12.8\ub16.4 vs 10.9\ub15.4 mm; p=0.023), while the Sokolow index and Rohmilt- Estes score were not different. At follow-up, individuals who developed (n=51) compared to those who did not develop MS showed a significant increase in Cornell voltage index (1.0\ub10.6 vs - 0.55\ub10.3 mm; p=0.035) and in Rohmilt-Estes score (0.17\ub10.17 vs -0.08\ub10.04; p=0.028). The change in Cornell index over time was directly correlated with change in the number of MS components (r=0.133; p=0.02) and HOMA-IR (r=0.117; p=0.046). The association between MS onset and increase in Cornell index / Rohmilt-Estes score was independent from confounders. Conclusions. In a young population of working subjects, the development of MS is associated with worsening features of LVH. Early LVH electrocardiographic screening in young subjects who develop the MS should be considered and performed using the Cornell voltage inde