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Rizzi A, Tartaglione L, Lucaccini Paoli L, Leo ML, Popolla V, Viti L, Barberio A, Di Leo M, Pontecorvi A, Pitocco D. Evaluation of time in tight range and the glycaemia risk index in adults with type 1 diabetes using an advanced hybrid closed loop system: A 1-year real-world assessment. Diabetes Obes Metab 2024; 26:4078-4086. [PMID: 39010292 DOI: 10.1111/dom.15766] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/25/2024] [Revised: 06/13/2024] [Accepted: 06/22/2024] [Indexed: 07/17/2024]
Abstract
AIM To assess the long-term glycaemic outcomes, with additional metrics, in adults with type 1 diabetes (T1D) using the Tandem t:slim X2 with Control-IQ technology advanced hybrid closed-loop (AHCL) system. METHODS This was a single-centre, retrospective study involving 56 T1D patients who transitioned to the Tandem t:slim X2 with Control-IQ system. The primary and secondary endpoints consisted of variations in time in tight range (TiTR; 70-140 mg/dL) and the glycaemia risk index (GRI), respectively. Additional standardized continuous glucose monitoring (CGM) metrics, mean sensor glucose, coefficient of variation, the glucose management indicator (GMI), HbA1c and insulin daily dose, were also evaluated. Variables were measured at baseline and at 15 days, 3 months, 6 months and 1 year after Tandem t:slim X2 Control-IQ initiation. Glucose outcomes are expressed as mean (standard deviation). RESULTS Use of Tandem t:slim X2 with Control-IQ over 1 year was associated with an increase in mean TiTR, from 38.11% (17.05%) to 43.10% (13.20%) (P = .059), and with a decline in the GRI, from 41.03 (25.48) to 28.55 (16.27) (P = .008). CGM metrics, including time in range and time above range, showed consistent improvements. Mean sensor glucose, the GMI and HbA1c decreased significantly over time. After an initial increase, insulin daily dose remained stable throughout the 12 months. CONCLUSIONS The results highlight the sustained effectiveness of Tandem t:slim X2 with Control-IQ in improving glycaemic outcomes over 1 year and support the use of this technology for the management of T1D.
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Affiliation(s)
- Alessandro Rizzi
- Diabetes Care Unit, Fondazione Policlinico Agostino Gemelli, Universita' Cattolica del Sacro Cuore, Rome, Italy
| | - Linda Tartaglione
- Diabetes Care Unit, Fondazione Policlinico Agostino Gemelli, Universita' Cattolica del Sacro Cuore, Rome, Italy
| | - Lorenzo Lucaccini Paoli
- Diabetes Care Unit, Fondazione Policlinico Agostino Gemelli, Universita' Cattolica del Sacro Cuore, Rome, Italy
| | - Maria Laura Leo
- Diabetes Care Unit, Fondazione Policlinico Agostino Gemelli, Universita' Cattolica del Sacro Cuore, Rome, Italy
| | - Valentina Popolla
- Diabetes Care Unit, Fondazione Policlinico Agostino Gemelli, Universita' Cattolica del Sacro Cuore, Rome, Italy
| | - Luca Viti
- Diabetes Care Unit, Fondazione Policlinico Agostino Gemelli, Universita' Cattolica del Sacro Cuore, Rome, Italy
| | - Annarita Barberio
- Diabetes Care Unit, Fondazione Policlinico Agostino Gemelli, Universita' Cattolica del Sacro Cuore, Rome, Italy
| | - Mauro Di Leo
- Diabetes Care Unit, Fondazione Policlinico Agostino Gemelli, Universita' Cattolica del Sacro Cuore, Rome, Italy
| | - Alfredo Pontecorvi
- Department of Endocrinology, Fondazione Policlinico Agostino Gemelli, Universita' Cattolica del Sacro Cuore, Rome, Italy
| | - Dario Pitocco
- Diabetes Care Unit, Fondazione Policlinico Agostino Gemelli, Universita' Cattolica del Sacro Cuore, Rome, Italy
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Resmini E, Zarra E, Dotti S, Rotondi G, Cornaghi AV, Madaschi S, Cimino E, Massari G, Pezzaioli LC, Buoso C, Sandri M, Girelli A. Impact on Glycemia Risk Index and other metrics in type 1 adult patients switching to Advanced Hybrid Closed-Loop systems: a one-year real-life experience. Eur J Med Res 2024; 29:365. [PMID: 39004734 PMCID: PMC11247841 DOI: 10.1186/s40001-024-01946-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2024] [Accepted: 06/23/2024] [Indexed: 07/16/2024] Open
Abstract
BACKGROUND Advanced Hybrid Closed-Loop system (AHCL) has profoundly changed type 1 diabetes therapy. This study primarily aimed to assess the impact on Glycemia Risk Index (GRI) and other continuous glucose monitoring (CGM) metrics when switching from one of four insulin strategies to AHCL in type 1 adult patients. METHODS A single-center, retrospective pre/post observational study; 198 patients (age 44.4 ± 12.7 years, 115 females/83 males, diabetes duration 24.7 ± 11.6 years, HbA1c 7.4 ± 1%), treated with different insulin therapies (MDI, CSII, SAP with PLGS, HCL) were assessed before and after switching to an AHCL (MiniMed 780G, Diabeloop Roche, Tandem Control-IQ) at 1, 3, 6, and 12 months. Mixed-effects multivariable regression models were used to estimate the mean pre/post variations at different time points, adjusted for potential confounders. RESULTS A month after the switch, there was an improvement in CGM metrics and HbA1c for all patients: GRI -10.7, GMI -0.27%, CV -2.1%, TAR>250 -3.7%, TAR180-250 -5.6%, TIR + 9.7%, HbA1c -0.54% (all p < 0.001). This improvement was maintained throughout the observational period (at 3, 6, and 12 months, with all p-values < 0.001). When improvements across the 780, Diabeloop, and Tandem CIQ devices were compared: Diabeloop demonstrated significantly better performance in terms of GRI, GMI, CV, TAR>250 at T1 (for all p < 0.01); 780 recorded highest average decrease in TAR180-250 (p = 0.020), while Tandem achieved the most significant reduction in TBR54-69 (p = 0.004). CONCLUSIONS Adopting an AHCL leads to a rapid and sustained improvement in GRI and other parameters of metabolic control for up to a year, regardless of prior insulin therapies, baseline conditions or brands.
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Affiliation(s)
- Eugenia Resmini
- Medicina Generale Diabetologia, Dipartimento di Continuità di Cura e Fragilità, ASST Spedali Civili, Brescia, Italy.
| | - Emanuela Zarra
- Medicina Generale Diabetologia, Dipartimento di Continuità di Cura e Fragilità, ASST Spedali Civili, Brescia, Italy
| | - Silvia Dotti
- Medicina Generale Diabetologia, Dipartimento di Continuità di Cura e Fragilità, ASST Spedali Civili, Brescia, Italy
| | - Giulia Rotondi
- Medicina Generale Diabetologia, Dipartimento di Continuità di Cura e Fragilità, ASST Spedali Civili, Brescia, Italy
| | - Angelo Vincenzo Cornaghi
- Medicina Generale Diabetologia, Dipartimento di Continuità di Cura e Fragilità, ASST Spedali Civili, Brescia, Italy
| | - Sara Madaschi
- Medicina Generale Diabetologia, Dipartimento di Continuità di Cura e Fragilità, ASST Spedali Civili, Brescia, Italy
| | - Elena Cimino
- Medicina Generale Diabetologia, Dipartimento di Continuità di Cura e Fragilità, ASST Spedali Civili, Brescia, Italy
| | - Giulia Massari
- Medicina Generale Diabetologia, Dipartimento di Continuità di Cura e Fragilità, ASST Spedali Civili, Brescia, Italy
| | - Letizia Chiara Pezzaioli
- Medicina Generale Diabetologia, Dipartimento di Continuità di Cura e Fragilità, ASST Spedali Civili, Brescia, Italy
| | - Caterina Buoso
- Medicina Generale Diabetologia, Dipartimento di Continuità di Cura e Fragilità, ASST Spedali Civili, Brescia, Italy
| | - Marco Sandri
- Medicina Generale Diabetologia, Dipartimento di Continuità di Cura e Fragilità, ASST Spedali Civili, Brescia, Italy
| | - Angela Girelli
- Medicina Generale Diabetologia, Dipartimento di Continuità di Cura e Fragilità, ASST Spedali Civili, Brescia, Italy
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Panfil K, Redel JM, Vandervelden CA, Lockee B, Kahkoska AR, Tallon EM, Williams DD, Clements MA. Correlation Between the Glycemia Risk Index and Longitudinal Hemoglobin A1c in Children and Young Adults With Type 1 Diabetes. J Diabetes Sci Technol 2024; 18:771-778. [PMID: 38715286 PMCID: PMC11307230 DOI: 10.1177/19322968241247219] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Abstract
BACKGROUND The glycemia risk index (GRI) is a composite metric developed and used to estimate quality of glycemia in adults with diabetes who use continuous glucose monitor (CGM) devices. In a cohort of youth with type 1 diabetes (T1D), we examined the utility of the GRI for evaluating quality of glycemia between clinic visits by analyzing correlations between the GRI and longitudinal glycated hemoglobin A1c (HbA1c) measures. METHOD Using electronic health records and CGM data, we conducted a retrospective cohort study to analyze the relationship between the GRI and longitudinal HbA1c measures in youth (T1D duration ≥1 year; ≥50% CGM wear time) receiving care from a Midwest pediatric diabetes clinic network (March 2016 to May 2022). Furthermore, we analyzed correlations between HbA1c and the GRI high and low components, which reflect time spent with high/very high and low/very low glucose, respectively. RESULTS In this cohort of 719 youth (aged = 2.5-18.0 years [median = 13.4; interquartile range [IQR] = 5.2]; 50.5% male; 83.7% non-Hispanic White; 68.0% commercial insurance), baseline GRI scores positively correlated with HbA1c measures at baseline and 3, 6, 9, and 12 months later (r = 0.68, 0.65, 0.60, 0.57, and 0.52, respectively). At all time points, strong positive correlations existed between HbA1c and time spent in hyperglycemia. Substantially weaker, negative correlations existed between HbA1c and time spent in hypoglycemia. CONCLUSIONS In youth with T1D, the GRI may be useful for evaluating quality of glycemia between scheduled clinic visits. Additional CGM-derived metrics are needed to quantify risk for hypoglycemia in this population.
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Affiliation(s)
| | | | | | - Brent Lockee
- Children’s Mercy Kansas City, Kansas
City, MO, USA
| | - Anna R. Kahkoska
- The University of North Carolina at
Chapel Hill, Chapel Hill, NC, USA
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Morrison D, Vogrin S, Zaharieva DP. Assessment of Glycemia Risk Index and Standard Continuous Glucose Monitoring Metrics in a Real-World Setting of Exercise in Adults With Type 1 Diabetes: A Post-Hoc Analysis of the Type 1 Diabetes and Exercise Initiative. J Diabetes Sci Technol 2024; 18:787-794. [PMID: 38629861 PMCID: PMC11307213 DOI: 10.1177/19322968241246458] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Abstract
BACKGROUND Standardized reporting of continuous glucose monitoring (CGM) metrics does not provide extra weighting for very high or very low glucose, despite their distinct clinical significance, and thus may underestimate glycemic risk in people with type 1 diabetes (T1D) during exercise. Glycemia Risk Index (GRI) is a novel composite metric incorporating clinician-validated extra weighting for glycemic extremes, which may provide a novel summary index of glycemia risk around exercise. METHODS Adults (≥18 years) in the T1D EXercise Initiative study wore CGM and activity trackers for four weeks. For this analysis, exercise days were defined as 24 hours following ≥20 minutes of exercise, with no other exercise in the 24-hour period. Sedentary days were defined as any 24 hours with no recorded exercise within that period or the preceding 24 hours. Linear mixed-effects regression was used to evaluate exercise effects on GRI and CGM metrics within 24 hours postexercise. RESULTS In 408 adults with T1D with >70% CGM and activity data, GRI on exercise (N = 3790) versus sedentary days (N = 1865) was significantly lower (mean [SD]: 29.9 [24.0] vs 34.0 [26.1], respectively, absolute mean difference -1.70 [-2.73, -0.67], P < .001), a ~5% reduction in glycemic risk. Percent time in range (TIR; 70-180 mg/dL) increased on exercise days (absolute mean difference 2.67 [1.83, 3.50], P < .001), as did time below range (TBR; relative mean difference 1.17 [1.12, 1.22], P < .001), while time above range (TAR) decreased (relative mean difference 0.84 [0.79, 0.88], P < .001). CONCLUSIONS Glycemia Risk Index improved on exercise versus sedentary days, despite increased TBR, which is weighted most heavily in the GRI calculation, due to a robust reduction in TAR.
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Affiliation(s)
- Dale Morrison
- Department of Medicine, St Vincent’s
Hospital Melbourne, The University of Melbourne, Melbourne, VIC, Australia
- Department of Endocrinology and
Diabetes, St Vincent’s Hospital Melbourne, Melbourne, VIC, Australia
| | - Sara Vogrin
- Department of Medicine, St Vincent’s
Hospital Melbourne, The University of Melbourne, Melbourne, VIC, Australia
| | - Dessi P. Zaharieva
- Division of Pediatric Endocrinology,
Department of Pediatrics, Stanford University, Stanford, CA, USA
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Panfil K, Vandervelden CA, Lockee B, Tallon EM, Williams DD, Lee JM. The Glycemia Risk Index Predicts Performance of Diabetes Self-Management Habits in Youth With Type 1 Diabetes Mellitus. J Diabetes Sci Technol 2024; 18:779-786. [PMID: 38708581 PMCID: PMC11307237 DOI: 10.1177/19322968241247215] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/07/2024]
Abstract
BACKGROUND The Glycemia Risk Index (GRI) was developed in adults with diabetes and is a validated metric of quality of glycemia. Little is known about the relationship between GRI and type 1 diabetes (T1D) self-management habits, a validated assessment of youths' engagement in habits associated with glycemic outcomes. METHOD We retrospectively examined the relationship between GRI and T1D self-management habits in youth with T1D who received care from a Midwest pediatric diabetes clinic network. The GRI was calculated using seven days of continuous glucose monitor (CGM) data, and T1D self-management habits were assessed ±seven days from the GRI score. A mixed-effects Poisson regression model was used to evaluate the total number of habits youth engaged in with GRI, glycated hemoglobin A1c (HbA1c), age, race, ethnicity, and insurance type as fixed effects and participant ID as a random effect to account for multiple clinic visits per individual. RESULTS The cohort included 1182 youth aged 2.5 to 18.0 years (mean = 13.8, SD = 3.5) comprising 50.8% male, 84.6% non-Hispanic White, and 64.8% commercial insurance users across a total of 6029 clinic visits. Glycemia Risk Index scores decreased as total number of habits performed increased, suggesting youth who performed more self-management habits achieved a higher quality of glycemia. CONCLUSIONS In youth using CGMs, GRI may serve as an easily obtainable metric to help identify youth with above target glycemia, and engagement/disengagement in the T1D self-management habits may inform clinicians with suitable interventions for improving glycemic outcomes.
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Affiliation(s)
| | | | - Brent Lockee
- Children’s Mercy Kansas City, Kansas
City, MO, USA
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Lee MH, Vogrin S, Jones TW, O’Neal DN. Hybrid Closed-Loop Versus Manual Insulin Delivery in Adults With Type 1 Diabetes: A Post Hoc Analysis Using the Glycemia Risk Index. J Diabetes Sci Technol 2024; 18:764-770. [PMID: 38372246 PMCID: PMC11307212 DOI: 10.1177/19322968241231307] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/20/2024]
Abstract
BACKGROUND Glycemia risk index (GRI) is a novel composite metric assessing overall glycemic risk, accounting for both hypoglycemia and hyperglycemia and weighted toward extremes. Data assessing GRI as an outcome measure in closed-loop studies and its relation with conventional key continuous glucose monitoring (CGM) metrics are limited. METHODS A post hoc analysis was performed to evaluate the sensitivity of GRI in assessing glycemic quality in adults with type 1 diabetes randomized to 26 weeks hybrid closed-loop (HCL) or manual insulin delivery (control). The primary outcome was GRI comparing HCL with control. Comparisons were made with changes in other CGM metrics including time in range (TIR), time above range (TAR), time below range (TBR), and glycemic variability (standard deviation [SD] and coefficient of variation [CV]). RESULTS GRI with HCL (N = 61) compared with control (N = 59) was significantly lower (mean [SD] 33.5 [11.7] vs 56.1 [14.4], respectively; mean difference -22.8 [-27.2, -18.3], P = .001). The mean increase in TIR was +14.8 (11.0, 18.5)%. GRI negatively correlated with TIR for combined arms (r = -.954; P = .001), and positively with TAR >250 mg/dL (r = .901; P = .001), TBR < 54 mg/dL (r = .416; P = .001), and glycemic variability (SD [r = .916] and CV [r = .732]; P = .001 for both). CONCLUSIONS Twenty-six weeks of HCL improved GRI, in addition to other CGM metrics, compared with standard insulin therapy. The improvement in GRI was proportionally greater than the change in TIR, and GRI correlated with all CGM metrics. We suggest that GRI may be an appropriate primary outcome for closed-loop trials.
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Affiliation(s)
- Melissa H. Lee
- Department of Medicine, The University
of Melbourne, Melbourne, VIC, Australia
- Department of Endocrinology and
Diabetes, St Vincent’s Hospital Melbourne, Melbourne, VIC, Australia
| | - Sara Vogrin
- Department of Medicine, The University
of Melbourne, Melbourne, VIC, Australia
| | - Timothy W. Jones
- Department of Endocrinology and
Diabetes, Perth Children’s Hospital, Perth, WA, Australia
- Telethon Kids Institute, The University
of Western Australia, Perth, WA, Australia
- School of Paediatrics and Child Health,
The University of Western Australia, Perth, WA, Australia
| | - David N. O’Neal
- Department of Medicine, The University
of Melbourne, Melbourne, VIC, Australia
- Department of Endocrinology and
Diabetes, St Vincent’s Hospital Melbourne, Melbourne, VIC, Australia
- The Australian Centre for Accelerating
Diabetes Innovations, Melbourne, VIC, Australia
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Passanisi S, Salzano G, Bombaci B, Minuto N, Bassi M, Bonfanti R, Scialabba F, Mozzillo E, Di Candia F, Monti S, Graziani V, Maffeis C, Piona CA, Arnaldi C, Tosini D, Felappi B, Roppolo R, Zanfardino A, Delvecchio M, Lo Presti D, Calzi E, Ripoli C, Franceschi R, Reinstadler P, Rabbone I, Maltoni G, Alibrandi A, Zucchini S, Marigliano M, Lombardo F. Sustained Effectiveness of an Advanced Hybrid Closed-Loop System in a Cohort of Children and Adolescents With Type 1 Diabetes: A 1-Year Real-World Study. Diabetes Care 2024; 47:1084-1091. [PMID: 38626260 DOI: 10.2337/dc23-2311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/03/2023] [Accepted: 03/28/2024] [Indexed: 04/18/2024]
Abstract
OBJECTIVE To investigate glucose metrics and identify potential predictors of the achievement of glycemic outcomes in children and adolescents during their first 12 months of MiniMed 780G use. RESEARCH DESIGN AND METHODS This multicenter, longitudinal, real-world study recruited 368 children and adolescents with type 1 diabetes (T1D) starting SmartGuard technology between June 2020 and June 2022. Ambulatory glucose profile data were collected during a 15-day run-in period (baseline), 2 weeks after automatic mode activation, and every 3 months. The influence of covariates on glycemic outcomes after 1 year of MiniMed 780G use was assessed. RESULTS After 15 days of automatic mode use, all glucose metrics improved compared with baseline (P < 0.001), except for time below range (P = 0.113) and coefficient of variation (P = 0.330). After 1 year, time in range (TIR) remained significantly higher than at baseline (75.3% vs. 62.8%, P < 0.001). The mean glycated hemoglobin (HbA1c) over the study duration was lower than the previous year (6.9 ± 0.6% vs. 7.4 ± 0.9%, P < 0.001). Time spent in tight range (70-140 mg/dL) was 51.1%, and the glycemia risk index was 27.6. Higher TIR levels were associated with a reduced number of automatic correction boluses (P < 0.001), fewer SmartGuard exits (P = 0.021), and longer time in automatic mode (P = 0.030). Individuals with baseline HbA1c >8% showed more relevant improvement in TIR levels (from 54.3% to 72.3%). CONCLUSIONS Our study highlights the sustained effectiveness of MiniMed 780G among youth with T1D. Findings suggest that even children and adolescents with low therapeutic engagement may benefit from SmartGuard technology.
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Affiliation(s)
- Stefano Passanisi
- Department of Human Pathology in Adult and Developmental Age "Gaetano Barresi," University of Messina, Messina, Italy
| | - Giuseppina Salzano
- Department of Human Pathology in Adult and Developmental Age "Gaetano Barresi," University of Messina, Messina, Italy
| | - Bruno Bombaci
- Department of Human Pathology in Adult and Developmental Age "Gaetano Barresi," University of Messina, Messina, Italy
| | - Nicola Minuto
- Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Istituto Giannina Gaslini, Genoa, Italy
| | - Marta Bassi
- Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Istituto Giannina Gaslini, Genoa, Italy
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, Genoa, Italy
| | - Riccardo Bonfanti
- Pediatric Diabetology Unit, Department of Pediatrics, Diabetes Research Institute, IRCCS San Raffaele Scientific Institute, Vita Salute San Raffaele University, Milan, Italy
| | - Francesco Scialabba
- Pediatric Diabetology Unit, Department of Pediatrics, Diabetes Research Institute, IRCCS San Raffaele Scientific Institute, Vita Salute San Raffaele University, Milan, Italy
| | - Enza Mozzillo
- Section of Pediatrics, Department of Translational Medical Science, Regional Center of Pediatric Diabetes, Federico II University of Naples, Naples, Italy
| | - Francesca Di Candia
- Section of Pediatrics, Department of Translational Medical Science, Regional Center of Pediatric Diabetes, Federico II University of Naples, Naples, Italy
| | - Sara Monti
- Pediatrics Unit, Department of Woman's and Child and Adolescent Health, Azienda Unità Sanitaria Locale (AUSL) Romagna, Bufalini Hospital, Cesena, Italy
| | - Vanna Graziani
- Pediatrics Unit, Department of Woman's and Child and Adolescent Health, AUSL Romagna, S. Maria delle Croci Hospital, Ravenna Italy
| | - Claudio Maffeis
- Pediatric Diabetes and Metabolic Disorders Unit, Regional Center for Pediatric Diabetes, University City Hospital, Verona, Italy
| | - Claudia Anita Piona
- Pediatric Diabetes and Metabolic Disorders Unit, Regional Center for Pediatric Diabetes, University City Hospital, Verona, Italy
| | - Claudia Arnaldi
- Unitá Operativa Semplice Diabetologia Pediatrica ASL Viterbo, Viterbo, Italy
| | - Davide Tosini
- Unitá Operativa Semplice Diabetologia Pediatrica ASL Viterbo, Viterbo, Italy
| | - Barbara Felappi
- U.S. Auxoendocrinologia Pediatrica, Unitá Operativa Complessa Pediatria-Clinica Pediatrica, Azienda Socio Sanitaria Territoriale (ASST) Spedali Civili, Brescia, Italy
| | - Rosalia Roppolo
- Unitá Operativa Semplice Dipartimentale Diabetologia Pediatrica, Dipartimento di Pediatria, Ospedale dei Bambini, Palermo, Italia
| | - Angela Zanfardino
- Department of Pediatrics, Regional Center of Pediatric Diabetology "G.Stoppoloni," University of Campania "Luigi Vanvitelli," Naples, Italy
| | - Maurizio Delvecchio
- Department of Biotechnological and Applied Clinical Sciences (DISCAB), University of L'Aquila, L'Aquila, Italy
| | - Donatella Lo Presti
- Regional Referral Centre of Pediatric Diabetes, University Hospital "Policlinico," Catania, Italy
| | - Elena Calzi
- Department of Pedatrics and Neonatology, ASST Crema Hospital, Crema, Italy
| | - Carlo Ripoli
- Pediatric Diabetology Unit, Department of Pediatrics, ASL 8 Cagliari, Cagliari, Italy
| | - Roberto Franceschi
- Department of Pediatrics, S. Chiara Hospital of Trento, Azienda Provinciale per i Servizi Sanitari, Trento, Italy
| | - Petra Reinstadler
- Ospedale di Bolzano - Azienda Sanitaria dell'Alto Adige, Bolzano, Italy
| | - Ivana Rabbone
- Division of Pediatrics, Department of Health Sciences, University of Piemonte Orientale, Novara, Italy
| | - Giulio Maltoni
- Pediatric Unit, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy
| | - Angela Alibrandi
- Unit of Statistical and Mathematical Sciences, Department of Economics, University of Messina, Messina, Italy
| | | | - Marco Marigliano
- Pediatric Diabetes and Metabolic Disorders Unit, Regional Center for Pediatric Diabetes, University City Hospital, Verona, Italy
| | - Fortunato Lombardo
- Department of Human Pathology in Adult and Developmental Age "Gaetano Barresi," University of Messina, Messina, Italy
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Fagherazzi G, Aguayo GA, Zhang L, Hanaire H, Picard S, Sablone L, Vergès B, Hamamouche N, Detournay B, Joubert M, Delemer B, Guilhem I, Vambergue A, Gourdy P, Hadjadj S, Velayoudom FL, Guerci B, Larger E, Jeandidier N, Gautier JF, Renard E, Potier L, Benhamou PY, Sola A, Bordier L, Bismuth E, Prévost G, Kessler L, Cosson E, Riveline JP. Heterogeneity of glycaemic phenotypes in type 1 diabetes. Diabetologia 2024:10.1007/s00125-024-06179-4. [PMID: 38780786 DOI: 10.1007/s00125-024-06179-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Accepted: 04/08/2024] [Indexed: 05/25/2024]
Abstract
AIMS/HYPOTHESIS Our study aims to uncover glycaemic phenotype heterogeneity in type 1 diabetes. METHODS In the Study of the French-speaking Society of Type 1 Diabetes (SFDT1), we characterised glycaemic heterogeneity thanks to a set of complementary metrics: HbA1c, time in range (TIR), time below range (TBR), CV, Gold score and glycaemia risk index (GRI). Applying the Discriminative Dimensionality Reduction with Trees (DDRTree) algorithm, we created a phenotypic tree, i.e. a 2D visual mapping. We also carried out a clustering analysis for comparison. RESULTS We included 618 participants with type 1 diabetes (52.9% men, mean age 40.6 years [SD 14.1]). Our phenotypic tree identified seven glycaemic phenotypes. The 2D phenotypic tree comprised a main branch in the proximal region and glycaemic phenotypes in the distal areas. Dimension 1, the horizontal dimension, was positively associated with GRI (coefficient [95% CI]) (0.54 [0.52, 0.57]), HbA1c (0.39 [0.35, 0.42]), CV (0.24 [0.19, 0.28]) and TBR (0.11 [0.06, 0.15]), and negatively with TIR (-0.52 [-0.54, -0.49]). The vertical dimension was positively associated with TBR (0.41 [0.38, 0.44]), CV (0.40 [0.37, 0.43]), TIR (0.16 [0.12, 0.20]), Gold score (0.10 [0.06, 0.15]) and GRI (0.06 [0.02, 0.11]), and negatively with HbA1c (-0.21 [-0.25, -0.17]). Notably, socioeconomic factors, cardiovascular risk indicators, retinopathy and treatment strategy were significant determinants of glycaemic phenotype diversity. The phenotypic tree enabled more granularity than traditional clustering in revealing clinically relevant subgroups of people with type 1 diabetes. CONCLUSIONS/INTERPRETATION Our study advances the current understanding of the complex glycaemic profile in people with type 1 diabetes and suggests that strategies based on isolated glycaemic metrics might not capture the complexity of the glycaemic phenotypes in real life. Relying on these phenotypes could improve patient stratification in type 1 diabetes care and personalise disease management.
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Affiliation(s)
- Guy Fagherazzi
- Deep Digital Phenotyping Research Unit, Department of Precision Health, Luxembourg Institute of Health, Strassen, Luxembourg.
| | - Gloria A Aguayo
- Deep Digital Phenotyping Research Unit, Department of Precision Health, Luxembourg Institute of Health, Strassen, Luxembourg
| | - Lu Zhang
- Bioinformatics Platform, Luxembourg Institute of Health, Strassen, Luxembourg
| | - Hélène Hanaire
- Department of Diabetology, Metabolic Diseases and Nutrition, CHU Toulouse, University of Toulouse, Toulouse, France
- Francophone Foundation for Diabetes Research, Paris, France
| | - Sylvie Picard
- Endocrinology and Diabetes, Point Medical, Dijon, France
| | - Laura Sablone
- Francophone Foundation for Diabetes Research, Paris, France
| | - Bruno Vergès
- Department of Endocrinology-Diabetology, Inserm LNC UMR1231, University of Burgundy, Dijon, France
| | | | | | - Michael Joubert
- Service d'Endocrinologie-Diabétologie (Endocrinology/Diabetes Unit), Centre Hospitalier Universitaire de Caen, Caen, France
| | - Brigitte Delemer
- Endocrinology, Diabetology and Nutrition Department, Robert Debré University Hospital, Reims, France
| | - Isabelle Guilhem
- Department of Endocrinology, Diabetes and Nutrition, University Hospital of Rennes, Rennes, France
| | - Anne Vambergue
- Endocrinology, Diabetology, Metabolism and Nutrition Department, Lille University Hospital, Lille, France
| | - Pierre Gourdy
- Department of Diabetology, Metabolic Diseases and Nutrition, CHU Toulouse, University of Toulouse, Toulouse, France
- Institute of Metabolic and Cardiovascular Diseases, UMR1297 Inserm/UPS, Toulouse University, Toulouse, France
| | - Samy Hadjadj
- Institut du thorax, INSERM, CNRS, Université Nantes, CHU Nantes, Nantes, France
| | - Fritz-Line Velayoudom
- Department of Endocrinology-Diabetology, University Hospital of Guadeloupe, Pointe-À-Pitre, France
- Inserm UMR1283, CNRS UMR8199, European Genomic Institute for Diabetes (EGID), Lille, France
| | - Bruno Guerci
- Department of Endocrinology, Diabetology, and Nutrition, Brabois Adult Hospital, University of Lorraine, Vandoeuvre-Lès-Nancy, France
| | - Etienne Larger
- University Paris Cité, Institut Cochin, U1016, Inserm, Paris, France
- Diabetology Department, Cochin Hospital, AP-HP, Paris, France
| | - Nathalie Jeandidier
- Department of Endocrinology, Diabetes and Nutrition, Hôpitaux Universitaires de Strasbourg, Université de Strasbourg, Strasbourg, France
| | - Jean-François Gautier
- Institut Necker Enfants Malades, Inserm U1151, CNRS UMR 8253, IMMEDIAB Laboratory, Paris, France
- Centre Universitaire de Diabétologie et de ses Complications, AP-HP, Hôpital Lariboisière, Paris, France
| | - Eric Renard
- Institute of Functional Genomics, University of Montpellier, CNRS, Inserm, Montpellier, France
- Department of Endocrinology, Diabetes, Nutrition, Montpellier University Hospital, Montpellier, France
| | - Louis Potier
- Institut Necker Enfants Malades, Inserm U1151, CNRS UMR 8253, IMMEDIAB Laboratory, Paris, France
- Department of Diabetology, Endocrinology and Nutrition, AP-HP, Bichat Hospital, Paris, France
| | | | - Agnès Sola
- Diabetology Department, Cochin Hospital, AP-HP, Paris, France
| | - Lyse Bordier
- Service d'Endocrinologie, Hôpital Bégin, Saint Mandé, France
| | - Elise Bismuth
- Robert-Debré University Hospital, Department of Paediatric Endocrinology and Diabetology, AP-HP, University of Paris, Paris, France
| | - Gaëtan Prévost
- Department of Endocrinology, Diabetes and Metabolic Diseases, Normandie Université, UNIROUEN, Rouen University Hospital, Centre d'Investigation Clinique (CIC-CRB)-Inserm 1404, Rouen University Hospital, Rouen, France
| | - Laurence Kessler
- Department of Endocrinology, Diabetes and Nutrition, Hôpitaux Universitaires de Strasbourg, Université de Strasbourg, Strasbourg, France
| | - Emmanuel Cosson
- Department of Endocrinology-Diabetology-Nutrition, AP-HP, Avicenne Hospital, Paris 13 University, Sorbonne Paris Cité, CRNH-IdF, CINFO, Bobigny, France
- Equipe de Recherche en Epidémiologie Nutritionnelle (EREN), Université Sorbonne Paris Nord and Université Paris CitéInserm, INRAE, CNAM, Centre of Research in Epidemiology and StatisticS (CRESS), Bobigny, France
| | - Jean-Pierre Riveline
- Institut Necker Enfants Malades, Inserm U1151, CNRS UMR 8253, IMMEDIAB Laboratory, Paris, France
- Centre Universitaire de Diabétologie et de ses Complications, AP-HP, Hôpital Lariboisière, Paris, France
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9
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Cai L, Shen W, Li J, Wang B, Sun Y, Chen Y, Gao L, Xu F, Xiao X, Wang N, Lu Y. Association between glycemia risk index and arterial stiffness in type 2 diabetes. J Diabetes Investig 2024; 15:614-622. [PMID: 38251792 PMCID: PMC11060162 DOI: 10.1111/jdi.14153] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/02/2023] [Revised: 01/05/2024] [Accepted: 01/10/2024] [Indexed: 01/23/2024] Open
Abstract
AIM This study aims to investigate the association of glycemia risk index (GRI), a novel composite metric derived from continuous glucose monitoring (CGM), with arterial stiffness in patients with type 2 diabetes. MATERIALS AND METHODS A total of 342 adults with type 2 diabetes were enrolled between April and June 2023 from 11 communities in Shanghai, China. Medical examinations, including measurements of anthropometric parameters, blood pressure, and venous blood samples were conducted. Brachial-ankle pulse wave velocity (baPWV) was examined to evaluate arterial stiffness. All the participants underwent a 14 day CGM recording and GRI was calculated from the CGM data. RESULTS The mean age was 70.3 ± 6.8 years, and 162 (47.4%) were male. Participants with a higher baPWV had significantly higher levels of GRI and hyperglycemia component (both P for trend < 0.05). Linear regression revealed the significant positive linear associations of the GRI with baPWV in unadjusted or adjusted models (All P < 0.05). In the multivariable logistic analysis, each increase in the GRI quartile was associated with a 1.30-fold (95% CI 1.01-1.68, P for trend < 0.05) higher prevalence of increased arterial stiffness after adjustment for age, sex, BMI, diabetes duration, current smoking status, blood pressure, and lipid profile. Subgroup analyses showed that the association between the GRI quartiles and increased arterial stiffness was stronger among participants with a diabetes duration ≥15 years (P for interaction = 0.014). CONCLUSION Glycemia risk index assessed by continuous glucose monitoring is associated with increased arterial stiffness in type 2 diabetes.
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Affiliation(s)
- Lingli Cai
- Institute and Department of Endocrinology and Metabolism, Shanghai Ninth People's HospitalShanghai Jiao Tong University School of MedicineShanghaiChina
| | - Wenqi Shen
- Institute and Department of Endocrinology and Metabolism, Shanghai Ninth People's HospitalShanghai Jiao Tong University School of MedicineShanghaiChina
| | - Jiang Li
- Institute and Department of Endocrinology and Metabolism, Shanghai Ninth People's HospitalShanghai Jiao Tong University School of MedicineShanghaiChina
| | - Bin Wang
- Institute and Department of Endocrinology and Metabolism, Shanghai Ninth People's HospitalShanghai Jiao Tong University School of MedicineShanghaiChina
| | - Ying Sun
- Institute and Department of Endocrinology and Metabolism, Shanghai Ninth People's HospitalShanghai Jiao Tong University School of MedicineShanghaiChina
| | - Yi Chen
- Institute and Department of Endocrinology and Metabolism, Shanghai Ninth People's HospitalShanghai Jiao Tong University School of MedicineShanghaiChina
| | - Ling Gao
- Key Laboratory of Endocrine Glucose and Lipids Metabolism and Brain AgingMinistry of EducationJinanShandongChina
- Department of EndocrinologyShandong Provincial Hospital Affiliated to Shandong First Medical UniversityJinanShandongChina
| | - Fei Xu
- iHuman Institute, School of Life Science and TechnologyShanghaiTech UniversityShanghaiChina
| | - Xinhua Xiao
- Department of Medical Research Center, Peking Union Medical College HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Ningjian Wang
- Institute and Department of Endocrinology and Metabolism, Shanghai Ninth People's HospitalShanghai Jiao Tong University School of MedicineShanghaiChina
| | - Yingli Lu
- Institute and Department of Endocrinology and Metabolism, Shanghai Ninth People's HospitalShanghai Jiao Tong University School of MedicineShanghaiChina
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10
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Passanisi S, Piona C, Salzano G, Marigliano M, Bombaci B, Morandi A, Alibrandi A, Maffeis C, Lombardo F. Aiming for the Best Glycemic Control Beyond Time in Range: Time in Tight Range as a New Continuous Glucose Monitoring Metric in Children and Adolescents with Type 1 Diabetes Using Different Treatment Modalities. Diabetes Technol Ther 2024; 26:161-166. [PMID: 37902743 DOI: 10.1089/dia.2023.0373] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/31/2023]
Abstract
Introduction: To evaluate time in tight range (TITR) 70-140 mg/dL (3.9-7.8 mmol/L), its correlation with standard continuous glucose monitoring (CGM) metrics and the clinical variables that possibly have a substantial impact on its value, in a large cohort of pediatric subjects using different treatment strategies. Materials and Methods: A total of 854 children and adolescents with type 1 diabetes were consecutively recruited in this real world, dual center, cross-sectional study. Participants were categorized into four treatment groups (multiple daily injections [MDI] + real-time CGM, MDI + intermittently scanned CGM, sensor augmented pump, and hybrid closed loop [HCL]). Demographical and clinical data, including CGM data, were collected and analyzed. Results: The overall study population exhibited an average TITR of 36.4% ± 12.8%. HCL users showed higher TITR levels compared to the other treatment groups (P < 0.001). A time in range (TIR) cut-off value of 71.9% identified subjects achieving a TITR ≥50% (area under curve [AUC] 0.98; 95% confidence interval 0.97-0.99, P < 0.001), and a strong positive correlation between these two metrics was observed (r = 0.95, P < 0.001). An increase in TIR of 1% was associated with 1.84 (R2 Nagelkerke = 0.35, P < 0.001) increased likelihood of achieving TITR ≥50%. Use of HCL systems (B = 7.78; P < 0.001), disease duration (B = -0.26, P = 0.006), coefficient of variation (B = -0.30, P = 0.004), and glycated hemoglobin (B = -8.82; P < 0.001) emerged as significant predictors of TITR levels. Conclusions: Our study highlights that most children and adolescents with type 1 diabetes present TITR levels below 50%, except those using HCL. Tailored interventions and strategies should be implemented to increase TITR.
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Affiliation(s)
- Stefano Passanisi
- Department of Human Pathology in Adult and Developmental Age "Gaetano Barresi," University of Messina, Messina, Italy
| | - Claudia Piona
- Pediatric Diabetes and Metabolic Disorders Unit, Regional Center for Pediatric Diabetes, University City Hospital, Verona, Italy
| | - Giuseppina Salzano
- Department of Human Pathology in Adult and Developmental Age "Gaetano Barresi," University of Messina, Messina, Italy
| | - Marco Marigliano
- Pediatric Diabetes and Metabolic Disorders Unit, Regional Center for Pediatric Diabetes, University City Hospital, Verona, Italy
| | - Bruno Bombaci
- Department of Human Pathology in Adult and Developmental Age "Gaetano Barresi," University of Messina, Messina, Italy
| | - Anita Morandi
- Pediatric Diabetes and Metabolic Disorders Unit, Regional Center for Pediatric Diabetes, University City Hospital, Verona, Italy
| | - Angela Alibrandi
- Department of Economics, Unit of Statistical and Mathematical Sciences, University of Messina, Messina, Italy
| | - Claudio Maffeis
- Pediatric Diabetes and Metabolic Disorders Unit, Regional Center for Pediatric Diabetes, University City Hospital, Verona, Italy
| | - Fortunato Lombardo
- Department of Human Pathology in Adult and Developmental Age "Gaetano Barresi," University of Messina, Messina, Italy
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11
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Passanisi S, Lombardo F, Mameli C, Bombaci B, Macedoni M, Zuccotti G, Dovc K, Battelino T, Salzano G, Delvecchio M. Safety, Metabolic and Psychological Outcomes of Medtronic MiniMed 780G™ in Children, Adolescents and Young Adults: A Systematic Review. Diabetes Ther 2024; 15:343-365. [PMID: 38038896 PMCID: PMC10838896 DOI: 10.1007/s13300-023-01501-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Accepted: 10/20/2023] [Indexed: 12/02/2023] Open
Abstract
The MiniMed™ 780G is a second-generation automated insulin delivery system that implements a modified proportional-integral-derivative algorithm with some features of an MD-Logic artificial pancreas algorithm. The system may deliver automatic correction boluses up to every 5 min, and it allows the user to choose between three glucose target setpoints (100, 110 and 120 mg/dL). We aimed to review the current evidence on this device in children, adolescents, and young adults living with type 1 diabetes. We screened 783 papers, but only 31 manuscripts were included in this review. Data on metabolic outcomes show that this system is safe as regards severe hypoglycaemia and diabetic ketoacidosis. The glycated haemoglobin may drop to levels about 7%, with CGM reports showing a time in range of 75-80%. The time above range and the time below range are within the recommended target in most of the subjects. Few studies evaluated the psychological outcomes. This system seems to be more effective than the first-generation automated insulin delivery systems. The MiniMed™ 780G has been associated with an improvement in sleep quality in subjects living with diabetes and their caregivers, along with an improvement in treatment satisfaction. Psychological distress is as reduced as the glucose control is improved. We also discuss some case reports describing particular situations in clinical practice. Finally, we think that data show that this system is a further step towards the improvement of the treatment of diabetes as concerns both metabolic and psychological outcomes.
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Affiliation(s)
- Stefano Passanisi
- Department of Human Pathology in Adult and Developmental Age "Gaetano Barresi", University of Messina, Messina, Italy
| | - Fortunato Lombardo
- Department of Human Pathology in Adult and Developmental Age "Gaetano Barresi", University of Messina, Messina, Italy
| | - Chiara Mameli
- Department of Pediatrics, Buzzi Children's Hospital, University of Milan, Milan, Italy
- Department of Biomedical and Clinical Science, University of Milan, Milan, Italy
| | - Bruno Bombaci
- Department of Human Pathology in Adult and Developmental Age "Gaetano Barresi", University of Messina, Messina, Italy
| | - Maddalena Macedoni
- Department of Pediatrics, Buzzi Children's Hospital, University of Milan, Milan, Italy
| | - Gianvincenzo Zuccotti
- Department of Pediatrics, Buzzi Children's Hospital, University of Milan, Milan, Italy
- Department of Biomedical and Clinical Science, University of Milan, Milan, Italy
| | - Klemen Dovc
- University Medical Center Ljubljana, University of Ljubljana, Ljubljana, Slovenia
| | - Tadej Battelino
- University Medical Center Ljubljana, University of Ljubljana, Ljubljana, Slovenia
| | - Giuseppina Salzano
- Department of Human Pathology in Adult and Developmental Age "Gaetano Barresi", University of Messina, Messina, Italy
| | - Maurizio Delvecchio
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy.
- Metabolic Disorders and Clinical Genetics, "Giovanni XXIII" Children's Hospital, AOU Policlinico-Giovanni XXIII, Via Giovanni Amendola 207, 70126, Bari, BA, Italy.
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12
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Lepore G, Borella ND, Castagna G, Ippolito S, Bonfadini S, Corsi A, Scaranna C, Dodesini AR, Bellante R, Trevisan R. Advanced Hybrid Closed-Loop System Achieves and Maintains Recommended Time in Range Levels for Up To 2 Years: Predictors of Best Efficacy. Diabetes Technol Ther 2024; 26:49-58. [PMID: 37902785 DOI: 10.1089/dia.2023.0261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/31/2023]
Abstract
Aim: To evaluate the long-term efficacy, up to 2 years, of an advanced hybrid closed-loop (AHCL) system and to assess predictors of best results of the therapy. Methods: We retrospectively evaluated 296 adults with type 1 diabetes mellitus [mean age 42.8 ± 16.5 years, men 42.9%, duration of diabetes 22.5 ± 12.8 years, body mass index 24.9 ± 4.7 kg/m2, baseline glycated hemoglobin (HbA1c) 63.4 ± 12.2 mmol/mol (8.0 ± 1.1%) ] who used the MiniMed™ 780G system. Demographic and clinical data were recorded. Continuous glucose monitoring (CGM)-derived metrics and insulin requirement were analyzed from the 4 weeks before and from every quarter after the switch to the AHCL system. Results: In the first quarter of AHCL treatment, all CGM metrics improved. Time in range (TIR) increased from 58.1 ± 17.5% to 70.3 ± 9.5% (P < 0.0001). The improvement lasted for up to 2 years of observation regardless of previous insulin therapies. Throughout the period of observation, 53.4% of participants achieved mean TIR >70%, 92.6% mean time below range <4%, and 46% mean glucose management indicator <53 mmol/mol (7.0%). At univariable logistic regression older age, lower baseline HbA1c and insulin requirement were associated with mean TIR >70%. At multivariable analysis, lower HbA1c remained independently associated with a better glycemic control. However, mean TIR increased more in participants with a higher baseline HbA1c. Conclusions: Switching to an AHCL leads to a rapid improvement in glycemic control lasting for up to 24 months along with a low risk for hypoglycemia, confirming the safety of the system. Lower baseline HbA1c was the main predictor of better efficacy of therapy, although higher baseline HbA1c was associated with the greatest improvement in mean TIR.
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Affiliation(s)
- Giuseppe Lepore
- Unit of Endocrine Diseases and Diabetology, Department of Medicine, ASST Papa Giovanni XXIII, Bergamo, Italy
| | - Nicolò Diego Borella
- Unit of Endocrine Diseases and Diabetology, Department of Medicine, ASST Papa Giovanni XXIII, Bergamo, Italy
| | - Giona Castagna
- Unit of Endocrine Diseases and Diabetology, Department of Medicine, ASST Papa Giovanni XXIII, Bergamo, Italy
- Department of Medicine, Università degli Studi di Milano-Bicocca, Milan, Italy
| | - Silvia Ippolito
- Unit of Endocrine Diseases and Diabetology, Department of Medicine, ASST Papa Giovanni XXIII, Bergamo, Italy
| | - Silvia Bonfadini
- Unit of Endocrine Diseases and Diabetology, Department of Medicine, ASST Papa Giovanni XXIII, Bergamo, Italy
| | - Anna Corsi
- Unit of Endocrine Diseases and Diabetology, Department of Medicine, ASST Papa Giovanni XXIII, Bergamo, Italy
| | - Cristiana Scaranna
- Unit of Endocrine Diseases and Diabetology, Department of Medicine, ASST Papa Giovanni XXIII, Bergamo, Italy
| | - Alessandro Roberto Dodesini
- Unit of Endocrine Diseases and Diabetology, Department of Medicine, ASST Papa Giovanni XXIII, Bergamo, Italy
| | - Rosalia Bellante
- Unit of Endocrine Diseases and Diabetology, Department of Medicine, ASST Papa Giovanni XXIII, Bergamo, Italy
| | - Roberto Trevisan
- Unit of Endocrine Diseases and Diabetology, Department of Medicine, ASST Papa Giovanni XXIII, Bergamo, Italy
- Department of Medicine, Università degli Studi di Milano-Bicocca, Milan, Italy
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