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AIMS: To evaluate the association between extrapolated time in range (eTIR), measured by self-monitoring of blood glucose (SMBG), and large-for-gestational-age (LGA) infants in pregnancies with type 1 diabetes (T1D). METHODS: Retrospective cohort analysis including singleton pregnancies with T1D who started antenatal care before 20 gestational weeks and delivered live newborns at a Brazilian hospital between 2010 and 2019, with LGA fetuses as the main outcome. Glycemic records acquired using SMBG were categorized as eTIR, extrapolated time below range (eTBR), and extrapolated time above range (eTAR). Women were divided into two groups (LGA and adequate for gestational age [AGA]) and compared regarding clinical characteristics, obstetric outcomes, and frequencies of eTIR, eTBR, and eTAR. Logistic regression analysis verified the independent predictive variables for LGA infants. RESULTS: Data from 125 pregnancies were analyzed. For the first, second and third trimesters, each 1 % increase in eTIR was associated with a decreased risk of LGA by 2.9 % (OR: 0.971; 95%CI: 0.945-0.998), 2.5 % (OR: 0.975; 95%CI: 0.951-0.999) and 2.3 % (OR: 0.977; 95%CI: 0.955-0.998) and each 1 % increase in eTAR was associated with an increased risk of LGA by 2.7 % (OR: 1.027; 95%CI: 1.005-1.050), 3.9 % (OR: 1.039; 95%CI: 1.014-1.063) and 4.6 % (OR: 1.046; 95%CI: 1.018-1.075), respectively. CONCLUSION: The concept of TIR can be extrapolated to patients undergoing SMBG to assess the risk of LGA infants in pregnant women with T1D.
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Automonitorização da Glicemia , Diabetes Mellitus Tipo 1 , Macrossomia Fetal , Gravidez em Diabéticas , Humanos , Gravidez , Feminino , Diabetes Mellitus Tipo 1/sangue , Diabetes Mellitus Tipo 1/epidemiologia , Diabetes Mellitus Tipo 1/complicações , Estudos Retrospectivos , Adulto , Gravidez em Diabéticas/epidemiologia , Gravidez em Diabéticas/sangue , Recém-Nascido , Macrossomia Fetal/epidemiologia , Idade Gestacional , Brasil/epidemiologia , Glicemia/análise , Glicemia/metabolismo , Peso ao Nascer/fisiologia , Estudos de Coortes , Fatores de Tempo , Adulto JovemRESUMO
BACKGROUND: This study investigated the characteristics associated with an increased risk of hypoglycemia, in elderly patients with type 1 diabetes mellitus (T1D) using automated insulin delivery (AID) systems. METHODS: Cross-sectional observational study including patients >60 years, using sensor-augmented insulin pump therapy with predictive low-glucose management (SAPT-PLGM), hybrid closed-loop (HCL), and advanced hybrid closed-loop (AHCL), for more than three months. A geriatric assessment was performed, and body composition was determined to investigate its association with achieving time below range (TBR) <70 mg/dL goals. RESULTS: The study included 59 patients (47.5% of men, mean age of 67.6 years, glycated hemoglobin [HbA1c] of 7.5 ± 0.6%, time in range (TIR) 77.8 ± 9.9%). Time below range <70 and <54 mg/dL were 2.2 ± 2.3% and 0.4 ± 0.81%, respectively. Patients with elevated TBR <70 mg/dL (>1%) had higher HbA1c levels, lower TIR, elevated time above range (TAR), and high glycemic variability. Regarding body composition, greater muscle mass, grip strength, and visceral fat were associated with a lower TBR <70 mg/dL. These factors were independent of the type of technology used, but TIR was higher when using AHCL systems compared with SAPT-PLGM and HCL systems. CONCLUSIONS: In elderly patients treated with AID systems with good functional status, lower lean mass, lower grip strength, and lower visceral fat percentage were associated with TBR greater than 1%, regardless of the device used. A similar finding along was found with CGM indicators such as higher HbA1c levels, lower TIR, higher TAR, and higher CV. Geriatric assessment is crucial for personalizing patient management.
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Objective: Using continuous glucose monitoring (CGM), we examined patterns in glycemia during school hours for children with type 1 diabetes, exploring differences between school and non-school time. Methods: We conducted a retrospective analysis of CGM metrics in children 7-12 years (n=217, diabetes duration 3.5±2.5 years, hemoglobin A1c 7.5±0.8%). Metrics were obtained for weekday school hours (8 AM to 3 PM) during four weeks in fall 2019. Two comparison settings included weekend (fall 2019) and weekday (spring 2020) data when children had transitioned to virtual school due to COVID-19. We used multilevel mixed models to examine factors associated with time in range (TIR) and compare glycemia between in-school, weekends, and virtual school. Results: Though CGM metrics were clinically similar across settings, TIR was statistically higher, and time above range (TAR), mean glucose, and standard deviation (SD) lower, for weekends and virtual school (p<0.001). Hour and setting exhibited a significant interaction for several metrics (p<0.001). TIR in-school improved from a mean of 40.9% at the start of the school day to 58.0% later in school, with a corresponding decrease in TAR. TIR decreased on weekends (60.8 to 50.7%) and virtual school (62.2 to 47.8%) during the same interval. Mean glucose exhibited a similar pattern, though there was little change in SD. Younger age (p=0.006), lower hemoglobin A1c (p<0.001), and insulin pump use (p=0.02) were associated with higher TIR in-school. Conclusion: Although TIR was higher for weekends and virtual school, glycemic metrics improve while in-school, possibly related to beneficial school day routines.
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Diabetes Mellitus Tipo 1 , Humanos , Criança , Diabetes Mellitus Tipo 1/tratamento farmacológico , Hemoglobinas Glicadas , Glicemia/análise , Automonitorização da Glicemia , Estudos RetrospectivosRESUMO
BACKGROUND: Evidence regarding the implementation of medium-term strategies in advanced hybrid closed-loop (AHCL) system users is limited. Therefore, this study aimed to describe the efficacy and safety of the AHCL system in patients with type 1 diabetes (T1D) on a six-month follow-up in a virtual diabetes clinic (VDC). METHOD: A prospective cohort of adult patients with T1D treated using the AHCL system (Mini Med 780G; Medtronic, Northridge, California) in a VDC follow-up. Standardized training and follow-up were conducted virtually. Clinical data and metabolic control outcomes were reported at baseline, and at three and six months. RESULTS: Sixty-four patients (mean age = 42 ± 14.6 years, 65% men, 54% with graduate education) were included. Percentage time in range (%TIR) increased significantly regardless of prior therapy with intermittently scanned continuous glucose monitoring + multiple daily injections and sensor-augmented pump therapy with predictive low-glucose management after starting AHCL and persisted during the follow-up period with no hypoglycemic events. The %TIR 70 to 180 mg/dL according to socioeconomic strata was 73.4% ± 5.3%, 78.1% ± 8.1%, and 84.2% ± 7.5% for the lower, middle, and upper strata, respectively. The sensor was used more frequently in the population with a higher education level. Adherence to sensor use and SmartGuard retention were higher in patients who underwent the VDC follow-up. CONCLUSIONS: Medium-term follow-up of users of AHCL systems in a VDC contributes to safely achieving %TIR goals. Virtual diabetes clinic follow-up favored adherence to sensor use and continuous SmartGuard use. Socioeconomic strata were associated with a better glycemic profile and education level was associated with better adherence to sensor use.
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ABSTRACT Objectives: To evaluate the alternate use of flash glucose monitoring (FGM) with self-monitoring blood glucose (SMBG), in patients with type 1 diabetes (T1D). Materials and methods: Two weeks of open FGM (P2), both preceded (P1) and followed by 2 weeks (P3) of SMBG with a blinded FGM system. Mean absolute relative difference (MARD) was calculated by (-FGMi − SMBGi-) / SMBGi, where it was a paired data sample. Results: In total, 34 patients were evaluated. Time in range (TIR) did not change between P1 and P2. In 12 patients (35.3%), TIR increased from 40% at P1 to 52% at P2 (p = 0.002) and in 22 (64.7%), TIR decreased or did not change. FGM use resulted in decreased % time spent in hypoglycemia (<70 mg/dL) (6.5% vs. 5.0%; p = 0.005), increased % time spent in hyperglycemia (>180 mg/dL) (44.5% to 51%; p = 0.046) with no significant change in % TIR. The proportion of patients who reached sensor-estimated glycated hemoglobin (eA1c) < 7% decreased from 23.5% at P1 to 12.9% at P2, p = 0.028. For the whole sample, the MARD between the two methods was 15.5% (95% CI 14.5-16.6%). For normal glucose range, hyperglycemic levels and hypoglycemic levels MARD were 16.0% (95% CI 15.0-17.0%), 13.3% (95% CI 11.5-15.2%) and 23.4% [95% CI 20.5-26.3%)], respectively. Conclusion: FGM after usual SMBG decreased the % time spent in hypoglycemia concomitant with an undesired increase in % time spent in hyperglycemia. Lower accuracy of FGM regarding hypoglycemia levels could result in overcorrection of hypoglycemia.
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BACKGROUND AND AIMS: Evidence supports the efficacy and safety of the Hybrid Close loop (HCL) system in patients with type 1 diabetes (T1D). However, limited data are available on the long-term outcomes of patients on HCL with telemedicine follow-up. METHODS: A prospective observational cohort study including T1D patients, who were upgrading to HCL system. Virtual training and follow-up were done through telemedicine. CGM data were analyzed to compare the baseline time in range (TIR), time below range (TBR), glycemic variability and auto mode (AM), with measurements performed at 3, 6 and 12 months. RESULTS: 134 patients were included with baseline A1c 7.6% ± 1.1. 40.5% had a severe hypoglycemia event in the last year. Baseline TIR, measured two weeks after starting AM was 78.6 ± 9.94%. No changes were evident at three (Mean difference - 0.15;CI-2.47,2.17;p = 0.96), six (MD-1.09;CI-3.42,1.24;p = 0.12) and 12 months (MD-1.30;CI-3.64,1.04;p = 0.08). No significant changes were found in TBR or glycemic variability throughout the follow-up. Use of AM was 85.6 ± 17.5% and percentage of use of sensor was 88.75 ± 9.5% at 12 months. No severe hypoglycemic (SH) events were reported. CONCLUSIONS: HCL systems allow to improve TIR, TBR and glycemic variability safely, early and sustained up to 1 year of follow-up in patients with T1D and high risk of hypoglycemia followed through telemedicine.
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Diabetes Mellitus Tipo 1 , Hipoglicemia , Telemedicina , Humanos , Diabetes Mellitus Tipo 1/etiologia , Insulina/uso terapêutico , Glicemia , Estudos Prospectivos , Sistemas de Infusão de Insulina/efeitos adversos , Hipoglicemiantes/uso terapêutico , Hipoglicemia/etiologia , Hipoglicemia/induzido quimicamente , Automonitorização da GlicemiaRESUMO
Objective: To evaluate the alternate use of flash glucose monitoring (FGM) with self-monitoring blood glucose (SMBG), in patients with type 1 diabetes (T1D). Materials and methods: Two weeks of open FGM (P2), both preceded (P1) and followed by 2 weeks (P3) of SMBG with a blinded FGM system. Mean absolute relative difference (MARD) was calculated by (|FGMi - SMBGi|) / SMBGi, where it was a paired data sample. Results: In total, 34 patients were evaluated. Time in range (TIR) did not change between P1 and P2. In 12 patients (35.3%), TIR increased from 40% at P1 to 52% at P2 (p = 0.002) and in 22 (64.7%), TIR decreased or did not change. FGM use resulted in decreased % time spent in hypoglycemia (<70 mg/dL) (6.5% vs. 5.0%; p = 0.005), increased % time spent in hyperglycemia (>180 mg/dL) (44.5% to 51%; p = 0.046) with no significant change in % TIR. The proportion of patients who reached sensor-estimated glycated hemoglobin (eA1c) < 7% decreased from 23.5% at P1 to 12.9% at P2, p = 0.028. For the whole sample, the MARD between the two methods was 15.5% (95% CI 14.5-16.6%). For normal glucose range, hyperglycemic levels and hypoglycemic levels MARD were 16.0% (95% CI 15.0-17.0%), 13.3% (95% CI 11.5-15.2%) and 23.4% [95% CI 20.5-26.3%)], respectively. Conclusion: FGM after usual SMBG decreased the % time spent in hypoglycemia concomitant with an undesired increase in % time spent in hyperglycemia. Lower accuracy of FGM regarding hypoglycemia levels could result in overcorrection of hypoglycemia.
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Diabetes Mellitus Tipo 1 , Hiperglicemia , Hipoglicemia , Humanos , Glicemia , Glucose , Estudos Prospectivos , Automonitorização da Glicemia/métodos , Brasil , Hipoglicemiantes/uso terapêutico , Atenção à SaúdeRESUMO
INTRODUCTION: Finding a goal of time in range (%TIR) that defines good glycemic control is necessary. Previous retrospective studies suggest good concordance between HbA1c ≤7% with a TIR >70%; however, the studies that included the largest number of patients used blood glucose measurement data with a follow-up time of less than 90 days. This study defined the TIR value that best discriminates HbA1c ≤7%. METHODS: We performed a prospective study of diagnostic tests based on a cohort of patients with type 1 diabetes (T1D) treated with a hybrid closed loop (HCL) followed for three months. The ability of %TIR to distinguish patients with HbA1c ≤7% was evaluated through receiver operating characteristic curve analysis. We determined the %TIR cutoff point with the best operating characteristics. RESULTS: A total of 118 patients were included (58.1% women, 47% overweight or obese, and 33% with high glycemic variability). A moderate negative correlation (R = -.54, P < .001) was found between %TIR and HBA1c. The discrimination ability was moderate, with an area under the curve of 0.7485 (95% confidence interval = 0.6608-0.8363). The cutoff point that best predicted HbA1c ≤7% was %TIR ≥75.5 (sensitivity 70%, specificity 67%). The findings were similar among those with a coefficient of variation (CV%) ≥36%. CONCLUSIONS: Our data suggest that the %TIR adequately identifies patients with HbA1c ≤7%. A target of TIR ≥75%, rather than the currently recommended TIR ≥70%, may be a more suitable value for optimal glycemic control.
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The goal of this study was to assess the 6-month effectiveness of hybrid closed loop on glycemic control in type 1 diabetes (T1D) patients in Latin America. An exploratory analysis of data prospectively collected from non-selected consecutive patients with T1D who initiated treatment with the MiniMed™ 670G system in Argentina was conducted. Baseline and follow-up visits at days 7, 28, 90, and 180 were carried out and data were downloaded at each visit. A total of 30 patients (age range 9-57 years, female 63.3%), 73.3% (n = 22) of whom previously used sensor augmented pump-predictive low glucose management (SAP-PLGM), with baseline glycated hemoglobin 7.4% ± 1% were included. Time in range between 70 and 180 mg/dL significantly increased from 65.1% at baseline to 77.3%, 76.2%, 75.7%, and 75.2% at days 7, 28, 90 and 180, respectively. Time above range (>180 mg/dL) significantly decreased from 33% to 22.5% (P < 0.001), while time below range (<70 mg/dL) did not change. Mean glucose levels were reduced from 163.5 mg/dL at baseline to 150.9 mg/dL (P = 0.001) at last visit. The Auto Mode feature was used > 90% of the time. Virtual training was successfully completed with a Net Promoter Score® (NPS®) of 87%. This analysis confirms that MiniMed 670G system use allowed successful achievement of glycemic control within recommended targets in a non-selected Latin American patient population who underwent virtual system training.
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Diabetes Mellitus Tipo 1 , Adolescente , Adulto , Glicemia/análise , Automonitorização da Glicemia , Criança , Diabetes Mellitus Tipo 1/tratamento farmacológico , Feminino , Controle Glicêmico , Humanos , Hipoglicemiantes/uso terapêutico , Insulina/uso terapêutico , Sistemas de Infusão de Insulina , América Latina , Pessoa de Meia-Idade , Adulto JovemRESUMO
BACKGROUND AND AIMS: In Colombia, the government established mandatory isolation after the first case of COVID-19 was reported. As a diabetes care center specialized in technology, we developed a virtual training program for patients with type 1 diabetes (T1D) who were upgrading to hybrid closed loop (HCL) system. The aim of this study is to describe the efficacy and safety outcomes of the virtual training program. METHOD: ology: A prospective observational cohort study was performed, including patients with diagnosis of T1D previously treated with multiple doses of insulin (MDI) or sensor augmented pump therapy (SAP) who were updating to HCL system, from March to July 2020. Virtual training and follow-up were done through the Zoom video conferencing application and Medtronic Carelink System version 3.1 software. CGM data were analyzed to compare the time in range (TIR), time below range (TBR) and glycemic variability, during the first two weeks corresponding to manual mode with the final two weeks of follow-up in automatic mode. RESULTS: 91 patients were included. Mean TIR achieved with manual mode was 77.3 ± 11.3, increasing to 81.6% ± 7.6 (p < 0.001) after two weeks of auto mode use. A significant reduction in TBR <70 mg/dL (2,7% ± 2,28 vs 1,83% ± 1,67, p < 0,001) and in glycemic variability (% coefficient of variation 32.4 vs 29.7, p < 0.001) was evident, independently of baseline therapy. CONCLUSION: HCL systems allows T1D patients to improve TIR, TBR and glycemic variability independently of previous treatment. Virtual training can be used during situations that limit the access of patients to follow-up centers.
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COVID-19/epidemiologia , Diabetes Mellitus Tipo 1/epidemiologia , Diabetes Mellitus Tipo 1/terapia , Sistemas de Infusão de Insulina , Educação de Pacientes como Assunto/métodos , Telemedicina/métodos , Adolescente , Adulto , Idoso , Automonitorização da Glicemia/métodos , COVID-19/prevenção & controle , Estudos de Coortes , Colômbia/epidemiologia , Feminino , Seguimentos , Humanos , Hipoglicemiantes/administração & dosagem , Masculino , Pessoa de Meia-Idade , Estudos Prospectivos , Adulto JovemRESUMO
The International Consensus in Time in Range (TIR) was recently released and defined the concept of the time spent in the target range between 70 and 180 mg/dL while reducing time in hypoglycemia, for patients using Continuous Glucose Monitoring (CGM). TIR was validated as an outcome measures for clinical Trials complementing other components of glycemic control like Blood glucose and HbA1c. The challenge is to implement this practice more widely in countries with a limited health public and private budget as it occurs in Brazil. Could CGM be used intermittently? Could self-monitoring blood glucose obtained at different times of the day, with the amount of data high enough be used? More studies should be done, especially cost-effective studies to help understand the possibility of having sensors and include TIR evaluation in clinical practice nationwide.
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BACKGROUND: Multidisciplinary interventions may be useful for children and adolescents with diabetes mellitus (DM), especially in areas where new blood glucose monitoring and control technologies are difficult to access. METHODS: PAANDA, a care program for adolescents and children with diabetes, was implemented in patients aged 0 to 18 years and 11 months. The effect of the intervention was determined by self-blood glucose monitoring (SBGM) and glycosylated hemoglobin (HbA1C ) levels at start and after 6 months. RESULTS: A total of 121 patients with DM were evaluated, mean age of 14.27 years (SD: 4.60 years). Blood glucose measurements in range (70-120 mg/dL pre-prandial or 70-180 mg/dL post-prandial) increased by 20.67% before breakfast, 8.14% after breakfast (both P-value <.001), 5.02% before lunch (P-value = .02), 8.66% after lunch (P-value <.001), 11.50% before dinner (P-value <.001), 11.87% after dinner (P-value <.001), and 8.00% at dawn (P-value = .001). This change was accompanied by fewer values in the hyperglycemic category (-19.49% before breakfast, -7.73% after breakfast, both P-value <.001) and hypoglycemia (-1.18%). HbA1C levels decreased significantly 1.8% (P-value = .018). Multivariate logistic regression analysis showed an increase in glycemic control associated with each month after the intervention time in the PAANDA program (P-value <.001 for all the time points evaluated) and a significant decrease in glycemic variability. CONCLUSIONS: The multidisciplinary PAANDA intervention had a beneficial effect on glycemic control, with an improved time in range in a population of children and adolescents with DM.