Efforts to screen kids for type 1 diabetes multiply.

Blood tests can detect the disease process early, avoiding complications and aiding treatment.

Baricitinib and ß-Cell Function in Patients with New-Onset Type 1 Diabetes.

BACKGROUND: Janus kinase (JAK) inhibitors, including baricitinib, block cytokine signaling and are effective disease-modifying treatments for several autoimmune diseases. Whether baricitinib preserves ß-cell function in type 1 diabetes is unclear. METHODS: In this phase 2, double-blind, randomized, placebo-controlled trial, we assigned patients with type 1 diabetes diagnosed during the previous 100 days to receive baricitinib (4 mg once per day) or matched placebo orally for 48 weeks. The primary outcome was the mean C-peptide level, determined from the area under the concentration-time curve, during a 2-hour mixed-meal tolerance test at week 48. Secondary outcomes included the change from baseline in the glycated hemoglobin level, the daily insulin dose, and measures of glycemic control assessed with the use of continuous glucose monitoring. RESULTS: A total of 91 patients received baricitinib (60 patients) or placebo (31 patients). The median of the mixed-meal-stimulated mean C-peptide level at week 48 was 0.65 nmol per liter per minute (interquartile range, 0.31 to 0.82) in the baricitinib group and 0.43 nmol per liter per minute (interquartile range, 0.13 to 0.63) in the placebo group (P = 0.001). The mean daily insulin dose at 48 weeks was 0.41 U per kilogram of body weight per day (95% confidence interval [CI], 0.35 to 0.48) in the baricitinib group and 0.52 U per kilogram per day (95% CI, 0.44 to 0.60) in the placebo group. The levels of glycated hemoglobin were similar in the two trial groups. However, the mean coefficient of variation of the glucose level at 48 weeks, as measured by continuous glucose monitoring, was 29.6% (95% CI, 27.8 to 31.3) in the baricitinib group and 33.8% (95% CI, 31.5 to 36.2) in the placebo group. The frequency and severity of adverse events were similar in the two trial groups, and no serious adverse events were attributed to baricitinib or placebo. CONCLUSIONS: In patients with type 1 diabetes of recent onset, daily treatment with baricitinib over 48 weeks appeared to preserve ß-cell function as estimated by the mixed-meal-stimulated mean C-peptide level. (Funded by JDRF International and others; BANDIT Australian New Zealand Clinical Trials Registry number, ACTRN12620000239965.).

Automated Insulin Delivery in Women with Pregnancy Complicated by Type 1 Diabetes.

BACKGROUND: Hybrid closed-loop insulin therapy has shown promise for management of type 1 diabetes during pregnancy; however, its efficacy is unclear. METHODS: In this multicenter, controlled trial, we randomly assigned pregnant women with type 1 diabetes and a glycated hemoglobin level of at least 6.5% at nine sites in the United Kingdom to receive standard insulin therapy or hybrid closed-loop therapy, with both groups using continuous glucose monitoring. The primary outcome was the percentage of time in the pregnancy-specific target glucose range (63 to 140 mg per deciliter [3.5 to 7.8 mmol per liter]) as measured by continuous glucose monitoring from 16 weeks' gestation until delivery. Analyses were performed according to the intention-to-treat principle. Key secondary outcomes were the percentage of time spent in a hyperglycemic state (glucose level >140 mg per deciliter), overnight time in the target range, the glycated hemoglobin level, and safety events. RESULTS: A total of 124 participants with a mean (±SD) age of 31.1±5.3 years and a mean baseline glycated hemoglobin level of 7.7±1.2% underwent randomization. The mean percentage of time that the maternal glucose level was in the target range was 68.2±10.5% in the closed-loop group and 55.6±12.5% in the standard-care group (mean adjusted difference, 10.5 percentage points; 95% confidence interval [CI], 7.0 to 14.0; P<0.001). Results for the secondary outcomes were consistent with those of the primary outcome; participants in the closed-loop group spent less time in a hyperglycemic state than those in the standard-care group (difference, -10.2 percentage points; 95% CI, -13.8 to -6.6); had more overnight time in the target range (difference, 12.3 percentage points; 95% CI, 8.3 to 16.2), and had lower glycated hemoglobin levels (difference, -0.31 percentage points; 95% CI, -0.50 to -0.12). Little time was spent in a hypoglycemic state. No unanticipated safety problems associated with the use of closed-loop therapy during pregnancy occurred (6 instances of severe hypoglycemia, vs. 5 in the standard-care group; 1 instance of diabetic ketoacidosis in each group; and 12 device-related adverse events in the closed-loop group, 7 related to closed-loop therapy). CONCLUSIONS: Hybrid closed-loop therapy significantly improved maternal glycemic control during pregnancy complicated by type 1 diabetes. (Funded by the Efficacy and Mechanism Evaluation Program; AiDAPT ISRCTN Registry number, ISRCTN56898625.).

Continuous Glucose Monitoring Impact and Implications of Real-World Evidence: Past, Present, and Future.

Randomized controlled trials, which are considered the highest level of scientific evidence, have shown significant glycemic benefits associated with use of continuous glucose monitoring (CGM) in individuals with diabetes who are treated with intensive insulin regimens. However, numerous prospective, retrospective, and observational studies have investigated the impact of CGM in various diabetes populations treated with nonintensive therapies. Results from these studies have contributed to changes in payer coverage, prescriber behaviors, and expanding use of CGM. This article reviews findings from recent real-world studies, highlights the key lessons learned from these studies, and discusses how we need to move forward in increasing utilization of and access to CGM among all diabetes patients who would benefit from this technology.

Presencia de autoanticuerpos anti islotes pancreáticos en diabetes tipo 1 durante la edad pediátrica / Presence of anti-pancreatic islet autoantibodies in type 1 diabetes in children

En la Diabetes tipo 1 (DM1) la pérdida de células ß pancreáticas es consecuencia de un proceso de autoinmunidad que cursa con la presencia de autoanticuerpos anti-islotes pancreáticos (AAPs). Estos AAPs son marcadores útiles para la clasificación de la enfermedad. En un centro pediátrico de tercer nivel se analizó la frecuencia de presentación de GADA, IA-2A, ZnT8A e IAA en un grupo con reciente debut entre enero 2018 y agosto 2021 (n= 90). Además, se investigó la frecuencia de presentación y relación de los AAPs con la edad, sexo y tiempo de evolución en pacientes en seguimiento (n= 240). En el grupo de debut se obtuvo positividad de GADA, IA-2A, ZnT8A y IAA en 77,8; 60; 62 y 47,8% de los pacientes respectivamente, un 4% no presentó AAPs. El 95,6% de los pacientes presentaron al menos un AAPs positivo. La frecuencia de IAA en el grupo en debut fue mayor en menores de 5 años. En el grupo en seguimiento el 75,2% resultaron GADA positivo (85,7% en mujeres y 62,8% en varones) p<0,05. IA-2A y ZnT8A fueron positivos en 45 y 51.7% respectivamente. El 91% presentaron al menos un AAP positivo. En este grupo se evidenció una menor positividad en función del tiempo de evolución. Se pudo determinar la frecuencia de presentación de los AAPs en un grupo en debut y la relación con la edad, sexo y tiempo de evolución en pacientes en seguimiento. La determinación de APPs facilita la correcta clasificación y elección de la terapia adecuada (AU)

In type 1 diabetes (DM1) the loss of pancreatic ß-cells is a consequence of an autoimmune process that results in the presence of pancreatic anti-islet autoantibodies (PAAs). PAAs are useful markers for the classification of the disease. The frequency of presentation of GADA, IA-2A, ZnT8A, and IAA in a group with recent debut seen between January 2018 and August 2021 (n= 90) was analyzed in a tertiary pediatric center. In addition, we investigated the frequency of presentation and association of PAAs with age, sex, and time of evolution in patients in follow-up (n= 240). In the debut group, GADA, IA2A, ZnT8A, and IAA positivity was found in 77.8, 60, 62, and 47.8% of patients, respectively; no PAAs were observed in 4% of the patients. Overall, 95.6% presented at least one positive PAA. The frequency of IAA in the debut group was higher in children younger than 5 years. In the follow-up group, 75.2% were GADA positive (85.7% of females and 62.8% of males) p<0.05. IA-2A and ZnT8A were positive in 45 and 51.7% respectively. Ninety-one percent presented with at least one positive PAA. In this group, a lower positivity was evidenced as a function of the time of evolution. The frequency of presentation of PAAs in a debut group and the relationship with age, sex, and time of evolution in patients in follow-up was demonstrated. The assessment of PAAs facilitates the correct classification and choice of adequate therapy (AU)

Trial of Hybrid Closed-Loop Control in Young Children with Type 1 Diabetes.

BACKGROUND: Closed-loop control systems of insulin delivery may improve glycemic outcomes in young children with type 1 diabetes. The efficacy and safety of initiating a closed-loop system virtually are unclear. METHODS: In this 13-week, multicenter trial, we randomly assigned, in a 2:1 ratio, children who were at least 2 years of age but younger than 6 years of age who had type 1 diabetes to receive treatment with a closed-loop system of insulin delivery or standard care that included either an insulin pump or multiple daily injections of insulin plus a continuous glucose monitor. The primary outcome was the percentage of time that the glucose level was in the target range of 70 to 180 mg per deciliter, as measured by continuous glucose monitoring. Secondary outcomes included the percentage of time that the glucose level was above 250 mg per deciliter or below 70 mg per deciliter, the mean glucose level, the glycated hemoglobin level, and safety outcomes. RESULTS: A total of 102 children underwent randomization (68 to the closed-loop group and 34 to the standard-care group); the glycated hemoglobin levels at baseline ranged from 5.2 to 11.5%. Initiation of the closed-loop system was virtual in 55 patients (81%). The mean (±SD) percentage of time that the glucose level was within the target range increased from 56.7±18.0% at baseline to 69.3±11.1% during the 13-week follow-up period in the closed-loop group and from 54.9±14.7% to 55.9±12.6% in the standard-care group (mean adjusted difference, 12.4 percentage points [equivalent to approximately 3 hours per day]; 95% confidence interval, 9.5 to 15.3; P<0.001). We observed similar treatment effects (favoring the closed-loop system) on the percentage of time that the glucose level was above 250 mg per deciliter, on the mean glucose level, and on the glycated hemoglobin level, with no significant between-group difference in the percentage of time that the glucose level was below 70 mg per deciliter. There were two cases of severe hypoglycemia in the closed-loop group and one case in the standard-care group. One case of diabetic ketoacidosis occurred in the closed-loop group. CONCLUSIONS: In this trial involving young children with type 1 diabetes, the glucose level was in the target range for a greater percentage of time with a closed-loop system than with standard care. (Funded by the National Institute of Diabetes and Digestive and Kidney Diseases; PEDAP ClinicalTrials.gov number, NCT04796779.).

Glycemia Around Exercise in Adults with Type 1 Diabetes Using Automated and Nonautomated Insulin Delivery Pumps: A Switch Pilot Trial.

In an in-patient switch study, 10 adults with type 1 diabetes (T1D) performed 45 min of moderate-intensity exercise on 2 occasions: (1) when using their usual insulin pump (UP) and (2) after transitioning to automated insulin delivery (AID) treatment (MiniMed™ 780G). Consensus glucose management guidelines for performing exercise were applied. Plasma glucose concentrations measured over a 3-h monitoring period were stratified into time below range (TBR, <3.9 mmol/L), time in range (TIR, 3.9-10.0 mmol/L), and time above range (TAR, >10.0 mmol/L). Overall, TBR (UP: 11 ± 21 vs. AID: 3% ± 10%, P = 0.413), TIR (UP: 53 ± 27 vs. AID: 66% ± 39%, P = 0.320), and TAR (UP: 37 ± 34 vs. AID: 31% ± 41%, P = 0.604) were similar between arms. A proportionately low number of people experienced exercise-induced hypoglycemia (UP: n = 2 vs. AID: n = 1, P = 1.00). In conclusion, switching to AID therapy did not alter patterns of glycemia around sustained moderate-intensity exercise in adults with T1D. Clinical Trial Registration number: NCT05133765.

The Predictive Ability of C-Peptide in Distinguishing Type 1 Diabetes From Type 2 Diabetes: A Systematic Review and Meta-Analysis.

OBJECTIVE: This systematic review and meta-analysis aimed to investigate the predictive ability of plasma connecting peptide (C-peptide) levels in discriminating type 1 diabetes (T1D) from type 2 diabetes (T2D) and to inform evidence-based guidelines in diabetes classification. METHODS: We conducted a holistic review and meta-analysis using PubMed, MEDLINE, EMBASE, and Scopus. The citations were screened from 1942 to 2021. The quality criteria and the preferred reporting items for systematic reviews and meta-analysis checklist were applied. The protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO) (CRD42022355088). RESULTS: A total of 23,658 abstracts were screened and 46 full texts reviewed. Of the 46 articles screened, 12 articles were included for the meta-analysis. Included studies varied by race, age, time, and proportion of individuals. The main outcome measure in all studies was C-peptide levels. A significant association was reported between C-peptide levels and the classification and diagnosis of diabetes. Furthermore, lower concentrations and the cutoff of <0.20 nmol/L for fasting or random plasma C-peptide was indicative of T1D. In addition, this meta-analysis revealed the predictive ability of C-peptide levels in discriminating T1D from T2D. Results were consistent using both fixed- and random-effect models. The I2 value (98.8%) affirmed the variability in effect estimates was due to heterogeneity rather than sampling error among all selected studies. CONCLUSION: Plasma C-peptide levels are highly associated and predictive of the accurate classification and diagnosis of diabetes types. A plasma C-peptide cutoff of ≤0.20 mmol/L is indicative of T1D and of ≥0.30 mmol/L in the fasting or random state is indicative of T2D.

Glucose Treatment Targets in Pregnancy - A Review of Evidence and Guidelines.

BACKGROUND: Maternal diabetes mellitus during pregnancy is associated with an increased risk of pregnancy complications for both the mother and the fetus. One of the most prevalent complications is pathological fetal growth, and particularly infants are born large for gestational age (LGA), which leads to problematic deliveries, including the need for caesarean section, instrumental delivery, and further perinatal complications. Glucose monitoring during pregnancy is essential for ensuring appropriate glycaemic control and to reduce these associated risks. The current methods of glucose monitoring include measuring glycosylated haemoglobin (HbA1c), selfmonitoring of capillary blood glucose (SMBG), and more recently, continuous glucose monitoring (CGM). Observational studies and randomised controlled trials (RCTs) have assessed the appropriate glycaemic targets for HbA1c, SMBG, and CGM in relation to pregnancy outcomes. OBJECTIVE: In this review, we have identified current international guidelines on glycaemic targets and reviewed the supporting evidence. METHODS: We performed an extensive literature search on glycaemic targets in pregnancies affected by diabetes, and we researched international guidelines from recognised societies. RESULTS AND CONCLUSION: The majority of studies used to define the glucose targets associated with the best pregnancy outcomes, across all modalities, were in women with type 1 diabetes. There were limited studies on women with type 2 diabetes and gestational diabetes. We, therefore, suggest that further research needs be conducted on glucose targets and clinical outcomes, specifically in these populations where CGM technology offers the greatest potential for monitoring glucose and improving pregnancy outcomes.

Personalized Blood Glucose Prediction for Type 1 Diabetes Using Evidential Deep Learning and Meta-Learning.

The availability of large amounts of data from continuous glucose monitoring (CGM), together with the latest advances in deep learning techniques, have opened the door to a new paradigm of algorithm design for personalized blood glucose (BG) prediction in type 1 diabetes (T1D) with superior performance. However, there are several challenges that prevent the widespread implementation of deep learning algorithms in actual clinical settings, including unclear prediction confidence and limited training data for new T1D subjects. To this end, we propose a novel deep learning framework, Fast-adaptive and Confident Neural Network (FCNN), to meet these clinical challenges. In particular, an attention-based recurrent neural network is used to learn representations from CGM input and forward a weighted sum of hidden states to an evidential output layer, aiming to compute personalized BG predictions with theoretically supported model confidence. The model-agnostic meta-learning is employed to enable fast adaptation for a new T1D subject with limited training data. The proposed framework has been validated on three clinical datasets. In particular, for a dataset including 12 subjects with T1D, FCNN achieved a root mean square error of 18.64±2.60 mg/dL and 31.07±3.62 mg/dL for 30 and 60-minute prediction horizons, respectively, which outperformed all the considered baseline methods with significant improvements. These results indicate that FCNN is a viable and effective approach for predicting BG levels in T1D. The well-trained models can be implemented in smartphone apps to improve glycemic control by enabling proactive actions through real-time glucose alerts.

Evaluation among trace elements, clinical parameters and type 1 diabetes according to sex: A new sight of auxiliary prediction in negative insulin auto-antibodies population.

BACKGROUND: Type 1 diabetes (T1D) exhibited sex-specific metabolic status including oxidative stress with dynamic change of trace elements, which emphasized the importance of the evaluation of trace elements according to sex. Besides, the most significant characteristic, insulin auto-antibodies, could not be found in all T1D patients, which needed the auxiliary prediction of clinical parameters. And it would benefit the early detection and treatment if some high-risk groups of T1D could predict and prevent the occurrence of disease through common clinical parameters. Hence, there was an urgent need to construct more effective and scientific statistical prediction models to serve clinic better. This study aimed to evaluate the sex-specific levels of trace elements and the relationship between trace elements and clinical parameters in T1D, and construct sex-specific auxiliary prediction model combined with trace elements and clinical parameters. METHODS: A total of 105 T1D patients with negative insulin auto-antibodies and 105 age/sex-matched healthy individuals were enrolled in First Hospital of Jilin University. Inductively Coupled Plasma Mass Spectrometry was performed for the measurement of calcium (Ca), magnesium (Mg), zinc (Zn), copper (Cu), iron (Fe), selenium (Se) in the serum, and the data of clinical parameters were received from medical record system. The lambda-mu-sigma method was used to evaluate the relationship between abnormal clinical parameters and trace elements. Training set and validation set were divided for the construction of predictable models in males and females: clinical parameters model, trace element model and the combined model (clinical parameters and trace elements). Goodness fit test, decision curve analysis and other related statistical methods were used to perform data analysis. RESULTS: Lower levels of Mg, Ca, Fe in the serum were found in T1D population in females compared with healthy population, while levels of Fe, Zn and Cu of serum in T1D individuals were higher than those of healthy population in males. Levels of serum Mg, Fe and Cu in T1D group were found with significant sex difference for (P < 0.05), and the levels of Fe and Cu in serum of males were higher than those of females, level of serum Mg in males was lower than those of females. Levels of serum Mg and Zn showed fluctuation trend with increased numbers of abnormal clinical parameters (NACP) in males. Serum Zn in females showed consistent elevated trend with NACP; serum Se increased first and then decreased with NACP in males and females. The auxiliary prediction model (Triglyceride, Total protein, serum Mg) was found with the highest predicted efficiency in males (AUC=0.993), while the model in females (Apolipoprotein A, Creatinine, Fe, Se, Zn/Cu ratio) showed the best predicted efficiency (AUC=0.951). The models had passed the verification in validation set, and Chi-square goodness-of-fit test, DCA results both confirmed their satisfactory clinical applicability. CONCLUSION: Sex-specific difference were found in serum Mg, Fe and Cu in T1D. The combination of triglyceride, total protein and serum Mg for males, and apolipoprotein A, creatinine, Fe, Se, Zn/Cu ratio for females could effectively predict T1D in patients with negative anti-bodies, which would provide alarm for the population with high-risk of T1D and serve the T1D prediction in patients with negative anti-bodies.

Intermittently Scanned Continuous Glucose Monitoring for Type 1 Diabetes.

BACKGROUND: In persons with type 1 diabetes and high glycated hemoglobin levels, the benefits of intermittently scanned continuous glucose monitoring with optional alarms for high and low blood glucose levels are uncertain. METHODS: In a parallel-group, multicenter, randomized, controlled trial involving participants with type 1 diabetes and glycated hemoglobin levels between 7.5% and 11.0%, we investigated the efficacy of intermittently scanned continuous glucose monitoring as compared with participant monitoring of blood glucose levels with fingerstick testing. The primary outcome was the glycated hemoglobin level at 24 weeks, analyzed according to the intention-to-treat principle. Key secondary outcomes included sensor data, participant-reported outcome measures, and safety. RESULTS: A total of 156 participants were randomly assigned, in a 1:1 ratio, to undergo intermittently scanned continuous glucose monitoring (the intervention group, 78 participants) or to monitor their own blood glucose levels with fingerstick testing (the usual-care group, 78 participants). At baseline, the mean (±SD) age of the participants was 44±15 years, and the mean duration of diabetes was 21±13 years; 44% of the participants were women. The mean baseline glycated hemoglobin level was 8.7±0.9% in the intervention group and 8.5±0.8% in the usual-care group; these levels decreased to 7.9±0.8% and 8.3±0.9%, respectively, at 24 weeks (adjusted mean between-group difference, -0.5 percentage points; 95% confidence interval [CI], -0.7 to -0.3; P<0.001). The time per day that the glucose level was in the target range was 9.0 percentage points (95% CI, 4.7 to 13.3) higher or 130 minutes (95% CI, 68 to 192) longer in the intervention group than in the usual-care group, and the time spent in a hypoglycemic state (blood glucose level, <70 mg per deciliter [<3.9 mmol per liter]) was 3.0 percentage points (95% CI, 1.4 to 4.5) lower or 43 minutes (95% CI, 20 to 65) shorter in the intervention group. Two participants in the usual-care group had an episode of severe hypoglycemia, and 1 participant in the intervention group had a skin reaction to the sensor. CONCLUSIONS: Among participants with type 1 diabetes and high glycated hemoglobin levels, the use of intermittently scanned continuous glucose monitoring with optional alarms for high and low blood glucose levels resulted in significantly lower glycated hemoglobin levels than levels monitored by fingerstick testing. (Funded by Diabetes UK and others; FLASH-UK ClinicalTrials.gov number, NCT03815006.).

Open-Source Automated Insulin Delivery in Type 1 Diabetes.

BACKGROUND: Open-source automated insulin delivery (AID) systems are used by many patients with type 1 diabetes. Data are needed on the efficacy and safety of an open-source AID system. METHODS: In this multicenter, open-label, randomized, controlled trial, we assigned patients with type 1 diabetes in a 1:1 ratio to use an open-source AID system or a sensor-augmented insulin pump (control). The patients included both children (defined as 7 to 15 years of age) and adults (defined as 16 to 70 years of age). The AID system was a modified version of AndroidAPS 2.8 (with a standard OpenAPS 0.7.0 algorithm) paired with a preproduction DANA-i insulin pump and Dexcom G6 CGM, which has an Android smartphone application as the user interface. The primary outcome was the percentage of time in the target glucose range of 70 to 180 mg per deciliter (3.9 to 10.0 mmol per liter) between days 155 and 168 (the final 2 weeks of the trial). RESULTS: A total of 97 patients (48 children and 49 adults) underwent randomization (44 to open-source AID and 53 to the control group). At 24 weeks, the mean (±SD) time in the target range increased from 61.2±12.3% to 71.2±12.1% in the AID group and decreased from 57.7±14.3% to 54.5±16.0% in the control group (adjusted difference, 14 percentage points; 95% confidence interval, 9.2 to 18.8; P<0.001), with no treatment effect according to age (P = 0.56). Patients in the AID group spent 3 hours 21 minutes more in the target range per day than those in the control group. No severe hypoglycemia or diabetic ketoacidosis occurred in either group. Two patients in the AID group withdrew from the trial owing to connectivity issues. CONCLUSIONS: In children and adults with type 1 diabetes, the use of an open-source AID system resulted in a significantly higher percentage of time in the target glucose range than the use of a sensor-augmented insulin pump at 24 weeks. (Supported by the Health Research Council of New Zealand; Australian New Zealand Clinical Trials Registry number, ACTRN12620000034932.).