Following the results of the EMPA-REG OUTCOME trial with Empagliflozin, is it possible to speak of a class effect?

The recently published cardiovascular outcomes data for the first sodium-glucose cotransporter 2 (SGLT2) inhibitor, empagliflozin, have shown cardiovascular safety and additional benefits in patients with type 2 diabetes and established cardiovascular disease. Empagliflozin showed lower rates of death from cardiovascular causes or from any causes and lower hospitalization rates from heart failure compared with placebo, both in addition to standard care. This commentary discusses the existence of a possible class effect considering the available evidence described for other SGLT2 inhibitors

Real-time estimation of plasma insulin concentration from continuous glucose monitor measurements

Continuous glucose monitors can measure interstitial glucose concentration in real time for closed-loop glucose control systems, known as artificial pancreas. These control systems use an insulin feedback to maintain plasma glucose concentration within a narrow and safe range, and thus to avoid health complications. As it is not possible to measure plasma insulin concentration in real time, insulin models have been used in literature to estimate them. Nevertheless, the significant interand intra-patient variability of insulin absorption jeopardizes the accuracy of these estimations. In order to reduce these limitations, our objective is to perform a real-time estimation of plasma insulin concentration from continuous glucose monitoring (CGM). Hovorka s glucose insulin model has been incorporated in an extended Kalman filter in which different selected time-variant model parameters have been considered as extended states. The observability of the original Hovorka s model and of several extended models has been evaluated by their Lie derivatives. We have evaluated this methodology with an in-silico study with 100 patients with Type 1 diabetes during 25 h. Furthermore, it has been also validated using clinical data from 12 insulin pump patients with Type 1 diabetes who underwent four mixed meal studies. Real-time insulin estimations have been compared to plasma insulin measurements to assess performance showing the validity of the methodology here used in comparison with that formerly used for insulin models. Hence, real-time estimations for plasma insulin concentration based on subcutaneous glucose monitoring can be beneficial for increasing the efficiency of control algorithms for the artificial pancreas.This work was partially supported by the Spanish Ministerio de Ciencia e Innovacion through Grant DPI-2010-20764-C02-01 and Grant DPI-2013-46982-C2-1-R, and the European Union through FEDER fund.De Pereda Sebastián, D.; Romero Vivó, S.; Ricarte Benedito, B.; Rossetti, P.; Ampudia Blasco, FJ.; Bondía Company, J. (2015). Real-time estimation of plasma insulin concentration from continuous glucose monitor measurements. Computer Methods in Biomechanics and Biomedical Engineering. Sep:1-9. https://doi.org/10.1080/10255842.2015.1077234S19Se

Impact of High Intensity Interval Training Using Elastic Bands on Glycemic Control in Adults with Type 1 Diabetes: A Pilot Study

[EN] High intensity interval training (HIIT) using elastic bands is easy to do, but no data on its impact on glycemic control in people with type 1 diabetes (T1D) are available. Six males with T1D performed three weekly sessions of HIIT using elastic bands for 12 weeks. Each session consisted of eight exercises. Glycemic control was evaluated by using intermittent scanning continuous glucose monitoring two weeks before study onset (baseline) and during the intervention period in the first two (first stage) and last two weeks (last stage). In the 24 h post-exercise, time-in-range (70-180 mg/dL) was reduced from baseline to the end of the study (67.2% to 63.0%), and time-above-range (>180 mg/dL) seemed to increase from baseline across the study (20.8% -> 27.5% -> 22.1%, from baseline -> first -> last stage), but did not show any statistical significance. Time in hypoglycemia (either < 70 mg/dL or <54 mg/dL) did not show statistically significant differences. This study shows that a HIIT program with elastic bands is safe and effective to perform in T1D patients, keeping blood glucose levels in a safe range.This study was funded by MINECO DPI2016-78831-C2-1-R, Agencia Estatal de Investigacion (PID2019-107722RB-C21/AEI/10.13039/501100011033), FEDER funds from EU, and the Vicerectorate of Research, Innovation and Technology Transference from the Universitat Politecnica de Valencia grant number PAID-06-18. This study was also supported by the official funding agency for biomedical research of the Spanish government, Institute of Health Carlos III (ISCIII) through CIBEROBN CB12/03/30038, and CIBERDEM CB17/08/00004, which is co-funded by the European Regional Development Fund.Martín-San Agustín, R.; Laguna Sanz, AJ.; Bondía Company, J.; Roche, E.; Benítez Martínez, JC.; Ampudia-Blasco, FJ. (2020). Impact of High Intensity Interval Training Using Elastic Bands on Glycemic Control in Adults with Type 1 Diabetes: A Pilot Study. Applied Sciences. 10(19). https://doi.org/10.3390/app10196988101

Extensive assessment of blood glucose monitoring during postprandial period and its impact on closed-loop performance

[EN] Background: Closed-loop (CL) systems aims to outperform usual treatments in blood glucose control and continuous glucose monitors (CGM) are a key component in such systems. Meals represents one of the main disturbances in blood glucose control, and postprandial period (PP) is a challenging situation for both CL system and CGM accuracy. Methods: We performed an extensive analysis of sensor¿s performance by numerical accuracy and precision during PP, as well as its influence in blood glucose control under CL therapy. Results: During PP the mean absolute relative difference (MARD) for both sensors presented lower accuracy in the hypoglycemic range (19.4 ± 12.8%) than in other ranges (12.2 ± 8.6% in euglycemic range and 9.3 ± 9.3% in hyperglycemic range). The overall MARD was 12.1 ± 8.2%. We have also observed lower MARD for rates of change between 0 and 2 mg/dl. In CL therapy, the 10 trials with the best sensor spent less time in hypoglycemia (PG < 70 mg/dl) than the 10 trials with the worst sensors (2 ± 7 minutes vs 32 ± 38 minutes, respectively). Conclusions: In terms of accuracy, our results resemble to previously reported. Furthermore, our results showed that sensors with the lowest MARD spent less time in hypoglycemic range, indicating that the performance of CL algorithm to control PP was related to sensor accuracy.The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This project has been partially supported by the Spanish Government through Grants DPI 2013-46982-C2-1-R, DPI 2016-78831-C2-1-R, DPI 2013-46982-C2-2-R, and DPI 2016-78831-C2-2-R, the National Council of Technological and Scientific Development, CNPq Brazil through Grants 202050/2015-7 and 207688/2014-1.Biagi, L.; Hirata-Bertachi, A.; Conget, I.; Quirós, C.; Giménez, M.; Ampudia-Blasco, F.; Rossetti, P.... (2017). Extensive assessment of blood glucose monitoring during postprandial period and its impact on closed-loop performance. Journal of Diabetes Science and Technology. 11(6):1089-1095. https://doi.org/10.1177/1932296817714272S10891095116Doyle, F. J., Huyett, L. M., Lee, J. B., Zisser, H. C., & Dassau, E. (2014). Closed-Loop Artificial Pancreas Systems: Engineering the Algorithms. Diabetes Care, 37(5), 1191-1197. doi:10.2337/dc13-2108Cengiz, E., & Tamborlane, W. V. (2009). A Tale of Two Compartments: Interstitial Versus Blood Glucose Monitoring. Diabetes Technology & Therapeutics, 11(S1), S-11-S-16. doi:10.1089/dia.2009.0002Cobelli, C., Schiavon, M., Dalla Man, C., Basu, A., & Basu, R. (2016). Interstitial Fluid Glucose Is Not Just a Shifted-in-Time but a Distorted Mirror of Blood Glucose: Insight from an In Silico Study. Diabetes Technology & Therapeutics, 18(8), 505-511. doi:10.1089/dia.2016.0112Castle, J. R., & Ward, W. K. (2010). Amperometric Glucose Sensors: Sources of Error and Potential Benefit of Redundancy. Journal of Diabetes Science and Technology, 4(1), 221-225. doi:10.1177/193229681000400127Basu, A., Dube, S., Veettil, S., Slama, M., Kudva, Y. C., Peyser, T., … Basu, R. (2014). Time Lag of Glucose From Intravascular to Interstitial Compartment in Type 1 Diabetes. Journal of Diabetes Science and Technology, 9(1), 63-68. doi:10.1177/1932296814554797Keenan, D. B., Grosman, B., Clark, H. W., Roy, A., Weinzimer, S. A., Shah, R. V., & Mastrototaro, J. J. (2011). Continuous Glucose Monitoring Considerations for the Development of a Closed-Loop Artificial Pancreas System. Journal of Diabetes Science and Technology, 5(6), 1327-1336. doi:10.1177/193229681100500603Van Bon, A. C., Jonker, L. D., Koebrugge, R., Koops, R., Hoekstra, J. B. L., & DeVries, J. H. (2012). Feasibility of a Bihormonal Closed-Loop System to Control Postexercise and Postprandial Glucose Excursions. Journal of Diabetes Science and Technology, 6(5), 1114-1122. doi:10.1177/193229681200600516Rossetti, P., Quirós, C., Moscardó, V., Comas, A., Giménez, M., Ampudia-Blasco, F. J., … Vehí, J. (2017). Closed-Loop Control of Postprandial Glycemia Using an Insulin-on-Board Limitation Through Continuous Action on Glucose Target. Diabetes Technology & Therapeutics, 19(6), 355-362. doi:10.1089/dia.2016.0443Bailey, T., Zisser, H., & Chang, A. (2009). New Features and Performance of a Next-Generation SEVEN-Day Continuous Glucose Monitoring System with Short Lag Time. Diabetes Technology & Therapeutics, 11(12), 749-755. doi:10.1089/dia.2009.0075Zschornack, E., Schmid, C., Pleus, S., Link, M., Klötzer, H.-M., Obermaier, K., … Freckmann, G. (2013). Evaluation of the Performance of a Novel System for Continuous Glucose Monitoring. Journal of Diabetes Science and Technology, 7(4), 815-823. doi:10.1177/193229681300700403Pleus, S., Schmid, C., Link, M., Zschornack, E., Klötzer, H.-M., Haug, C., & Freckmann, G. (2013). Performance Evaluation of a Continuous Glucose Monitoring System under Conditions Similar to Daily Life. Journal of Diabetes Science and Technology, 7(4), 833-841. doi:10.1177/193229681300700405Zisser, H. C., Bailey, T. S., Schwartz, S., Ratner, R. E., & Wise, J. (2009). Accuracy of the SEVEN® Continuous Glucose Monitoring System: Comparison with Frequently Sampled Venous Glucose Measurements. Journal of Diabetes Science and Technology, 3(5), 1146-1154. doi:10.1177/193229680900300519Obermaier, K., Schmelzeisen-Redeker, G., Schoemaker, M., Klötzer, H.-M., Kirchsteiger, H., Eikmeier, H., & del Re, L. (2013). Performance Evaluations of Continuous Glucose Monitoring Systems: Precision Absolute Relative Deviation is Part of the Assessment. Journal of Diabetes Science and Technology, 7(4), 824-832. doi:10.1177/193229681300700404Clarke, W. L., Cox, D., Gonder-Frederick, L. A., Carter, W., & Pohl, S. L. (1987). Evaluating Clinical Accuracy of Systems for Self-Monitoring of Blood Glucose. Diabetes Care, 10(5), 622-628. doi:10.2337/diacare.10.5.622Martin Bland, J., & Altman, D. (1986). STATISTICAL METHODS FOR ASSESSING AGREEMENT BETWEEN TWO METHODS OF CLINICAL MEASUREMENT. The Lancet, 327(8476), 307-310. doi:10.1016/s0140-6736(86)90837-8Breton, M., & Kovatchev, B. (2008). Analysis, Modeling, and Simulation of the Accuracy of Continuous Glucose Sensors. Journal of Diabetes Science and Technology, 2(5), 853-862. doi:10.1177/193229680800200517Kropff, J., Bruttomesso, D., Doll, W., Farret, A., Galasso, S., Luijf, Y. M., … DeVries, J. H. (2014). Accuracy of two continuous glucose monitoring systems: a head‐to‐head comparison under clinical research centre and daily life conditions. Diabetes, Obesity and Metabolism, 17(4), 343-349. doi:10.1111/dom.12378Reddy, M., Herrero, P., Sharkawy, M. E., Pesl, P., Jugnee, N., Pavitt, D., … Oliver, N. S. (2015). Metabolic Control With the Bio-inspired Artificial Pancreas in Adults With Type 1 Diabetes. Journal of Diabetes Science and Technology, 10(2), 405-413. doi:10.1177/1932296815616134Pleus, S., Schoemaker, M., Morgenstern, K., Schmelzeisen-Redeker, G., Haug, C., Link, M., … Freckmann, G. (2015). Rate-of-Change Dependence of the Performance of Two CGM Systems During Induced Glucose Swings. Journal of Diabetes Science and Technology, 9(4), 801-807. doi:10.1177/193229681557871

Basal plus basal-bolus approach in type 2 diabetes

This is a copy of an article published in the Diabetes Technology and Therapeutics © 2011 [copyright Mary Ann Liebert, Inc.]; Diabetes Technology and Therapeutics is available online at: http://online.liebertpub.com.[EN] Type 2 diabetes is characterized by insulin resistance and progressive b-cell deterioration. As b-cell function declines, most patients with type 2 diabetes treated with oral agents, in monotherapy or combination, will require insulin therapy. Addition of basal insulin (glargine, detemir, or NPH/neutral protamine lispro insulin) to previous treatment is accepted as the simplest way to start insulin therapy in those patients. But even when basal insulin is adequately titrated, some patients will also need prandial insulin to achieve or maintain individual glycemic targets over time. Starting with premixed insulin is an effective option, but it is frequently associated with increased hypoglycemia risk, ¿xed meal schedules, and weight gain. As an alternative, a novel approached known as ``basal plus strategy¿¿ has been developed. This approach considers the addition of increasing injections of prandial insulin, beginning with the meal that has the major impact on postprandial glucose values. Finally, if this is not enough intensi¿cation to basal¿bolus will be necessary. In reducing hyperglycemia, this modality still remains the most effective option, even in people with type 2 diabetes. This article will review the currently evidence on the basal plus strategy and also its progression to basal¿bolus therapy. In addition, practical recommendations to start and adjust basal plus therapy will be provided.F.J.A.-B. has received honoraria as speaker and/or consultant from Abbott, AstraZeneca, Bristol-Myers Squibb, Glaxo-SmithKline, LifeScan, Lilly, Madaus, MannKind Corp., Medtronic, Menarini, Merch Farma y Quimica, SA, MSD, Novartis, Novo Nordisk, Pfizer, Roche, sanofi-aventis, Schering-Plough, and Solvay. In addition, F.J.A.-B. has participated in clinical trials supported totally or partially by AstraZeneca, Glaxo-SmithKline, LifeScan, Lilly, MSD, Novo Nordisk, Pfizer, sanofi-aventis, and Servier. P. R. has no potential conflicts of interest to declare. J.F.A. has received honoraria as speaker and/or consultant form AstraZeneca, Ferrer, Glaxo-SmithKline, Laboratorios Dr. Esteve, Lilly, MSD, and Solvay.Ampudia-Blasco, J.; Rossetti ., P.; Ascaso, JF. (2011). Basal plus basal-bolus approach in type 2 diabetes. Diabetes Technology & Therapeutics. 13:75-83. doi:10.1089/dia.2011.0001S75831

Closed-Loop Control of Postprandial Glycemia Using an Insulin-on-Board Limitation Through Continuous Action on Glucose Target

This is a copy of an article published in the Diabetes Technology & Therapeutics © 2017 [copyright Mary Ann Liebert, Inc.]; Diabetes Technology & Therapeutics is available online at: https://www.liebertpub.com/.[EN] Background: Postprandial (PP) control remains a challenge for closed-loop (CL) systems. Few studies with inconsistent results have systematically investigated the PP period. Objective: To compare a new CL algorithm with current pump therapy (open loop [OL]) in the PP glucose control in type 1 diabetes (T1D) subjects. Methods: A crossover randomized study was performed in two centers. Twenty T1D subjects (F/M 13/7, age 40.7 -10.4 years, disease duration 22.6 +/- 9.9 years, and A1c 7.8% +/- 0.7%) underwent an 8-h mixed meal test on four occasions. In two (CL1/CL2), after meal announcement, a bolus was given followed by an algorithmdriven basal infusion based on continuous glucose monitoring (CGM). Alternatively, in OL1/OL2 conventional pump therapy was used. Main outcome measures were as follows: glucose variability, estimated with the coefficient of variation (CV) of the area under the curve (AUC) of plasma glucose (PG) and CGM values, and from the analysis of the glucose time series; mean, maximum (C-max), and time to C-max glucose concentrations and time in range (180 mg/dL). Results: CVs of the glucose AUCs were low and similar in all studies (around 10%). However, CL achieved greater reproducibility and better PG control in the PP period: CL1 = CL2 0.05) nor the need for oral glucose was significantly different (CL 40.0% vs. OL 22.5% of meals; P = 0.054). Conclusions: This novel CL algorithm effectively and consistently controls PP glucose excursions without increasing hypoglycemia. Study registered at ClinicalTrials.gov: study number NCT02100488.This work was supported by the Spanish Ministry of Economy and Competitiveness through Grants DPI2013-46982-C2-1-R and DPI2013-46982-C2-2-R, and the EU through FEDER funds. C.Q. is the recipient of a grant from the Hospital Clinic i Universitari of Barcelona ("Ajut a la recerca Josep Font 2014-2017").Rossetti, P.; Quirós, C.; Moscardo-Garcia, V.; Comas, A.; Giménez, M.; Ampudia-Blasco, F.; León, F.... (2017). Closed-Loop Control of Postprandial Glycemia Using an Insulin-on-Board Limitation Through Continuous Action on Glucose Target. Diabetes Technology & Therapeutics. 19(6):355-362. https://doi.org/10.1089/dia.2016.0443S35536219

Hemorragia suprarrenal bilateral poscirugía. A propósito de un caso

Bilateral adrenal haemorrhage (BAH) is a rare but serious condition, which can lead to acute adrenal insufficiency. We present a case of an BAH that occurred after an intervention for lumbar canal stenosis. It was essential for the diagnosis falling hemoglobin and imaging tests. The patient was treated with hydrocortisone substitute orally. A stress situation is a risk factor for BAH, so this condition should be considered in the differential diagnosis of postoperative complications. It is important to suspect it to begin replacement therapy as soon as possible.La hemorragia suprarrenal bilateral (HSB) es una entidad rara pero grave, que puede derivar en insuficiencia suprarrenal aguda. Se presenta un caso de una HSB que tuvo lugar tras una intervención por estenosis de canal lumbar. Fue fundamental para el diagnóstico la caída de hemoglobina y las pruebas de imagen. La paciente recibió tratamiento sustitutivo con hidrocortisona vía oral. Una situación de estrés es un factor de riesgo para HSB, por lo que esta patología debe tenerse en cuenta en el diagnóstico diferencial de las complicaciones poscirugía. Es importante sospecharla para comenzar lo antes posible el tratamiento sustitutivo

Evaluation of a novel continuous glucose monitoring-based method for mealtime insulin dosing - the iBolus - in subjects with type 1 diabetes using continuous subcutaneous insulin infusion therapy: a randomized controlled trial

This is a copy of an article published in the Diabetes Technology and Therapeutics © 2012 [copyright Mary Ann Liebert, Inc.]; Diabetes Technology and Therapeutics is available online at: http://online.liebertpub.com.[EN] Objective: Prandial insulin dosing is an empirical practice associated frequently with poor reproducibility in postprandial glucose response. Based on continuous glucose monitoring (CGM), a method for prandial insulin administration (iBolus) is presented and evaluated for people with type 1 diabetes using CSII therapy. Subjects and Methods: An individual patient¿s model for a 5-h postprandial period was obtained from 6-day ambulatory CGM and used for iBolus calculation in 12 patients with type 1 diabetes. In a double-blind, crossover study each patient underwent four meal tests with 40 g or 100 g of carbohydrates (CHOs), both on two occasions. For each meal, the iBolus or the traditional bolus (tBolus) was given before mealtime (t 0) in a randomized order. We measured the postprandial glycemic response as the area under the curve of plasma glucose (AUC-PG0¿5h) and variability as the individual coef¿cient of variation (CV) of AUC-PG0¿5h. The contribution of the insulin-to-CHO ratio, CHO, plasma glucose at t 0 (PGt0), and insulin dose to AUC-PG0¿5h and its CV was also investigated. Results: AUC-PG0¿5h was similar with either bolus for 40-g (iBolus vs. tBolus, 585.5¿127.5 vs. 689.2¿180.7 mg/dL$h) or 100-g (752.1¿237.7 vs. 760.0¿263.2 mg/dL$h) CHO meals. A multiple regression analysis revealed a signi¿cant model only for the tBolus, with PGt0 being the best predictor of AUC-PG0¿5h explaining approximately 50% of the glycemic response. Observed variability was greater with the iBolus (CV, 16.7¿15.3% vs. 10.1¿12.5%) but independent of the factors studied. Conclusions: A CGM-based algorithm for calculation of prandial insulin is feasible, although it does not reduce unpredictability of individual glycemic responses. Causes of variability need to be identi¿ed and analyzed for further optimization of postprandial glycemic control.We are grateful to Mrs. Sara Correa, Fundacion INCLIVA-Hospital Clinico Universitario de Valencia, and Mrs. Geles Viguer, Hospital Clinico Universitario de Valencia, for their invaluable help in conducting the study. We also thanks Dr. Carmine Fanelli, University of Perugia, Dr. Howard Zisser, Sansum Diabetes Research Institute, and Prof. Alberto Ferrer, Universitat Politecnica de Valencia, for their suggestions on study design and data analysis. The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007/2013) under grant agreement 252085 and from the Spanish Ministry of Science under grants DPI2010-20764-C02-01 and DPI2011-28112-C04-01.Rossetti, P.; Ampudia Blasco, FJ.; Laguna Sanz, AJ.; Revert Tomás, A.; Vehí Casellas, J.; Ascaso, JF.; Bondía Company, J. (2012). Evaluation of a novel continuous glucose monitoring-based method for mealtime insulin dosing - the iBolus - in subjects with type 1 diabetes using continuous subcutaneous insulin infusion therapy: a randomized controlled trial. Diabetes Technology & Therapeutics. 14(11):1043-1052. https://doi.org/10.1089/dia.2012.0145S10431052141

Relapsing insulin-induced lipoatrophy, cured by prolonged low-dose oral prednisone: a case report

<p>Abstract</p> <p>Introduction</p> <p>Circumscript, progressing lipoatrophy at the insulin injection sites is an unexplained, however rare condition in diabetes mellitus.</p> <p>Case presentation</p> <p>We report a case of severe localised lipoatrophy developing during insulin pump-treatment (continuous subcutaneous insulin infusion) with the insulin analogue lispro (Humalog^®) in a woman with type-1 diabetes mellitus. After 11 months of progressing lipoatrophy at two spots on the abdomen, low-dose prednisone (5-10 mg) p.o. was given at breakfast for 8 months, whereby the atrophic lesions centripetally re-filled with subcutaneous fat tissue (confirmed by MRI) despite ongoing use of insulin lispro. However, 4 weeks after cessation of prednisone, lipoatrophy relapsed, but resolved after another 2 months of low-dose prednisone. No further relapse was noted during 12 months of follow-up on insulin-pump therapy with Humalog^®.</p> <p>Conclusion</p> <p>Consistent with an assumed inflammatory nature of the condition, low-dose oral prednisone appeared to have cured the lipoatrophic reaction in our patient. Our observation suggests a temporary intolerance of the subcutaneous fat tissue to insulin lispro (Humalog^®), triggered by an unknown endogenous mechanism.</p

Patient-reported outcomes in adults with type 1 diabetes in global real-world clinical practice: The SAGE study

AimsTo conduct a secondary analysis of the SAGE study to evaluate the association between glycaemic control and patient-reported outcomes (PROs), in adults with type 1 diabetes (T1DM) across different age groups and regions.Materials and methodsSAGE was a multinational, cross-sectional, observational study in adults with T1DM. Data were collected at a single visit, analysed according to predefined age groups (26-44, 45-64, and ≥65 years), and reported across different regions. PRO questionnaires were applied to assess hypoglycaemia fear (Hypoglycemia Fear Survey-II), diabetes-related distress (Problem Areas In Diabetes questionnaire), insulin treatment satisfaction (Insulin Treatment Satisfaction Questionnaire), and diabetes-specific quality of life (QoL; Audit of Diabetes-Dependent Quality of Life). Multivariable analysis was performed to evaluate the relationship between glycated haemoglobin (HbA1c) target achievement (less than 7% and individualised targets) with PRO scores.ResultsThe PRO scores showed relatively low levels of diabetes-related emotional distress and fear of hypoglycaemia, moderate to high treatment satisfaction, and low diabetes-related impact on QoL. Results were generally comparable across age groups with some regional variability. Achievement of the HbA1c less than 7% target was associated with less worry about hypoglycaemia, lower diabetes-related emotional distress, higher insulin treatment satisfaction, and higher QoL. Achievement of individualised HbA1c targets was associated with lower diabetes-related emotional distress and higher insulin treatment satisfaction.ConclusionsBetter glycaemic control was most closely associated with low emotional distress due to diabetes and high patient-reported insulin treatment satisfaction