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1.
Diabetes Obes Metab ; 2022 Jan 04.
Artigo em Inglês | MEDLINE | ID: mdl-34984825

RESUMO

Laboratory measured glycosylated hemoglobin (HbA1c) is the gold standard for assessing glycemic control in people with diabetes and correlates with their risk of long-term complications. The emergence of continuous glucose monitoring (CGM) has highlighted limitations of HbA1c testing. HbA1c can only be reviewed infrequently and can mask the risk of hypoglycaemia or extreme glucose fluctuations. While CGM provides insights in the risk of hypoglycaemia as well as daily fluctuations of glucose, it can also be used to calculate an estimated HbA1c (eA1c) that has been used as a substitute of laboratory HbA1c. However, it is evident that eA1c and HbA1c values can differ widely. The glucose management indicator (GMI), calculated exclusively from CGM data, has been proposed. It uses the same scale (% or mmol/mol) as HbA1c, but is based on short-term average glucose values, rather than long-term glucose exposure. HbA1c and GMI values differ in up to 81% of individuals by more than ±0.1% and by more than ±0.3% in 51% of cases. Here, we review the factors that define these differences, such as the time period being assessed, the variation in glycation rates and factors such as anaemia and hemoglobinopathies. Recognising and understanding the factors that cause differences between HbA1c and GMI is an important clinical skill. In circumstances when HbA1c is elevated above GMI, further attempts at intensification of therapy based solely on the HbA1c value may increase the risk of hypoglycaemia. The observed difference between GMI and HbA1c also informs the important question about the predictive ability of GMI regarding long term complications. This article is protected by copyright. All rights reserved.

2.
Diabet Med ; : e14755, 2021 Dec 04.
Artigo em Inglês | MEDLINE | ID: mdl-34862815

RESUMO

BACKGROUND: The COVID-19 pandemic has led to the rapid implementation of remote care delivery in type 1 diabetes. We studied current modes of care delivery, healthcare professional experiences and impact on insulin pump training in type 1 diabetes care in the United Kingdom (UK). METHODS: The UK Diabetes Technology Network designed a 48-question survey aimed at health care professionals providing care in type 1 diabetes. RESULTS: One hundred and forty three health care professionals (48% diabetes physicians, 52% diabetes educators, 88% working in adult services) from approximately 75 UK centres (52% university hospitals, 46% general and community hospitals), responded to the survey. Telephone consultations were the main modality of care delivery. There was a higher reported time taken for video consultations versus telephone (p<0.001). Common barriers to remote consultations were patient familiarity with technology (72%) and access to patient device data (67%). We assessed the impact on insulin pump training. A reduction in total new pump starts (73%) and renewals (61%) was highlighted. Common barriers included patient digital literacy (61%), limited health care professional experience (46%) and time required per patient (44%). When grouped according to size of insulin pump service, pump starts and renewals in larger services were less impacted by the pandemic compared to smaller services. CONCLUSION: This survey highlights UK health care professionals experiences of remote care delivery. Whilst supportive of virtual care models, a number of factors highlighted, especially patient digital literacy, need to be addressed to improve virtual care delivery and device training.

3.
Diabet Med ; : e14758, 2021 Dec 04.
Artigo em Inglês | MEDLINE | ID: mdl-34862829

RESUMO

AIMS: Reliable estimation of the time spent in different glycemic ranges (time-in-ranges, TIRs) requires sufficiently long continuous glucose monitoring (CGM). In a 2019 paper (Battelino et al., Diabetes Care, 2019), an international panel of experts suggested using a correlation-based approach to obtain the minimum number of days for reliable TIRs estimates. More recently, in (Camerlingo et al., Diabetes Obes. Metab., 2021) we presented a mathematical equation linking the number of monitoring days to the uncertainty around TIRs estimates. In this work, we compare these two approaches. METHODS: The first 100 and 150 days of data were extracted from Study A (148 subjects, ~180 days), and the first 100, 150, 200, 250, and 300 days of data from Study B (45 subjects, ~365 days). For each of these data windows, the minimum monitoring duration was computed using correlation-based and equation-based approaches. The suggestions were compared for the windows of different durations extracted from the same study, and for the windows of equal duration extracted from different studies. RESULTS: When changing the dataset duration, the correlation-based approach produces inconsistent results, ranging from 23 to 64 days, for TIR. The equation-based approach was found to be robust versus this issue, as it is affected only by the characteristics of the population being monitored. Indeed, to grant a confidence interval of 5% around TIR, it suggests 18 days for windows from Study A, and 17 days for windows from Study B. CONCLUSIONS: The equation-based approach offers advantages for the design of clinical trials having time-in-ranges as final endpoints, with focus on trial duration.

4.
Diabetes Metab Syndr ; 16(1): 102345, 2021 Nov 22.
Artigo em Inglês | MEDLINE | ID: mdl-34920199

RESUMO

BACKGROUND AND AIM: The prevalence of diabetes is on its rise and South Asia bears a huge burden. Several factors such as heterogeneity in genetics, socio-economic factors, diet, and sedentary behavior contribute to the heightened risk of developing diabetes, its rapid progression, and the development of complications in this region. Even though there have been considerable advances in glucose monitoring technologies, diabetes treatments and therapeutics, glycemic control in South Asia remains suboptimal. The successful implementation of treatment interventions and metrics for the attainment of glycemic goals depends on appropriate guidelines that accord with the characteristics of the diabetes population. METHOD: The data were collected from studies published for more than the last ten years in the electronic databases PubMed and Google Scholar on the various challenges in the assessment and achievement of recommended TIR targets in the SA population using the keywords: Blood glucose, TIR, TAR, TBR, HbA1c, hypoglycemia, CGM, Gestational diabetes mellitus (GDM), and diabetes. RESULTS: The objective of this recommendation is to discuss the limitations in considering the IC-TIR Expert panel recommendations targets and to propose some modifications in the lower limit of TIR in older/high-risk population, upper limit of TAR, and flexibility in the percentage of time spent in TAR for pregnant women (GDM, T2DM) for the South Asian population. CONCLUSION: The review sheds insights into some of the major concerns in implementing the IC-TIR recommendations in South Asian population where the prevalence of diabetes and its complications are significantly higher and modifications to the existing guidelines for use in routine clinical practice.

5.
J Psychosom Res ; 150: 110634, 2021 11.
Artigo em Inglês | MEDLINE | ID: mdl-34610494

RESUMO

OBJECTIVE: Severe hypoglycemia complicates insulin therapy for type 1 diabetes, with impaired awareness of hypoglycemia (IAH) being a major risk factor. We explored associations between the personality traits, alexithymia and perfectionism, and cognitive barriers to hypoglycemia avoidance described in IAH, and evaluated their prevalence in people with and without IAH. METHODS: Cross-sectional exploratory study. Ninety adults with type 1 diabetes, 54 hypoglycemia aware and 36 with IAH, completed validated questionnaires exploring alexithymia (Total Alexithymia Scale [TAS-20]) and perfectionism (Frost Multidimensional Perfectionism Scale [FMPS]); and cognitive barriers related to hypoglycemia avoidance (Attitudes to Awareness Questionnaire [A2A]. RESULTS: Alexithymia and perfectionism scores correlated positively with cognitive barriers associated with IAH. Specifically, alexthymia scores correlated with the 'Hyperglycaemia Avoidance Prioritised' factor (r = 0.265; p = .02, n = 77) and the 'Asymptomatic Hypoglycemia Normalised' factor (r = 0.252-0.255; p = .03, n = 77). Perfectionism scores correlated with the 'Hyperglycaemia Avoidance Prioritised' factor (r = 0.525; p < .001, n = 66). Overall, IAH participants were significantly more likely to score at the high end for alexithymia (17.6% vs. 1.9%, p = .008, n = 87) and at the extreme ends (high and low) for perfectionism (69.0% vs. 40.0%, χ2 (1) = 6.24, p = .01, n = 77). CONCLUSION: These novel data showing associations between alexithymia and perfectionism scores and maladaptive health beliefs in IAH suggest the intriguing possibility that personality traits may contribute to the risk of IAH, perhaps through their influence on incentives to avoid hypoglycemia. If confirmed, measuring such traits may help tailor early adjunctive psychological intervention to reduce hypoglycemia burden for people with IAH.


Assuntos
Diabetes Mellitus Tipo 1 , Hipoglicemia , Perfeccionismo , Adulto , Sintomas Afetivos/epidemiologia , Conscientização , Estudos Transversais , Diabetes Mellitus Tipo 1/complicações , Humanos
7.
Diabet Med ; : e14678, 2021 Aug 25.
Artigo em Inglês | MEDLINE | ID: mdl-34432914

RESUMO

AIMS: To review and synthesise the contemporary qualitative evidence, relating to the individual, healthcare professional and system-level barriers and facilitators to injectable therapies in people with type 2 diabetes, and evaluate (using an intersectional approach to explore the diverse perspectives of different identities) whether views have changed with treatment and guideline advancements. METHODS: A meta-ethnography approach used. Eight databases searched from the years 2006 (GLP-1 analogues introduced) to February 2021. Study selection (using a pre-defined inclusion criteria), quality appraisal and data extraction, conducted independently by two reviewers. RESULTS: Screened 7143 abstracts, assessed 93 full-text papers for eligibility and included 42 studies-using data from 818 individuals with type 2 diabetes and 160 healthcare professionals. Studies covered a diverse range of views from healthcare professionals and individuals, including those relating to older adults and people from ethnic migrant backgrounds, and 10 studies rated moderate to strong research value. Key themes abstracted: barriers (physical/psychological/social) and facilitators (motivation/capability/opportunity). CONCLUSIONS: The first synthesis of contemporary qualitative data to adopt an intersectionality approach and explore diverse views relating to barriers and facilitators that influence engagement with injectable treatments for type 2 diabetes. A model is presented to help patients, health practitioners and policy makers identify barriers and facilitators and understand the complex interplay of physical, psychological and social factors involved when prescribing injectable therapies. Despite advances in injectable treatments and guidelines, findings highlight the many barriers that still exist and show how strongly held culturally-specific health beliefs of people from diverse socio-economic and ethnic backgrounds can become substantial obstacles to treatment.

8.
Diabetes Ther ; 12(9): 2289-2310, 2021 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-34338994

RESUMO

People with diabetes are at greater risk for negative outcomes from COVID-19. Though this risk is multifactorial, poor glycaemic control before and during admission to hospital for COVID-19 is likely to contribute to the increased risk. The COVID-19 pandemic and restrictions on mobility and interaction can also be expected to impact on daily glucose management of people with diabetes. Telemonitoring of glucose metrics has been widely used during the pandemic in people with diabetes, including adults and children with T1D, allowing an exploration of the impact of COVID-19 inside and outside the hospital setting on glycaemic control. To date, 27 studies including 69,294 individuals with T1D have reported the effect of glycaemic control during the COVID-19 pandemic. Despite restricted access to diabetes clinics, glycaemic control has not deteriorated for 25/27 cohorts and improved in 23/27 study groups. Significantly, time in range (TIR) 70-180 mg/dL (3.9-10 mmol/L) increased across 19/27 cohorts with a median 3.3% (- 6.0% to 11.2%) change. Thirty per cent of the cohorts with TIR data reported an average clinically significant TIR improvement of 5% or more, possibly as a consequence of more accurate glucose monitoring and improved connectivity through telemedicine. Periodic consultations using telemedicine enables care of people with diabetes while limiting the need for in-person attendance at diabetes clinics. Reports that sustained hyperglycaemia and early-stage diabetic ketoacidosis may go untreated because of the lockdown and concerns about potential exposure to the risk of infection argue for wider access to glucose telemonitoring. Therefore, in this paper we have critically reviewed reports concerning use of telemonitoring in the acute hospitalized setting as well as during daily diabetes management. Furthermore, we discuss the indications and implications of adopting telemonitoring and telemedicine in the present challenging time, as well as their potential for the future.

9.
Diabetes Ther ; 12(9): 2311-2327, 2021 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-34390477

RESUMO

Telemedicine in diabetes care has been evolving over several years, particularly since the advent of cloud-connected technologies for diabetes management, such as glucose monitoring devices, including continuous glucose monitoring (CGM) systems, that facilitate sharing of glucose data between people with diabetes and their healthcare professionals in near-real time. Extreme social distancing and shielding in place for vulnerable patients during the COVID-19 pandemic has created both the challenge and the opportunity to provide care at a distance on a large scale. Available evidence suggests that glucose control has in fact improved during this period for people with diabetes who are able to use CGM devices for remote glucose monitoring. The development of telemedicine as part of the standard of care in diabetes faces significant challenges in the European context, particularly in terms of providing consistent and effective care at a distance to large populations of patients while using robust systems that can be supported by large regional and national healthcare services. These challenges include a fragmented approach to healthcare technology assessment and reimbursement, lack of eHealth education and literacy, particularly amongst healthcare professionals, lack of data integration, as well as concerns about electronic health records, patient consent and privacy. Here we review the benefits of and challenges to wider application of telemedicine and telemonitoring in the post-pandemic future, with the aim to ensure that the value of these eHealth services is provided to patients, healthcare providers and health systems.

10.
Comput Methods Programs Biomed ; 209: 106303, 2021 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-34380077

RESUMO

BACKGROUND AND OBJECTIVE: As continuous glucose monitoring (CGM) becomes common in research and clinical practice, there is a need to understand how CGM-based hypoglycemia relates to hypoglycemia episodes defined conventionally as patient reported hypoglycemia (PRH). Data show that CGM identify many episodes of low interstitial glucose (LIG) that are not experienced by patients, and so the aim of this study is to use different PRH simulations to optimize CGM parameters of threshold (h) and duration (d) to provide the best PRH detection performance. METHODS: The algorithm uses particle Markov chain Monte Carlo optimization to identify the optimal h and d which maximize an objective function for detecting PRH. We tested our algorithm by creating three different cases of PRH simulations. RESULTS: We added three types of simulated PRH events to 10 weeks of anonymized CGM data from 96 type 1 diabetes people to see if the algorithm can detect the optimal parameters set out in the simulations. In simulation 1, we changed the locations of PRHs with respect to LIG episodes in the CGM signal to simulate random optimal LIG parameters for every individual. In simulation 2, the PRHs are CGM glucose <3.9 mmol/L followed by at least 20 min of rise > 0.11 mmol/L/min. Simulation 3 is like simulation 2 but with glucose threshold of 3.0 mmol/L. The median [interquartile range] of deviation between the optimized (found by the algorithm) and the optimal (known) h and d are -0.07% [-0.4, 1.9] and -1.3% [-5.9, 6.8], respectively across the subjects for simulation 1. The mean [min max] of the optimized LIG parameters are h = 3.8 [3.7, 3.8] mmol/L and d = 12 [10, 14] min for simulation 2 and they are h = 3.0 [2.9, 3] mmol/L and d = 10 [8, 14] min for simulation 3 across a 10-fold cross validation. CONCLUSIONS: This work demonstrates the feasibility of the algorithm to find the best-fit definition of CGM-based hypoglycemia for PRH detection. In a prospective clinical study collecting CGM and PRH, the current algorithm will be used to optimize the definition of hypoglycemia with respect to PRH with the ambition of using the resulted definition as a surrogate for PRH in clinical practice.


Assuntos
Diabetes Mellitus Tipo 1 , Hipoglicemia , Glicemia , Automonitorização da Glicemia , Humanos , Hipoglicemia/diagnóstico , Estudos Prospectivos
11.
Am J Transplant ; 2021 Aug 05.
Artigo em Inglês | MEDLINE | ID: mdl-34355503

RESUMO

The UK islet allotransplant program is nationally funded to deliver one or two transplants over 12 months to individuals with type 1 diabetes and recurrent severe hypoglycemia. Analyses were undertaken 10 years after program inception to evaluate associations between transplanted mass; single versus two transplants; time between two transplants and graft survival (stimulated C-peptide >50 pmol/L) and function. In total, 84 islet transplant recipients were studied. Uninterrupted graft survival over 12 months was attained in 23 (68%) single and 47 (94%) (p = .002) two transplant recipients (separated by [median (IQR)] 6 (3-8) months). 64% recipients of one or two transplants with uninterrupted function at 12 months sustained graft function at 6 years. Total transplanted mass was associated with Mixed Meal Tolerance Test stimulated C-peptide at 12 months (p < .01). Despite 1.9-fold greater transplanted mass in recipients of two versus one islet infusion (12 218 [9291-15 417] vs. 6442 [5156-7639] IEQ/kg; p < .0001), stimulated C-peptide was not significantly higher. Shorter time between transplants was associated with greater insulin dose reduction at 12 months (beta -0.35; p = .02). Graft survival over the first 12 months was greater in recipients of two versus one islet transplant in the UK program, although function at 1 and 6 years was comparable. Minimizing the interval between 2 islet infusions may maximize cumulative impact on graft function.

12.
Diabetes Obes Metab ; 23(11): 2446-2454, 2021 11.
Artigo em Inglês | MEDLINE | ID: mdl-34212483

RESUMO

AIM: To compute the uncertainty of time-in-ranges, such as time in range (TIR), time in tight range (TITR), time below range (TBR) and time above range (TAR), to evaluate glucose control and to determine the minimum duration of a trial to achieve the desired precision. MATERIALS AND METHODS: Four formulas for the aforementioned time-in-ranges were obtained by estimating the equation's parameters on a training set extracted from study A (226 subjects, ~180 days, 5-minute Dexcom G4 Platinum sensor). The formulas were then validated on the remaining data. We also illustrate how to adjust the parameters for sensors with different sampling rates. Finally, we used study B (45 subjects, ~365 days, 15-minute Abbott Freestyle Libre sensor) to further validate our results. RESULTS: Our approach was effective in predicting the uncertainty when time-in-ranges are estimated using n days of continuous glucose monitoring (CGM), matching the variability observed in the data. As an example, monitoring a population with TIR = 70%, TITR = 50%, TBR = 5% and TAR = 25% for 30 days warrants a precision of ±3.50%, ±3.68%, ±1.33% and ±3.66%, respectively. CONCLUSIONS: The presented approach can be used to both compute the uncertainty of time-in-ranges and determine the minimum duration of a trial to achieve the desired precision. An online tool to facilitate its implementation is made freely available to the clinical investigator.


Assuntos
Glicemia , Diabetes Mellitus Tipo 1 , Automonitorização da Glicemia , Diabetes Mellitus Tipo 1/tratamento farmacológico , Humanos , Fatores de Tempo
13.
J Diabetes Sci Technol ; : 19322968211012392, 2021 May 12.
Artigo em Inglês | MEDLINE | ID: mdl-33978501

RESUMO

BACKGROUND: In the management of type 1 diabetes (T1D), systematic and random errors in carb-counting can have an adverse effect on glycemic control. In this study, we performed an in silico trial aiming at quantifying the impact of different levels of carb-counting error on glycemic control. METHODS: The T1D patient decision simulator was used to simulate 7-day glycemic profiles of 100 adults using open-loop therapy. The simulation was repeated for different values of systematic and random carb-counting errors, generated with Gaussian distribution varying the error mean from -10% to +10% and standard deviation (SD) from 0% to 50%. The effect of the error was evaluated by computing the difference of time inside (∆TIR), above (∆TAR) and below (∆TBR) the target glycemic range (70-180mg/dl) compared to the reference case, that is, absence of error. Finally, 3 linear regression models were developed to mathematically describe how error mean and SD variations result in ∆TIR, ∆TAR, and ∆TBR changes. RESULTS: Random errors globally deteriorate the glycemic control; systematic underestimations lead to, on average, up to 5.2% more TAR than the reference case, while systematic overestimation results in up to 0.8% more TBR. The different time in range metrics were linearly related with error mean and SD (R2>0.95), with slopes of ßMEAN=0.21, ßSD=-0.07 for ∆TIR, ßMEAN=-0.25, ßSD=+0.06 for ∆TAR, and ßMEAN=0.05, ßSD=+0.01 for ∆TBR. CONCLUSIONS: The quantification of carb-counting error impact performed in this work may be useful understanding causes of glycemic variability and the impact of possible therapy adjustments or behavior changes in different glucose metrics.

14.
Diabetes Obes Metab ; 23(8): 1989-1994, 2021 08.
Artigo em Inglês | MEDLINE | ID: mdl-33999488

RESUMO

We report a real-world evaluation of the first commercially approved automated insulin delivery (AID) system, MiniMed 670G (670G), and open source-automated insulin delivery (OS-AID) systems. This was undertaken as a retrospective observational study in adults with type 1 diabetes using AID systems for 6 months or longer in a publicly funded health service using clinically validated data. Sixty-eight adults (38 670G, 30 OS-AID systems) were included. OS-AID system users were younger, had a shorter diabetes duration and a higher education status. OS-AID systems displayed a significantly better change in HbA1c (median -0.9% [-0.4%, -1.1%] vs. -0.1% [IQR -0.7%, 0.2%], P = .004) and time in range 3.9-10 mmol/L (mean 78.5%, SD ± 12.0% vs. 68.2% ± 14.7%, P = .024) compared with 670G. Both systems showed minimal hypoglycaemia, with OS-AID systems revealing significantly improved secondary outcomes of mean glucose and percentage of time more than 10 mmol/L, with a higher percentage of time of less than 3 mmol/L. OS-AID system users displayed improved glycaemic outcomes with no clinical safety concerns compared with 670G, although higher weight-adjusted insulin dose and weight gain were noted. The study highlights key differences in OS-AID system user characteristics that are important for interpreting real-world findings from recent OS-AID system studies.


Assuntos
Diabetes Mellitus Tipo 1 , Pâncreas Artificial , Adulto , Glicemia , Automonitorização da Glicemia , Diabetes Mellitus Tipo 1/tratamento farmacológico , Diabetes Mellitus Tipo 1/epidemiologia , Humanos , Hipoglicemiantes/uso terapêutico , Insulina/uso terapêutico , Sistemas de Infusão de Insulina
16.
Diabetes Metab Res Rev ; 37(7): e3449, 2021 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-33763974

RESUMO

The main objective of diabetes control is to correct hyperglycaemia while avoiding hypoglycaemia, especially in insulin-treated patients. Fear of hypoglycaemia is a hurdle to effective correction of hyperglycaemia because it promotes under-dosing of insulin. Strategies to minimise hypoglycaemia include education and training for improved hypoglycaemia awareness and the development of technologies to allow their early detection and thus minimise their occurrence. Patients with impaired hypoglycaemia awareness would benefit the most from these technologies. The purpose of this systematic review is to review currently available or in-development technologies that support detection of hypoglycaemia or hypoglycaemia risk, and identify gaps in the research. Nanomaterial use in sensors is a promising strategy to increase the accuracy of continuous glucose monitoring devices for low glucose values. Hypoglycaemia is associated with changes on vital signs, so electrocardiogram and encephalogram could also be used to detect hypoglycaemia. Accuracy improvements through multivariable measures can make already marketed galvanic skin response devices a good noninvasive alternative. Breath volatile organic compounds can be detected by dogs and devices and alert patients at hypoglycaemia onset, while near-infrared spectroscopy can also be used as a hypoglycaemia alarms. Finally, one of the main directions of research are deep learning algorithms to analyse continuous glucose monitoring data and provide earlier and more accurate prediction of hypoglycaemia. Current developments for early identification of hypoglycaemia risk combine improvements of available 'needle-type' enzymatic glucose sensors and noninvasive alternatives. Patient usability will be essential to demonstrate to allow their implementation for daily use in diabetes management.

17.
Diabet Med ; 38(7): e14546, 2021 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-33616262
18.
BMJ Open ; 11(1): e040438, 2021 01 18.
Artigo em Inglês | MEDLINE | ID: mdl-33462097

RESUMO

INTRODUCTION: The successful treatment of type 1 diabetes (T1D) requires those affected to employ insulin therapy to maintain their blood glucose levels as close to normal to avoid complications in the long-term. The Dose Adjustment For Normal Eating (DAFNE) intervention is a group education course designed to help adults with T1D develop and sustain the complex self-management skills needed to adjust insulin in everyday life. It leads to improved glucose levels in the short term (manifest by falls in glycated haemoglobin, HbA1c), reduced rates of hypoglycaemia and sustained improvements in quality of life but overall glucose levels remain well above national targets. The DAFNEplus intervention is a development of DAFNE designed to incorporate behavioural change techniques, technology and longer-term structured support from healthcare professionals (HCPs). METHODS AND ANALYSIS: A pragmatic cluster randomised controlled trial in adults with T1D, delivered in diabetes centres in National Health Service secondary care hospitals in the UK. Centres will be randomised on a 1:1 basis to standard DAFNE or DAFNEplus. Primary clinical outcome is the change in HbA1c and the primary endpoint is HbA1c at 12 months, in those entering the trial with HbA1c >7.5% (58 mmol/mol), and HbA1c at 6 months is the secondary endpoint. Sample size is 662 participants (approximately 47 per centre); 92% power to detect a 0.5% difference in the primary outcome of HbA1c between treatment groups. The trial also measures rates of hypoglycaemia, psychological outcomes, an economic evaluation and process evaluation. ETHICS AND DISSEMINATION: Ethics approval was granted by South West-Exeter Research Ethics Committee (REC ref: 18/SW/0100) on 14 May 2018. The results of the trial will be published in a National Institute for Health Research monograph and relevant high-impact journals. TRIAL REGISTRATION NUMBER: ISRCTN42908016.


Assuntos
Diabetes Mellitus Tipo 1/terapia , Ensaios Clínicos Controlados Aleatórios como Assunto , Autogestão , Adulto , Diabetes Mellitus Tipo 1/psicologia , Hemoglobina A Glicada/análise , Hemoglobina A Glicada/metabolismo , Humanos , Educação de Pacientes como Assunto , Qualidade de Vida , Medicina Estatal
19.
Diabetes Metab Res Rev ; 37(6): e3418, 2021 09.
Artigo em Inglês | MEDLINE | ID: mdl-33098260

RESUMO

Initiating insulin therapy with a basal insulin analogue has become a standard of care in the treatment of type 2 diabetes mellitus (T2DM). Despite increasing choices in pharmacological approaches, intensified glucose monitoring and improvements in quality of care, many patients do not achieve the desired level of glycaemic control. Although insulin therapy, when optimized, can help patients reach their glycaemic goals, there are barriers to treatment initiation on both the side of the patient and provider. Providers experience barriers based on their perceptions of patients' capabilities and concerns. They may lack the confidence to solve the practical problems of insulin therapy and avoid decisions they perceive as risky for their patients. In this study, we review recommendations for basal insulin initiation, focussing on glycaemic targets, titration, monitoring, and combination therapy with non-insulin anti-hyperglycaemic medications. We provide practical advice on how to address some of the key problems encountered in everyday clinical practice and give recommendations where there are gaps in knowledge or guidelines. We also discuss common challenges faced by people with T2DM, such as weight gain and hypoglycaemia, and how providers can address and overcome them.

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