Plain English summaryMany young adults with type 1 diabetes (T1D) find it hard to control their blood glucose levels. With lots of things going on in their lives, their diabetes is often not the most important thing to them. That means they do not always take care of their T1D, for example by going to clinic appointments. Young adults with T1D do not usually get the chance to make suggestions on how to improve diabetes services. Being involved could help young adults to shape the diabetes care services that support them. Since 2014 a diabetes research team based in Galway has been looking at ways to improve how diabetes services are delivered to young adults. Eight young adults (aged 18-25 years) with T1D called the Young Adult Panel (YAP) are members of this team and have helped design the "D1 Now" intervention which aims to improve diabetes services. The YAP came up with questions to ask other young adults with T1D, their families and friends and healthcare providers about their experiences of healthcare services and how these could be improved. The YAP also shared messages from the research at national conferences and on local radio. They helped with writing sections of a grant application to take this research work forward. Our experience has shown the importance of involving young adults with T1D in helping to design research focusing on ways to improve their diabetes service that will help them and other young adults to live with diabetes in the future. O'Hara et al. Research Involvement and Engagement (2017) 3:21 DOI 10.1186/s40900-017-0068-9(Continued from previous page) Abstract Background Research indicates that young adults (18-25 year olds) with type 1 diabetes (T1D) often disengage from health services and their general diabetes management. Involving young adults with T1D in co-designing research to develop a behaviour change intervention to improve engagement with health services could potentially improve overall self management and health. A local youth mental health organisation called Jigsaw, Galway developed a very successful model for involving users in service design and development. Based on this model, the aim was to form a Young Adult Panel (YAP) of 18-25 year olds with T1D and involve them in all aspects of a study to develop an intervention to improve health and wellbeing for young adults with T1D called D1 Now.Methods Recruitment of young adults was achieved through a multimedia campaign. A consultation event was organised, followed by interviews with interested young adults. A panel of 8 members was selected. Following initial training for YAP members in committee skills and an introduction to different research methods and terms, YAP members participated in different stages of the research process. They were represented on the research study steering group and attended research meetings. They developed research materials, reviewed and interpreted research findings and helped develop the online platform to enhance engagement between young adults and their diabetes healthcare providers....

Risk of type 1 diabetes at 3 years is high for initially multiple and single Ab+ IT and multiple Ab+ NT. Genetic predisposition, age, and male sex are significant risk factors for development of Ab+ in twins.

A female patient was treated for type 1 diabetes following presentation at 12 years of age with hyperglycaemia, polydipsia and weight loss. Eleven years later, while screening relatives attending a genetic diabetes clinic, she was identified as potentially harbouring a mutation in thehepatocyte nuclear factor 1A (HNF1A)gene. Biochemical testing supported the diagnosis of HNF1A-maturity onset diabetes of the young (MODY) and genetic screening was positive for a heterozygous mutation in theHNF1Agene. The patient transitioned from insulin to sulfonylurea therapy. Three years later, in the setting of poor metabolic control, the patient presented to the emergency department with a history of nausea, vomiting and palpitations. A diagnosis of diabetic ketoacidosis (DKA) was confirmed and successfully treated. Although a diagnosis of HNF1A-MODY is rarely considered in a patient with a history of DKA, we demonstrate that DKA is possible in the setting of non-compliance with sulfonylurea therapy.

These results have prompted a re think of how health care professionals can deliver a service that better suits the needs of this challenging patient group.

MODY is a rare form of diabetes caused by impaired insulin production attributable to autosomal dominant monogenic mutations. It is an important diagnosis as it results in a treatment change for 25% of patients, allows for the screening of 1 st degree relatives and identifies patients who have MODY subtypes associated with reduced rates of micro- and macro-vascular complications. Diagnosing MODY is challenging and several MODY risk factor calculators have been proposed to guide rational genetic testing. The aim of this study was to retrospectively apply the MODY risk factor calculators to patients with diagnosed MODY who attended the diabetes service at a tertiary hospital in the West of Ireland to identify the most accurate calculator in predicting MODY in this patient cohort. MODY risk factor calculators in the literature focus on young age at diagnosis, low BMI and low HbA1c as defining features of MODY. Ellard, Bellanne-Chantelot et al. (2008) proposed age at diagnosis ≤25, BMI <30 and HbA1c ≤58.8 mmol/L as the recommended criteria for genetic testing in MODY, and this captured 6/21 (28.57%) patients with MODY in our cohort. Thanabalasingham, Pal et al. (2012) proposed age at diagnosis ≤30, BMI <30 and HbA1c ≤63.9 mmol/L, which accounted for 8/21 (38.1%) of our MODY patients. The MODY Probability Calculator proposed by Shields et al. (2012) was developed using logistic regression to determine the probability of MODY. Variables include current age, age at diagnosis, sex, treatment with insulin, time to insulin treatment, BMI, HbA1c and parental history of diabetes. The MODY Probability Calculator cannot be directly compared to the other calculators, as it does not define clinical criteria in a binary fashion but assigns a weighting to each factor. Patients have to be aged ≤35 at diagnosis for this calculator to be applied, which resulted in the exclusion of 3/22 patients in our cohort. 9/22 (40.9%) patients had a positive predictive value (PPV) of >50%, which conferred a 0.47/100 false negative rate and a 3/100 false positive rate if used as the basis for referring for genetic testing. 5/22 (22.73%) patients had a PPV of >75%, which conferred a 0.9/100 false negative rate and a 1.2/100 false positive rate, which is highly sensitive and specific. 12/22 (54.55%) patients had a PPV of >20%, which conferred a 0.14/100 false negative rate and a 16.8/100 false positive rate. This work demonstrates that the MODY Probability Calculator currently achieves the best balance of sensitivity / specificity in diagnosing patients with MODY. Nevertheless, a significant portion (10/22) of known MODY patients were not identified. Limitations include excluding patients aged >35 at diagnosis and excluding patients with a strong family history of diabetes who do not have an affected parent. These calculators are diagnostic adjuncts in the Endocrinologist’s toolbox to stratify MODY risk but do not replace clinical judgement.