BackgroundDifferentiating between type 1 and type 2 diabetes is fundamental to ensuring appropriate management of patients, but can be challenging, especially when treating with insulin. The 2010 UK Practical Classification Guidelines for Diabetes were developed to help make the differentiation.AimTo assess diagnostic accuracy of the UK guidelines against ‘gold standard’ definitions of type 1 and type 2 diabetes based on measured C-peptide levels.Design and settingIn total, 601 adults with insulin-treated diabetes and diabetes duration ≥5 years were recruited in Devon, Northamptonshire, and Leicestershire.MethodBaseline information and home urine sample were collected. Urinary C-peptide creatinine ratio (UCPCR) measures endogenous insulin production. Gold standard type 1 diabetes was defined as continuous insulin treatment within 3 years of diagnosis and absolute insulin deficiency (UCPCR<0.2 nmol/mmol ≥5 years post-diagnosis); all others classed as having type 2 diabetes. Diagnostic performance of the clinical criteria was assessed and other criteria explored using receiver operating characteristic (ROC) curves.ResultsUK guidelines correctly classified 86% of participants. Most misclassifications occurred in patients classed as having type 1 diabetes who had significant endogenous insulin levels (57 out of 601; 9%); most in those diagnosed ≥35 years and treated with insulin from diagnosis, where 37 out of 66 (56%) were misclassified. Time to insulin and age at diagnosis performed best in predicting long-term endogenous insulin production (ROC AUC = 0.904 and 0.871); BMI was a less strong predictor of diabetes type (AUC = 0.824).ConclusionCurrent UK guidelines provide a pragmatic clinical approach to classification reflecting long-term endogenous insulin production; caution is needed in older patients commencing insulin from diagnosis, where misclassification rates are increased.

ObjectiveTo assess the care given to the babies born at the threshold of viability over the last 20 years using regional and national data.DesignPopulation-based retrospective study.SettingFormer ‘Trent’ health region.ParticipantsBabies born between 1 January 1991 and 31 December 2010 at 22+0 to 25+6 weeks gestational age.Main outcome measureSurvival and use of respiratory support.MethodsData of all babies born between 1 January 1991 and 31 December 2010 with a gestational age of 22+0 to 25+6 weeks and admitted to a neonatal unit were extracted from The Neonatal Survey. Use of respiratory support in terms of ventilation and continuous positive airway pressure (CPAP) for this group of babies was calculated as a proportion of the total used by the whole neonatal intensive care population within the defined study area.ResultsThe proportion of babies surviving to discharge increased significantly over time in those born at 24 and 25 weeks (p<0.01) but failed to achieve statistical significance for those at 23 weeks (p=0.08). No babies born at 22 weeks survived. The babies born at 22–25 weeks accounted for 26.3% of all ventilation and 21.5% of CPAP given.ConclusionOur work concurs with the current UK guidelines. There could be advantages in focusing the care of babies born at 23 weeks to a small number of intensive care units to allow specialist expertise to develop in all aspects of the management of these babies. However, focusing care will not necessarily improve survival or reduce morbidity.

BackgroundThe widespread use of smartphones makes effective therapies such as cognitive–behavioural therapy (CBT) potentially accessible to large numbers of people.AimsThis paper reports the usage data of the first trial of Catch It, a new CBT smartphone app.MethodUptake and usage rates, fidelity of user responses to CBT principles, and impact on reported negative and positive moods were assessed.ResultsA relatively modest proportion of people chose to download the app. Once used, the app tended to be used more than once, and 84% of the user-generated content was consistent with the basic concepts of CBT. There were statistically significant reductions in negative mood intensity and increases in positive mood intensity.ConclusionsSmartphone apps have potential beneficial effects in mental health through the application of basic CBT principles. More research with randomised controlled trial designs should be conducted.Declaration of interestNone.Copyright and usage© The Royal College of Psychiatrists 2016. This is an open access article distributed under the terms of the Creative Commons Non-Commercial, No Derivatives (CC BY-NC-ND) licence.

ObjectivesTo evaluate and compare the lifetime costs associated with strategies to identify individuals with monogenic diabetes and change their treatment to more appropriate therapy.DesignA decision analytical model from the perspective of the National Health Service (NHS) in England and Wales was developed and analysed. The model was informed by the literature, routinely collected data and a clinical study conducted in parallel with the modelling.SettingSecondary care in the UK.ParticipantsSimulations based on characteristics of patients diagnosed with diabetes <30 years old.InterventionsFour test-treatment strategies to identify individuals with monogenic diabetes in a prevalent cohort of diabetics diagnosed under the age of 30 years were modelled: clinician-based genetic test referral, targeted genetic testing based on clinical prediction models, targeted genetic testing based on biomarkers, and blanket genetic testing. The results of the test-treatment strategies were compared with a strategy of no genetic testing.Primary and secondary outcome measuresDiscounted lifetime costs, proportion of cases of monogenic diabetes identified.ResultsBased on current evidence, strategies using clinical characteristics or biomarkers were estimated to save approximately £100–£200 per person with diabetes over a lifetime compared with no testing. Sensitivity analyses indicated that the prevalence of monogenic diabetes, the uptake of testing, and the frequency of home blood glucose monitoring had the largest impact on the results (ranging from savings of £400–£50 per person), but did not change the overall findings. The model is limited by many model inputs being based on very few individuals, and some long-term data informed by clinical opinion.ConclusionsCosts to the NHS could be saved with targeted genetic testing based on clinical characteristics or biomarkers. More research should focus on the economic case for the use of such strategies closer to the time of diabetes diagnosis.Trial registration numberNCT01238380.

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