Safety and effectiveness of SGLT2 inhibitors in a UK population with type 2 diabetes and aged over 70 years: an instrumental variable approach.

AIMS/HYPOTHESIS: Older adults are under-represented in trials, meaning the benefits and risks of glucose-lowering agents in this age group are unclear. The aim of this study was to assess the safety and effectiveness of sodium-glucose cotransporter 2 inhibitors (SGLT2i) in people with type 2 diabetes aged over 70 years using causal analysis. METHODS: Hospital-linked UK primary care data (Clinical Practice Research Datalink, 2013-2020) were used to compare adverse events and effectiveness in individuals initiating SGLT2i compared with dipeptidyl peptidase-4 inhibitors (DPP4i). Analysis was age-stratified: <70 years (SGLT2i n=66,810, DPP4i n=76,172), ≥70 years (SGLT2i n=10,419, DPP4i n=33,434). Outcomes were assessed using the instrumental variable causal inference method and prescriber preference as the instrument. RESULTS: Risk of diabetic ketoacidosis was increased with SGLT2i in those aged ≥70 (incidence rate ratio compared with DPP4i: 3.82 [95% CI 1.12, 13.03]), but not in those aged <70 (1.12 [0.41, 3.04]). However, incidence rates with SGLT2i in those ≥70 was low (29.6 [29.5, 29.7]) per 10,000 person-years. SGLT2i were associated with similarly increased risk of genital infection in both age groups (incidence rate ratio in those <70: 2.27 [2.03, 2.53]; ≥70: 2.16 [1.77, 2.63]). There was no evidence of an increased risk of volume depletion, poor micturition control, urinary frequency, falls or amputation with SGLT2i in either age group. In those ≥70, HbA1c reduction was similar between SGLT2i and DPP4i (-0.3 mmol/mol [-1.6, 1.1], -0.02% [0.1, 0.1]), but in those <70, SGLT2i were more effective (-4 mmol/mol [4.8, -3.1], -0.4% [-0.4, -0.3]). CONCLUSIONS/INTERPRETATION: Causal analysis suggests SGLT2i are effective in adults aged ≥70 years, but increase risk for genital infections and diabetic ketoacidosis. Our study extends RCT evidence to older adults with type 2 diabetes.

Phenotype-based targeted treatment of SGLT2 inhibitors and GLP-1 receptor agonists in type 2 diabetes.

AIMS/HYPOTHESIS: A precision medicine approach in type 2 diabetes could enhance targeting specific glucose-lowering therapies to individual patients most likely to benefit. We aimed to use the recently developed Bayesian causal forest (BCF) method to develop and validate an individualised treatment selection algorithm for two major type 2 diabetes drug classes, sodium-glucose cotransporter 2 inhibitors (SGLT2i) and glucagon-like peptide-1 receptor agonists (GLP1-RA). METHODS: We designed a predictive algorithm using BCF to estimate individual-level conditional average treatment effects for 12-month glycaemic outcome (HbA1c) between SGLT2i and GLP1-RA, based on routine clinical features of 46,394 people with type 2 diabetes in primary care in England (Clinical Practice Research Datalink; 27,319 for model development, 19,075 for hold-out validation), with additional external validation in 2252 people with type 2 diabetes from Scotland (SCI-Diabetes [Tayside & Fife]). Differences in glycaemic outcome with GLP1-RA by sex seen in clinical data were replicated in clinical trial data (HARMONY programme: liraglutide [n=389] and albiglutide [n=1682]). As secondary outcomes, we evaluated the impacts of targeting therapy based on glycaemic response on weight change, tolerability and longer-term risk of new-onset microvascular complications, macrovascular complications and adverse kidney events. RESULTS: Model development identified marked heterogeneity in glycaemic response, with 4787 (17.5%) of the development cohort having a predicted HbA1c benefit >3 mmol/mol (>0.3%) with SGLT2i over GLP1-RA and 5551 (20.3%) having a predicted HbA1c benefit >3 mmol/mol with GLP1-RA over SGLT2i. Calibration was good in hold-back validation, and external validation in an independent Scottish dataset identified clear differences in glycaemic outcomes between those predicted to benefit from each therapy. Sex, with women markedly more responsive to GLP1-RA, was identified as a major treatment effect modifier in both the UK observational datasets and in clinical trial data: HARMONY-7 liraglutide (GLP1-RA): 4.4 mmol/mol (95% credible interval [95% CrI] 2.2, 6.3) (0.4% [95% CrI 0.2, 0.6]) greater response in women than men. Targeting the two therapies based on predicted glycaemic response was also associated with improvements in short-term tolerability and long-term risk of new-onset microvascular complications. CONCLUSIONS/INTERPRETATION: Precision medicine approaches can facilitate effective individualised treatment choice between SGLT2i and GLP1-RA therapies, and the use of routinely collected clinical features for treatment selection could support low-cost deployment in many countries.

The challenges of identifying and studying type 1 diabetes in adults.

Diagnosing type 1 diabetes in adults is difficult since type 2 diabetes is the predominant diabetes type, particularly with an older age of onset (approximately >30 years). Misclassification of type 1 diabetes in adults is therefore common and will impact both individual patient management and the reported features of clinically classified cohorts. In this article, we discuss the challenges associated with correctly identifying adult-onset type 1 diabetes and the implications of these challenges for clinical practice and research. We discuss how many of the reported differences in the characteristics of autoimmune/type 1 diabetes with increasing age of diagnosis are likely explained by the inadvertent study of mixed populations with and without autoimmune aetiology diabetes. We show that when type 1 diabetes is defined by high-specificity methods, clinical presentation, islet-autoantibody positivity, genetic predisposition and progression of C-peptide loss remain broadly similar and severe at all ages and are unaffected by onset age within adults. Recent clinical guidance recommends routine islet-autoantibody testing when type 1 diabetes is clinically suspected or in the context of rapid progression to insulin therapy after a diagnosis of type 2 diabetes. In this moderate or high prior-probability setting, a positive islet-autoantibody test will usually confirm autoimmune aetiology (type 1 diabetes). We argue that islet-autoantibody testing of those with apparent type 2 diabetes should not be routinely undertaken as, in this low prior-prevalence setting, the positive predictive value of a single-positive islet antibody for autoimmune aetiology diabetes will be modest. When studying diabetes, extremely high-specificity approaches are needed to identify autoimmune diabetes in adults, with the optimal approach depending on the research question. We believe that until these recommendations are widely adopted by researchers, the true phenotype of late-onset type 1 diabetes will remain largely misunderstood.

The impact of population-level HbA1c screening on reducing diabetes diagnostic delay in middle-aged adults: a UK Biobank analysis.

AIMS/HYPOTHESIS: Screening programmes can detect cases of undiagnosed diabetes earlier than symptomatic or incidental diagnosis. However, the improvement in time to diagnosis achieved by screening programmes compared with routine clinical care is unclear. We aimed to use the UK Biobank population-based study to provide the first population-based estimate of the reduction in time to diabetes diagnosis that could be achieved by HbA1c-based screening in middle-aged adults. METHODS: We studied UK Biobank participants aged 40-70 years with HbA1c measured at enrolment (but not fed back to participants/clinicians) and linked primary and secondary healthcare data (n=179,923) and identified those with a pre-existing diabetes diagnosis (n=13,077, 7.3%). Among the remaining participants (n=166,846) without a diabetes diagnosis, we used an elevated enrolment HbA1c level (≥48 mmol/mol [≥6.5%]) to identify those with undiagnosed diabetes. For this group, we used Kaplan-Meier analysis to assess the time between enrolment HbA1c measurement and subsequent clinical diabetes diagnosis up to 10 years, and Cox regression to identify clinical factors associated with delayed diabetes diagnosis. RESULTS: In total, 1.0% (1703/166,846) of participants without a diabetes diagnosis had undiagnosed diabetes based on calibrated HbA1c levels at UK Biobank enrolment, with a median HbA1c level of 51.3 mmol/mol (IQR 49.1-57.2) (6.8% [6.6-7.4]). These participants represented an additional 13.0% of diabetes cases in the study population relative to the 13,077 participants with a diabetes diagnosis. The median time to clinical diagnosis for those with undiagnosed diabetes was 2.2 years, with a median HbA1c at clinical diagnosis of 58.2 mmol/mol (IQR 51.0-80.0) (7.5% [6.8-9.5]). Female participants with lower HbA1c and BMI measurements at enrolment experienced the longest delay to clinical diagnosis. CONCLUSIONS/INTERPRETATION: Our population-based study shows that HbA1c screening in adults aged 40-70 years can reduce the time to diabetes diagnosis by a median of 2.2 years compared with routine clinical care. The findings support the use of HbA1c screening to reduce the time for which individuals are living with undiagnosed diabetes.

Comparison of causal forest and regression-based approaches to evaluate treatment effect heterogeneity: an application for type 2 diabetes precision medicine.

OBJECTIVE: Precision medicine requires reliable identification of variation in patient-level outcomes with different available treatments, often termed treatment effect heterogeneity. We aimed to evaluate the comparative utility of individualized treatment selection strategies based on predicted individual-level treatment effects from a causal forest machine learning algorithm and a penalized regression model. METHODS: Cohort study characterizing individual-level glucose-lowering response (6 month reduction in HbA1c) in people with type 2 diabetes initiating SGLT2-inhibitor or DPP4-inhibitor therapy. Model development set comprised 1,428 participants in the CANTATA-D and CANTATA-D2 randomised clinical trials of SGLT2-inhibitors versus DPP4-inhibitors. For external validation, calibration of observed versus predicted differences in HbA1c in patient strata defined by size of predicted HbA1c benefit was evaluated in 18,741 patients in UK primary care (Clinical Practice Research Datalink). RESULTS: Heterogeneity in treatment effects was detected in clinical trial participants with both approaches (proportion predicted to have a benefit on SGLT2-inhibitor therapy over DPP4-inhibitor therapy: causal forest: 98.6%; penalized regression: 81.7%). In validation, calibration was good with penalized regression but sub-optimal with causal forest. A strata with an HbA1c benefit > 10 mmol/mol with SGLT2-inhibitors (3.7% of patients, observed benefit 11.0 mmol/mol [95%CI 8.0-14.0]) was identified using penalized regression but not causal forest, and a much larger strata with an HbA1c benefit 5-10 mmol with SGLT2-inhibitors was identified with penalized regression (regression: 20.9% of patients, observed benefit 7.8 mmol/mol (95%CI 6.7-8.9); causal forest 11.6%, observed benefit 8.7 mmol/mol (95%CI 7.4-10.1). CONCLUSIONS: Consistent with recent results for outcome prediction with clinical data, when evaluating treatment effect heterogeneity researchers should not rely on causal forest or other similar machine learning algorithms alone, and must compare outputs with standard regression, which in this evaluation was superior.

Cherenkov Radiation in Optical Fibres as a Versatile Machine Protection System in Particle Accelerators.

Machine protection systems in high power particle accelerators are crucial. They can detect, prevent, and respond to events which would otherwise cause damage and significant downtime to accelerator infrastructure. Current systems are often resource heavy and operationally expensive, reacting after an event has begun to cause damage; this leads to facilities only covering certain operational modes and setting lower limits on machine performance. Presented here is a new type of machine protection system based upon optical fibres, which would be complementary to existing systems, elevating existing performance. These fibres are laid along an accelerator beam line in lengths of ∼100 m, providing continuous coverage over this distance. When relativistic particles pass through these fibres, they generate Cherenkov radiation in the optical spectrum. This radiation propagates in both directions along the fibre and can be detected at both ends. A calibration based technique allows the location of the Cherenkov radiation source to be pinpointed to within 0.5 m with a resolution of 1 m. This measurement mechanism, from a single device, has multiple applications within an accelerator facility. These include beam loss location monitoring, RF breakdown prediction, and quench prevention. Detailed here are the application processes and results from measurements, which provide proof of concept for this device for both beam loss monitoring and RF breakdown detection. Furthermore, highlighted are the current challenges for future innovation.

Understanding the pathogenesis of lean non-autoimmune diabetes in an African population with newly diagnosed diabetes.

AIMS/HYPOTHESIS: Apparent type 2 diabetes is increasingly reported in lean adult individuals in sub-Saharan Africa. However, studies undertaking robust clinical and metabolic characterisation of lean individuals with new-onset type 2 diabetes are limited in this population. This cross-sectional study aimed to perform a detailed clinical and metabolic characterisation of newly diagnosed adult patients with diabetes in Uganda, in order to compare features between lean and non-lean individuals. METHODS: Socio-demographic, clinical, biophysical and metabolic (including oral glucose tolerance test) data were collected on 568 adult patients with newly diagnosed diabetes. Participants were screened for islet autoantibodies to exclude those with autoimmune diabetes. The remaining participants (with type 2 diabetes) were then classified as lean (BMI <25 kg/m2) or non-lean (BMI ≥25 kg/m2), and their socio-demographic, clinical, biophysical and metabolic characteristics were compared. RESULTS: Thirty-four participants (6.4%) were excluded from analyses because they were positive for pancreatic autoantibodies, and a further 34 participants because they had incomplete data. For the remaining 500 participants, the median (IQR) age, BMI and HbA1c were 48 years (39-58), 27.5 kg/m2 (23.6-31.4) and 90 mmol/mol (61-113) (10.3% [7.7-12.5]), respectively, with a female predominance (approximately 57%). Of the 500 participants, 160 (32%) and 340 (68%) were lean and non-lean, respectively. Compared with non-lean participants, lean participants were mainly male (60.6% vs 35.3%, p<0.001) and had lower visceral adiposity level (5 [4-7] vs 11 [9-13], p<0.001) and features of the metabolic syndrome (uric acid, 246.5 [205.0-290.6] vs 289 [234-347] µmol/l, p<0.001; leptin, 660.9 [174.5-1993.1] vs 3988.0 [1336.0-6595.0] pg/ml, p<0.001). In addition, they displayed markedly reduced markers of beta cell function (oral insulinogenic index 0.8 [0.3-2.5] vs 1.6 [0.6-4.6] pmol/mmol; 120 min serum C-peptide 0.70 [0.33-1.36] vs 1.02 [0.60-1.66] nmol/l, p<0.001). CONCLUSIONS/INTERPRETATION: Approximately one-third of participants with incident adult-onset non-autoimmune diabetes had BMI <25 kg/m2. Diabetes in these lean individuals was more common in men, and predominantly associated with reduced pancreatic secretory function rather than insulin resistance. The underlying pathological mechanisms are unclear, but this is likely to have important management implications.

Mortality amongst children and adolescents with type 1 diabetes in sub-Saharan Africa: The case study of the Changing Diabetes in Children program in Cameroon.

INTRODUCTION: Type 1 diabetes in Africa has been associated with high mortality attributed mainly to poor insulin access. Free insulin provision programs for people with type 1 diabetes have been introduced across Africa recently. We aimed to determine the mortality rate and associated factors in a cohort of children and adolescents with type 1 diabetes who receive free insulin treatment in sub-Saharan Africa. METHODS: We conducted a retrospective analysis using the Changing Diabetes in Children (CDiC) medical records in Cameroon between 2011 and 2015. RESULTS: The overall mortality rate was 33.0 per 1000 person-years (95% CI 25.2-43.2). Most deaths (71.7%) occurred outside of the hospital setting, and the cause of death was known only in 13/53 (24.5%). Mortality was substantially higher in CDiC participants followed up in regional clinics compared to the main urban CDiC clinic in Yaounde; 41 per 1000 years (95% CI 30.8-56.0) versus 17.5 per 1000 years (95% CI 9.4-32.5), and in those with no formal education compared to those who had some level of education; 68.0 per 1000 years (95% CI 45.1-102.2) versus 23.6 per 1000 years (95% CI 16.5-33.8). In Cox proportional multivariable analysis, urban place of care (HR = 0.23, 95% CI 0.09-0.57; p = 0.002) and formal education (HR = 0.42, 95% CI 0.22-0.79; p = 0.007) were independently associated with mortality. CONCLUSION: Despite free insulin provision, mortality remains high in children and adolescents with type 1 diabetes in Cameroon and is substantially higher in rural settings and those with no formal education.

Choice of HbA1c threshold for identifying individuals at high risk of type 2 diabetes and implications for diabetes prevention programmes: a cohort study.

BACKGROUND: Type 2 diabetes (T2D) is common and increasing in prevalence. It is possible to prevent or delay T2D using lifestyle intervention programmes. Entry to these programmes is usually determined by a measure of glycaemia in the 'intermediate' range. This paper investigated the relationship between HbA1c and future diabetes risk and determined the impact of varying thresholds to identify those at high risk of developing T2D. METHODS: We studied 4227 participants without diabetes aged ≥ 40 years recruited to the Exeter 10,000 population cohort in South West England. HbA1c was measured at study recruitment with repeat HbA1c available as part of usual care. Absolute risk of developing diabetes within 5 years, defined by HbA1c ≥ 48 mmol/mol (6.5%), according to baseline HbA1c, was assessed by a flexible parametric survival model. RESULTS: The overall absolute 5-year risk (95% CI) of developing T2D in the cohort was 4.2% (3.6, 4.8%). This rose to 7.1% (6.1, 8.2%) in the 56% (n = 2358/4224) of participants classified 'high-risk' with HbA1c ≥ 39 mmol/mol (5.7%; ADA criteria). Under IEC criteria, HbA1c ≥ 42 mmol/mol (6.0%), 22% (n = 929/4277) of the cohort was classified high-risk with 5-year risk 14.9% (12.6, 17.2%). Those with the highest HbA1c values (44-47 mmol/mol [6.2-6.4%]) had much higher 5-year risk, 26.4% (22.0, 30.5%) compared with 2.1% (1.5, 2.6%) for 39-41 mmol/mol (5.7-5.9%) and 7.0% (5.4, 8.6%) for 42-43 mmol/mol (6.0-6.1%). Changing the entry criterion to prevention programmes from 39 to 42 mmol/mol (5.7-6.0%) reduced the proportion classified high-risk by 61%, and increased the positive predictive value (PPV) from 5.8 to 12.4% with negligible impact on the negative predictive value (NPV), 99.6% to 99.1%. Increasing the threshold further, to 44 mmol/mol (6.2%), reduced those classified high-risk by 59%, and markedly increased the PPV from 12.4 to 23.2% and had little impact on the NPV (99.1% to 98.5%). CONCLUSIONS: A large proportion of people are identified as high-risk using current thresholds. Increasing the risk threshold markedly reduces the number of people that would be classified as high-risk and entered into prevention programmes, although this must be balanced against cases missed. Raising the entry threshold would allow limited intervention opportunities to be focused on those most likely to develop T2D.

Predicting and elucidating the etiology of fatty liver disease: A machine learning modeling and validation study in the IMI DIRECT cohorts.

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is highly prevalent and causes serious health complications in individuals with and without type 2 diabetes (T2D). Early diagnosis of NAFLD is important, as this can help prevent irreversible damage to the liver and, ultimately, hepatocellular carcinomas. We sought to expand etiological understanding and develop a diagnostic tool for NAFLD using machine learning. METHODS AND FINDINGS: We utilized the baseline data from IMI DIRECT, a multicenter prospective cohort study of 3,029 European-ancestry adults recently diagnosed with T2D (n = 795) or at high risk of developing the disease (n = 2,234). Multi-omics (genetic, transcriptomic, proteomic, and metabolomic) and clinical (liver enzymes and other serological biomarkers, anthropometry, measures of beta-cell function, insulin sensitivity, and lifestyle) data comprised the key input variables. The models were trained on MRI-image-derived liver fat content (<5% or ≥5%) available for 1,514 participants. We applied LASSO (least absolute shrinkage and selection operator) to select features from the different layers of omics data and random forest analysis to develop the models. The prediction models included clinical and omics variables separately or in combination. A model including all omics and clinical variables yielded a cross-validated receiver operating characteristic area under the curve (ROCAUC) of 0.84 (95% CI 0.82, 0.86; p < 0.001), which compared with a ROCAUC of 0.82 (95% CI 0.81, 0.83; p < 0.001) for a model including 9 clinically accessible variables. The IMI DIRECT prediction models outperformed existing noninvasive NAFLD prediction tools. One limitation is that these analyses were performed in adults of European ancestry residing in northern Europe, and it is unknown how well these findings will translate to people of other ancestries and exposed to environmental risk factors that differ from those of the present cohort. Another key limitation of this study is that the prediction was done on a binary outcome of liver fat quantity (<5% or ≥5%) rather than a continuous one. CONCLUSIONS: In this study, we developed several models with different combinations of clinical and omics data and identified biological features that appear to be associated with liver fat accumulation. In general, the clinical variables showed better prediction ability than the complex omics variables. However, the combination of omics and clinical variables yielded the highest accuracy. We have incorporated the developed clinical models into a web interface (see: https://www.predictliverfat.org/) and made it available to the community. TRIAL REGISTRATION: ClinicalTrials.gov NCT03814915.

Terahertz Gas-Phase Spectroscopy Using a Sub-Wavelength Thick Ultrahigh-Q Microresonator.

The terahertz spectrum provides tremendous opportunities for broadband gas-phase spectroscopy, as numerous molecules exhibit strong fundamental resonances in the THz frequency range. However, cutting-edge THz gas-phase spectrometer require cumbersome multi-pass gas cells to reach sufficient sensitivity for trace level gas detection. Here, we report on the first demonstration of a THz gas-phase spectrometer using a sub-wavelength thick ultrahigh-Q THz disc microresonator. Leveraging the microresonator's ultrahigh quality factor in excess of 120,000 as well as the intrinsically large evanescent field, allows for the implementation of a very compact spectrometer without the need for complex multi-pass gas cells. Water vapour concentrations as low as 4 parts per million at atmospheric conditions have been readily detected in proof-of-concept experiments.

Type 1 diabetes defined by severe insulin deficiency occurs after 30 years of age and is commonly treated as type 2 diabetes.

AIMS/HYPOTHESIS: Late-onset type 1 diabetes can be difficult to identify. Measurement of endogenous insulin secretion using C-peptide provides a gold standard classification of diabetes type in longstanding diabetes that closely relates to treatment requirements. We aimed to determine the prevalence and characteristics of type 1 diabetes defined by severe endogenous insulin deficiency after age 30 and assess whether these individuals are identified and managed as having type 1 diabetes in clinical practice. METHODS: We assessed the characteristics of type 1 diabetes defined by rapid insulin requirement (within 3 years of diagnosis) and severe endogenous insulin deficiency (non-fasting C-peptide <200 pmol/l) in 583 participants with insulin-treated diabetes, diagnosed after age 30, from the Diabetes Alliance for Research in England (DARE) population cohort. We compared characteristics with participants with retained endogenous insulin secretion (>600 pmol/l) and 220 participants with severe insulin deficiency who were diagnosed under age 30. RESULTS: Twenty-one per cent of participants with insulin-treated diabetes who were diagnosed after age 30 met the study criteria for type 1 diabetes. Of these participants, 38% did not receive insulin at diagnosis, of whom 47% self-reported type 2 diabetes. Rapid insulin requirement was highly predictive of severe endogenous insulin deficiency: 85% required insulin within 1 year of diagnosis, and 47% of all those initially treated without insulin who progressed to insulin treatment within 3 years of diagnosis had severe endogenous insulin deficiency. Participants with late-onset type 1 diabetes defined by development of severe insulin deficiency had similar clinical characteristics to those with young-onset type 1 diabetes. However, those with later onset type 1 diabetes had a modestly lower type 1 diabetes genetic risk score (0.268 vs 0.279; p < 0.001 [expected type 2 diabetes population median, 0.231]), a higher islet autoantibody prevalence (GAD-, islet antigen 2 [IA2]- or zinc transporter protein 8 [ZnT8]-positive) of 78% at 13 years vs 62% at 26 years of diabetes duration; (p = 0.02), and were less likely to identify as having type 1 diabetes (79% vs 100%; p < 0.001) vs those with young-onset disease. CONCLUSIONS/INTERPRETATION: Type 1 diabetes diagnosed over 30 years of age, defined by severe insulin deficiency, has similar clinical and biological characteristics to that occurring at younger ages, but is frequently not identified. Clinicians should be aware that patients progressing to insulin within 3 years of diagnosis have a high likelihood of type 1 diabetes, regardless of initial diagnosis.

What to do with diabetes therapies when HbA1c lowering is inadequate: add, switch, or continue? A MASTERMIND study.

BACKGROUND: It is unclear what to do when people with type 2 diabetes have had no or a limited glycemic response to a recently introduced medication. Intra-individual HbA1c variability can obscure true response. Some guidelines suggest stopping apparently ineffective therapy, but no studies have addressed this issue. METHODS: In a retrospective cohort analysis using the UK Clinical Practice Research Datalink (CPRD), we assessed the outcome of 55,530 patients with type 2 diabetes starting their second or third non-insulin glucose-lowering medication, with a baseline HbA1c > 58 mmol/mol (7.5%). For those with no HbA1c improvement or a limited response at 6 months (HbA1c fall < 5.5 mmol/mol [0.5%]), we compared HbA1c 12 months later in those who continued their treatment unchanged, switched to new treatment, or added new treatment. RESULTS: An increase or a limited reduction in HbA1c was common, occurring in 21.9% (12,168/55,230), who had a mean HbA1c increase of 2.5 mmol/mol (0.2%). After this limited response, continuing therapy was more frequent (n = 9308; 74%) than switching (n = 1177; 9%) or adding (n = 2163; 17%). Twelve months later, in those who switched medication, HbA1c fell (- 6.8 mmol/mol [- 0.6%], 95%CI - 7.7, - 6.0) only slightly more than those who continued unchanged (- 5.1 mmol/mol [- 0.5%], 95%CI - 5.5, - 4.8). Adding another new therapy was associated with a substantially better reduction (- 12.4 mmol/mol [- 1.1%], 95%CI - 13.1, - 11.7). Propensity score-matched subgroups demonstrated similar results. CONCLUSIONS: Where glucose-lowering therapy does not appear effective on initial HbA1c testing, changing agents does not improve glycemic control. The initial agent should be continued with another therapy added.

Free-space coupling to symmetric high-Q terahertz whispering-gallery mode resonators.

We report on the coupling of a free-space Gaussian beam to symmetric high-quality (Q) whispering-gallery mode resonators (WGMRs) for terahertz (THz) radiation. We achieve very high excitation efficiencies up to 50% to THz WGMs with a Q-factor of 1.5×104 at 0.7 THz. The high coupling efficiencies have been realized by leveraging a Gaussian beam with a nearly diffraction-limited focal spot, as well as readily available low-loss, high-index silicon spheres with diameters comparable to the wavelength. The results convincingly underline the viability of free-space coupling in the THz frequency range.

Anomalous blue-shift of terahertz whispering-gallery modes via dielectric and metallic tuning.

The vast majority of resonant systems show a red-shift for the resonance frequency when a perturbation, e.g., losses, is introduced to the system. In contrast, here we report for the first time, to the best of our knowledge, the experimental demonstration of both red- and anomalous blue-shifting of whispering-gallery modes (WGMs) using dielectric and metallic substrates. The maximum blue-shift is more than three times as large as the expected red-shift, proving that the anomalous blue-shift is more than a peculiar curiosity. The experiments are performed in the terahertz frequency range with coherent continuous-wave spectroscopy. The results establish dielectric and metallic tuning as a novel and viable approach to tune high-quality WGMs and provide valuable insights into the anomalous blue-shift of WGM cavity systems. The tuning capabilities for these compact monolithic resonators are of significant interest for fundamental science and technological applications alike.

Time trends in prescribing of type 2 diabetes drugs, glycaemic response and risk factors: A retrospective analysis of primary care data, 2010-2017.

AIM: To describe population-level time trends in prescribing patterns of type 2 diabetes therapy, and in short-term clinical outcomes (glycated haemoglobin [HbA1c], weight, blood pressure, hypoglycaemia and treatment discontinuation) after initiating new therapy. MATERIALS AND METHODS: We studied 81 532 people with type 2 diabetes initiating a first- to fourth-line drug in primary care between 2010 and 2017 inclusive in United Kingdom electronic health records (Clinical Practice Research Datalink). Trends in new prescriptions and subsequent 6- and 12-month adjusted changes in glycaemic response (reduction in HbA1c), weight, blood pressure and rates of hypoglycaemia and treatment discontinuation were examined. RESULTS: Use of dipeptidyl peptidase-4 inhibitors as second-line therapy near doubled (41% of new prescriptions in 2017 vs. 22% in 2010), replacing sulphonylureas as the most common second-line drug (29% in 2017 vs. 53% in 2010). Sodium-glucose co-transporter-2 inhibitors, introduced in 2013, comprised 17% of new first- to fourth-line prescriptions by 2017. First-line use of metformin remained stable (91% of new prescriptions in 2017 vs. 91% in 2010). Over the study period there was little change in average glycaemic response and in the proportion of people discontinuing treatment. There was a modest reduction in weight after initiating second- and third-line therapy (improvement in weight change 2017 vs. 2010 for second-line therapy: -1.5 kg, 95% confidence interval [CI] -1.9, -1.1; P < 0.001), and a slight reduction in systolic blood pressure after initiating first-, second- and third-line therapy (improvement in systolic blood pressure change 2017 vs. 2010 range: -1.7 to -2.1 mmHg; all P < 0.001). Hypoglycaemia rates decreased over time with second-line therapy (incidence rate ratio 0.94 per year, 95% CI 0.88, 1.00; P = 0.04), mirroring the decline in use of sulphonylureas. CONCLUSIONS: Recent changes in prescribing of therapy for people with type 2 diabetes have not led to a change in glycaemic response and have resulted in modest improvements in other population-level short-term clinical outcomes.

Random non-fasting C-peptide testing can identify patients with insulin-treated type 2 diabetes at high risk of hypoglycaemia.

AIMS/HYPOTHESIS: The aim of this study was to determine whether random non-fasting C-peptide (rCP) measurement can be used to assess hypoglycaemia risk in insulin-treated type 2 diabetes. METHODS: We compared continuous glucose monitoring-assessed SD of blood glucose and hypoglycaemia duration in 17 patients with insulin-treated type 2 diabetes and severe insulin deficiency (rCP < 200 pmol/l) and 17 matched insulin-treated control patients with type 2 diabetes but who had preserved endogenous insulin (rCP > 600 pmol/l). We then assessed the relationship between rCP and questionnaire-based measures of hypoglycaemia in 256 patients with insulin-treated type 2 diabetes and a comparison group of 209 individuals with type 1 diabetes. RESULTS: Continuous glucose monitoring (CGM)-assessed glucose variability and hypoglycaemia was greater in individuals with rCP < 200 pmol/l despite similar mean glucose. In those with low vs high C-peptide, SD of glucose was 4.2 (95% CI 3.7, 4.6) vs 3.0 (2.6, 3.4) mmol/l (p < 0.001). In the low-C-peptide vs high-C-peptide group, the proportion of individuals experiencing sustained hypoglycaemia ≤ 4 mmol/l was 94% vs 41% (p < 0.001), the mean rate of hypoglycaemia was 5.5 (4.4, 6.7) vs 2.1 (1.4, 2.9) episodes per person per week (p = 0.004) and the mean duration was 630 (619, 643) vs 223 (216, 230) min per person per week (p = 0.01). Hypoglycaemia ≤ 3 mmol/l was infrequent in individuals with preserved C-peptide (1.8 [1.2, 2.6] episodes per person per week vs 0.4 [0.1, 0.8] episodes per person per week for low vs high C-peptide, p = 0.04) and only occurred at night. In a population-based cohort with insulin-treated type 2 diabetes, self-reported hypoglycaemia was twice as frequent in those with rCP < 200 pmol/l (OR 2.0, p < 0.001) and the rate of episodes resulting in loss of consciousness or seizure was five times higher (OR 5.0, p = 0.001). The relationship between self-reported hypoglycaemia and C-peptide was similar in individuals with type 1 and type 2 diabetes. CONCLUSIONS/INTERPRETATION: Low rCP is associated with increased glucose variability and hypoglycaemia in patients with insulin-treated type 2 diabetes and represents a practical, stable and inexpensive biomarker for assessment of hypoglycaemia risk.