Disengagement and loss to follow-up in intravitreal injection clinics for neovascular age-related macular degeneration.

BACKGROUND/OBJECTIVES: Timely assessment and treatment of patients with neovascular AMD (nAMD) are crucial to preservation of vision. Loss to follow up (LTFU) in these patients is a problem but this has not been systematically investigated. SUBJECTS/METHODS: A retrospective review of electronic medical records of patients with nAMD first treated with anti-VEGF therapy from 1st Jan 2014 to 31st Dec 2018, was conducted in January 2021. Any patient not seen for more than 12 months was classed as no longer attending. RESULTS: Of the 1328 patients who attended between 2014 and 2018, 348 had failed to attend and were eligible for inclusion in this study. Reasons noted for discontinuation of care: discharged by clinician (33.3%), died (20.7%), moved to another unit outside of area (17.5%), stopped attending due to ill-health (13.5%), discharged due to failure to attend (5.6%) and patient choice to no longer attend (4.6%). There were 16 (4.6%) who did not receive any further appointments despite clinician request for follow-up. After 5 years, 50.5% of patients were no longer attending for treatment. Age was a factor in failure to attend, with 7 out of 12 patients aged >100 years no longer being followed up, compared to 1 out of 11 of 50-59 year-olds. CONCLUSIONS: When analysing visual outcomes in an AMD service it is important to characterise the patients who are lost to follow up. The outcomes for this group may be avoidably poor and understanding the factors influencing LTFU rate is crucial to addressing shortcomings in a hospital AMD service.

Epidemiology of moderately severe and severe non-proliferative diabetic retinopathy in South West England.

AIMS: To estimate the incidence of early treatment diabetic retinopathy study (ETDRS) level 47 and 53 and progression to treatment with panretinal photocoagulation (PRP) for proliferative DR (PDR). METHODS: Log-linear regression was used to estimate the incidence of level 47-53 or worse for 33,009 people with diabetes (PWD) in Gloucestershire during 2013-2016 by calendar year and diabetes type, based on the first recording. Progression was analysed in Gloucestershire and Bristol with a parametric survival analysis examining the association of baseline and time-varying demographic and clinical factors on time to PRP after the first recording of level 47-53. RESULTS: Incidence decreased from 0.57 (95% confidence intervals (CI) 0.48-0.67) per 100 PWD in 2013 to 0.35 (95% CI 0.29-0.43) in 2016 (p < 0.001). For progression, 338 eligible PWD from Gloucestershire and 418 from Bristol were followed for a median of 1.4 years; 78 and 83% had Type 2 diabetes and a median (interquartile range) of 15 (10-22) and 17 (11-25) years duration of diagnosed diabetes respectively. Three years from the incident ETDRS 47-53, 18.9% and 17.2% had received PRP respectively. For Gloucestershire, severe IRMA and updated mean HbA1c were associated with an increase in the risk of initiating PRP (hazard ratio 3.14 (95% CI: 1.60-6.15) and 1.21 (95% CI: 1.06-1.38 per 10 mmol/mol) respectively). CONCLUSION: This study provides additional understanding of this population and shows that a high proportion of patients with ETDRS levels 47-53 need to be monitored as they are at high risk of progressing to PDR.

Testing the performance of risk prediction models to determine progression to referable diabetic retinopathy in an Irish type 2 diabetes cohort.

BACKGROUND /AIMS: To evaluate the performance of existing prediction models to determine risk of progression to referable diabetic retinopathy (RDR) using data from a prospective Irish cohort of people with type 2 diabetes (T2D). METHODS: A cohort of 939 people with T2D followed prospectively was used to test the performance of risk prediction models developed in Gloucester, UK, and Iceland. Observed risk of progression to RDR in the Irish cohort was compared with that derived from each of the prediction models evaluated. Receiver operating characteristic curves assessed models' performance. RESULTS: The cohort was followed for a total of 2929 person years during which 2906 screening episodes occurred. Among 939 individuals followed, there were 40 referrals (4%) for diabetic maculopathy, pre-proliferative DR and proliferative DR. The original Gloucester model, which includes results of two consecutive retinal screenings; a model incorporating, in addition, systemic biomarkers (HbA1c and serum cholesterol); and a model including results of one retinopathy screening, HbA1c, total cholesterol and duration of diabetes, had acceptable discriminatory power (area under the curve (AUC) of 0.69, 0.76 and 0.77, respectively). The Icelandic model, which combined retinopathy grading, duration and type of diabetes, HbA1c and systolic blood pressure, performed very similarly (AUC of 0.74). CONCLUSION: In an Irish cohort of people with T2D, the prediction models tested had an acceptable performance identifying those at risk of progression to RDR. These risk models would be useful in establishing more personalised screening intervals for people with T2D.

Prevalence and incidence of diabetic retinopathy (DR) in the UK population of Gloucestershire.

PURPOSE: To estimate prevalence and incidence of diabetic retinopathy (DR) in a UK region by severity between 2012 and 2016 and risk factors for progression to proliferative DR (PDR). METHODS: Electronic medical records from people with diabetes (PWD) ≥18 years seen at the Gloucestershire Diabetic Eye Screening Programme (GDESP) and the hospital eye clinic were analysed (HEC). Prevalence and incidence of DR per 100 PWD (%) by calendar year, grade and diabetes type were estimated using log-linear regression. Progression to PDR and associated risk factors were estimated using parametric survival analyses. RESULTS: Across the study period, 35 873 PWD had at least one DR assessment. They were aged 66 (56-75) years (median (interquartile range)), 57% male, 5 (1-10) years since diabetes diagnosis, 93% Type 2 diabetes. Prevalence of DR decreased from 38.9% (95% CI: 38.1%, 39.8%) in 2012 to 36.6% (95% CI: 35.9%, 37.3%) in 2016 (p < 0.001). Incidence of any DR decreased from 10.9% (95% CI: 10.4%, 11.5%) in 2013 to 8.5% (95% CI: 8.1%, 9.0%) in 2016 (p < 0.001). Prevalence of PDR decreased from 3.5% (95% CI: 3.3%, 3.8%) in 2012 to 3.1% (95% CI 2.9%, 3.3%) in 2016 (p = 0.008). Incidence of PDR did not change over time. HbA1c and bilateral moderate-severe NPDR were statistically significant risk factors associated with progression to PDR. CONCLUSIONS: Incidence and prevalence of DR decreased between 2012 and 2016 in this well-characterized population of the UK.

Incidence of sight-threatening diabetic retinopathy in an established urban screening programme: An 11-year cohort study.

AIMS: Systematic annual screening to detect sight-threatening diabetic retinopathy (STDR) is established in the United Kingdom. We designed an observational cohort study to provide up-to-date data for policy makers and clinical researchers on incidence of key screening endpoints in people with diabetes attending one screening programme running for over 30 years. METHODS: All people with diabetes aged ≥12 years registered with general practices in the Liverpool health district were offered inclusion. Data sources comprised: primary care (demographics, systemic risk factors), Liverpool Diabetes Eye Screening Programme (retinopathy grading), Hospital Eye Services (slit lamp biomicroscopy assessment of screen positives). RESULTS: 133,366 screening episodes occurred in 28,384 people over 11 years. Overall incidences were: screen positive 6.7% (95% CI 6.5-6.8), screen positive for retinopathy 3.1% (3.0-3.1), unassessable images 2.6% (2.5-2.7), other significant eye diseases 1.0% (1.0-1.1). 1.6% (1.6-1.7) had sight-threatening retinopathy confirmed by slit lamp biomicroscopy. The annual incidence of screen positive and screen positive for retinopathy showed consistent declines from 8.8%-10.6% and 4.4%-4.6% in 2007/09 to 4.4%-6.8% and 2.3%-2.9% in 2013/17, respectively. Rates of STDR (true positive) were consistently below 2% after 2008/09. Screen positive rates were higher in first time attenders (9.9% [9.4-10.2] vs. 6.1% [6.0-6.2]) in part due to ungradeable images (4.1% vs. 2.3%) and other eye disease (2.4% vs. 0.8%). 4.5% (3.9-5.2) of previous non-attenders had sight-threatening retinopathy. Compared with people with type 2 diabetes, those with type 1 disease demonstrated higher rates of screen positive (11.9% vs. 6.0%) and STDR (6.4% vs. 1.2%). Overall prevalence of any retinopathy was 27.2% (27.0-27.4). CONCLUSIONS: In an established screening programme with a stable population screen, positive rates show a consistent fall over time to a low level. Of those who are screen positive, fewer than 50% are screen positive for diabetic retinopathy. Most are due to sight threatening maculopathy. The annual incidence of STDR is under 2% suggesting future work on redefining screen positive and supporting extended intervals for people at low risk. Higher rates of screen positive and STDR are seen in first time attenders. Those who have never attended for screening should be specifically targeted.

Safety and cost-effectiveness of individualised screening for diabetic retinopathy: the ISDR open-label, equivalence RCT.

AIMS/HYPOTHESIS: Using variable diabetic retinopathy screening intervals, informed by personal risk levels, offers improved engagement of people with diabetes and reallocation of resources to high-risk groups, while addressing the increasing prevalence of diabetes. However, safety data on extending screening intervals are minimal. The aim of this study was to evaluate the safety and cost-effectiveness of individualised, variable-interval, risk-based population screening compared with usual care, with wide-ranging input from individuals with diabetes. METHODS: This was a two-arm, parallel-assignment, equivalence RCT (minimum 2 year follow-up) in individuals with diabetes aged 12 years or older registered with a single English screening programme. Participants were randomly allocated 1:1 at baseline to individualised screening at 6, 12 or 24 months for those at high, medium and low risk, respectively, as determined at each screening episode by a risk-calculation engine using local demographic, screening and clinical data, or to annual screening (control group). Screening staff and investigators were observer-masked to allocation and interval. Data were collected within the screening programme. The primary outcome was attendance (safety). A secondary safety outcome was the development of sight-threatening diabetic retinopathy. Cost-effectiveness was evaluated within a 2 year time horizon from National Health Service and societal perspectives. RESULTS: A total of 4534 participants were randomised. After withdrawals, there were 2097 participants in the individualised screening arm and 2224 in the control arm. Attendance rates at first follow-up were equivalent between the two arms (individualised screening 83.6%; control arm 84.7%; difference -1.0 [95% CI -3.2, 1.2]), while sight-threatening diabetic retinopathy detection rates were non-inferior in the individualised screening arm (individualised screening 1.4%, control arm 1.7%; difference -0.3 [95% CI -1.1, 0.5]). Sensitivity analyses confirmed these findings. No important adverse events were observed. Mean differences in complete case quality-adjusted life-years (EuroQol Five-Dimension Questionnaire, Health Utilities Index Mark 3) did not significantly differ from zero; multiple imputation supported the dominance of individualised screening. Incremental cost savings per person with individualised screening were £17.34 (95% CI 17.02, 17.67) from the National Health Service perspective and £23.11 (95% CI 22.73, 23.53) from the societal perspective, representing a 21% reduction in overall programme costs. Overall, 43.2% fewer screening appointments were required in the individualised arm. CONCLUSIONS/INTERPRETATION: Stakeholders involved in diabetes care can be reassured by this study, which is the largest ophthalmic RCT in diabetic retinopathy screening to date, that extended and individualised, variable-interval, risk-based screening is feasible and can be safely and cost-effectively introduced in established systematic programmes. Because of the 2 year time horizon of the trial and the long time frame of the disease, robust monitoring of attendance and retinopathy rates should be included in any future implementation. TRIAL REGISTRATION: ISRCTN 87561257 FUNDING: The study was funded by the UK National Institute for Health Research. Graphical abstract.

Prospective evaluation of an artificial intelligence-enabled algorithm for automated diabetic retinopathy screening of 30 000 patients.

BACKGROUND/AIMS: Human grading of digital images from diabetic retinopathy (DR) screening programmes represents a significant challenge, due to the increasing prevalence of diabetes. We evaluate the performance of an automated artificial intelligence (AI) algorithm to triage retinal images from the English Diabetic Eye Screening Programme (DESP) into test-positive/technical failure versus test-negative, using human grading following a standard national protocol as the reference standard. METHODS: Retinal images from 30 405 consecutive screening episodes from three English DESPs were manually graded following a standard national protocol and by an automated process with machine learning enabled software, EyeArt v2.1. Screening performance (sensitivity, specificity) and diagnostic accuracy (95% CIs) were determined using human grades as the reference standard. RESULTS: Sensitivity (95% CIs) of EyeArt was 95.7% (94.8% to 96.5%) for referable retinopathy (human graded ungradable, referable maculopathy, moderate-to-severe non-proliferative or proliferative). This comprises sensitivities of 98.3% (97.3% to 98.9%) for mild-to-moderate non-proliferative retinopathy with referable maculopathy, 100% (98.7%,100%) for moderate-to-severe non-proliferative retinopathy and 100% (97.9%,100%) for proliferative disease. EyeArt agreed with the human grade of no retinopathy (specificity) in 68% (67% to 69%), with a specificity of 54.0% (53.4% to 54.5%) when combined with non-referable retinopathy. CONCLUSION: The algorithm demonstrated safe levels of sensitivity for high-risk retinopathy in a real-world screening service, with specificity that could halve the workload for human graders. AI machine learning and deep learning algorithms such as this can provide clinically equivalent, rapid detection of retinopathy, particularly in settings where a trained workforce is unavailable or where large-scale and rapid results are needed.

Macula service evaluation and assessing priorities for anti-VEGF treatment in the light of COVID-19.

PURPOSE: To assess the treatment position of all patients who have had an anti-VEGF injection in 2020, prior to the UK lockdown on 23 March. To assess methods of service quality evaluation in setting benchmarks for comparison after the situation stabilized. To consider what proportion could be delayed based on national guidelines and varying vision parameters. Finally, to measure how many patients actually attended. METHOD: A retrospective analysis of data collected from our electronic medical record was performed. Age, sex, reason for injection, visual acuity (VA) for both treated and untreated eyes and number of injections were recorded. The proportion of patients and eyes with ≥ 70 letters were calculated as an assessment of quality of service provision. The proportion of patients that could be delayed was estimated based on published guidelines and varying the parameters of difference between treated and untreated eyes. Finally, the number of patients who actually attended was recorded. RESULTS: About 3364 eyes (2229 neovascular age-related macular degeneration (nAMD), 427 diabetic macular oedema (DMO), 599 retinal vein occlusion (RVO) and 109 other) from 2924 patients were analysed. At the last appointment with injection, 64.4% of patients achieved ≥ 70 letters in their better-seeing eye. Mean VA of the treated eye was 61.5 letters, and 36.9% achieved ≥ 70. The mean number of injections was 16, 90% with aflibercept. Of the patients receiving treatment to one eye, 57.6% was receiving treatment to their worse seeing eye. In 18.2% this eye was > 20 letters worse and in 5.07% > 40 letters worse than the untreated eye. Using Royal College of Ophthalmologists (RCOphth) guidelines, (treat nAMD 8 weekly, delay majority of RVO and DMO) 24.8% would be delayed. From 2738 appointments during the first 4 weeks of lockdown (booked prior to lockdown), doctors rescheduled 1025 and patients did not attend 820, leaving 893 who were seen (33%). CONCLUSIONS: Assessing the treatment position of patients prior to COVID-19 lockdown enables objective stratification for prioritization for continued treatment. If RCOphth guidelines were followed 24.8% could be delayed and if treating the worse seeing eye up to 57.6%. Many scheduled patients elected not to attend, with 67% not seen in the first 4 weeks. The impact of non-attendance and delays may be evaluated later.

Prevalence of admission plasma glucose in 'diabetes' or 'at risk' ranges in hospital emergencies with no prior diagnosis of diabetes by gender, age and ethnicity.

AIMS: To establish the prevalence of admission plasma glucose in 'diabetes' and 'at risk' ranges in emergency hospital admissions with no prior diagnosis of diabetes; characteristics of people with hyperglycaemia; and factors influencing glucose measurement. METHODS: Electronic patient records for 113 097 hospital admissions over 1 year from 2014 to 2015 included 43 201 emergencies with glucose available for 31 927 (74%) admissions, comprising 22 045 people. Data are presented for 18 965 people with no prior diagnosis of diabetes and glucose available on first attendance. RESULTS: Three quarters (14 214) were White Europeans aged 62 (43-78) years, median (IQ range); 12% (2241) South Asians 46 (32-64) years; 9% (1726) Unknown/Other ethnicities 43 (29-61) years; and 4% (784) Afro-Caribbeans 49 (33-63) years, P < .001. Overall, 5% (1003) had glucose in the 'diabetes' range (≥11.1 mmol/L) higher at 8% (175) for South Asians; 16% (3042) were 'at risk' (7.8-11.0 mmol/L), that is 17% (2379) White Europeans, 15% (338) South Asians, 14% (236) Unknown/Others and 11% (89) Afro-Caribbeans, P < .001. The prevalence for South Asians aged <30 years was 2.1% and 5.2%, respectively, 2.6% and 8.6% for Afro-Caribbeans <30 years, and 2.0% and 8.4% for White Europeans <40 years. Glucose increased with age and was more often in the 'diabetes' range for South Asians than White Europeans with South Asian men particularly affected. One third of all emergency admissions were for <24 hours with 58% of these having glucose measured compared to 82% with duration >24 hours. CONCLUSIONS: Hyperglycaemia was evident in 21% of adults admitted as an emergency; various aspects related to follow-up and initial testing, age and ethnicity need to be considered by professional bodies addressing undiagnosed diabetes in hospital admissions.

Individualised screening for diabetic retinopathy: the ISDR study-rationale, design and methodology for a randomised controlled trial comparing annual and individualised risk-based variable-interval screening.

INTRODUCTION: Currently, all people with diabetes (PWD) aged 12 years and over in the UK are invited for screening for diabetic retinopathy (DR) annually. Resources are not increasing despite a 5% increase in the numbers of PWD nationwide each year. We describe the rationale, design and methodology for a randomised controlled trial (RCT) evaluating the safety, acceptability and cost-effectiveness of personalised variable-interval risk-based screening for DR. This is the first randomised trial of personalised screening for DR and the largest ophthalmic RCT in the UK. METHODS AND ANALYSIS: PWD attending seven screening clinics in the Liverpool Diabetic Eye Screening Programme were recruited into a single site RCT with a 1:1 allocation to individualised risk-based variable-interval or annual screening intervals. A risk calculation engine developed for the trial estimates the probability that an individual will develop referable disease (screen positive DR) within the next 6, 12 or 24 months using demographic, retinopathy and systemic risk factor data from primary care and screening programme records. Dynamic, secure, real-time data connections have been developed. The primary outcome is attendance for follow-up screening. We will test for equivalence in attendance rates between the two arms. Secondary outcomes are rates and severity of DR, visual outcomes, cost-effectiveness and health-related quality of life. The required sample size was 4460 PWD. Recruitment is complete, and the trial is in follow-up. ETHICS AND DISSEMINATION: Ethical approval was obtained from National Research Ethics Service Committee North West - Preston, reference 14/NW/0034. Results will be presented at international meetings and published in peer-reviewed journals. This pragmatic RCT will inform screening policy in the UK and elsewhere. TRIAL REGISTRATION NUMBER: ISRCTN87561257; Pre-results.

Personalized risk-based screening for diabetic retinopathy: A multivariate approach versus the use of stratification rules.

AIMS: To evaluate our proposed multivariate approach to identify patients who will develop sight-threatening diabetic retinopathy (STDR) within a 1-year screen interval, and explore the impact of simple stratification rules on prediction. MATERIALS AND METHODS: A 7-year dataset (2009-2016) from people with diabetes (PWD) was analysed using a novel multivariate longitudinal discriminant approach. Level of diabetic retinopathy, assessed from routine digital screening photographs of both eyes, was jointly modelled using clinical data collected over time. Simple stratification rules based on retinopathy level were also applied and compared with the multivariate discriminant approach. RESULTS: Data from 13 103 PWD (49 520 screening episodes) were analysed. The multivariate approach accurately predicted whether patients developed STDR or not within 1 year from the time of prediction in 84.0% of patients (95% confidence interval [CI] 80.4-89.7), compared with 56.7% (95% CI 55.5-58.0) and 79.7% (95% CI 78.8-80.6) achieved by the two stratification rules. While the stratification rules detected up to 95.2% (95% CI 92.2-97.6) of the STDR cases (sensitivity) only 55.6% (95% CI 54.5-56.7) of patients who did not develop STDR were correctly identified (specificity), compared with 85.4% (95% CI 80.4-89.7%) and 84.0% (95% CI 80.7-87.6%), respectively, achieved by the multivariate risk model. CONCLUSIONS: Accurate prediction of progression to STDR in PWD can be achieved using a multivariate risk model whilst also maintaining desirable specificity. While simple stratification rules can achieve good levels of sensitivity, the present study indicates that their lower specificity (high false-positive rate) would therefore necessitate a greater frequency of eye examinations.

Cost-effectiveness of digital surveillance clinics with optical coherence tomography versus hospital eye service follow-up for patients with screen-positive maculopathy.

BACKGROUND: Annually 2.7 million individuals are offered screening for diabetic retinopathy (DR) in England. Spectral-Domain Optical Coherence Tomography (SD-OCT) has the potential to relieve pressure on NHS services by correctly identifying patients who are screen positive for maculopathy on two-dimensional photography without evidence of clinically significant macular oedema (CSMO), limiting the number of referrals to hospitals. We aim to assess whether the addition of SDOCT imaging in digital surveillance clinics is a cost-effective intervention relative to hospital eye service (HES) follow-up. METHODS: We used patient-level data from the Gloucestershire Diabetic Eye Screening Service linked to the local digital surveillance programme and HES between 2012 and 2015. A model was used to simulate the progression of individuals with background diabetic retinopathy (R1) and diabetic maculopathy (M1) following DR screening across the clinic pathways over 12 months. RESULTS: Between January 2012 and December 2014, 696 people undergoing DR screening were found to have screen-positive maculopathy in at least one eye for the first time, with a total of 766 eyes identified as having R1M1. The mean annual cost of assessing and surveillance through the SD-OCT clinic pathway was £101 (95% CI: 91-139) as compared with £177 (95%CI: 164-219) under the HES pathway. Surveillance under an SD-OCT clinic generated cost savings of £76 (95% CI: 70-81) per patient. CONCLUSIONS: Our analysis shows that SD-OCT surveillance of patients diagnosed as R1M1 at DR screening is not only cost-effective but generates considerable cost savings.

Individualised variable-interval risk-based screening for sight-threatening diabetic retinopathy: the Liverpool Risk Calculation Engine.

AIMS/HYPOTHESIS: Individualised variable-interval risk-based screening offers better targeting and improved cost-effectiveness in screening for diabetic retinopathy. We developed a generalisable risk calculation engine (RCE) to assign personalised intervals linked to local population characteristics, and explored differences in assignment compared with current practice. METHODS: Data from 5 years of photographic screening and primary care for people with diabetes, screen negative at the first of > 1 episode, were combined in a purpose-built near-real-time warehouse. Covariates were selected from a dataset created using mixed qualitative/quantitative methods. Markov modelling predicted progression to screen-positive (referable diabetic retinopathy) against the local cohort history. Retinopathy grade informed baseline risk and multiple imputation dealt with missing data. Acceptable intervals (6, 12, 24 months) and risk threshold (2.5%) were established with patients and professional end users. RESULTS: Data were from 11,806 people with diabetes (46,525 episodes, 388 screen-positive). Covariates with sufficient predictive value were: duration of known disease, HbA1c, age, systolic BP and total cholesterol. Corrected AUC (95% CIs) were: 6 months 0.88 (0.83, 0.93), 12 months 0.90 (0.87, 0.93) and 24 months 0.91 (0.87, 0.94). Sensitivities/specificities for a 2.5% risk were: 6 months 0.61, 0.93, 12 months 0.67, 0.90 and 24 months 0.82, 0.81. Implementing individualised RCE-based intervals would reduce the proportion of people becoming screen-positive before the allocated screening date by > 50% and the number of episodes by 30%. CONCLUSIONS/INTERPRETATION: The Liverpool RCE shows sufficient performance for a local introduction into practice before wider implementation, subject to external validation. This approach offers potential enhancements of screening in improved local applicability, targeting and cost-effectiveness.

Can HbA1c detect undiagnosed diabetes in acute medical hospital admissions?

OBJECTIVE: To study hyperglycaemia in acute medical admissions to Irish regional hospital. RESEARCH DESIGN AND METHODS: From 2005 to 2007, 2061 white Caucasians, aged >18 years, were admitted by 1/7 physicians. Those with diabetes symptoms/complications but no previous record of hyperglycaemia (n=390), underwent OGTT with concurrent HbA1c in representative subgroup (n=148). Comparable data were obtained for 108 primary care patients at risk of diabetes. RESULTS: Diabetes was diagnosed immediately by routine practice in 1% (22/2061) [aged 36 (26-61) years (median IQ range)/55% (12/22) male] with pre-existing diabetes/dysglycaemia present in 19% (390/2061) [69 (58-80) years/60% (235/390) male]. Possible diabetes symptoms/complications were identified in 19% [70 (59-79) years/57% (223/390) male] with their HbA1c similar to primary care patients [54 (46-61) years], 5.7 (5.3-6.0)%/39 (34-42)mmol/mol (n=148) vs 5.7 (5.4-6.1)%/39 (36-43)mmol/mol, p=0.35, but lower than those diagnosed on admission, 10.2 (7.4-13.3)%/88 (57-122)mmol/mol, p<0.001. Their fasting plasma glucose (FPG) was similar to primary care patients, 5.2 (4.8-5.7) vs 5.2 (4.8-5.9) mmol/L, p=0.65, but 2hPG higher, 9.0 (7.3-11.4) vs 5.5 (4.4-7.5), p<0.001. HbA1c identified diabetes in 10% (15/148) with 14 confirmed on OGTT but overall 32% (48/148) were in diabetic range on OGTT. The specificity of HbA1c in 2061 admissions was similar to primary care, 99% vs 96%, p=0.20, but sensitivity lower, 38% vs 93%, p<0.001 (63% on FPG/23% on 2hPG, p=0.037, in those with possible symptoms/complications). CONCLUSION: HbA1c can play a diagnostic role in acute medicine as it diagnosed another 2% of admissions with diabetes but the discrepancy in sensitivity shows that it does not reflect transient/acute hyperglycaemia resulting from the acute medical event.

Menopausal Status and Abdominal Obesity Are Significant Determinants of Hepatic Lipid Metabolism in Women.

BACKGROUND: Android fat distribution (abdominal obesity) is associated with insulin resistance, hepatic steatosis, and greater secretion of large very low-density lipoprotein (VLDL) particles in men. Since abdominal obesity is becoming increasingly prevalent in women, we aimed to investigate the relationship between android fat and hepatic lipid metabolism in pre- and postmenopausal women. METHODS AND RESULTS: We used a combination of stable isotope tracer techniques to investigate intrahepatic fatty acid synthesis and partitioning in 29 lean and 29 abdominally obese women (android fat/total fat 0.065 [0.02 to 0.08] and 0.095 [0.08 to 0.11], respectively). Thirty women were premenopausal aged 35 to 45 and they were matched for abdominal obesity with 28 postmenopausal women aged 55 to 65. As anticipated, abdominal obese women were more insulin resistant with enhanced hepatic secretion of large (404±30 versus 268±26 mg/kg lean mass, P<0.001) but not small VLDL (160±11 versus 142±13). However, postmenopausal status had a pronounced effect on the characteristics of small VLDL particles, which were considerably triglyceride-enriched (production ratio of VLDL2- triglyceride:apolipoprotein B 30±5.3 versus 19±1.6, P<0.05). In contrast to postmenopausal women, there was a tight control of hepatic fatty acid metabolism and triglyceride production in premenopausal women, whereby oxidation (rs=-0.49, P=0.006), de novo lipogenesis (rs=0.55, P=0.003), and desaturation (rs=0.48, P=0.012) were closely correlated with abdominal obesity-driven large VLDL-triglyceride secretion rate. CONCLUSIONS: In women, abdominal obesity is a major driver of hepatic large VLDL particle secretion, whereas postmenopausal status was characterized by increased small VLDL particle size. These data provide a mechanistic basis for the hyperlipidemia observed in postmenopausal obesity.

Development of a cost-effectiveness model for optimisation of the screening interval in diabetic retinopathy screening.

BACKGROUND: The English NHS Diabetic Eye Screening Programme was established in 2003. Eligible people are invited annually for digital retinal photography screening. Those found to have potentially sight-threatening diabetic retinopathy (STDR) are referred to surveillance clinics or to Hospital Eye Services. OBJECTIVES: To determine whether personalised screening intervals are cost-effective. DESIGN: Risk factors were identified in Gloucestershire, UK using survival modelling. A probabilistic decision hidden (unobserved) Markov model with a misgrading matrix was developed. This informed estimation of lifetime costs and quality-adjusted life-years (QALYs) in patients without STDR. Two personalised risk stratification models were employed: two screening episodes (SEs) (low, medium or high risk) or one SE with clinical information (low, medium-low, medium-high or high risk). The risk factor models were validated in other populations. SETTING: Gloucestershire, Nottinghamshire, South London and East Anglia (all UK). PARTICIPANTS: People with diabetes in Gloucestershire with risk stratification model validation using data from Nottinghamshire, South London and East Anglia. MAIN OUTCOME MEASURES: Personalised risk-based algorithm for screening interval; cost-effectiveness of different screening intervals. RESULTS: Data were obtained in Gloucestershire from 12,790 people with diabetes with known risk factors to derive the risk estimation models, from 15,877 people to inform the uptake of screening and from 17,043 people to inform the health-care resource-usage costs. Two stratification models were developed: one using only results from previous screening events and one using previous screening and some commonly available GP data. Both models were capable of differentiating groups at low and high risk of development of STDR. The rate of progression to STDR was 5 per 1000 person-years (PYs) in the lowest decile of risk and 75 per 1000 PYs in the highest decile. In the absence of personalised risk stratification, the most cost-effective screening interval was to screen all patients every 3 years, with a 46% probability of this being cost-effective at a £30,000 per QALY threshold. Using either risk stratification models, screening patients at low risk every 5 years was the most cost-effective option, with a probability of 99-100% at a £30,000 per QALY threshold. For the medium-risk groups screening every 3 years had a probability of 43-48% while screening high-risk groups every 2 years was cost-effective with a probability of 55-59%. CONCLUSIONS: The study found that annual screening of all patients for STDR was not cost-effective. Screening this entire cohort every 3 years was most likely to be cost-effective. When personalised intervals are applied, screening those in our low-risk groups every 5 years was found to be cost-effective. Screening high-risk groups every 2 years further improved the cost-effectiveness of the programme. There was considerable uncertainty in the estimated incremental costs and in the incremental QALYs, particularly with regard to implications of an increasing proportion of maculopathy cases receiving intravitreal injection rather than laser treatment. Future work should focus on improving the understanding of risk, validating in further populations and investigating quality issues in imaging and assessment including the potential for automated image grading. STUDY REGISTRATION: Integrated Research Application System project number 118959. FUNDING DETAILS: The National Institute for Health Research Health Technology Assessment programme.