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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.

Background: The American Diabetes Association task force on standardization of insulin assays in 1996 showed wide variation in assay bias. Newer assays are specific for insulin, with several now available on automated immunoassay analyzers. Methods: In 2004, we compared 11 commercially available insulin assays by analyzing 150 serum samples (99 fasting/51 postprandial) from study participants with various degrees of glucose intolerance (exclusions being type 1 diabetes, insulin treatment, or presence of insulin antibodies). All assays were calibrated against International Reference Preparation 66/304. One assay was not specific for insulin and another was an RIA; 10 assays used enzyme/chemiluminescent labels. Bland–Altman difference plots were modified to use the mean insulin from all assays on the x-axis as a common comparator. Results: As in the 1996 study, insulin values from the different assays varied by a factor of 2, with the nonspecific assay ranking in the middle of the distribution. Spearman rank correlation coefficients, for ranking samples vs the mean, were 0.983–0.997. Both offsets and concentration-dependent differences were seen in the modified difference plots. Imprecision (mean CV) for automated assays (3%) was not significantly different from manual assays (5%). Similar values were obtained when one automated assay was run in laboratories in both the UK and the US. Results of 1 assay showed lower insulin concentrations in heparinized plasma than in serum. Conclusions: Assay performance must be considered before comparing insulin results. The 2-fold variation in insulin results may be related to specificity, manufacturers’ calibration procedures or conversion factors.

Background/aimsHuman 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.MethodsRetinal 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.ResultsSensitivity (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.ConclusionThe 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.

UKPDS 59: Hyperglycemia and Other Potentially Modifiable Risk Factors for Peripheral Vascular Disease in Type 2 Diabetes Amanda I. Adler , MD, PHD 1 , Richard J. Stevens , PHD 1 , Andrew Neil , FRCP 2 , Irene M. Stratton , MSC 1 , Andrew J. M. Boulton , FRCP 3 , Rury R. Holman , FRCP 1 and for the U.K. Prospective Diabetes Study Group 1 Diabetes Trials Unit, Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, U.K. 2 Division of Public Health and Primary Health Care, Institute of Health Sciences, University of Oxford, Oxford, U.K. 3 Department of Medicine, University of Manchester, Manchester, U.K. Abstract OBJECTIVE —To determine the role of hyperglycemia in prospective analyses of peripheral vascular disease (PVD) in type 2 diabetes, taking into account other potential risk factors. RESEARCH DESIGN AND METHODS —Potential risk factors for the development of PVD were examined in 3,834 of 5,102 individuals enrolled in the U.K. Prospective Diabetes Study (UKPDS) without PVD at diagnosis of diabetes, followed for 6 years, and for whom relevant data were available. PVD was defined as two of the following: ankle-arm blood pressure index <0.8, absence of both dorsalis pedis and posterior tibial pulses to palpation in one or both legs, and intermittent claudication. Logistic regression was used to estimate the association between potential risk factors measured 3–4 months after diagnosis of diabetes and incident PVD. The prevalence of PVD at 3-year intervals to 18 years was determined. RESULTS —Hyperglycemia, assessed as HbA 1c , was associated with an increased risk for incident PVD, independent of other risk factors including age, increased systolic blood pressure, reduced HDL cholesterol, smoking, prior cardiovascular disease, peripheral sensory neuropathy, and retinopathy. Each 1% increase in HbA 1c was associated with a 28% increased risk of PVD (95% CI 12–46), and each 10-mmHg increase in systolic blood pressure with a 25% increase in risk (95% CI 10–43). CONCLUSIONS —Hyperglycemia, as well as smoking, dyslipidemia, and blood pressure are potentially modifiable risk factors for the development of PVD. AAI, ankle-arm index DBP, diastolic blood pressure DP, dorsalis pedis ESR, erythrocyte sedimentation rate PT, posterior tibial PVD, peripheral vascular disease SBP, systolic blood pressure UKPDS, U.K. Prospective Diabetes Study Footnotes Address correspondence and reprint requests to Dr. A. I. Adler, Diabetes Trials Unit, Radcliffe Infirmary, Woodstock Road, Oxford OX2 6HE, U.K. E-mail: amanda.adler{at}dtu.ox.ac.uk . Received for publication 28 August 2001 and accepted in revised form 10 February 2002. A table elsewhere in this issue shows conventional and Système International (SI) units and conversion factors for many substances.

Risk Factors for Myocardial Infarction Case Fatality and Stroke Case Fatality in Type 2 Diabetes UKPDS 66 Richard J. Stevens , PHD , Ruth L. Coleman , BSC , Amanda I. Adler , FRCP , Irene M. Stratton , MSC , David R. Matthews , FRCP and Rury R. Holman , FRCP From The Diabetes Trials Unit and the Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, U.K. Address correspondence and reprint requests to Dr. Richard Stevens, Diabetes Trials Unit, Oxford Centre for Diabetes, Endocrinology and Metabolism, Churchill Hospital, Old Road, Oxford OX3 7LJ, U.K. E-mail: risk.engine{at}dtu.ox.ac.uk Abstract OBJECTIVE —Patients with diabetes have a higher case fatality rate in myocardial infarction (MI) or stroke than those without diabetes: that is, MI and stroke are more often fatal if diabetes is present. We investigated whether the risk of MI or stroke being fatal in type 2 diabetes can be estimated using information available around the time diabetes is diagnosed. RESEARCH DESIGN AND METHODS —Analyses were based on 674 cases of MI (351 fatal) that occurred in 597 of 5,102 U.K. Prospective Diabetes Study (UKPDS) patients for whom covariate data were available during a median follow-up of 7 years. Multivariate logistic regression was used to examine differences in risk factors, measured within 2 years of diagnosis of diabetes, between fatal and nonfatal MI. Similar analyses were performed for 234 strokes (48 fatal) that occurred in 199 patients. RESULTS —Patients with fatal MI had higher HbA 1c than those with nonfatal MI (odds ratio 1.17 per 1% HbA 1c , P = 0.014). Patients with fatal stroke had higher HbA 1c than those with nonfatal stroke (odds ratio 1.37 per 1% HbA 1c , P = 0.007). Other risk factors for MI case fatality included increased age, blood pressure, and urine albumin level. CONCLUSIONS —The risk of MI or stroke being fatal in type 2 diabetes is associated with risk factors, including HbA 1c , measured many years before onset of MI or stroke. Equations have been added to the UKPDS Risk Engine to estimate likely case fatality rates in MI and stroke. CHD, coronary heart disease MI, myocardial infarction sBP, systolic blood pressure UKPDS, U.K. Prospective Diabetes Study Footnotes A table elsewhere in this issue shows conventional and Système International (SI) units and conversion factors for many substances. Accepted September 20, 2003. Received March 27, 2003. DIABETES CARE

Background /AimsTo 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).MethodsA 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.ResultsThe 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).ConclusionIn 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.

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. Glucose needs to be measured in all adults admitted as an emergency not just those over 40/30 years old, as younger people particularly South Asians and Afro‐Caribbeans are at risk of being admitted with undiagnosed diabetes. Overall, 5% of emergency admissions had glucose in the ‘diabetes’ range, 8% if South Asian and Afro‐Caribbean, with 16% of people in the ‘at risk’ range. One third of all emergency admissions were for <24 hours with 58% of these having glucose measured compared to 82% with duration >24 hours.

Aims/hypothesisUsing 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.MethodsThis 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.ResultsA 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/interpretationStakeholders 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 registrationISRCTN 87561257FundingThe study was funded by the UK National Institute for Health Research.

BackgroundAnnually 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.MethodsWe 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.ResultsBetween 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.ConclusionsOur analysis shows that SD-OCT surveillance of patients diagnosed as R1M1 at DR screening is not only cost-effective but generates considerable cost savings.