Counting the lifetime cost of obesity: Analysis based on national England data.

AIM: Obesity has a significant impact on all-cause mortality rate and overall health care resource use (HCRU). These outcomes are also strongly linked to age, sex and local deprivation of the population. We aimed to establish the lifetime costs of obesity by demographic group/geographic area using published mortality rates and HCRU use for integrated care boards (ICB) in England in the context of costs of therapeutic intervention. METHODS: Population and expected mortality rates by age, sex and deprivation were obtained from national data. Obesity class prevalence was taken from the health of the nation study. The published impact of obesity by age, group, sex and deprivation on mortality and HCRU were applied to estimate life years lost and lifetime HCRU [by sex, age band and body mass index (BMI) class for each ICB]. The year 2019 was chosen as the study basis data to avoid influences of COVID-19 pandemic on obesity rates with application of 2022/23 HCRU values. Outcomes including prevalence, deaths, life years lost, HCRU and lifetime HCRU were compared by age and sex groups across four BMI classes normal/underweight (BMI <25 kg/m2 ), overweight (25-29.9 kg/m2 ), obese class I and II (30-39.9 kg/m2 ), and obese class III (≥40), with benchmarking being set against all population being BMI <25 kg/m2 overall and by each of the 42 ICBs. We also associated future life with deaths to provide an estimate of 'future life years lost' occurring each year. RESULTS: Total population aged >16 years was 45.4 million (51% female). PREVALENCE: 13.7 million (28% of the total adult population) had a BMI ≥30 mg/m2 and BMI ≥40 kg/m2 were 1.50 million (12%) of these 1.0 million (68%) were female and of these 0.6 million 40% were women aged 16-49 years. In addition, 35% of those with a BMI ≥40 kg/m2 were in the top deprivation quintile (i.e. overall 20%). Mortality was based on expected deaths of 518K/year, and modelling suggested that if a BMI <25 kg/m2 was achieved in all individuals, the death rate would fall by 63K to 455K/year for the English population (12% reduction). For those with a BMI ≥40 kg/m2 the predicted reduction was 12K deaths (54% lower); while in those aged 16-49 years with a BMI ≥40 kg/m2 72% of deaths were linked to obesity. For future life years lost, we estimated 2.5 years were lost in people with BMI 30-39.9 kg/m2 6.7 years when BMI ≥40 kg/m2 . However, for those aged 16-49 years with a BMI ≥40 kg/m2 , 8.3 years were lost. HCRU, for weight reduction, the annual HCRU decrease from BMI ≥40 kg/m2 to BMI 30-39.9 kg/m2 was £342 per person and from BMI 30-39.9 to 25-29.9 kg/m2 the reduction was £316/person. However, lifetime costs were similar because of reduced life expectancy for obese individuals. In quality adjusted life years (QALY), overall, 791 689 future life years were lost (13.1% of all) in people with BMI ≥25 kg/m2 and were related to excess weight. When the NICE £30 000 per QALY value was applied to the estimated total 791 689 future life years lost then the potential QALY value reduction lost was equivalent to £24 billion/year or £522/person in the obese population. For morbidly obese men and women the potential QALY value lost was £2864/person/year. Regarding geography, across the 42 ICBs, we observed significant variation in the prevalence of BMI ≥40 (1.8%-4.3%), excess mortality (11.6%-15.4%) and HCRU linked to higher BMI (7.2%-8.8%). The areas with the greatest impact on HCRU were in the north-west, north-east and Midlands of England, while the south shows less impact. CONCLUSION: The expected increases in annual HCRU because of obesity, when considered over a lifetime, are being mitigated by the increased mortality of obese individuals. Our data suggest that simple short-term HCRU reduction brought about through BMI reduction will be insufficient to fund additional specialist weight reduction interventions. The HRCUs associated with BMI are not in most cases related to short-term health conditions. They are a cumulative result over a number of years, so for age 16-49 years reducing BMI from ≥40 to 30-39.9 kg/m2 might show an annual decrease in HCRU/person by £325/year for women and £80/year for men but this might not have immediately occurred within that year. For those aged >70 years reducing BMI from ≥40 to 30-39.9 kg/m2 might show an annual decrease in HCRU/person by £777/year for women and £796/year for men but also may not be manifest within that year. However, for the morbidly obese men and women, the potential QALY value lost was £2864 per person per year with the potential for these funds to be applied to intensive weight management programmes, including pharmacotherapy.

Failure to control conventional cardiovascular risk factors in women with type 2 diabetes might explain worse mortality.

INTRODUCTION: The standardised mortality rate (SMR) for people with diabetes in England is 1.5-1.7, with differences in outcomes between sexes. There has been little work examining the factors that could have an impact on this or on what may determine sex differences in outcome. METHODS: Data were extracted for patients with type 2 diabetes (T2D) in Salford (England) in 2010 for the years up to 2020, including any deaths recorded. Expected deaths were calculated from annual Office of National Statistics mortality rate and life expectancy by age and gender, adjusted for the local Index of Multiple Deprivation (IMD). This provided the SMR deprivation (SMRd), and life expectancy years lost per death (LEYLD). The effects of treatment type, and clinical features on SMRd relative to sex were examined by univariable and multivariable analysis. RESULTS: Data from n = 11,806 (F = 5184; M = 6622) patients were included. Of these, n = 5540 were newly diagnosed and n = 3921 died (F = 1841; M = 2080). In total, n = 78,930 patient years. The expected deaths numbered n = 2596 (adjusted for age, sex, and IMD). Excess deaths were n = 1325 (F = 689; M = 636). Life expectancy years lost (LEYL) 18,989 (F = 9714; M = 9275). SMRd 1.51 (F = 1.60; M = 1.44) and LEYLD 4.84 years (F = 5.28; M = 4.46). The impact of risk factors was not different by sex. However, women had higher prevalence of % diagnosed >65 years of age; % last eGFR <60 mLs/min/1.73 m2 , and lower prevalence of % prescribed ACE-inhibitor/ARB, DPP4-inhibitor and SGLT2-inhibitor. Applying the male prevalence rate to the female population and expected mortality suggested n = 437 (55%) of excess T2D female deaths were attributed to sex difference in the prevalence of these risk and protective factors. CONCLUSIONS: Outcomes in women with T2DM are worse than in men, contributed to by greater prevalence of adverse factors and less prescribing of cardioprotective medication.

Evaluation of thyroid function monitoring in people treated with lithium: Advice based on real-world data.

INTRODUCTION: Blood test monitoring is essential for the management of lithium treatment and National Institute for Health and Care Excellence guidance recommends 6-monthly serum testing of thyroid function. We examined conformity to these guidelines and the impact of monitoring outside these intervals. METHODS: We extracted serum lithium and thyroid hormone results at one centre between January 2009 and December 2020. We identified 266 patients who started lithium during this period with no history of thyroid abnormality within the previous 2 years and were at risk of developing thyroid abnormalities. We examined the interval between tests, time between onset of lithium testing and first thyroid-stimulating hormone (TSH) outside the laboratory reference range and assessed impact of testing outside recommended 6-monthly intervals. RESULTS: The most common testing frequency was 3 months (±1 month), accounting for 17.3% of test intervals. Kaplan-Meier analysis showed that most thyroid dysfunction manifests within 3 years (proportion with abnormal TSH at 3 years = 91.4%, 19.9% of total patients). In the first 3 months after commencing lithium therapy, eight patients developed subclinical hypothyroidism and had clinical follow-up data available. Of these, half spontaneously normalized without clinical intervention. In the remaining patients, thyroxine replacement was only initiated after multiple occasions of subclinical hypothyroidism (median = 2 years after initiating lithium, range: 6 months to 3 years). CONCLUSION: The peak interval at 3 months suggests that thyroid function is frequently checked at the same time as serum lithium, indicating too frequent testing. Our data support the recommended 6-monthly testing interval and highlight poor adherence to it.

Serum lithium test requesting across three UK regions: an evaluation of adherence to monitoring guidelines.

BACKGROUND: Bipolar disorder is the fourth most common mental health condition, affecting ~ 1% of UK adults. Lithium is an effective treatment for prevention of relapse and hospital admission, and is widely recommended as a first-line treatment. We previously showed in other areas that laboratory testing patterns are variable with sub-optimal conformity to guidance. We therefore examined lithium results and requesting patterns relative to monitoring recommendations. METHODS: Data on serum lithium levels and intervals between requests were extracted from Clinical Biochemistry laboratory information systems at the University Hospitals of North Midlands, Salford Royal Foundation Trust and Pennine Acute Hospitals from 2012 to 2018 (46,555 requests; 3371 individuals). Data were examined with respect to region/source of request, age and sex. RESULTS: Across all sites, lithium levels on many requests were outside the recommended UK therapeutic range (0.4-0.99 mmol/L); 19.2% below the range and 6.1% above the range (median [Li]: 0.60 mmol/L). A small percentage were found at the extremes (3.2% at < 0.1 mmol/L, 1.0% at ≥1.4 mmol/L). Most requests were from general practice (56.3%) or mental health units (34.4%), though those in the toxic range (≥1.4 mmol/L) were more likely to be from secondary care (63.9%). For requesting intervals, there was a distinct peak at 12 weeks, consistent with guidance for those stabilised on lithium therapy. There was no peak at 6 months, as recommended for those aged < 65 years on unchanging therapy, though re-test intervals in this age group were more likely to be longer. There was a peak at 0-7 days, reflecting those requiring closer monitoring (e.g. treatment initiation, toxicity). However, for those with initial lithium concentrations within the BNF range (0.4-0.99 mmol/L), 69.4% of tests were requested outside expected testing frequencies. CONCLUSIONS: Our data showed: (a) lithium levels are often maintained at the lower end of the recommended therapeutic range, (b) patterns of lithium results and testing frequency were comparable across three UK sites with differing models of care and, (c) re-test intervals demonstrate a noticeable peak at the recommended 3-monthly, but not at 6-monthly intervals. Many tests were repeated outside expected frequencies, indicating the need for measures to minimise inappropriate testing.

Modelling the impact of the mandatory use of face coverings on public transport and in retail outlets in the UK on COVID-19-related infections, hospital admissions and mortality.

INTRODUCTION: The rapid spread of the pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2/)(COVID-19) virus resulted in governments around the world instigating a range of measures, including mandating the wearing of face coverings on public transport/in retail outlets. METHODS: We developed a sequential assessment of the risk reduction provided by face coverings using a step-by-step approach. The UK Office of National Statistics (ONS) Population Survey data were utilised to determine the baseline total number of community-derived infections. These were linked to reported hospital admissions/hospital deaths to create case admission risk ratio and admission-related fatality rate. We evaluated published evidence to establish an infection risk reduction for face coverings. We calculated an Infection Risk Score (IRS) for a number of common activities and related it to the effectiveness of reducing infection and its consequences, with a face covering, and evaluated their effect when applied to different infection rates over 3 months from July 24, 2020, when face coverings were made compulsory in England on public transport/retail outlets. RESULTS: We show that only 7.3% of all community-based infection risk is associated with public transport/retail outlets. In the week of July 24, The reported weekly community infection rate was 29 400 new cases at the start (July 24). The rate of growth in hospital admissions and deaths for England was around -15%/week, suggesting the infection rate, R, in the most vulnerable populations was just above 0.8. In this situation, average infections over the evaluated 13 week follow-up period, would be 9517/week with face covering of 40% effectiveness, thus, reducing average infections by 844/week, hospital admissions by 8/week and deaths by 0.6/week; a fall of 9% over the period total. If, however, the R-value rises to 1.0, then, average community infections would stay at 29 400/week and mandatory face coverings could reduce average weekly infections by 3930, hospital admissions by 36 and deaths by 2.9/week; a 13% reduction. If the R-value rose and stayed at 1.2, then, expected average community-derived hospital admissions would be 975/week and 40% effective face coverings would reduce this by 167/week and reduce possible expected hospital deaths from 80/week to 66/week. These reductions should be seen in the context that there was an average of 102 000/week all-cause hospital emergency admissions in England in June and 8900 total reported deaths in the week ending August 7, 2020. CONCLUSION: We have illustrated that the policy on mandatory use of face coverings in retail outlets/on public transport may have been very well followed, but may be of limited value in reducing hospital admissions and deaths, at least at the time that it was introduced, unless infections begin to rise faster than currently seen. The impact appears small compared with all other sources of risk, thereby raising questions regarding the effectiveness of the policy.

Inadequate postpartum screening for type 2 diabetes in women with previous gestation diabetes mellitus: A retrospective audit of practice over 17 years.

INTRODUCTION: Women with gestational diabetes (GDM) are at greatly increased risk of type 2 diabetes (T2DM). The UK guidance recommends screening for T2DM at around 6-week postpartum and annually thereafter. We evaluated conformity to this guidance in two separate time periods. METHODS: The proportion of tests performed within guidance was assessed using longitudinal plasma glucose and glycated haemoglobin data in two cohorts (1999-2007, n = 251; 2015-2016, n = 260) from hospital records on women previously diagnosed with GDM. RESULTS: In the 1999-2007 and 2015-2016 cohorts, 59.8% and 35.0% of women had the recommended postpartum testing, respectively (P < .001); just 13.5% and 14.2%, respectively, underwent the first annual test on time. During long-term follow-up of the 1999-2007 cohort (median follow-up: 12.3 years), the proportion of women tested in any given year averaged 34.2% over a 17-year period; there was a progressive decline in the proportion of women receiving a yearly test with time since delivery (P = .002). Over the follow-up period, 85 women from the 1999-2007 cohort developed blood test results in the diabetic range with a median time to presumed DM diagnosis of 5.2 years (range 0.11-15.95 years). Kaplan-Meier analysis showed that 18.8% of women had blood test results in the diabetes range by 5-year postpartum and 37.8% by 10-year postpartum. CONCLUSIONS: Despite high profile guidelines and a clear clinical rationale to screen women with a past diagnosis of GDM, many women did not receive adequate screening for T2DM both in the short term and long term. This suggests that alternative approaches are needed to ensure effective follow-up of this high-risk group. To have an impact, interventions need to be tailored to a young, generally healthy group in which traditional approaches to follow-up may not be best suited.

Improving type 2 diabetes mellitus glycaemic outcomes is possible without spending more on medication: Lessons from the UK National Diabetes Audit.

AIMS: To determine the factors at general practice level that relate to glycaemic control outcomes in people with type 2 diabetes (T2DM). METHODS: Data were accessed from 4050 general practices (50% of total) covering 1.6 million patients with T2DM in the UK National Diabetes Audit 2013 to 2014 and 2014 to 2015. This audit reported characteristics, services and outcomes in the T2DM population, including percentage of patients who had total glycaemic control (TGC), defined as glycated haemoglobin (HbA1c) ≤7.5% (58 mmol/mol), and the percentage who were at higher glycaemic risk (HGR), defined as HbA1c >10% (86 mmol/mol); the respective figures were 67.2% and 6.2%. The medication data were examined in terms of annual defined daily doses (DDDs). Multivariate linear regression analysis was used to identify associations between DDD and patient and practice characteristics. RESULTS: Over the period 2012/2013 to 2015/2016, patient numbers grew 4% annually and annual medication expenditure by 8%, but glycaemic control outcomes did not improve. The main findings were that practices with better outcomes: had a higher percentage of patients aged >65 years; provided more effective diabetes services (including case identification, care checks, patient education, percentage of patients with blood pressure and cholesterol under control and more patients with type 1 diabetes achieving target HbA1c levels); spent less overall on prescribing per patient with T2DM; and on average, prescribed fewer sulphonylureas, less insulin (for patients with T2DM), fewer glucagon-like peptide-1 agonists, more metformin, more dipeptidyl peptidase-4 inhibitors, and more blood glucose monitoring strips. Ethnicity and social disadvantage and levels of thiazolidinedione (glitazone) prescribing had no significant impact on outcomes. Sodium-glucose co-transporter-2 inhibitor use was too low for an effect to be observed in the period examined. CONCLUSIONS: If all practices brought their service and medication to the level of the top decile practices, they could achieve 74.7% compared with the median of 67.3% of patients achieving TGC, showing an increase of 213 000 in patients achieving TGC, while reducing the number at HGR to 3.8% compared with 6.1%, benefiting 62 000 patients. This could have a major impact on the overall consequent healthcare costs of managing diabetes complications with their attendant mortality risks.

Sodium-glucose co-transporter-2 inhibitors, the latest residents on the block: Impact on glycaemic control at a general practice level in England.

AIMS: To determine, using published general practice-level data, how differences in Type 2 diabetes mellitus (T2DM) prescribing patterns relate to glycaemic target achievement levels. METHODS: Multiple linear regression modelling was used to link practice characteristics and defined daily dose (DDD) of different classes of medication in 2015/2016 and changes between that year and the year 2014/2015 in medication to proportion of patients achieving target glycaemic control (glycated haemoglobin A1c [HbA1c] ≤58 mmol/mol [7.5%]) and proportion of patients at high glycaemic risk (HbA1c >86 mmol/mol [10.0%]) for practices in the National Diabetes Audit with >100 people with T2DM on their register. RESULTS: Overall, HbA1c outcomes were not different between the years studied. Although, in percentage terms, most practices increased their use of sodium-glucose co-transporter-2 (SGLT2) inhibitors (96%), dipeptidyl peptidase-4 (DPP-4) inhibitors (76%) and glucagon-like peptide 1 (GLP-1) analogues (53%), there was wide variation in the use of older and newer therapies. For example, 12% of practices used >200% of the national average for some newer agents. In cross-sectional analysis, greater prescribing of metformin and analogue insulin were associated with a higher proportion of patients achieving HbA1c ≤58 mmol/mol; the use of SGLT2 inhibitors and metformin was associated with a reduced proportion of patients with HbA1c >86 mol/mol; otherwise associations for sulphonylureas, GLP-1 analogues, SGLT2 inhibitors and DPP-4 inhibitors were neutral or negative. In year-on-year analysis there was ongoing deterioration in glycaemic control, which was offset to some extent by increased use of SGLT2 inhibitors and GLP-1 analogues, which were associated with a greater proportion of patients achieving HbA1c levels ≤58 mmol/mol and a smaller proportion of patients with HbA1c levels >86 mmol/mol. SGLT2 inhibitor prescribing was associated with significantly greater improvements than those found for GLP-1 analogues. CONCLUSION: Greater use of newer agents was associated with improvement in glycaemic outcomes but was not sufficient to compensate for the prevailing decline. This may reflect wide variability in the prescribing of newer agents. We found that SGLT inhibitors may be superior to other oral agents in relation to HbA1c outcome. Serious consideration should be given to their use.

The frequency of testing for glycated haemoglobin, HbA1c, is linked to the probability of achieving target levels in patients with suboptimally controlled diabetes mellitus.

Background We previously showed, in patients with diabetes, that >50% of monitoring tests for glycated haemoglobin (HbA1c) are outside recommended intervals and that this is linked to diabetes control. Here, we examined the effect of tests/year on achievement of commonly utilised HbA1c targets and on HbA1c changes over time. Methods Data on 20,690 adults with diabetes with a baseline HbA1c of >53 mmol/mol (7%) were extracted from Clinical Biochemistry Laboratory records at three UK hospitals. We examined the effect of HbA1c tests/year on (i) the probability of achieving targets of ≤53 mmol/mol (7%) and ≤48 mmol/mol (6.5%) in a year using multi-state modelling and (ii) the changes in mean HbA1c using a linear mixed-effects model. Results The probabilities of achieving ≤53 mmol/mol (7%) and ≤48 mmol/mol (6.5%) targets within 1 year were 0.20 (95% confidence interval: 0.19-0.21) and 0.10 (0.09-0.10), respectively. Compared with four tests/year, having one test or more than four tests/year were associated with lower likelihoods of achieving either target; two to three tests/year gave similar likelihoods to four tests/year. Mean HbA1c levels were higher in patients who had one test/year compared to those with four tests/year (mean difference: 2.64 mmol/mol [0.24%], p<0.001). Conclusions We showed that ≥80% of patients with suboptimal control are not achieving commonly recommended HbA1c targets within 1 year, highlighting the major challenge facing healthcare services. We also demonstrated that, although appropriate monitoring frequency is important, testing every 6 months is as effective as quarterly testing, supporting international recommendations. We suggest that the importance HbA1c monitoring frequency is being insufficiently recognised in diabetes management.

Polycystic ovarian syndrome: Assessment of approaches to diagnosis and cardiometabolic monitoring in UK primary care.

INTRODUCTION: Polycystic ovarian syndrome (PCOS) is one of the commonest endocrine disorders affecting women of reproductive age. We examined the specific tests that are done in primary care to lead to the diagnosis of PCOS, and to support the diagnosis once made. METHODS: One thousand seven hundred and ninety-seven women were identified from a pooled GP practice database. The search included all patients defined with PCOS or related terms. Records included demographic information, medical history (diagnoses), blood test results and whether a pelvic ultrasound scan had been performed. RESULTS: The most common age of PCOS diagnosis was 20-29 years; 67.7% of the women had at least one concomitant Read-coded diagnosis. Most pelvic ultrasound scans were performed in the month immediately prior to diagnosis. In the 12 months prior to the diagnosis of PCOS being made, 30.5% of women underwent a measurement of their serum total testosterone level while 29.6% had their serum SHBG measured. For serum oestradiol, the corresponding statistics were 28.4%, LH 45.3% and for FSH 45.5% checked before diagnosis. Fasting blood glucose, random glucose and HbA1c were checked in 10.2%, 18.8% and 4.2%, of women before diagnosis, respectively, but in only 7.9%, 6.0% and 3.4% of women in the 24 months after diagnosis. There was a tendency for endocrine testing (oestradiol, LH, FSH, testosterone, SHBG) to peak in the weeks before diagnosis. For plasma glucose, testing was performed more evenly over time as for serum cholesterol. Of all women diagnosed with PCOS, 32.8% were prescribed metformin, 3.7% antihypertensives, 2.2% statins and 63.5% an oestrogen-containing contraceptive pill or HRT. CONCLUSION: The underlying pathophysiology of PCOS is still not fully understood. As a result, treatment is often focused on individual symptoms, not the syndrome itself. Robust laboratory led protocols would provide the necessary information to enable an appropriate diagnostic evaluation/cardometabolic monitoring.

Pre-eclampsia is associated with a twofold increase in diabetes: a systematic review and meta-analysis.

AIMS/HYPOTHESIS: Pre-eclampsia is a pregnancy-specific multisystem disorder and a state of physiological insulin resistance. Our aim was to systematically evaluate and quantify the evidence on the relationship between pre-eclampsia and the future risk of diabetes. METHODS: We conducted a systematic review and meta-analysis of studies that evaluated diabetes in women with and without pre-eclampsia. We performed a systematic search of MEDLINE and EMBASE to identify relevant studies. Independent double data extractions were conducted by four reviewers. Random-effects meta-analysis was used to estimate the risk of future diabetes following pre-eclampsia. RESULTS: A total of 21 studies were identified with more than 2.8 million women, including more than 72,500 women with pre-eclampsia. Meta-analysis of studies that adjusted for potential confounders demonstrated that pre-eclampsia was independently associated with an increased risk of future diabetes (RR 2.37 [95% CI 1.89, 2.97]). This risk appeared in studies that followed women from less than 1 year postpartum (RR 1.97 [95% CI 1.35, 2.87]) and persisted to more than 10 years postpartum (RR 1.95 [95% CI 1.28, 2.97]). After adjusting for BMI or gestational diabetes, pre-eclampsia remained linked with an increased risk of future diabetes (RR 2.38 [95% CI 1.74, 3.24] and RR 2.36 [95% CI 1.94, 2.88], respectively). CONCLUSIONS/INTERPRETATION: Pre-eclampsia is independently associated with a twofold increase in future diabetes. Our study highlights the importance of clinical risk assessment for the future development of diabetes in women with pre-eclampsia. We recommend detailed evaluation of a screening programme for diabetes in this high-risk population.

Is the Current Cut Point for Glycated Haemoglobin (HbA1c) Correct for Diagnosing Diabetes Mellitus in Premenopausal Women? Evidence to Inform Discussion.

INTRODUCTION: Women are on average diagnosed with diabetes mellitus at later age than men but have higher mortality. As the diagnosis of diabetes mellitus is primarily based on HbA1c, the use of a non-specific reference range and cut point for diabetes mellitus that does not account for gender differences in diabetes could potentially lead to underdiagnosis of diabetes mellitus in women and missed opportunities for intervention. We investigated whether a contributing factor to the later diagnosis in women may be a difference in distribution of HbA1c in premenopausal women versus men of the same age by comparing HbA1c values in men and women across multiple sites in the UK. METHODS: We analysed the HbA1c levels of 146,907 individuals who underwent single testing only and had HbA1c ≤ 50 mmol/mol between 2012 and 2019 in one laboratory (cohort 1). This was replicated in six laboratories with 938,678 individuals tested between 2019 and 2021 (cohort 2). RESULTS: In cohort 1, women < 50 years old had an HbA1c distribution markedly lower than that in men by a mean of 1.6 mmol/mol (p < 0.0001), while the difference in the distribution of HbA1c for individuals aged ≥ 50 years was less pronounced (mean difference 0.9 mmol/mol, p < 0.0001). For individuals under the age of 50, HbA1c in women lagged by up to 10 years compared to men. Similar findings were found in cohort 2. We estimated an additional 17% (n = 34,953) of undiagnosed women aged < 50 years in England and Wales could be reclassified to have diabetes mellitus, which may contribute to up to 64% of the difference in mortality rates between men/women with diabetes mellitus aged 16-50 years. CONCLUSION: The HbA1c cut point for diagnosis of diabetes mellitus may need to be re-evaluated in women under the age of 50 years. Early identification of diabetes mellitus in women has the potential to improve women's health outcomes in the longer term.

Antiepileptic drugs and the fetal epigenome.

Antiepileptic drugs (AEDs) can lower maternal folate and increase maternal homocysteine levels, which are known to affect the methyl cycle and hence DNA methylation levels. The influence of in utero exposure to AEDs on fetal DNA methylation was investigated. Genome-wide fetal epigenomic profiles were determined using the Infinium 27K BeadArray from Illumina (San Diego, CA, U.S.A.). The Infinium array measures approximately 27,000 CpG loci associated with 14,496 genes at single-nucleotide resolution. Eighteen cord blood samples (nine samples from babies exposed to AEDs and nine controls) from otherwise uncomplicated pregnancies were compared. Unsupervised hierarchic clustering was used to compare the calculated methylation profiles. A clear distinction between the methylation profiles of samples from babies exposed to AEDs in utero compared with controls was detected. These data provide evidence of an epigenetic effect associated with antenatal AED and high-dose folate supplementation during pregnancy. The differences in fetal DNA methylation of those exposed to AEDs shows that a genome-wide effect of methylation is evident. In addition, the epigenetic changes observed appear to be, in this limited sample, independent of extremes of birth weight centiles. These preliminary data highlight possible mechanisms by which AEDs might influence fetal outcomes and the potential of optimizing AED-specific folate supplementation regimens to offset these effects.

The Utility of Salivary Cortisone in the Overnight Dexamethasone Suppression Test in Adrenal Incidentalomas.

CONTEXT: Guidelines recommend the assessment of cortisol secretion in patients with adrenal incidentalomas (AI) using the overnight dexamethasone suppression test (ONDST). This requires attendance at a health care facility and venepuncture. Alternatively, the ONDST can be done by measuring salivary cortisol and cortisone, which can be collected at home. OBJECTIVE: We aimed to assess the utility of these measurements in patients with AI. METHODS: A retrospective analysis of data from 173 patients with AI who underwent an ONDST and salivary cortisol/cortisone diurnal studies. Serum and salivary cortisol and salivary cortisone were collected at 09:00, late night, and at 09:00 the following morning after dexamethasone. Dexamethasone levels were measured in the postdexamethasone samples. Serum and salivary samples were analyzed with liquid chromatography-tandem mass spectrometry. RESULTS: We identified a strong correlation between salivary cortisone and serum cortisol after 1 mg of dexamethasone (r = 0.95). Stepwise multivariate regression showed that postdexamethasone salivary cortisone, baseline serum cortisol, salivary cortisone suppression (predexamethasone/postdexamethasone ratio), and sex were the only significant or near-significant independent variables. Performance of predictive indices using these 4 parameters (sensitivity = 88.5%, specificity = 91.2%; kappa 0.80) and postdexamethasone salivary cortisone alone (sensitivity = 85.3%, specificity = 91.7%; kappa 0.77) were comparable when used to predict an ONDST serum cortisol of ≤50 nmol/L. No correlation was observed with any of the other measured parameters. CONCLUSION: In AI patients, after dexamethasone, salivary cortisone correlates very strongly with serum cortisol in the ONDST and could therefore be used as an alternative sampling method which does not require venepuncture or attendance at hospital.

Assessment of the effect of the COVID-19 pandemic on UK HbA1c testing: implications for diabetes management and diagnosis.

AIMS: The COVID-19 pandemic, and the focus on mitigating its effects, has disrupted diabetes healthcare services worldwide. We aimed to quantify the effect of the pandemic on diabetes diagnosis/management, using glycated haemoglobin (HbA1c) as surrogate, across six UK centres. METHODS: Using routinely collected laboratory data, we estimated the number of missed HbA1c tests for 'diagnostic'/'screening'/'management' purposes during the COVID-19 impact period (CIP; 23 March 2020 to 30 September 2020). We examined potential impact in terms of: (1) diabetes control in people with diabetes and (2) detection of new diabetes and prediabetes cases. RESULTS: In April 2020, HbA1c test numbers fell by ~80%. Overall, across six centres, 369 871 tests were missed during the 6.28 months of the CIP, equivalent to >6.6 million tests nationwide. We identified 79 131 missed 'monitoring' tests in people with diabetes. In those 28 564 people with suboptimal control, this delayed monitoring was associated with a 2-3 mmol/mol HbA1c increase. Overall, 149 455 'screening' and 141 285 'diagnostic' tests were also missed. Across the UK, our findings equate to 1.41 million missed/delayed diabetes monitoring tests (including 0.51 million in people with suboptimal control), 2.67 million screening tests in high-risk groups (0.48 million within the prediabetes range) and 2.52 million tests for diagnosis (0.21 million in the pre-diabetes range; ~70 000 in the diabetes range). CONCLUSIONS: Our findings illustrate the widespread collateral impact of implementing measures to mitigate the impact of COVID-19 in people with, or being investigated for, diabetes. For people with diabetes, missed tests will result in further deterioration in diabetes control, especially in those whose HbA1c levels are already high.