Real-world practice level data analysis confirms link between variability within Blood Glucose Monitoring Strip (BGMS) and glycosylated haemoglobin (HbA1c) in Type 1 Diabetes.

AIMS/HYPOTHESIS: Our aim was to quantify the impact of Blood Glucose Monitoring Strips variability (BGMSV) at GP practice level on the variability of reported glycated haemoglobin (HbA1cV) levels. METHODS: Overall GP Practice BGMSV and HbA1cV were calculated from the quantity of main types of BGMS being prescribed combined with the published accuracy, as % results within ±% bands from reference value for the selected strip type. The regression coefficient between the BGMSV and HbA1cV was calculated. To allow for the aggregation of estimated three tests/day over 13 weeks (ie, 300 samples) of actual Blood Glucose (BG) values up to the HbA1c, we multiplied HbA1cV coefficient by √300 to estimate an empirical value for impact of BGMSV on BGV. RESULTS: Four thousand five hundred and twenty-four practice years with 159 700 T1DM patient years where accuracy data were available for more than 80% of strips prescribed were included, with overall BGMSV 6.5% and HbA1c mean of 66.9 mmol/mol (8.3%) with variability of 13 mmol/mol equal to 19% of the mean. At a GP practice level, BGMSV and HbA1cV as % of mean HbA1c (in other words, the spread of HbA1c) were closely related with a regression coefficient of 0.176, P ±4.5 mmol/L from target, compared with the best performing BGMS with BG >±2.2 mmol/L from reference on 1/20 occasions. CONCLUSION: Use of more variable/less accurate BGMS is associated both theoretically and in practice with a larger variability in measured BG and HbA1c, with implications for patient confidence in their day-to-day monitoring experience

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

INTRODUCTION: Blood test monitoring is essential for management of lithium treatment and NICE guidance recommends 6-monthly serum testing of thyroid function. We examined conformity to these guidelines and impact of monitoring outside these intervals. METHODS: We extracted serum lithium and thyroid hormone results at one centre between Jan 2009-Dec 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 interval between tests, time between onset of lithium testing and first TSH outside the laboratory reference range and assessed impact of testing outside recommended 6-monthly intervals. RESULTS: The most common testing frequency was 3-monthly (±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 from commencing lithium therapy, 8 patients developed subclinical hypothyroidism and had clinical follow-up data available. Of these, half spontaneously normalised 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-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 supports the recommended 6-monthly testing interval and highlights poor adherence to it

Sars-Cov-2 Infection in People with Type 1 Diabetes and Hospital Admission: An Analysis of Risk Factors for England

Introduction: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus (coronavirus disease 2019 [COVID-19]) pandemic revealed the vulnerability of specific population groups in relation to susceptibility to acute deterioration in their health, including hospital admission and mortality. There is less data on outcomes for people with type 1 diabetes (T1D) following SARS-CoV-2 infection than for those with type 2 diabetes (T2D). In this study we set out to determine the relative likelihood of hospital admission following SARS-CoV-2 infection in people with T1D when compared to those without T1D. Methods: This study was conducted as a retrospective cohort study and utilised an all-England dataset. Electronic health record data relating to people in a national England database (NHS England’s Secure Data Environment, accessed via the BHF Data Science Centre's CVD-COVID-UK/COVID-IMPACT consortium) were analysed. The cohort consisted of patients with a confirmed SARS-CoV-2 infection, and the exposure was whether or not an individual had T1D prior to infection (77,392 patients with T1D). The patients without T1D were matched for sex, age and approximate date of the positive COVID-19 test, with three SARS-CoV-2-infected people living without diabetes (n = 223,995). Potential factors influencing the relative likelihood of the outcome of hospital admission within 28 days were ascertained using univariable and multivariable logistic regression. Results: Median age of the people living with T1D was 37 (interquartile range 25–52) years, 47.4% were female and 89.6% were of white ethnicity. Mean body mass index was 27 (standard error [SE] 0.022) kg/m2, and mean glycated haemoglobin (HbA1c) was 67.3 (SE 0.069) mmol/mol (8.3%). A significantly higher proportion of people with T1D (10.7%) versus matched non-diabetes individuals (3.9%) were admitted to hospital. In combined analysis including individuals with T1D and matched controls, multiple regression modelling indicated that the factors independently relating to a higher likelihood of hospital admission were: T1D (odds ratio [OR] 1.71, 95% confidence interval [CI] 1.62–1.80]), age (OR 1.02, 95% CI 1.02–1.03), social deprivation (higher Townsend deprivation score: OR 1.07, 95% CI 1.06–1.08), lower estimated glomerular filtration rate (eGFR) value (OR 0.975, 95% CI 0.974–0.976), non-white ethnicity (OR black 1.19, 95% CI 1.06–1.33/OR Asian 1.21, 95% CI 1.05–1.39) and having asthma (OR 1.27, 95% CI 1.19–1.35]), chronic obstructive pulmonary disease (OR 2.10, 95% CI 1.89–2.32), severe mental illness (OR 1.83, 95% CI 1.57–2.12) or hypertension (OR 1.44, 95% CI 1.37–1.52). Conclusion: In this all-England study, we describe that, following confirmed infection with SARS-CoV-2, the risk factors for hospital admission for people living with T1D are similar to people without diabetes following confirmed SARS-CoV-2 infection, although the former were more likely to be admitted to hospital. The younger age of individuals with T1D in relation to risk stratification must be taken into account in any ongoing risk reduction strategies regarding COVID-19/future viral pandemics

Correction to: Sars-Cov-2 Infection in People with Type 1 Diabetes and Hospital Admission: An Analysis of Risk Factors for England

The article “Sars-Cov-2 Infection in People with Type 1 Diabetes and Hospital Admission: An Analysis of Risk Factors for England”, written by Adrian H. Heald, David A. Jenkins, Richard Williams, Rajshekhar N. Mudaliar, Amber Khan, Akheel Syed, Naveed Sattar, Kamlesh Khunti, Asma Naseem, Kelly A. Bowden-Davies, J. Martin Gibson, William Ollier, on behalf of the CVD-COVID-UK/COVID-IMPACT Consortium was originally published electronically on the publisher’s Internet portal (currently SpringerLink) on August 25, 2023, without open access. Now, the article is updated with open access as This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The original article has been corrected

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

COVID-19 Vaccination and Diabetes Mellitus: How Much Has It Made a Difference to Outcomes Following Confirmed COVID-19 Infection?

Introduction: Since early 2020 the whole world has been challenged by the SARS-CoV-2 virus (COVID-19), its successive variants and the associated pandemic caused. We have previously shown that for people living with type 2 diabetes (T2DM), the risk of being admitted to hospital or dying following a COVID-19 infection progressively decreased through the first months of 2021. In this subsequent analysis we have examined how the UK COVID-19 vaccination programme impacted differentially on COVID-19 outcomes in people with T1DM or T2DM compared to appropriate controls. Methods: T1DM and T2DM affected individuals were compared with their matched controls on 3:1 ratio basis. A 28-day hospital admission or mortality was used as the binary outcome variable with diabetes status and vaccination for COVID-19 as the main exposure variables. Results: A higher proportion of T1DM individuals vs their controls was found to be vaccinated at the point of their first recorded positive COVID-19 test when compared to T2DM individuals vs their controls. Regarding the 28-day hospital admission rate, there was a greater and increasing protective effect of subsequent vaccination dosage (one, two or three) in mitigating the effects of COVID-19 infection versus no vaccination in T1DM than in T2DM individuals when compared with matched controls. Similar effects were observed in T2DM for death. Across both diabetes and non-diabetes individuals, those at greater socio-economic disadvantage were more likely to test positive for COVID-19 in the early phase of the pandemic. For T2DM individuals socio-economic disadvantage was associated with a greater likelihood of hospital admission and death, independent of vaccination status. Age and male sex were also independently associated with 28-day hospital admission in T2DM and to 28-day mortality, independent of vaccination status. African ethnicity was also an additional factor for hospital admission in people with T2DM. Conclusion: A beneficial effect of COVID-19 vaccination was seen in mitigating the harmful effects of COVID-19 infection; this was manifest in reduced hospital admission rate in T1DM individuals with a lesser effect in T2DM when compared with matched controls, regarding both hospital admission and mortality. Socio-economic disadvantage influenced likelihood of COVID-19 confirmed infection and the likelihood of hospital admission/death independent of the number of vaccinations given in T2DM

Can we check serum lithium levels less often without compromising patient safety?

BACKGROUND: Lithium is viewed as the first-line long-term treatment for prevention of relapse in people with bipolar disorder. AIMS: This study examined factors associated with the likelihood of maintaining serum lithium levels within the recommended range and explored whether the monitoring interval could be extended in some cases. METHOD: We included 46 555 lithium rest requests in 3371 individuals over 7 years from three UK centres. Using lithium results in four categories (<0.4 mmol/L; 0.40-0.79 mmol/L; 0.80-0.99 mmol/L; ≥1.0 mmol/L), we determined the proportion of instances where lithium results remained stable or switched category on subsequent testing, considering the effects of age, duration of lithium therapy and testing history. RESULTS: For tests within the recommended range (0.40-0.99 mmol/L categories), 84.5% of subsequent tests remained within this range. Overall, 3 monthly testing was associated with 90% of lithium results remaining within range, compared with 85% at 6 monthly intervals. In cases where the lithium level in the previous 12 months was on target (0.40-0.79 mmol/L; British National Formulary/National Institute for Health and Care Excellence criteria), 90% remained within the target range at 6 months. Neither age nor duration of lithium therapy had any significant effect on lithium level stability. Levels within the 0.80-0.99 mmol/L category were linked to a higher probability of moving to the ≥1.0 mmol/L category (10%) compared with those in the 0.4-0.79 mmol/L group (2%), irrespective of testing frequency. CONCLUSION: We propose that for those who achieve 12 months of lithium tests within the 0.40-0.79 mmol/L range, the interval between tests could increase to 6 months, irrespective of age. Where lithium levels are 0.80-0.99 mmol/L, the test interval should remain at 3 months. This could reduce lithium test numbers by 15% and costs by ~$0.4 m p.a

2010 SSO John Wayne Clinical Research Lecture: Rectal Cancer Outcome Improvements in Europe: Population-Based Outcome Registrations will Conquer the World

During the past two decades, rectal cancer treatment has improved considerably in Europe. Clinical trials played a crucial role in improving surgical techniques, (neo)adjuvant treatment schedules, imaging, and pathology. However, there is still a wide variation in outcome after rectal cancer. In most western health care systems, efforts are made to reduce hospital variation by focusing on selective referral and encouraging patients to seek care in high-volume hospitals. On the other hand, the expertise for diagnosis and treatment of common types of cancer should be preferably widespread and easily accessible for all patients. As an alternative to volume-based referral, hospitals and surgeons can improve their results by learning from their own outcome statistics and those from colleagues treating a similar patient group. Several European surgical (colo)rectal audits have led to improvements with a greater impact than any of the adjuvant therapies currently under study. However, differences remain between European countries, which cannot be easily explained. To generate the best care for colorectal cancer in the whole of Europe and to meet political and public demands for transparency, the European CanCer Organisation (ECCO) initiated an international, multidisciplinary, outcome-based quality improvement program: European Registration of Cancer Care (EURECCA). The goal is to create a multidisciplinary European registration structure for patient, tumor, and treatment characteristics linked to outcome registration. Clinical trials will always play a major role in improving rectal cancer treatment. To further improve outcomes and diminish variation, EURECCA will establish the basis for a strong, multidisciplinary, international audit structure that can be used as a template for similar projects worldwide

Variability in Test Interval Is Linked to Glycated Haemoglobin (HbA1c) Trajectory over Time

Aims. We previously showed that the glycated haemoglobin (HbA1c) testing frequency links to diabetes control. Here, we examine the effect of variability in test interval, adjusted for the frequency, on change in HbA1c (delta HbA1c). Materials & Methods. HbA1c results were collected on 83,872 people with HbA1c results at baseline and 5 years (+/- 3 months) later and >= 6 tests during this period. We calculated the standard deviation (SD) of test interval for each individual and examined the link between deciles of SD of the test interval and delta HbA1c level, stratified by baseline HbA1c. Results. In general, less variability in testing frequency (more consistent monitoring) was associated with better diabetes control. This was most evident with moderately raised baseline HbA1c levels (7.0-9.0% (54-75 mmol/mol)). For example, in those with a starting HbA1c of 7.0-7.5% (54-58 mmol/mol), the lowest SD decile was associated with little change in HbA1c over 5 years, while for those with the highest decile, HbA1c rose by 0.4-0.6% (4-6 mmol/mol; p < 0.0001). Multivariate analysis showed that the association was independent of the age/sex/hospital site. Subanalysis suggested that the effect was most pronounced in those aged < 65 years with baseline HbA1c of 7.0-7.5% (54-58 mmol/mol). We observed a 6.7-fold variation in the proportion of people in the top-three SD deciles across general practices. Conclusions. These findings indicate that the consistency of testing interval, not the just number of tests/year, is important in maintaining diabetes control, especially in those with moderately raised HbA1c levels. Systems to improve regularity of HbA1c testing are therefore needed, especially given the impact of COVID-19 on diabetes monitoring