The Relation of Diabetes Complications to a New Interpretation of Glycaemic Variability from Continuous Glucose Monitoring in People with Type 1 Diabetes.

INTRODUCTION: Microvascular and macrovascular complications in type 1 diabetes (T1D) may be linked to endothelial stress due to glycaemic variability. Continuous glucose monitoring systems (CGMs) provide new opportunities to quantify this variability, utilising the amplitude of glucose change summated over time. The aim of this study was to examine whether this determination of glucose variability (GV) is associated with microvascular clinical sequelae. METHODS: Continuous glucose monitoring values were downloaded for 89 type 1 diabetes mellitus (T1D) individuals for up to 18 months from 2021 to 2023. Data for patient demographics was also taken from the patient record which included Sex, Date of Birth, and Date of Diagnosis. The recorded laboratory glycated haemoglobin (HbA1c) test results were also recorded. The glucose management index (GMI) was calculated from average glucose readings for 18 months using the formula GMI (%) = (0.82-(Average glucose/100)). This was then adjusted to give GMI (mmol/mol) = 10.929 * (GMI (%) - 2.15). Average Glucose Fluctuation (AGF) was calculated by adding up the total absolute change value between all recorded results over 18 months and dividing by the number of results minus one. The % Above Critical Threshold (ACT) was calculated by summing the total number of occurrences for each result value. A cumulative 95% limit was then applied to identify the glucose value that only 5% of results exceeded in the overall population. Using this value, we estimated the percentage of total tests that were above the Critical Threshold (ACT). RESULTS: Results for the 89 individuals (44 men and 45 women) were analysed over 18 months. The mean age of participants was 43 years and the mean duration of diabetes was 18 years. A total of 3.22 million readings were analysed, giving an average of 10.3 mmol/L blood glucose. Those with the largest change in glucose from reading to reading, summated over time, showed the greatest change in eGFR of 3.12 ml/min/1.73 m2 (p = 0.007). People with a higher proportion of glucose readings > 18 mmol/L showed a fall in eGFR of 2.8 ml/min/1.73 m2 (p = 0.009) and experienced higher rates of sight-threatening retinopathy (44% of these individuals) (p = 0.01) as did 39% of individuals in the highest tertile of glucose levels (p = 0.008). CONCLUSION: Those individuals with T1D in the highest tertile of reading-to-reading glucose change showed the greatest change in eGFR. Those with a higher proportion of glucose readings > 18 mmol/L also showed a fall in eGFR and experienced higher rates of sight-threatening retinopathy, as did people with higher mean glucose. Discussions with T1D individuals could reflect on how the percentage recorded glucose above a critical level and degree of change in glucose are important in avoiding future tissue complications.

Unveiling the Spectrum of Glucose Variability: A Novel Perspective on FreeStyle Libre Monitoring Data.

INTRODUCTION: Since the introduction of insulin therapy, it has become apparent that type 1 diabetes (T1D) is accompanied by long-term microvascular and macrovascular complications. In the context of the many benefits of continuous glucose monitoring (CGM), there remain opportunities to study the large amount of data now available in order to maximise its potential in the endeavour to reduce the occurrence of diabetes tissue complications in the longer term. METHODS: Continuous glucose monitoring values were downloaded for 89 type 1 diabetes mellitus (T1D) individuals for up to 18 months from 2021 to 2023. Data for patient demographics was also taken from the patient record which included Sex, Date of Birth, and Date of Diagnosis. The recorded laboratory glycated haemoglobin (HbA1c) test results were also recorded. The glucose management index (GMI) was calculated from average glucose readings for 18 months using the formula GMI (%) = (0.82 - (Average glucose/100)). This was then adjusted to give GMI (mmol/mol) = 10.929 * (GMI (%) - 2.15). Average Glucose Fluctuation (AGF) was calculated by adding up the total absolute change value between all recorded results over 18 months and dividing by the number of results minus one. The % Above Critical Threshold (ACT) was calculated by summing the total number of occurrences for each result value. A cumulative 95% limit was then applied to identify the glucose value that only 5% of results exceeded in the overall population. Using this value, we estimated the percentage of total tests that were above the Critical Threshold (ACT). RESULTS: The mean age of the participants was 42.6 years, and the mean duration of T1D was 18.4 years. A total of 3.22 million readings were analysed, yielding an average blood glucose level of 10.3 mmol/l and a GMI of 57.2 mmol/mol. There was a strong correlation between GMI and measured HbA1c (r2 = 0.82). However, there were patients who had an above-critical threshold (ACT) of 4-10% at a GMI of 60 mmol/mol or less. The percentage average value at the time of day (%AVTD) was applied to all blood glucose readings at each 15-min interval throughout the day, averaged over 18 months. The %AVTD of GMI (overall average 57.2 mmol/mol) increased after midday, dipped at 18:00, and peaked at 22:00. The %AVTD of AGF (overall average 0.60 mmol/l) showed higher change rates after 09:00 declining at the end of the day. The %AVTD of ACT peaked at 22:00, with those having the highest %ACT showing an additional peak at 15:00. CONCLUSIONS: We have shown here that the percentage glucose results above 18 mmol/l (top 5% of distribution) increased exponentially above 54 mmol/mol HbA1c. The %AVTD is introduced as a useful measure. Our data indicate that over the 24-h period, improvement in metabolic control could be focussed on the afternoon and evening, when there are higher-than-average levels of GMI, a higher-than-average degree of glucose change, and higher-than-average risks of being above the critical threshold. In conclusion, a measure of glycaemic variation based on the amplitude of glucose change to a population mean could be used to provide valuable clinical insights into glucose change over a 24-h period.

Changes in primary care visits for respiratory illness during the COVID-19 pandemic: a multinational study by the International Consortium of Primary Care Big Data Researchers (INTRePID).

Objectives: The majority of patients with respiratory illness are seen in primary care settings. Given COVID-19 is predominantly a respiratory illness, the INTernational ConsoRtium of Primary Care BIg Data Researchers (INTRePID), assessed the pandemic impact on primary care visits for respiratory illnesses. Design: Definitions for respiratory illness types were agreed on collectively. Monthly visit counts with diagnosis were shared centrally for analysis. Setting: Primary care settings in Argentina, Australia, Canada, China, Norway, Peru, Singapore, Sweden and the United States. Participants: Over 38 million patients seen in primary care settings in INTRePID countries before and during the pandemic, from January 1st, 2018, to December 31st, 2021. Main outcome measures: Relative change in the monthly mean number of visits before and after the onset of the pandemic for acute infectious respiratory disease visits including influenza, upper and lower respiratory tract infections and chronic respiratory disease visits including asthma, chronic obstructive pulmonary disease, respiratory allergies, and other respiratory diseases. Results: INTRePID countries reported a marked decrease in the average monthly visits for respiratory illness. Changes in visits varied from -10.9% [95% confidence interval (CI): -33.1 to +11.3%] in Norway to -79.9% (95% CI: -86.4% to -73.4%) in China for acute infectious respiratory disease visits and - 2.1% (95% CI: -12.1 to +7.8%) in Peru to -59.9% (95% CI: -68.6% to -51.3%) in China for chronic respiratory illness visits. While seasonal variation in allergic respiratory illness continued during the pandemic, there was essentially no spike in influenza illness during the first 2 years of the pandemic. Conclusion: The COVID-19 pandemic had a major impact on primary care visits for respiratory presentations. Primary care continued to provide services for respiratory illness, although there was a decrease in infectious illness during the COVID pandemic. Understanding the role of primary care may provide valuable information for COVID-19 recovery efforts and planning for future global emergencies.

Intellectual Disabilities and Neurocognitive Impairment in Adult Patients with Inherited Metabolic Diseases: A UK Single Centre Experience.

Inherited metabolic diseases (IMDs) are a group of heterogeneous genetic disorders resulting in substrate accumulation, energy deficiency, or complex molecular defects due to the failure of specific molecules to act as enzymes, cofactors, transporters, or receptors in specific metabolic pathways. The pathophysiological changes seen in IMDs are sometimes associated with intellectual disability (ID) or neurocognitive decline, necessitating multidisciplinary input. We here describe our experience at one tertiary metabolic centre in the UK. We reviewed the case prevalence and existing service provision in one adult IMD service covering a multi-ethnic population of 10 million in North England. In our cohort of 2268 IMD patients, 1598 patients had general metabolic conditions (70.5%), and 670 had lysosomal storage disease/disorders (LSD)s (29.5%). The overall prevalence of ID and neurocognitive decline was found to be 15.7% (n = 357), with patients with LSDs accounting for 23.5% (n = 84) of affected patients. Given the prevalence of ID in adults with IMDs, access to multidisciplinary input from neuropsychology and neuropsychiatry services is important. Education of healthcare professionals to diagnose IMDs in patients with ID, in addition to neurocognitive and neuropsychiatric presentations, will avoid missed diagnoses of IMD and will have a positive effect on patient outcomes.

Are weight loss and metabolic outcomes of bariatric surgery influenced by candidate glucocorticoid receptor gene polymorphisms? A prospective study.

BACKGROUND: Bariatric surgery is the most effective treatment for severe obesity. There can be variation in the degree of weight reduction following bariatric surgery. It is unknown whether single nucleotide polymorphisms (SNPs) in the glucocorticoid receptor locus (GRL) affect postoperative weight loss and metabolic outcomes. MATERIALS/METHODS: We studied the association between selected candidate SNPs and postoperative weight loss and metabolic outcomes in patients with severe obesity undergoing bariatric surgery. The polymorphisms rs41423247 (Bcl1), rs56149945 (N363S) and rs6189/rs6190 (ER22/23EK) were analysed. RESULTS: The 139 participants included 95 women (68.3%) and had a median (interquartile range) age of 53.0 (46.0-60.0) years and mean (SD) weight of 140.8 (28.8) kg and body mass index of 50.3 (8.6) kg/m2. At baseline, 59 patients had type 2 diabetes (T2D), 60 had hypertension and 35 had obstructive sleep apnoea syndrome treated with continuous positive airway pressure (CPAP). 84 patients (60.4%) underwent gastric bypass and 55 (39.6%) underwent sleeve gastrectomy. There were no significant differences in weight loss, glycated haemoglobin (HbA1c) or lipid profile categorized by genotype status, sex or median age. There was significant weight reduction after bariatric surgery with a postoperative BMI of 34.1 (6.8) kg/m2 at 24 months (p < 0.001). CONCLUSION: While GRL polymorphisms with a known deleterious effect on adipose tissue mass and function may have a small, additive effect on the prevalence of obesity and related metabolic disorders in the population, we suggest that the relatively weak biological influence of these SNPs is readily overcome by bariatric surgery.

The prevalence of long COVID in people with diabetes mellitus-evidence from a UK cohort.

Background: It was apparent from the early phase of the SARS-CoV-2 virus (COVID-19) pandemic that a multi-system syndrome can develop in the weeks following a COVID-19 infection, now referred to as Long COVID. Given that people living with diabetes are at increased risk of hospital admission/poor outcomes following COVID-19 infection we hypothesised that they may also be more susceptible to developing Long COVID. We describe here the prevalence of Long COVID in people living with diabetes when compared to matched controls in a Northwest UK population. Methods: This was a retrospective cohort study of people who had a recorded diagnosis of type 1 diabetes (T1D) or type 2 diabetes (T2D) who were alive on 1st January 2020 and who had a proven COVID-19 infection. We used electronic health record data from the Greater Manchester Care Record collected from 1st January 2020 to 16th September 2023, we determined the prevalence of Long COVID in people with T1D and T2D vs matched individuals without diabetes (non-DM). Findings: There were 3087 T1D individuals with 14,077 non-diabetes controls and 3087 T2D individuals with 14,077 non-diabetes controls and 29,700 T2D individuals vs 119,951 controls. For T1D, there was a lower proportion of Long COVID diagnosis and/or referral to a Long COVID service at 0.33% vs 0.48% for matched controls. The prevalence of Long COVID In T2D individuals was 0.53% vs 1:3 matched controls 0.54%. For T2D, there were differences by sex in the prevalence of Long COVID in comparison with 1:3 matched controls. For Long COVID between males with T2D and their matched controls, the prevalence was lower in matched controls at 0.46%.vs 0.54% (0.008). When considering the prevalence of LC between females with T2D and their matched controls, the prevalence was higher in matched controls at 0.61% vs 0.53% (0.007). The prevalence of Long COVID in males with T2D vs females was not different. T2D patients at older vs younger age were at reduced risk of developing Long COVID (OR 0.994 [95% CI) [0.989, 0.999]). For females there was a minor increase of risk (OR 1.179, 95% CI [1.002, 1.387]). Presence of a higher body mass index (BMI) was also associated an increased risk of developing Long COVID (OR 1.013, 95% CI [1.001, 1.026]). The estimated general population prevalence of Long COVID based on general practice coding (not self-reported) of this diagnosis was 0.5% of people with a prior acute COVID-19 diagnosis. Interpretation: Recorded Long COVID was more prevalent in men with T2D than in matched non-T2D controls with the opposite seen for T2D women, with recorded Long COVID rates being similar for T2D men and women. Younger age, female sex and higher BMI were all associated with a greater likelihood of developing Long COVID when taken as individual variables. There remains an imperative for continuing awareness of Long COVID as a differential diagnosis for multi-system symptomatic presentation in the context of a previous acute COVID-19 infection. Funding: The time of co-author RW was supported by the NIHR Applied Research Collaboration Greater Manchester (NIHR200174) and the NIHR Manchester Biomedical Research Centre (NIHR203308).

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.

Effectiveness of locally produced ready-to-use supplementary foods on the prevention of stunting in children aged 6-23 months: a community-based trial from Pakistan.

Undernutrition is a major public health problem in developing countries. Around 40·2 % of children are stunted in Pakistan. This longitudinal study aimed to assess the effectiveness of locally produced ready-to-use supplementary foods in the prevention of stunting by detecting change in of children in intervention v. control arm against the 2006 WHO growth reference. A community-based non-randomised cluster-controlled trial was conducted from January 2018 to December 2020 in the district of Kurram, Khyber Pakhtunkhwa, Pakistan. A total of 80 clusters (each cluster comprising ≈ 250-300 households) were defined in the catchment population of twelve health facilities. Children aged 6-18 months were recruited n 1680. The intervention included a daily ration of 50 g - locally produced ready-to-use-supplementary food (Wawa-Mum). The main outcome of this study was a change in length for age z-score (LAZ) v. WHO growth standards. Comparison between the interventions was by t test and ANOVA. Cox proportional hazard models were used to assess the association between stunting occurrence and the utilisation of locally produced supplement. Out of the total 1680, fifty-one out of the total 1680, 51·1 out of the total 1680 and 51·1 % (n 859) were male. Mean age 13·9 months (sd + 859) were male. Mean age 13·9 months (sd + -4·4). At baseline, 36·9 % (n 618) were stunted. In the intervention group, mean LAZ score significantly increased from -1·13(2·2 sd) at baseline to -0·93(1·8 sd) at 6-month follow-up (P value 0·01) compared with the control group. The incidence rate of stunting in the intervention arm was 1·3 v. 3·4 per person year in the control arm. The control group had a significantly increased likelihood of stunting (Hazard Ratio (HR) 1·7, 95 % CI 1·46, 2·05, P value < 0·001) v. the intervention group. Locally produced ready-to-use supplementary food is an effective intervention for reducing stunting in children below 2 years of age. This can be provided as part of a malnutrition prevention package to overcome the alarming rates of stunting in Pakistan.

Impact of Bariatric Surgery on Subtilisin/Kexin Type 9 (PCSK9) Gene Expression and Inflammation in the Adipose Tissue of Obese Diabetic Rats.

Bariatric surgery improves dyslipidaemia and reduces body weight, but it remains unclear how bariatric surgery modulates gene expression in fat cells to influence the proprotein convertase subtilisin/kexin type 9 (PCSK-9) and low-density lipoprotein receptor (LDLR) gene expression. The expression of the PCSK9/LDLR/tumor necrosis factor-alpha (TNFα) gene in adipose tissue was measured in two groups of Zucker Diabetic Sprague Dawley (ZDSD) rats after Roux-en-Y gastric bypass (RYGB) surgery or 'SHAM' operation. There was lower PCSK9 (p = 0.02) and higher LDLR gene expression (p = 0.02) in adipose tissue in rats after RYGB. Weight change did not correlate with PCSK9 gene expression (r = -0.5, p = 0.08) or TNFα gene expression (r = -0.4, p = 0.1). TNFα gene expression was positively correlated with PCSK9 gene expression (r = 0.7, p = 0.001) but not correlated with LDLR expression (r = -0.3, p = 0.3). Circulating triglyceride levels were lower in RYGB compared to the SHAM group (1.1 (0.8-1.4) vs. 1.5 (1.0-4.2), p = 0.038) mmol/L with no difference in cholesterol levels. LDLR gene expression was increased post-bariatric surgery with the potential to reduce the number of circulating LDL particles. PCSK9 gene expression and TNFα gene expression were positively correlated after RYGB in ZDSD rats, suggesting that the modulation of pro-inflammatory pathways in adipose tissue after RYGB may partly relate to PCSK9 and LDLR gene expression.

Adult Male Hypogonadism: A Laboratory Medicine Perspective on Its Diagnosis and Management.

Testosterone (T), the principal androgen secreted by the testes, plays an essential role in male health. Male hypogonadism is diagnosed based on a combination of associated clinical signs and symptoms and laboratory confirmation of low circulating T levels. In this review, we have highlighted factors, both biological and analytical, that introduce variation into the measurement of serum T concentrations in men; these need to be considered when requesting T levels and interpreting results. There is an ongoing need for analytical standardisation of T assays and harmonisation of pre- and post-analytical laboratory practices, particularly in relation to the laboratory reference intervals provided to clinicians. Further, there is a need to share with service users the most up-to-date and evidence-based action thresholds for serum T as recommended in the literature. Estimation of free testosterone may be helpful. Causes of secondary hypogonadism should be considered. A comprehensive approach is required in the management of male hypogonadism, including lifestyle modification as well as medication where appropriate. The goal of treatment is the resolution of symptoms as well as the optimisation of metabolic, cardiovascular, and bone health. The advice of an endocrinologist should be sought when there is doubt about the cause and appropriate management of the hypogonadism.

Diabetes foot complications and standardized mortality rate in type 2 diabetes.

AIM: To quantify the impact of foot complications on mortality outcomes in people with type 2 diabetes (T2D), and how routinely measured factors might modulate that risk. MATERIALS AND METHODS: Data for individuals with T2D for 2010-2020, from the Salford Integrated Care Record (Salford, UK), were extracted for laboratory and clinical data, and deaths. Annual expected deaths were taken from Office of National Statistics mortality data. An index of multiple deprivation (IMD) adjusted the standardized mortality ratio (SMR_IMD). Life years lost per death (LYLD) was estimated from the difference between expected and actual deaths. RESULTS: A total of 11 806 T2D patients were included, with 5583 new diagnoses and 3921 deaths during 2010-2020. The number of expected deaths was 2135; after IMD adjustment, there were 2595 expected deaths. Therefore, excess deaths numbered 1326 (SMR_IMD 1.51). No foot complications were evident in n = 9857. This group had an SMR_IMD of 1.13 and 2.74 LYLD. In total, 2979 patients had any foot complication recorded. In this group, the SMD_IMR was 2.29; of these, 2555 (75%) had only one foot complication. Patients with a foot complication showed little difference in percentage HbA1c more than 58 mmol/mol. In multivariate analysis, for those with a foot complication and an albumin-to-creatinine ratio of more than 3 mg/mmol, the odds ratio (OR) for death was 1.93, and for an estimated glomerular filtration rate of less than 60 mL/min/1.73m2 , the OR for death was 1.92. CONCLUSIONS: Patients with T2D but without a foot complication have an SMR_IMD that is only slightly higher than that of the general population. Those diagnosed with a foot complication have a mortality risk that is double that of those without T2D.

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.

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.

First episode psychosis and weight gain a longitudinal perspective in Cheshire UK: a comparison between individuals with nonaffective versus affective psychosis.

Early weight gain following initiation of antipsychotic treatment predicts longer-term weight gain, with attendant long-term consequences including premature cardiovascular events/death. An important question is whether there is a difference in weight change over time between people with affective versus nonaffective psychosis. Here we describe the results of a real-world analysis of the BMI change in the months postdiagnosis with affective versus nonaffective psychosis. Methods: We undertook an anonymised search across one Primary Care Network in Cheshire, UK with a total population of 32 301 individuals. We reviewed the health records of anyone who had been diagnosed over a 10-year period between June 2012 and June 2022 for the first time with first episode nonaffective psychosis versus psychosis associated with depression or bipolar affective disorder (affective psychosis). Results: The overall % change in BMI was +8% in nonaffective psychosis individuals and +4% in those with a diagnosis of affective psychosis - however, the distribution was markedly skewed for nonaffective psychosis patients. Using caseness as >30% increase in BMI; affective = 4% cases and nonaffective = 13% cases, there was a three-fold difference in terms of increase in BMI. In regression analysis, the r2 linking the initial BMI to % change in BMI was 0.13 for nonaffective psychosis and 0.14 for affective psychosis. Conclusion: The differences observed here in the distribution of weight change over time between individuals with affective versus nonaffective psychosis may relate to underlying constitutional differences. The phenotypic and genetic factors underlying this difference remain to be defined.