Virulence-associated genes in faecal and clinical Escherichia coli isolates cultured from broiler chickens in Australia.

A healthy chicken's intestinal flora harbours a rich reservoir of Escherichia coli as part of the commensal microbiota. However, some strains, known as avian pathogenic E. coli (APEC), carry specific virulence genes (VGs) that enable them to invade and cause extraintestinal infections such as avian colibacillosis. Although several VG combinations have been identified, the pathogenic mechanisms associated with APEC are ill-defined. The current study screened a subset of 88 E. coli isolates selected from 237 pre-existing isolates obtained from commercial poultry flocks in Australia. The 88 isolates were selected based on their enterobacterial repetitive intergenic consensus (ERIC) and antimicrobial resistance (AMR) profiles and included 29 E. coli isolates cultured from chickens with colibacillosis (referred to as clinical E. coli or CEC) and 59 faecal E. coli (FEC) isolates cultured from clinically healthy chickens. The isolates were screened for the presence of 35 previously reported VGs. Of these, 34 were identified, with iucA not being detected. VGs focG, hlyA and sfa/foc were only detected in FEC isolates. Eight VGs had a prevalence of 90% or above in the CEC isolates. Specifically, astA (100%); feoB (96.6%); iutA, iss, ompT, iroN and hlyF (all 93.1%); and vat (89.7%). The prevalence of these were significantly lower in FEC isolates (astA 79.7%, feoB 77.9%, iutA 52.5%, iss 45.8%, ompT 50.9%, iroN 37.3%, hlyF 50.9% and vat 42.4%). The odds ratios that each of these eight VGs were more likely to be associated with CEC than FEC ranged from 7.8 to 21.9. These eight VGs may be used to better define APEC and diagnostically detect APEC in Australia. Further investigations are needed to identify the roles of these VGs in pathogenicity.

Antimicrobial susceptibility patterns of aerobic bacteria isolated from canine urinary samples in South East Queensland, 2013 to 2018.

Urinary tract infections are a common diagnosis in dogs presenting to veterinary practice. Veterinarians often treat suspected infections empirically, either in the absence of culture and susceptibility testing results or whilst waiting for them. This study aimed to identify the bacteria most frequently isolated from canine urinary samples and their antimicrobial susceptibility patterns in South East Queensland (SEQ) to help guide responsible empirical antimicrobial prescription by the veterinary community in this geographical location. Cumulative antibiograms were generated from the results of 1284 culture-positive urinary samples in SEQ, obtained from a commercial veterinary laboratory over a 5-year period. Escherichia coli was the most commonly isolated bacterial species (43%), followed by Staphylococcus spp. (23%), Proteus spp. (21%) and Enterococcus spp. (10%). Of the six most common isolates, 97% had susceptibility to at least one low-importance antimicrobial. Susceptibility to the low-importance and first-line antimicrobial recommendation, amoxicillin, was 81% for E. coli and 24% for Staphylococcus spp. Susceptibility of both E. coli and Staphylococcus spp. to medium-importance and commonly recommended empirical antimicrobials, trimethoprim sulphonamides and amoxicillin-clavulanic acid was ≥85% and >92% for high-importance antimicrobials enrofloxacin and ceftiofur. Of the E. coli and Staphylococcus spp. isolates, 8.8% and 4%, respectively, were considered multidrug resistant. There was no increase in resistance to antimicrobials detected over the study period. Susceptibilities suggest low- and medium-importance antimicrobials remain acceptable first-line empirical treatments. However, this should be continually assessed and updated using local surveillance data.

Understanding barriers to reducing antimicrobials on Australian dairy farms: A qualitative analysis.

INTRODUCTION: Reducing antibiotic use in production animal systems is one strategy which may help to limit the development of antimicrobial resistance. To reduce antimicrobial use in food-producing animals, it is important to first understand how antibiotics are used on farm and what barriers exist to decreasing their use. In dairy production systems, mastitis is one of the most common reasons for administering antimicrobials. Therefore, it is important to understand the motivations and behaviours of dairy farmers in relation to the diagnosis, treatment and prevention of mastitis. MATERIALS AND METHODS: In this study, we interviewed a sample of dairy farmers and dairy industry professionals from the major dairying regions of eastern Australia regarding their current practices used to diagnose, treat, and control subclinical and clinical mastitis. Inductive thematic analysis was used to code interview transcripts and identify the recurrent themes. RESULTS: Four overarching themes were identified: (1) the challenges associated with the detection and diagnosis of clinical mastitis, including with laboratory culture, (2) the motivations behind treatment decisions for different cases, (3) decisions around dry cow therapy and the role of herd recording, and (4) concerns regarding the development of antimicrobial resistance. DISCUSSION: This study identifies several challenges which may limit the ability of Australian dairy farmers to reduce antimicrobial use on farm, such as the need for rapid and reliable diagnostic tests capable of identifying the pathogenic causes of mastitis and the difficulties associated with conducting herd recording for the implementation of selective dry cow therapy. Industry professionals were concerned that farmers were not using individual cow records to aid in treatment decisions, which could result in unnecessary antimicrobial use. The results of this study can act as the basis for future research aimed at assessing these issues across the broader Australian dairy industry.

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.

A Longitudinal Clinical Trajectory Analysis Examining the Accumulation of Co-morbidity in People with Type 2 Diabetes (T2D) Compared with Non-T2D Individuals.

BACKGROUND: Type 2 diabetes mellitus (T2D) is commonly associated with an increasing complexity of multimorbidity. While some progress has been made in identifying genetic and non-genetic risk factors for T2D, understanding the longitudinal clinical history of individuals before/after T2D diagnosis may provide additional insights. METHODS: In this study, we utilised longitudinal data from the DARE (Diabetes Alliance for Research in England) study to examine the trajectory of clinical conditions in individuals with and without T2D. Data from 1932 individuals (T2D n = 1196 vs. matched non-T2D controls n = 736) were extracted and subjected to trajectory analysis over a period of up to 50 years (25 years pre-diagnosis/25 years post-diagnosis). We also analysed the cumulative proportion of people with diagnosed coronary artery disease (CAD) in their general practice (GP) record with an analysis of lower respiratory tract infection (RTI) as a comparator group. RESULTS: The mean age of diagnosis of T2D was 52.6 (95% confidence interval 52.0-53.4) years. In the years leading up to T2D diagnosis, individuals who eventually received a T2D diagnosis consistently exhibited a considerable increase in several clinical phenotypes. Additionally, immediately prior to T2D diagnosis, a significantly greater prevalence of hypertension (35%)/RTI (34%)/heart conditions (17%)/eye, nose, throat infection (19%) and asthma (12%) were observed. The corresponding trajectory of each of these conditions was much less dramatic in the matched controls. Post-T2D diagnosis, proportions of T2D individuals exhibiting hypertension/chronic kidney disease/retinopathy/infections climbed rapidly before plateauing. At the last follow-up by quintile of disadvantage, the proportion (%) of people with diagnosed CAD was 6.4% for quintile 1 (least disadvantaged) and 11% for quintile 5 (F = 3.4, p = 0.01 for the difference between quintiles). CONCLUSION: These findings provide novel insights into the onset/natural progression of T2D, suggesting an early phase of inflammation-related disease activity before any clinical diagnosis of T2D is made. Measures that reduce social inequality have the potential in the longer term to reduce the social gradient in health outcomes reported here.

Developing flexible models for genetic evaluations in smallholder crossbred dairy farms.

The productivity of smallholder dairy farms is very low in developing countries. Important genetic gains could be realized using genomic selection, but genetic evaluations need to be tailored for lack of pedigree information and very small farm sizes. To accommodate this situation, we propose a flexible Bayesian model for the genetic evaluation of milk yield, which allows us to simultaneously account for nongenetic random effects for farms and varying SNP variance (BayesR model). First, we used simulations based on real genotype data from Indian crossbred dairy cattle to demonstrate that the proposed model can separate the true genetic and nongenetic parameters even for small farm sizes (2 cows on average) although with high standard errors in scenarios with low heritability. The accuracy of genomic genetic evaluation increased until farm size was approximately 5. We then applied the model to real data from 4,655 crossbred cows with 106,109 monthly test day milk records and 689,750 autosomal SNPs. We estimated a heritability of 0.16 (0.04) for milk yield and using cross-validation, a genomic estimated breeding value (GEBV) accuracy of 0.45 and bias (regression of phenotype on GEBV) of 1.04 (0.26). Estimated genetic parameters were very similar using BayesR, BayesC, and genomic BLUP approaches. Candidate genes near the top variants, IMMP2L and ARHGEF2, have been previously associated with milk protein composition, mastitis resistance, and milk cholesterol content. The estimated heritability and GEBV accuracy for milk yield are much lower than those from intensive or pasture-based systems in many countries. Further increases in the number of phenotyped and genotyped animals in farms with at least 2 cows (preferably 3-5, to allow for dropout of cows) are needed to improve the estimation of genetic effects in these smallholder dairy farms.

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.

Non-theatre emergency airway management: a multicentre prospective observational study.

Emergency airway management events are common, unpredictable and associated with high complication rates. This multicentre prospective observational study across eight acute NHS hospitals in southeast England reports the incidence and nature of non-theatre emergency airway management events. Data were collected from non-theatre emergency airway management, including adverse events, over a continuous 28-day window, and recorded on an electronic case report form. Events were classified according to type (advanced airway; simple airway; and cardiac arrest). A total of 166 events were recorded, with 111 advanced airway events involving tracheal intubation or tracheostomy management. Senior personnel with three or more years of airway management experience were present for 105/111 (95%) advanced airway management episodes. There was a significant reduction in consultant or equivalent presence out-of-hours (21/64, 33%) vs. in-hours (34/47, 72%) (p < 0.001). We found high utilisation of videolaryngoscopy (95/106, 90%) and universal use of capnography for all advanced airway management events. This was lower during cardiac arrest when videolaryngoscopy was used in 11/16 (69%) of tracheal intubations and capnography in 21/32 (66%) of all cardiac arrest episodes. Adverse outcomes during advanced airway management (excluding during cardiac arrest) occurred in 53/111 (48%) episodes, including hypoxia (desaturation to Sp O2 < 80% in 14/111, 13%) and hypotension (systolic blood pressure < 80 mmHg in 27/111, 25%). Adverse outcomes were not associated with time of day or experience level of airway practitioners. We conclude that there is a disparity between consultant presence for advanced airway interventions in- and out-of-hours; high utilisation of videolaryngoscopy and capnography, especially for advanced airway interventions; and a high incidence of hypotension and hypoxaemia, including critical values, during non-theatre airway management.

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.

A study to investigate genetic factors associated with weight gain in people with diabetes: analysis of polymorphisms in four relevant genes.

BACKGROUND: Weight change is often seen in people with diabetes. We investigated the effects of genes associated with weight change/glucose handling/insulin-signalling. MATERIALS/METHODS: DNA from diabetes individuals and non-diabetes individuals, plus clinical data, were available from the DARE study (n = 379 individuals: T1D n = 111; T2D n = 222; controls n = 46). Weight gain was assessed by temporal change of Body Mass Index (BMI). Genotyping was performed for CAV1rs926198, LEPRrs1137101, BDNFrs6265 and FTOrs9939609. RESULTS: No differences in genotype distributions were observed for the four SNPs in all groups un-stratified by weight gain. Following stratification differences in genotype distribution were observed. For those BMI relatively stable; controls showed a difference in genotype distributions versus T1D (CAV1rs926198, LEPRrs1137101). In T2D vs controls, significant differences were observed in genotype distribution for all four genes. For BMI increase, the only difference by category was LEPRrs1137101 (bothT1D/T2D vs controls). In BMI-stable groups, CAV1rs926198, T1D individuals showed lower T allele frequency (p=0.004) vs non-diabetes and for LEPRrs1137101 a higher G allele frequency versus controls (p=0.002). For T2D, CAV1rs926198, T allele frequency was lower in T2D than controls (p=0.005). For LEPR rs1137101, the G allele frequency was higher than in controls (p=0.004). In those with BMI increase, LEPRrs1137101 T1D individuals had higher G allele frequency versus controls (p=0.002) as did T2D vs controls (p=0.03). CONCLUSION: Differences in allele frequency were seen between diabetes individuals and non-diabetes diagnosed at baseline in relation to the likelihood of BMI increase of >10%. It is established that the G allele of LEPRrs1137101 is associated with weight gain/obesity. However, this is the first report of CAV1rs926198 polymorphism being associated with weight stability/gain in diabetes.

Inclusion4EU: Co-Designing a Framework for Inclusive Software Design and Development.

Digital technology is now pervasive, however, not all groups have uniformly benefitted from technological changes and some groups have been left behind or digitally excluded. Comprehensive data from the 2017 Current Population Survey shows that older people and persons with disabilities still lag behind in computer and internet access. Furthermore unique ethical, privacy and safety implications exist for the use of technology for older persons and people with disabilities and careful reflection is required to incorporate these aspects, which are not always part of a traditional software lifecycle. In this paper we present the Inclusion4EU project that aims to co-design a new framework, guidelines and checklists for inclusive software design and development with end-users from excluded categories, academics with expertise in human-computer interaction and industry practitioners from software engineering.

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.

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.

A study protocol for a double-blind randomised placebo-controlled trial evaluating the efficacy of carrageenan nasal and throat spray for COVID-19 prophylaxis-ICE-COVID.

INTRODUCTION: At present, vaccines form the only mode of prophylaxis against COVID-19. The time needed to achieve mass global vaccination and the emergence of new variants warrants continued research into other COVID-19 prevention strategies. The severity of COVID-19 infection is thought to be associated with the initial viral load, and for infection to occur, viruses including SARS-CoV-2 must first penetrate the respiratory mucus and attach to the host cell surface receptors. Carrageenan, a sulphated polysaccharide extracted from red edible seaweed, has shown efficacy against a wide range of viruses in clinical trials through the prevention of viral entry into respiratory host cells. Carrageenan has also demonstrated in vitro activity against SARS-CoV-2. METHODS AND ANALYSIS: A single-centre, randomised, double-blinded, placebo-controlled phase III trial was designed. Participants randomised in a 1:1 allocation to either the treatment arm, verum Coldamaris plus (1.2 mg iota-carrageenan (Carragelose®), 0.4 mg kappa-carrageenan, 0.5% sodium chloride and purified water), or placebo arm, Coldamaris sine (0.5% sodium chloride) spray applied daily to their nose and throat for 8 weeks, while completing a daily symptom tracker questionnaire for a total of 10 weeks. PRIMARY OUTCOME: Acquisition of COVID-19 infection as confirmed by a positive PCR swab taken at symptom onset or seroconversion during the study. Secondary outcomes include symptom type, severity and duration, subsequent familial/household COVID-19 infection and infection with non-COVID-19 upper respiratory tract infections. A within-trial economic evaluation will be undertaken, with effects expressed as quality-adjusted life years. DISCUSSION: This is a single-centre, phase III, double-blind, randomised placebo-controlled clinical trial to assess whether carrageenan nasal and throat spray reduces the risk of development and severity of COVID-19. If proven effective, the self-administered prophylactic spray would have wider utility for key workers and the general population. TRIAL REGISTRATION: NCT04590365; ClinicalTrials.gov NCT04590365. Registered on 19 October 2020.

Distress and Living with Diabetes: Defining Characteristics Through an Online Survey.

INTRODUCTION: There is considerable evidence for diabetes reducing quality of life. The impact of such a diagnosis on mental health is less well understood and was subsequently explored here. METHODS: Online PHQ-9 scores (which calculate the severity of depression), Diabetes Distress Screening Scale (DDSS) and EQ-5D-5L (quality-of-life) questionnaires were completed by patients with diabetes, followed by the extraction of data where possible from responders' clinical records. RESULTS: A total of 133 people submitted questionnaires. However, not all data items could be completed by each patient; 35% (45/130) had type I diabetes mellitus (T1DM); 55% (64/117) were women. The overall median age of 117 responders was 60 (IQR 50-68 years). The median aggregated response scores were: EQ-5D-5L 0.74 (IQR 0.64-0.85) (lower quality of life than UK population median of 0.83), DDSS 1.9 (IQR1.3-2.7) (≥ 2 indicates moderate distress) and PHQ-9 5 (IQR2-11) (≥ 5 indicates depression). Higher diabetes distress (DDSS)/lower quality of life EQ-5D-5L/higher depressive symptoms (PHQ-9) linked to female sex (DDSS 0.5/25% above median), younger age (< 50 years DDSS 0.7/35% above median), fewer years after diagnosis (< 10 years DDSS 0.8/40% above median), and obesity (BMI > 35 DDSS 0.6/30% above median). Additionally, a HbA1c reading of ≤ 48 mmol/mol was associated with higher DDSS scores, as did a reduction of more than 5 mmol/mol in HbA1c over the last three HbA1c measurements. The 30 individuals with a history of prescribed antidepressant medication also showed higher diabetes distress scores (DDSS 0.9, equating to 45% above the median). The DDSS score elevation came from an increase in emotional burden and regimen-related distress. DDSS scores were not significantly linked to diabetes type, insulin use, absolute level/change in blood glucose HbA1c. Physician-related distress showed a similar pattern. CONCLUSIONS: A low level of stress in relation to diabetes management may be associated with lower HbA1c. The larger impact of diabetes on mental health in younger women/people with shorter diabetes duration should be noted when considering psychosocial intervention/behavior change messaging. Physician-related distress is a potentially remediable factor. However, this sample was self-selecting, limiting generalization to other samples.