ABSTRACT
Aim: People with type 1 or type 2 diabetes have a higher hospital admission rate following Covid-19 infection. This study aims to determine the degree to which the results of a previous study in Greater Manchester (GM) could be replicated in national-level data for England. Method(s): We focussed on the univariable regression analysis, which shows the association between admission and Covid-19 infection in people with diabetes. Modelling was conducted using logistic regression on data from the Covid-IMPACT database. Odds ratios were compared descriptively with the previous study. Result(s): In people with type 2 diabetes, factors associated with an increased risk of hospitalisation similar to the previous study were: older age, male sex, higher social deprivation, higher body mass index (BMI), higher cholesterol, lower eGFR, taking an ACE-inhibitor/ ARB, not taking metformin, and having asthma or hypertension. Patients with COPD, and those taking aspirin or clopidogrel also had increased risk, but the national data showed a greater risk (GM COPD odds ratio 1.89 [1.63-2.19] vs national 2.34 [2.28-2.40] / aspirin 1.49 [1.34-1.66] vs 1.66 [1.63-1.70] / clopidogrel 1.71 [1.47-1.98] vs 1.99 [1.94-2.04]). Similar results were observed in patients with type 1 diabetes. However, due to the increase in sample size, many factors which were previously not statistically significant have become significant, such as in type 2 diabetes BMI, low HDL-cholesterol. Conclusion(s): We have successfully replicated the methods, results and conclusions of our previous study in relation to factors associated with increased risk of hospital admission in diabetes individuals. Regional databases are suitable for large cohort studies, and in this instance produced similar results to a national database, validating our previous findings.
ABSTRACT
Aims: We have shown previously in 93 individuals with type 1 diabetes using the FreeStyle Libre flash glucose monitor that the week after their first Covid-19 vaccination, the percent 'time in target range 3.9-10mmol/ l' (%TTR) average went from 55.2%-> 52.4% (effect size -5.1%) with 58% of people recording a fall. 47 (50%) people with HbA1c < 56mmol/mol %TTR went from 69.3-> 63.5 (-8.3%) and 24 (25%) people using insulin+oral treatment 56.7%-> 50.7% (-10.1%). We have now repeated the exercise after the most recent Covid-19 vaccination. Method(s): FreeStyle Libre data and medical records of the same patients from the previous study were examined for the week before and week after their most recent Covid-19 vaccination. () in the results section show change in %TTR as % of the prior value to show effect size. TTR% results from 2 weeks before and after were also considered. Result(s): Median time between vaccines was 38 weeks IQR (37-40). After the latest vaccination average %TTR average went from 51.1%-> 49.8% (-2.5%) with a reduction found in 54% of patients. Impact on the 39 patients with HbA1c < 56mmol/mol -% TTR from 66.2%-> 61.8% (-6.5%) and the 20 (25%) patients using insulin+oral %TTR from 48.2%-> 47.1% (-2.2%). 65% of the patients whose %TTR fell previously, fell again after this vaccination. Fortnight average %TTR 53.5%-> 52.1% (-2.7%) whereas in the previous study across fortnight %TTR 55.4%-> 54.0% (-2.4%). Conclusion(s): The perturbation effect on blood glucose with 1st Covid-19 vaccination was seen again in the latest vaccination but reduced in magnitude, confirming that a significant group of type 1 diabetes individuals' glycaemic control is still being impacted by the Covid-19 vaccination.
ABSTRACT
Introduction: People with diabetes are particularly at high risk of becoming seriously unwell after contracting covid-19 infection. We do not fully understand underlying factors contributing to such risk/their respective contributions to outcomes. Methods: This population-based study included people living in the Greater Manchester conurbation with a recorded diagnosis of type 1 diabetes and type 2 diabeetes +subsequent covid-19 infection. Each individual with type 1 diabetes (n = 862)/ type 2 diabetes (n = 13,225) was matched with 3 covid-19 infected non-diabetes controls. Results: For type 1 diabetes individuals, the hospital admission rate in the first 28 days after covid-19 positive test was 10%vs4.7% in age/gender-matched controls (relative risk [RR] 2.1). For type 2 diabetes individuals, the hospital admission rate in the first 28 days after a covid-19 positive test was 16.3%vs11.6% in age/gender-matched controls(RR 1.4). Average Townsend score was higher in type 2 diabetes (1.8) vs matched controls(0.4), with a higher proportion of type 2 diabetes people in the top 2 quintiles of greatest disadvantage(p < 0.001). Within the group of covid-19 infected type 1 diabetes affected individuals, factors influencing the likelihood of admission included;age/body mass index (BMI)/ hypertension/ HbA1c/low HDL-cholesterol/ lower estimated glomerular filtration rate(eGFR)/COPD/being of African/ mixed ethnicity. In covid-19 infected type 2 diabetes individuals, factors potentially related to a higher admission rate included;age/Townsend Index/co-morbidity with COPD/asthma and severe mental illness(SMI)+lower eGFR. Metformin prescription lowered the admission likelihood. Conclusion: In a UK population, we have confirmed significantly higher likelihood of admission in people with diabetes following covid-19 infection. Several factors mediate the increased likelihood of hospital admission including metformin. For type 2 diabetes, the majority of factors related to increased admission rate are common to the general population but more prevalent in type 2 diabetes.
ABSTRACT
Introduction: Frequency of HbA1c testing links to outcome in terms of HbA1c control in diabetes. The influence of the variability of test-retest interval on HbA1c change needs to be determined. Methods: HbA1c results were collected from laboratory records on 3,872 people: HbA1c results at baseline and 5 years( ± 3 months) later with at least 6-tests during this period. We calculated the standard deviation (SD) of test interval for each individual. We then examined the link between deciles of SD of test interval/HbA1c level, stratified by baseline HbA1c. Results: In general, less variability in testing frequency = more consistent monitoring associated with better diabetes control over a 5-year period. This was most evident with moderately raised baseline HbA1c levels(54-75mmol/ mol[7.0-9.0%]). For example, in those with a starting HbA1c of 54-58mmol/ mol[7.0-7.5%], the lowest SDdecile associated with little change in HbA1c over 5 years, while for the highest SDdecile, HbA1c rose by 4-6mmol/ mol[0.4-0.6%], (p < 0.0001, standard beta 0.09-0.10). Multivariate analysis showed that the association was independent of age/sex/hospital site. Stratification by age suggested that the effect was most pronounced in those aged <65 years with baseline HbA1c 54-58mmol/ mol[7.0- 7.5%] (p < 0.0001, standard beta = 0.12). We also observed a 6.7-fold variation in the proportion of people in the top three SDdeciles across general practices. Conclusion/Interpretation: These findings indicate that consistency of testing interval, not just numbers of tests/year, is important in maintaining diabetes control, especially in those with moderately raised HbA1c. This suggests the need for developing systems to improve the regularity of HbA1c testing, especially given the recent impact of covid-19 on diabetes monitoring.
ABSTRACT
Introduction: In this study we set out to determine the relative likelihood of death following covid-19 infection in people with type 2 diabetes when compared to those without type 2 diabetes. Methods: Analysis of digital health record data was performed relating to people living in the Greater Manchester conurbation (population 2.82 million) who had a recorded diagnosis of type 2 diabetes and subsequent covid-19 confirmed infection. Each individual with type 2 diabetes (n = 13,807) was matched with three covid-19 infected non-diabetes controls (n = 39583). Results: For type 2 diabetes individuals, their mortality rate after a covid-19 positive test was 7.7% vs 6.0% in matched controls;the relative risk (RR) of death was 1.28. From univariate analysis performed within type 2 diabetes individuals, likelihood of death following covid-19 recorded infection was lower in people taking metformin, sodium glucose cotransporter-inhibitor 2(SGLT-2i) or glucagon-like peptide-1( GLP-1) agonist. A lower estimated glomerular filtration rate (eGFR) was associated with a higher mortality rate, as was hypertension history. Likelihood of death following covid-19 infection was also higher in those people with diagnosis of COPD/severe enduring mental illness, and in people taking aspirin/ clopidogrel/insulin. Smoking in people with type 2 diabetes significantly increased mortality rate. In combined analysis of type 2 diabetes patients/controls, multiple regression modelling indicated that factors independently relating to higher likelihood of death (accounting for 26% of variance) were: type 2 diabetes/age/ malegender/social deprivation (higher Townsend index). Conclusion: Following confirmed infection with covid- 19 a number of factors are associated with mortality in type 2 diabetes individuals. Prescription of metformin, SGLT-2is or GLP-1 agonists + non-smoking status associated with reduced risk of death for people with type 2 diabetes. Age/male sex/social disadvantage associated with an increased risk of death.