Diabetes and the COVID-19 pandemic.

Almost immediately after the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus emerged, it was evident that people with chronic diseases, including diabetes, were disproportionately affected, with an increased risk of hospitalisation and mortality. Over the ensuing 2 years, the indirect effects of the pandemic on healthcare delivery in the short term have become prominent, along with the lingering effects of the virus in those directly infected. In the wake of the pandemic and without any evidence from high quality studies, a number of national and international consensus recommendations were published, which were subsequently rapidly updated based on observational studies. There have been unprecedented disruptions from both direct and indirect impacts of coronavirus disease-2019 (COVID-19) in people with diabetes. In this review, we summarise the impact of acute COVID-19 in people with diabetes, discuss how the presentation and epidemiology during the pandemic, including presentation of diabetic ketoacidosis and new-onset diabetes, has changed, and we consider the wider impact of the pandemic on patients and healthcare service delivery, including some of the areas of uncertainty. Finally, we make recommendations on prioritising patients as we move into the recovery phase and also how we protect people with diabetes for the future, as COVID-19 is likely to become endemic.

Effectiveness of digital and remote provision of the Healthier You: NHS Diabetes Prevention Programme during the COVID-19 pandemic.

AIMS: To assess weight change in the Healthier You: NHS Diabetes Prevention Programme (NHS DPP) delivered via video conferencing (remote) sessions or delivered via specific digital interventions through apps or websites, during the COVID-19 pandemic compared to group-based face-to-face interventions, pre-pandemic. METHODS: Prospectively collected national service-level data relating to individuals with non-diabetic hyperglycaemia (HbA1c 42-47 mmol/mol (6.0%-6.4%) or fasting plasma glucose 5.5-6.9 mmol/L) referred to the NHS DPP from June 2016 to March 2022. RESULTS: Between March 2020 and March 2022, 335,961 people were referred to the programme and were offered a choice of remote or digital intervention. This was preceded by 556,793 people referred to the face-to-face programme between June 2016 and February 2022. Uptakes to intervention sessions were 47% for those offered a choice and 39% for face-to-face. Remote and digital participants were significantly younger (60 and 56 vs. 65 years) and heavier (86.1 kg and 91.0 kg vs. 84.1 kg) compared to face-to-face. Weight change was assessed for 42,407 remote, 7699 digital and 97,205 face-to-face participants with sufficient time to have finished the programme and no missing data. Mean weight losses for participants attending at least one intervention session were: 2.40 (2.36-2.44) kg, 2.59 (2.49-2.68) kg and 2.01 (1.98-2.04) kg for remote, digital and face-to-face participants respectively. Corresponding mean weight losses for those who completed the programme were: 3.24 (3.19-3.30) kg, 4.76 (4.60-4.92) kg and 3.04 (3.00-3.07) kg. There were no significant differences in weight change between interventions by ethnicity and deprivation. CONCLUSIONS: Weight losses achieved through remote and digital interventions were greater than those previously achieved through face-to-face interventions, without evidence of exacerbation of health inequalities.

Comparative Incidence of Diabetes Following Hospital Admission for COVID-19 and Pneumonia: A Cohort Study.

OBJECTIVE: The incidence of diabetes may be elevated following coronavirus disease 2019 (COVID-19), but it is unclear whether this is specific to severe acute respiratory syndrome coronavirus 2 infection, associated with shared risk factors for severe COVID-19 and diabetes, and/or a generic risk following illness. RESEARCH DESIGN AND METHODS: People admitted to the hospital for COVID-19 and/or pneumonia between 1 April 2020 and 31 August 2020 in England were linked with the National Diabetes Audit to identify incident diabetes after discharge up to 31 March 2021. Comparator cohorts admitted with pneumonia over the same dates in 2017, 2018, and 2019 were followed until 31 March 2018, 31 March 2019, and 31 March 2020, respectively. Poisson regression models were used to calculate adjusted diabetes incidence rates. RESULTS: Using the cohort of people discharged from the hospital following a diagnosis of COVID-19 without pneumonia in 2020 as the standard population (incidence rate 16.4 [95% CI 12.8-20.7] per 1,000 person-years), adjusting for age, sex, ethnicity, and deprivation, gave incidence rates of 19.0 (95% CI 13.8-25.6) and 16.6 (95% CI 13.3-20.4) per 1,000 person-years for those admitted for COVID-19 with pneumonia and pneumonia without COVID-19, respectively, in 2020. These rates are not significantly different from those found after hospital admission for pneumonia in 2019, 2018, and 2017, at 13.7 (95% CI 10.8-17.3), 13.8 (95% CI 10.9-17.4), and 14.2 (95% CI 10.9-18.3) per 1,000 person-years, respectively. CONCLUSIONS: Our data do not support a clear impact of COVID-19 on the incidence of diabetes compared with risks in several comparator groups, including contemporaneously assessed risks in people hospitalized with pneumonia.

The impact of the COVID-19 pandemic on diabetes services: planning for a global recovery.

The COVID-19 pandemic has disproportionately affected certain groups, such as older people (ie, >65 years), minority ethnic populations, and people with specific chronic conditions including diabetes, cardiovascular disease, kidney disease, and some respiratory diseases. There is now evidence of not only direct but also indirect adverse effects of COVID-19 in people with diabetes. Recurrent lockdowns and public health measures throughout the pandemic have restricted access to routine diabetes care, limiting new diagnoses, and affecting self-management, routine follow-ups, and access to medications, as well as affecting lifestyle behaviours and emotional wellbeing globally. Pre-pandemic studies have shown that short-term delays in delivery of routine care, even by 12 months, are associated with adverse effects on risk factor control and worse microvascular, macrovascular, and mortality outcomes in people with diabetes. Disruptions within the short-to-medium term due to natural disasters also result in worse diabetes outcomes. However, the true magnitude of the indirect effects of the COVID-19 pandemic on long-term outcomes and mortality in people with diabetes is still unclear. Disasters tend to exacerbate existing health disparities; as we recover ambulatory diabetes services in the aftermath of the pandemic, there is an opportunity to prioritise those with the greatest need, and to target resources and interventions aimed at improving outcomes and reducing inequality.

Associations between reductions in routine care delivery and non-COVID-19-related mortality in people with diabetes in England during the COVID-19 pandemic: a population-based parallel cohort study.

BACKGROUND: The Office for Health Improvement and Disparities, part of the UK Government Department of Health and Social Care, highlighted an emerging signal of increased non-COVID-19-related deaths in England between July and October, 2021, with a potentially disproportionate higher increase in people with diabetes. We aimed to substantiate and quantify this apparent excess mortality, and to investigate the association between diabetes routine care delivery and non-COVID-19-related-mortality in people with diabetes before and after the onset of the pandemic. METHODS: In this population-based parallel cohort study, we used the National Diabetes Audit (NDA) to identify people with diabetes in England. The primary outcome was non-COVID-19-related deaths between July 3, 2021, and Oct 15, 2021, in participants in the 2021 COVID-19 cohort (registered in the NDA in the periods Jan 1, 2019, to March 31, 2020, and Jan 1, 2020, to March 31, 2021) compared with deaths between June 29, 2019, and Oct 11, 2019 (the equivalent 15-week period in 2019) in the 2019 pre-COVID-19 comparator cohort (people registered in the NDA in the periods Jan 1, 2017, to March 31, 2018, and Jan 1, 2018 to March 31, 2019). In each cohort, multivariable logistic regression examined whether completion of eight diabetes care processes in each of the two years before the index mortality year was associated with non-COVID-19-related death, adjusting for diabetes type, age, sex, ethnicity, and socioeconomic deprivation. FINDINGS: There were 3 218 570 people in the 2021 cohort and 2 973 645 people in the 2019 comparator cohort. In the 2021 cohort, there were 30 118 non-COVID-19-related deaths in people with diabetes, compared with 27 132 in the comparator cohort, representing an 11% increase (95% CI 9-13). The unadjusted incidence rate ratio (IRR) for mortality in the 2021 cohort compared to the 2019 cohort was 1·026 (1·009-1·043; p=0·003), which was unchanged after adjustment for age, sex, ethnicity, socioeconomic deprivation, and diabetes type (IRR 1·023 (1·006-1·040); p=0·007). In the 2021 cohort, 853 660 (26·5%) people received all eight care processes in 2020-21 compared with 1 547 240 (48·1%) people in 2019-20; a 44·8% (95% CI 44·7-45·0) relative reduction. In the pre-COVID-19 comparator cohort, 1 370 315 (46·1%) people with diabetes received all eight care processes in 2018-19 compared with 1 437 740 (48·3%) in 2017-18; a 4·7% (95% CI 4·5-4·9) relative decrease. Non-COVID-19-related mortality in the 2021 cohort was highest in people who did not receive all eight care processes in either of the two previous years (OR 2·67 [95% CI 2·56-2·77]; p<0·001) compared with those who received all eight care processes in both previous years. Mortality was also significantly higher in those who received all eight care processes in 2019-20 but not in 2020-21 (OR 1·66 [95% CI 1·59-1·73]; p<0·001) or not in 2019-20 but in 2020-21 (OR 1·27 [1·20-1·35]; p<0·001). This pattern of association was similar in the 2019 pre-COVID-19 cohort. INTERPRETATION: Our results show an increased risk of mortality in those who did not receive all eight care processes in one or both of the previous two years. Our results provide evidence that the increased rate of non-COVID-19-related mortality in people with diabetes in England observed between July 3, and Oct 15 of 2021 is associated with a reduction in completion of routine diabetes care processes following the pandemic onset in 2020. FUNDING: None.

Temporal trends in emergency admissions for diabetic ketoacidosis in people with diabetes in England before and during the COVID-19 pandemic: a population-based study.

BACKGROUND: Diabetic ketoacidosis (DKA) has been reported to be increasing in frequency during the COVID-19 pandemic. We aimed to examine the rates of DKA hospital admissions and the patient demographics associated with DKA during the pandemic compared with in prepandemic years. METHODS: Using a comprehensive, multiethnic, national dataset, the Secondary Uses Service repository, we extracted all emergency hospital admissions in England coded with DKA from March 1 to June 30, 2020 (first wave of the pandemic), July 1 to Oct 31, 2020 (post-first wave), and Nov 1, 2020, to Feb 28, 2021 (second wave), and compared these with DKA admissions in the equivalent periods in 2017-20. We also examined baseline characteristics, mortality, and trends in patients who were admitted with DKA. FINDINGS: There were 8553 admissions coded with DKA during the first wave, 8729 during the post-first wave, and 10 235 during the second wave. Compared with preceding years, DKA admissions were 6% (95% CI 4-9; p<0·0001) higher in the first wave of the pandemic (from n=8048), 6% (3-8; p<0·0001) higher in the post-first wave (from n=8260), and 7% (4-9; p<0·0001) higher in the second wave (from n=9610). In the first wave, DKA admissions reduced by 19% (95% CI 16-21) in those with pre-existing type 1 diabetes (from n=4965 to n=4041), increased by 41% (35-47) in those with pre-existing type 2 diabetes (from n=2010 to n=2831), and increased by 57% (48-66) in those with newly diagnosed diabetes (from n=1072 to n=1681). Compared with prepandemic, type 2 diabetes DKA admissions were similarly common in older individuals and men but were higher in those of non-White ethnicities during the first wave. The increase in newly diagnosed DKA admissions occurred across all age groups and these were significantly increased in men and people of non-White ethnicities. In the post-first wave, DKA admissions did not return to the baseline level of previous years; DKA admissions were 14% (11-17) lower in patients with type 1 diabetes (from n=5208 prepandemic to n=4491), 30% (24-36) higher in patients with type 2 diabetes (from n=2011 to n=2613), and 56% (47-66) higher in patients with newly diagnosed diabetes (from n=1041 to n=1625). During the second wave, DKA admissions were 25% (22-27) lower in patients with type 1 diabetes (from n=5769 prepandemic to n=4337), 50% (44-56) higher in patients with type 2 diabetes (from n=2608 to n=3912), and 61% (52-70) higher in patients with newly diagnosed diabetes (from n=1234 to n=1986). INTERPRETATION: Our results provide evidence for differences in the numbers and characteristics of people presenting with DKA during the COVID-19 pandemic compared with in the preceding 3 years. Greater awareness of risk factors for DKA in type 2 diabetes and vigilance for newly diagnosed diabetes presenting with DKA during the COVID-19 pandemic might help mitigate the increased impact of DKA. FUNDING: None.

Prescription of glucose-lowering therapies and risk of COVID-19 mortality in people with type 2 diabetes: a nationwide observational study in England.

BACKGROUND: In patients with type 2 diabetes, hyperglycaemia is an independent risk factor for COVID-19-related mortality. Associations between pre-infection prescription for glucose-lowering drugs and COVID-19-related mortality in people with type 2 diabetes have been postulated but only investigated in small studies and limited to a few agents. We investigated whether there are associations between prescription of different classes of glucose-lowering drugs and risk of COVID-19-related mortality in people with type 2 diabetes. METHODS: This was a nationwide observational cohort study done with data from the National Diabetes Audit for people with type 2 diabetes and registered with a general practice in England since 2003. Cox regression was used to estimate the hazard ratio (HR) of COVID-19-related mortality in people prescribed each class of glucose-lowering drug, with covariate adjustment with a propensity score to address confounding by demographic, socioeconomic, and clinical factors. FINDINGS: Among the 2 851 465 people with type 2 diabetes included in our analyses, 13 479 (0·5%) COVID-19-related deaths occurred during the study period (Feb 16 to Aug 31, 2020), corresponding to a rate of 8·9 per 1000 person-years (95% CI 8·7-9·0). The adjusted HR associated with recorded versus no recorded prescription was 0·77 (95% CI 0·73-0·81) for metformin and 1·42 (1·35-1·49) for insulin. Adjusted HRs for prescription of other individual classes of glucose-lowering treatment were as follows: 0·75 (0·48-1·17) for meglitinides, 0·82 (0·74-0·91) for SGLT2 inhibitors, 0·94 (0·82-1·07) for thiazolidinediones, 0·94 (0·89-0·99) for sulfonylureas, 0·94 (0·83-1·07) for GLP-1 receptor agonists, 1·07 (1·01-1·13) for DPP-4 inhibitors, and 1·26 (0·76-2·09) for α-glucosidase inhibitors. INTERPRETATION: Our results provide evidence of associations between prescription of some glucose-lowering drugs and COVID-19-related mortality, although the differences in risk are small and these findings are likely to be due to confounding by indication, in view of the use of different drug classes at different stages of type 2 diabetes disease progression. In the context of the COVID-19 pandemic, there is no clear indication to change prescribing of glucose-lowering drugs in people with type 2 diabetes. FUNDING: None.

Risk prediction of covid-19 related death and hospital admission in adults after covid-19 vaccination: national prospective cohort study.

OBJECTIVES: To derive and validate risk prediction algorithms to estimate the risk of covid-19 related mortality and hospital admission in UK adults after one or two doses of covid-19 vaccination. DESIGN: Prospective, population based cohort study using the QResearch database linked to data on covid-19 vaccination, SARS-CoV-2 results, hospital admissions, systemic anticancer treatment, radiotherapy, and the national death and cancer registries. SETTINGS: Adults aged 19-100 years with one or two doses of covid-19 vaccination between 8 December 2020 and 15 June 2021. MAIN OUTCOME MEASURES: Primary outcome was covid-19 related death. Secondary outcome was covid-19 related hospital admission. Outcomes were assessed from 14 days after each vaccination dose. Models were fitted in the derivation cohort to derive risk equations using a range of predictor variables. Performance was evaluated in a separate validation cohort of general practices. RESULTS: Of 6 952 440 vaccinated patients in the derivation cohort, 5 150 310 (74.1%) had two vaccine doses. Of 2031 covid-19 deaths and 1929 covid-19 hospital admissions, 81 deaths (4.0%) and 71 admissions (3.7%) occurred 14 days or more after the second vaccine dose. The risk algorithms included age, sex, ethnic origin, deprivation, body mass index, a range of comorbidities, and SARS-CoV-2 infection rate. Incidence of covid-19 mortality increased with age and deprivation, male sex, and Indian and Pakistani ethnic origin. Cause specific hazard ratios were highest for patients with Down's syndrome (12.7-fold increase), kidney transplantation (8.1-fold), sickle cell disease (7.7-fold), care home residency (4.1-fold), chemotherapy (4.3-fold), HIV/AIDS (3.3-fold), liver cirrhosis (3.0-fold), neurological conditions (2.6-fold), recent bone marrow transplantation or a solid organ transplantation ever (2.5-fold), dementia (2.2-fold), and Parkinson's disease (2.2-fold). Other conditions with increased risk (ranging from 1.2-fold to 2.0-fold increases) included chronic kidney disease, blood cancer, epilepsy, chronic obstructive pulmonary disease, coronary heart disease, stroke, atrial fibrillation, heart failure, thromboembolism, peripheral vascular disease, and type 2 diabetes. A similar pattern of associations was seen for covid-19 related hospital admissions. No evidence indicated that associations differed after the second dose, although absolute risks were reduced. The risk algorithm explained 74.1% (95% confidence interval 71.1% to 77.0%) of the variation in time to covid-19 death in the validation cohort. Discrimination was high, with a D statistic of 3.46 (95% confidence interval 3.19 to 3.73) and C statistic of 92.5. Performance was similar after each vaccine dose. In the top 5% of patients with the highest predicted covid-19 mortality risk, sensitivity for identifying covid-19 deaths within 70 days was 78.7%. CONCLUSION: This population based risk algorithm performed well showing high levels of discrimination for identifying those patients at highest risk of covid-19 related death and hospital admission after vaccination.

Obesity as a Risk Factor for Severe COVID-19: Summary of the Best Evidence and Implications for Health Care.

PURPOSE OF REVIEW: To collate the best evidence from several strands-epidemiological, genetic, comparison with historical data and mechanistic information-and ask whether obesity is an important causal and potentially modifiable risk factor for severe COVID-19 outcomes. RECENT FINDINGS: Several hundred studies provide powerful evidence that body mass index (BMI) is a strong linear risk factor for severe COVID-19 outcomes, with recent studies suggesting ~5-10% higher risk for COVID-19 hospitalisation per every kg/m2 higher BMI. Genetic data concur with hazard ratios increasing by 14% per every kg/m2 higher BMI. BMI to COVID-19 links differ markedly from prior BMI-infection associations and are further supported as likely causal by multiple biologically plausible pathways. Excess adiposity appears to be an important, modifiable risk factor for adverse COVID-19 outcomes across all ethnicities. The pandemic is also worsening obesity levels. It is imperative that medical systems worldwide meet this challenge by upscaling investments in obesity prevention and treatments.

Cohort profile: National Diabetes Audit for England and Wales.

The National Diabetes Audit (NDA) collates and analyses data on the quality and variation in clinical care and outcomes for people with diabetes. It also provides opportunities to assess trends, determinants, and outcomes of diabetes to help guide clinical and public health priorities. COHORT: Between 1 January 2003 and 31 March 2020, a total of 5,280,885 people diagnosed with diabetes were included in at least one NDA data collection. To this date, median follow-up was 12 and 8 years for people with type 1 diabetes and type 2 diabetes respectively. Comparisons with the 2019/20 Quality and Outcomes Framework show it included 98% of adults in England and Wales with diagnosed type 1 and type 2 diabetes. Data include demographic characteristics (age, sex, ethnicity, age at diagnosis, deprivation), risk factors (HbA1c , blood pressure, cholesterol, body mass index, smoking status) diabetic and cardiovascular complications and deaths. SECONDARY ANALYSIS: Secondary analyses have included comparisons of HbA1c and blood pressure measurements in cohorts with similar characteristics to the Epidemiology of Diabetes Interventions and Complications study and the UK Prospective Diabetes Study; COVID-19 related mortality in people with type 1 and type 2 diabetes and incidence of type 2 diabetes following admission to intensive care units. FUTURE PLANS: Commissioned NDA reports will continue to inform service development in England and Wales. The same data, with or without linkages to other external datasets, are also a rich resource for clinically orientated research.

Living risk prediction algorithm (QCOVID) for risk of hospital admission and mortality from coronavirus 19 in adults: national derivation and validation cohort study.

OBJECTIVE: To derive and validate a risk prediction algorithm to estimate hospital admission and mortality outcomes from coronavirus disease 2019 (covid-19) in adults. DESIGN: Population based cohort study. SETTING AND PARTICIPANTS: QResearch database, comprising 1205 general practices in England with linkage to covid-19 test results, Hospital Episode Statistics, and death registry data. 6.08 million adults aged 19-100 years were included in the derivation dataset and 2.17 million in the validation dataset. The derivation and first validation cohort period was 24 January 2020 to 30 April 2020. The second temporal validation cohort covered the period 1 May 2020 to 30 June 2020. MAIN OUTCOME MEASURES: The primary outcome was time to death from covid-19, defined as death due to confirmed or suspected covid-19 as per the death certification or death occurring in a person with confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in the period 24 January to 30 April 2020. The secondary outcome was time to hospital admission with confirmed SARS-CoV-2 infection. Models were fitted in the derivation cohort to derive risk equations using a range of predictor variables. Performance, including measures of discrimination and calibration, was evaluated in each validation time period. RESULTS: 4384 deaths from covid-19 occurred in the derivation cohort during follow-up and 1722 in the first validation cohort period and 621 in the second validation cohort period. The final risk algorithms included age, ethnicity, deprivation, body mass index, and a range of comorbidities. The algorithm had good calibration in the first validation cohort. For deaths from covid-19 in men, it explained 73.1% (95% confidence interval 71.9% to 74.3%) of the variation in time to death (R2); the D statistic was 3.37 (95% confidence interval 3.27 to 3.47), and Harrell's C was 0.928 (0.919 to 0.938). Similar results were obtained for women, for both outcomes, and in both time periods. In the top 5% of patients with the highest predicted risks of death, the sensitivity for identifying deaths within 97 days was 75.7%. People in the top 20% of predicted risk of death accounted for 94% of all deaths from covid-19. CONCLUSION: The QCOVID population based risk algorithm performed well, showing very high levels of discrimination for deaths and hospital admissions due to covid-19. The absolute risks presented, however, will change over time in line with the prevailing SARS-C0V-2 infection rate and the extent of social distancing measures in place, so they should be interpreted with caution. The model can be recalibrated for different time periods, however, and has the potential to be dynamically updated as the pandemic evolves.

Risk factors for COVID-19-related mortality in people with type 1 and type 2 diabetes in England: a population-based cohort study.

BACKGROUND: Diabetes has been associated with increased COVID-19-related mortality, but the association between modifiable risk factors, including hyperglycaemia and obesity, and COVID-19-related mortality among people with diabetes is unclear. We assessed associations between risk factors and COVID-19-related mortality in people with type 1 and type 2 diabetes. METHODS: We did a population-based cohort study of people with diagnosed diabetes who were registered with a general practice in England. National population data on people with type 1 and type 2 diabetes collated by the National Diabetes Audit were linked to mortality records collated by the Office for National Statistics from Jan 2, 2017, to May 11, 2020. We identified the weekly number of deaths in people with type 1 and type 2 diabetes during the first 19 weeks of 2020 and calculated the percentage change from the mean number of deaths for the corresponding weeks in 2017, 2018, and 2019. The associations between risk factors (including sex, age, ethnicity, socioeconomic deprivation, HbA1c, renal impairment [from estimated glomerular filtration rate (eGFR)], BMI, tobacco smoking status, and cardiovascular comorbidities) and COVID-19-related mortality (defined as International Classification of Diseases, version 10, code U07.1 or U07.2 as a primary or secondary cause of death) between Feb 16 and May 11, 2020, were investigated by use of Cox proportional hazards models. FINDINGS: Weekly death registrations in the first 19 weeks of 2020 exceeded the corresponding 3-year weekly averages for 2017-19 by 672 (50·9%) in people with type 1 diabetes and 16 071 (64·3%) in people with type 2 diabetes. Between Feb 16 and May 11, 2020, among 264 390 people with type 1 diabetes and 2 874 020 people with type 2 diabetes, 1604 people with type 1 diabetes and 36 291 people with type 2 diabetes died from all causes. Of these total deaths, 464 in people with type 1 diabetes and 10 525 in people with type 2 diabetes were defined as COVID-19 related, of which 289 (62·3%) and 5833 (55·4%), respectively, occurred in people with a history of cardiovascular disease or with renal impairment (eGFR <60 mL/min per 1·73 m2). Male sex, older age, renal impairment, non-white ethnicity, socioeconomic deprivation, and previous stroke and heart failure were associated with increased COVID-19-related mortality in both type 1 and type 2 diabetes. Compared with people with an HbA1c of 48-53 mmol/mol (6·5-7·0%), people with an HbA1c of 86 mmol/mol (10·0%) or higher had increased COVID-19-related mortality (hazard ratio [HR] 2·23 [95% CI 1·50-3·30, p<0·0001] in type 1 diabetes and 1·61 [1·47-1·77, p<0·0001] in type 2 diabetes). In addition, in people with type 2 diabetes, COVID-19-related mortality was significantly higher in those with an HbA1c of 59 mmol/mol (7·6%) or higher than in those with an HbA1c of 48-53 mmol/mol (HR 1·22 [95% CI 1·15-1·30, p<0·0001] for 59-74 mmol/mol [7·6-8·9%] and 1·36 [1·24-1·50, p<0·0001] for 75-85 mmol/mol [9·0-9·9%]). The association between BMI and COVID-19-related mortality was U-shaped: in type 1 diabetes, compared with a BMI of 25·0-29·9 kg/m2, a BMI of less than 20·0 kg/m2 had an HR of 2·45 (95% CI 1·60-3·75, p<0·0001) and a BMI of 40·0 kg/m2 or higher had an HR of 2·33 (1·53-3·56, p<0·0001); the corresponding HRs for type 2 diabetes were 2·33 (2·11-2·56, p<0·0001) and 1·60 (1·47-1·75, p<0·0001). INTERPRETATION: Deaths in people with type 1 and type 2 diabetes rose sharply during the initial COVID-19 pandemic in England. Increased COVID-19-related mortality was associated not only with cardiovascular and renal complications of diabetes but, independently, also with glycaemic control and BMI. FUNDING: None.

Associations of type 1 and type 2 diabetes with COVID-19-related mortality in England: a whole-population study.

BACKGROUND: Although diabetes has been associated with COVID-19-related mortality, the absolute and relative risks for type 1 and type 2 diabetes are unknown. We assessed the independent effects of diabetes status, by type, on in-hospital death in England in patients with COVID-19 during the period from March 1 to May 11, 2020. METHODS: We did a whole-population study assessing risks of in-hospital death with COVID-19 between March 1 and May 11, 2020. We included all individuals registered with a general practice in England who were alive on Feb 16, 2020. We used multivariable logistic regression to examine the effect of diabetes status, by type, on in-hospital death with COVID-19, adjusting for demographic factors and cardiovascular comorbidities. Because of the absence of data on total numbers of people infected with COVID-19 during the observation period, we calculated mortality rates for the population as a whole, rather than the population who were infected. FINDINGS: Of the 61 414 470 individuals who were alive and registered with a general practice on Feb 16, 2020, 263 830 (0·4%) had a recorded diagnosis of type 1 diabetes, 2 864 670 (4·7%) had a diagnosis of type 2 diabetes, 41 750 (0·1%) had other types of diabetes, and 58 244 220 (94·8%) had no diabetes. 23 698 in-hospital COVID-19-related deaths occurred during the study period. A third occurred in people with diabetes: 7434 (31·4%) in people with type 2 diabetes, 364 (1·5%) in those with type 1 diabetes, and 69 (0·3%) in people with other types of diabetes. Unadjusted mortality rates per 100 000 people over the 72-day period were 27 (95% CI 27-28) for those without diabetes, 138 (124-153) for those with type 1 diabetes, and 260 (254-265) for those with type 2 diabetes. Adjusted for age, sex, deprivation, ethnicity, and geographical region, compared with people without diabetes, the odds ratios (ORs) for in-hospital COVID-19-related death were 3·51 (95% CI 3·16-3·90) in people with type 1 diabetes and 2·03 (1·97-2·09) in people with type 2 diabetes. These effects were attenuated to ORs of 2·86 (2·58-3·18) for type 1 diabetes and 1·80 (1·75-1·86) for type 2 diabetes when also adjusted for previous hospital admissions with coronary heart disease, cerebrovascular disease, or heart failure. INTERPRETATION: The results of this nationwide analysis in England show that type 1 and type 2 diabetes were both independently associated with a significant increased odds of in-hospital death with COVID-19. FUNDING: None.