Search

Background: Heart failure is common, complex, and often associated with coexisting chronic medical conditions and a high mortality. We aimed to assess the epidemiology of people admitted to hospital with heart failure with reduced ejection fraction (HFrEF) and heart failure with preserved ejection fraction (HFpEF), including the period covering the COVID-19 pandemic, which was previously not well characterised., Methods: In this retrospective, cohort study, we used whole-population electronic health records with 57 million individuals in England to identify patients hospitalised with heart failure as the primary diagnosis in any consultant episode of an in-patient admission to a National Health Service (NHS) hospital. We excluded individuals with less than 1 year of medical history records in primary or secondary care; admissions to NHS hospitals for which less than 10% of heart failure cases were linkable to the National Heart Failure Audit (NHFA); individuals younger than 18 years at the time of the heart failure hospitalisation; and patients who died in hospital during the index heart failure admission. For patients with new onset heart failure, we assessed incidence rates of 30-day and 1-year all-cause and cause-specific (cardiovascular, non-cardiovascular, and heart failure-related) emergency rehospitalisation and mortality after discharge, and dispensed guideline-recommended medical therapy (GRMT). Follow-up occurred from the index admission to the earliest occurrence of the event of interest, death, or end of data coverage. We estimated adjusted hazard ratios (HRs) to compare HFrEF with HFpEF. We computed population-attributable fractions to quantify the percentage of outcomes attributable to coexisting chronic medical conditions., Findings: Among 233 320 patients identified who survived the index heart failure admission across 335 NHS hospitals between Jan 1, 2019, and Dec 31, 2022, 101 320 (43·4%) had HFrEF, 71 910 (30·8%) had HFpEF, and 60 090 (25·8%) had an unknown classification. In patients with new onset heart failure, there were reductions in all-cause 30-day (-5·2% [95% CI -7·7 to -2·6] in 2019-22) and 1-year rehospitalisation rates (-3·9% [-6·6 to -1·2]). Declining 30-day rehospitalisation rates affected patients with HFpEF (-4·8% [-9·2 to -0·2]) and HFrEF (-6·2% [-10·5 to -1·6]), although 1-year rates were not statistically significant for patients with HFpEF (-2·2% [-6·6 to 2·3] vs -5·7% [-10·6 to -0·5] for HFrEF). There were no temporal trends in incidence rates of 30-day or 1-year mortality after discharge. The rates of all-cause (HR 1·20 [1·18-1·22]) and cause-specific rehospitalisation were uniformly higher in those with HFpEF than those with HFrEF. Patients with HFpEF also had higher rates of 1-year all-cause mortality after discharge (HR 1·07 [1·05-1·09]), driven by excess risk of non-cardiovascular death (HR 1·25 [1·21-1·29]). Rates of rehospitalisation and mortality were highest in patients with coexisting chronic kidney disease, chronic obstructive pulmonary disease, dementia, and liver disease. Chronic kidney disease contributed to 6·5% (5·6-7·4) of rehospitalisations within 1 year for HFrEF and 5·0% (4·1-5·9) of rehospitalisations for HFpEF, double that of any other coexisting condition. There was swift implementation of newer GRMT, but markedly lower dispensing of these medications in patients with coexisting chronic kidney disease., Interpretation: Rates of rehospitalisation in patients with heart failure in England have decreased during 2019-22. Further population health improvements could be reached through enhanced implementation of GRMT, particularly in patients with coexisting chronic kidney disease, who, despite being at high risk, remain undertreated., Funding: Wellcome Trust, Health Data Research UK, British Heart Foundation Data Science Centre., Competing Interests: Declaration of interests RAF received studentship awards from the Health Data Research UK-The Alan Turing Institute Wellcome Trust PhD Programme in Health Data Science (grant 218529/Z/19/Z). PR received a grant from the Dr Johannes and Hertha Tuba Foundation. BLN reports fees for travel support, advisory boards, scientific presentations, and steering committee roles from AstraZeneca, Alexion, Bayer, Boehringer Ingelheim, Cambridge Healthcare Research, Cornerstone Medical Education, Janssen, Limbic, Medscape, Novo Nordisk, and Travere Therapeutics with all honoraria paid to the George Institute for Global Health. CT received a studentship from the University College London UK Research and Innovation Centre for doctoral training in AI-enabled healthcare (EP/S021612/1), Medical Research Council Clinical Top-Up, and a studentship from the National Institute for Health and Care Research (NIHR) Biomedical Research Centre at University College London Hospital NHS Trust. NC received a personal fellowship from the Research Foundation Flanders and a research grant from the European Society of Cardiology. ER is funded by Forte Swedish Research Council for Health, Working Life And Welfare (2022–00882) individual postdoctoral fellowship, and Vetenskapsrådet Swedish Research Council (grant 2023–01982). SD received research funding from GlaxoSmithKline, AstraZeneca, Bayer, and BenevolentAI. CS is a director of the British Heart Foundation Data Science Centre and a chief scientist and deputy director at Health Data Research UK; has codeveloped National Health Service (NHS) England Secure Data Environment; and leads the CVD-COVID UK/COVID-IMPACT Consortium. SEP has a leadership role for the European Association of Cardiovascular Imaging, received consulting fees from Circle Cardiovascular Imaging, and holds an advisory role for the PROTEUS trial (NCT05028179). GMC served on the board of directors of Satellite Healthcare; served as chair or cochair of trial steering committees for Akebia, AstraZeneca, CSL Behring, Sanifit, and Vertex; served as an advisor for Applaud, CloudCath, Durect, Eliaz Therapeutics, Miromatrix, Outset, Physiowave, Renibus, and Unicycive; and served on data safety monitoring boards for Bayer, Mineralys, and ReCor. KK acted as a consultant or speaker and receiving grants for investigator-initiated studies from AstraZeneca, Abbott, Amgen, Bayer, Daiichi-Sankyo, Embecta, Nestle Health Science, Novartis, Novo Nordisk, Roche, Servier, Sanofi-Aventis, Lilly, MSD, Boehringer Ingelheim, Oramed Pharmaceuticals, and Applied Therapeutics; and was a chair of the scientific advisory group for Emergencies Ethnicity Subgroup. JS has direct or indirect stock ownership in Anagram Kommunikation, Sence Research, Symptoms Europe, and MinForskning; and professional services to Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, Eli Lilly, Gilead, GSK, Göteborg University, Itrim, Ipsen, Janssen, Karolinska Institutet, LIF, Linköping University, Novo Nordisk, Parexel, Pfizer, Region Stockholm, Region Uppsala, Sanofi, STRAMA, Takeda, TLV, Uppsala University, Vifor Pharma, and WeMind. CA received grants from the National Health Medical Research Council (Medical Research Futures Fund) and NSW Health; and honoraria from AstraZeneca, Novo Nordisk, and Amgen. JGFC reports receipt of personal honoraria for lectures and advisory boards from Pharmacosmos, Vifor, AstraZeneca, Amgen, Bayer, Novartis, and Servier; has received research grants through The University of Glasgow from Pharmacosmos and Vifor; and received funding from the British Heart Foundation Center of Research Excellence (RE/18/6134217). JD reports grants, personal fees, and non-financial support from MSD and Novartis; grants from Pfizer and AstraZeneca; and is part of the International Cardiovascular and Metabolic Advisory Board for Novartis, Steering Committee of UK Biobank, MRC International Advisory Group, MRC High Throughput Science Omics Panel, Scientific Advisory Committee for Sanofi, International Cardiovascular and Metabolism Research and Development Portfolio Committee for Novartis, AstraZeneca Genomics Advisory Board, Scientific Advisory Board of Nightingale Health, Access Board of Our Future Health, and Scientific Advisory Committee of Leducq Foundation. JJVM received payments through Glasgow University for work on clinical trials, consulting, and other activities from Amgen, AstraZeneca, Bayer, Cardurion, Cytokinetics, GSK, KBP Biosciences, and Novartis; personal consultancy fees from Alnylam Pharma, Bayer, BMS, George Clinical, Ionis Pharma, Novartis, Regeneron Pharma, and River 2 Renal; personal lecture fees from Abbott, Alkem Metabolics, AstraZeneca, Blue Ocean Scientific Solutions, Boehringer Ingelheim, Canadian Medical and Surgical Knowledge, Emcure Pharma, Eris Lifesciences, European Academy of CME, Hikma Pharmaceuticals, Imagica Health, Intas Pharma, JB Pharma, Lupin Pharma, Medscape (Heart.org), ProAdWise Communications, Radcliffe Cardiology, Sun Pharma, The Corpus, Translation Research Group, and Translational Medicine Academy; and is a director of Global Clinical Trial Partners. MV received research grant support, served on advisory boards, or had speaker engagements with American Regent, Amgen, AstraZeneca, Bayer, Baxter, Boehringer Ingelheim, Chiesi, Cytokinetics, Lexicon Pharmaceuticals, Merck, Novartis, Novo Nordisk, Pharmacosmos, Relypsa, Roche Diagnostics, Sanofi, and Tricog Health; and participates on clinical trial committees for AstraZeneca, Galmed, Novartis, Bayer, Occlutech, and Impulse Dynamics. AMW received funding from the British Heart Foundation Data Science Centre (HDRUK2023.0239) and NIHR (NIHR303137). All other authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Background: COVID-19 pandemic restrictions may have influenced behaviours related to weight., Aim: To describe patterns of weight change among adults living in England with type 2 diabetes (T2D) and/or hypertension during the pandemic., Design and Setting: An observational cohort study using the routinely collected health data of approximately 40% of adults living in England, accessed through the OpenSAFELY service inside TPP., Method: Clinical and sociodemographic characteristics associated with rapid weight gain (>0.5 kg/m 2 /year) were investigated using multivariable logistic regression., Results: Data were extracted on adults with T2D ( n = 1 231 455, 43.9% female, and 76.0% White British) or hypertension ( n = 3 558 405, 49.7% female, and 84.3% White British). Adults with T2D lost weight overall (median δ = -0.1 kg/m 2 /year [interquartile range {IQR} -0.7-0.4]). However, rapid weight gain was common (20.7%) and associated with the following: sex (male versus female: adjusted odds ratio [aOR] 0.78 [95% confidence interval {CI} = 0.77 to 0.79]); age (older age reduced odds, for example, aged 60-69 years versus 18-29 years: aOR 0.66 [95% CI = 0.61 to 0.71]); deprivation (least deprived Index of Multiple Deprivation [IMD] quintile versus most deprived IMD quintile: aOR 0.87 [95% CI = 0.85 to 0.89]); White ethnicity (Black versus White: aOR 0.95 [95% CI = 0.92 to 0.98]); mental health conditions (for example, depression: aOR 1.13 [95% CI = 1.12 to 1.15]); and diabetes treatment (non-insulin treatment versus no pharmacological treatment: aOR 0.68 [95% CI = 0.67 to 0.69]). Adults with hypertension maintained stable weight overall (median δ = 0.0 kg/m 2 /year [IQR -0.6-0.5]); however, rapid weight gain was common (24.7%) and associated with similar characteristics as in T2D., Conclusion: Among adults living in England with T2D and/or hypertension, rapid pandemic weight gain was more common among females, younger adults, those living in more deprived areas, and those with mental health conditions., (© The Authors.)

Objectives: To describe the direct impact of coronavirus disease 2019 (COVID-19) infection on morbidity and mortality in people with multiple long-term conditions (MLTCs)., Design: A systematic review and meta-analysis including observational studies., Setting: Studies conducted between 1 January 2020 and 4 May 2023 across 51 countries were identified from five databases., Participants: A total of 4,084,469 patients with confirmed COVID-19 infection., Main Outcome Measures: Pooled risk ratios (RRs) for mortality, hospitalisation, severe disease, intensive care unit (ICU) admission and mechanical ventilation were estimated with random effect meta-analysis models., Results: A total of 38,356 studies were identified and 111 included. In most (74%) of the studies, MLTCs referred to having two or more long-term conditions. Others described MLTCs by high weighted indices: the Charlson Comorbidity Index in 11% and the Clinical Frailty Score in 7%. Using the National Institutes of Health quality assessment tool for observational studies, the risk of bias was judged as low and moderate in 86 and 25 studies, respectively. Having MLTCs was associated with increased mortality (RR: 2.61 [95% CI: 2.27 to 3.0]); hospitalisation (2.4 [1.92 to 2.99]); severe disease (2.61 [1.92 to 3.54]); ICU admission (1.22 [1.07 to 1.39]) and mechanical ventilation (1.83 [1.18 to 2.84]) compared with those with no MLTCs. Pooled RRs for adverse outcomes were higher in children and young people compared with all age groups. In meta-regression analyses, men were more likely to need ICU admission ( p  = 0.013) and mechanical ventilation ( p  = 0.002)., Conclusions: Public health policies, clinical and preventative interventions should prioritise people with MLTCs to minimise direct adverse outcomes from COVID-19 disease.

Objectives: This study examines clinically confirmed long-COVID symptoms and diagnosis among individuals with COVID in England, aiming to understand prevalence and associated risk factors using electronic health records. To further understand long COVID, the study also explored differences in risks and symptom profiles in three subgroups: hospitalised, non-hospitalised, and untreated COVID cases., Methods: A population-based longitudinal cohort study was conducted using data from 1,554,040 individuals with confirmed SARS-CoV-2 infection via Clinical Practice Research Datalink. Descriptive statistics explored the prevalence of long COVID symptoms 12 weeks post-infection, and Cox regression models analysed the associated risk factors. Sensitivity analysis was conducted to test the impact of right-censoring data., Results: During an average 400-day follow-up, 7.4% of individuals with COVID had at least one long-COVID symptom after acute phase, yet only 0.5% had long-COVID diagnostic codes. The most common long-COVID symptoms included cough (17.7%), back pain (15.2%), stomach-ache (11.2%), headache (11.1%), and sore throat (10.0%). The same trend was observed in all three subgroups. Risk factors associated with long-COVID symptoms were female sex, non-white ethnicity, obesity, and pre-existing medical conditions like anxiety, depression, type II diabetes, and somatic symptom disorders., Conclusions: This study is the first to investigate the prevalence and risk factors of clinically confirmed long-COVID in the general population. The findings could help clinicians identify higher risk individuals for timely intervention and allow decision-makers to more efficiently allocate resources for managing long-COVID., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Prof. Christina Van Der Feltz-Cornelis received travel and accommodation in UK for lectures from The Lloyd Register Foundation and honoraries from Janssen UK and royalties for books on psychiatry. Prof. Christina Van Der Feltz-Cornelis has also received grants from the National Institute for Health Research, British Medical Association, European Union’s Horizon 2020 research programme and the Netherlands Organisation for Health Research and Development. Prof. Amitava Banerjee has received grants and/or fees from the National Institute for Health Research, British Medical Association, UK Research and Innovation, European Union’s Horizon 2020 research and innovation programme and EFPIA, and AstraZeneca. Dr. Michael G Crooks has received grants, fees and/or non-financial support from the National Institute for Health and Care Research, AstraZeneca, Boehringer Ingelheim, Chiesi, GlaxoSmithKline, Philips, and Pfizer. Prof. Kamlesh Khunti was chair of the ethnicity subgroup of the UK Scientific Advisory Group for Emergencies (SAGE) and has acted as a consultant, speaker or received grants for investigator-initiated studies from Astra Zeneca and Pfizer. K.K. (chair) and A.B. are members of the National Long Covid Research Group that informs the chief medical officer for England. All other authors have no conflicts of interest to report., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Objective: To identify highest-risk subgroups for COVID-19 and Long COVID(LC), particularly in contexts of influenza and cardiovascular disease(CVD)., Methods: Using national, linked electronic health records for England (NHS England Secure Data Environment via CVD-COVID-UK/COVID-IMPACT Consortium), we studied individuals (of all ages) with COVID-19 and LC (2020-2023). We compared all-cause hospitalization and mortality by prior CVD, high CV risk, vaccination status (COVID-19/influenza), and CVD drugs, investigating impact of vaccination and CVD prevention using population preventable fractions., Results: Hospitalization and mortality were 15.3% and 2.0% among 17,373,850 individuals with COVID-19 (LC rate 1.3%), and 16.8% and 1.4% among 301,115 with LC. Adjusted risk of mortality and hospitalization were reduced with COVID-19 vaccination ≥ 2 doses(COVID-19:HR 0.36 and 0.69; LC:0.44 and 0.90). With influenza vaccination, mortality was reduced, but not hospitalization (COVID-19:0.86 and 1.01, and LC:0.72 and 1.05). Mortality and hospitalization were reduced by CVD prevention in those with CVD, e.g., anticoagulants- COVID:19:0.69 and 0.92; LC:0.59 and 0.88; lipid lowering- COVID-19:0.69 and 0.86; LC:0.68 and 0.90. COVID-19 vaccination averted 245044 of 321383 and 7586 of 8738 preventable deaths after COVID-19 and LC, respectively., Interpretation: Prior CVD and high CV risk are associated with increased hospitalization and mortality in COVID-19 and LC. Targeted COVID-19 vaccination and CVD prevention are priority interventions., Funding: NIHR. HDR UK., Competing Interests: Declarations of competing interest KK is chair of the ethnicity subgroup of the UK Scientific Advisory Group for Emergencies (SAGE) and is a member of SAGE. KK (Chair) and AB are members of the LC Research Group that reports to the Chief Medical Officer for England. All other authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

The first dose of COVID-19 vaccines led to an overall reduction in cardiovascular events, and in rare cases, cardiovascular complications. There is less information about the effect of second and booster doses on cardiovascular diseases. Using longitudinal health records from 45.7 million adults in England between December 2020 and January 2022, our study compared the incidence of thrombotic and cardiovascular complications up to 26 weeks after first, second and booster doses of brands and combinations of COVID-19 vaccines used during the UK vaccination program with the incidence before or without the corresponding vaccination. The incidence of common arterial thrombotic events (mainly acute myocardial infarction and ischaemic stroke) was generally lower after each vaccine dose, brand and combination. Similarly, the incidence of common venous thrombotic events, (mainly pulmonary embolism and lower limb deep venous thrombosis) was lower after vaccination. There was a higher incidence of previously reported rare harms after vaccination: vaccine-induced thrombotic thrombocytopenia after first ChAdOx1 vaccination, and myocarditis and pericarditis after first, second and transiently after booster mRNA vaccination (BNT-162b2 and mRNA-1273). These findings support the wide uptake of future COVID-19 vaccination programs., (© 2024. The Author(s).)

The importance of integrated care for complex, multiple long term conditions was acknowledged before the COVID pandemic but remained a challenge. The pandemic and consequent development of Long COVID required rapid adaptation of health services to address the population's needs, requiring service redesigns including integrated care. This Delphi consensus study was conducted in the UK and found similar integrated care priorities for Long COVID and complex, multiple long term conditions, provided by 480 patients and health care providers, with an 80% consensus rate. The resultant recommendations were based on more than 1400 responses from survey participants and were supported by patients, health care professionals, and by patient charities. Participants identified the need to allocate resources to: support integrated care, provide access to care and treatments that work, provide diagnostic procedures that support the personalization of treatment in an integrated care environment, and enable structural consultation between primary and specialist care settings including physical and mental health care. Based on the findings we propose a model for delivering integrated care by a multidisciplinary team to people with complex multisystem conditions. These recommendations can inform improvements to integrated care for complex, multiple long term conditions and Long COVID at international level., (© 2024. The Author(s).)

Background: Evidence on the long-term employment consequences of SARS-CoV-2 infection is lacking. We used data from a large, community-based sample in the UK to estimate associations between Long Covid and employment outcomes., Methods: This was an observational, longitudinal study using a pre-post design. We included survey participants from 3 February 2021 to 30 September 2022 when they were aged 16-64 years and not in education. Using conditional logit modelling, we explored the time-varying relationship between Long Covid status ≥12 weeks after a first test-confirmed SARS-CoV-2 infection (reference: pre-infection) and labour market inactivity (neither working nor looking for work) or workplace absence lasting ≥4 weeks., Results: Of 206 299 participants (mean age 45 years, 54% female, 92% white), 15% were ever labour market inactive and 10% were ever long-term absent during follow-up. Compared with pre-infection, inactivity was higher in participants reporting Long Covid 30 to <40 weeks [adjusted odds ratio (aOR): 1.45; 95% CI: 1.17-1.81] or 40 to <52 weeks (aOR: 1.34; 95% CI: 1.05-1.72) post-infection. Combining with official statistics on Long Covid prevalence, and assuming a correct statistical model, our estimates translate to 27 000 (95% CI: 6000-47 000) working-age adults in the UK being inactive because of Long Covid in July 2022., Conclusions: Long Covid is likely to have contributed to reduced participation in the UK labour market, though it is unlikely to be the sole driver. Further research is required to quantify the contribution of other factors, such as indirect health effects of the pandemic., (© The Author(s) 2024. Published by Oxford University Press on behalf of the European Public Health Association.)

The COVID-19 pandemic has caused major disruptions in clinical services for people with chronic long-term conditions. In this narrative review, we assess the indirect impacts of the COVID-19 pandemic on diabetes services globally and the resulting adverse effects on rates of diagnosing, monitoring, and prescribing in people with type 2 diabetes. We summarise potential practical approaches that could address these issues and improve clinical services and outcomes for people living with diabetes during the recovery phase of the pandemic., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: A.M. has received speaker fees from Boehringer Ingelheim, AstraZeneca, Abbot, Lupin, Sanofi, Abbott and Jannsen. C.H. has received funding from the following companies for speaker fees, providing education or attendance at conferences: Boehringer Ingelheim, Astra Zeneca, Lilly, MSD, Takeda, Novo Nordisk, Sanofi, Napp, Abbott and Dexcom. J.V. was the National Clinical Director for Diabetes and Obesity at NHS England. K.K. has acted as a consultant, speaker or received grants for investigator-initiated studies for Astra Zeneca, Bayer, Novartis, Novo Nordisk, Sanofi-Aventis, Eli Lilly and Merck Sharp & Dohme, Boehringer Ingelheim, Oramed Pharmaceuticals, Roche and Applied Therapeutics. K.K. is chair of the ethnicity subgroup of the UK Scientific Advisory Group for Emergencies (SAGE) and is a member of SAGE.KKs research group developed the Diabetes Risk Score recommended by NICE for screening for diabetes. DMA reports research grants from AbbVie, Almirall, Celgene, Eli Lilly, Janssen, Novartis, UCB, and the LEO Foundation. M.R has received consulting fees from Eli Lilly and Company. N.K. has received honoraria from Astra Zeneca, Bayer, Novartis, Novo Nordisk, Sanofi-Aventis, Lilly and Merck Sharp & Dohme, Boehringer Ingelheim and Abbott for speaker meetings and advisory boards. N.M. has received funding from the following companies for providing educational sessions, attendance at conferences and for attending advisory boards: Boehringer Ingelheim, Astra Zeneca, Lilly, MSD, Takeda, Novo Nordisk, Sanofi, Napp, Abbott, MyLan, Roche, Ascensia and Dexcom. N.S. has received grants from AstraZeneca, Boehringer Ingelheim, Novartis, and Roche Diagnostics; and consulting fees from Afimmune, Amgen, AstraZeneca, Boehringer Ingelheim, Eli Lilly and Company, Hanmi Pharmaceuticals, Merck Sharp & Dohme, Novartis, Novo Nordisk, Pfizer, and Sanofi. All other authors declare no conflicts of interest., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Pre-existing cardiovascular disease (CVD) or cardiovascular risk factors have been associated with an increased risk of complications following hospitalisation with COVID-19, but their impact on the rate of recovery following discharge is not known., Objectives: To determine whether the rate of patient-perceived recovery following hospitalisation with COVID-19 was affected by the presence of CVD or cardiovascular risk factors., Methods: In a multicentre prospective cohort study, patients were recruited following discharge from the hospital with COVID-19 undertaking two comprehensive assessments at 5 months and 12 months. Patients were stratified by the presence of either CVD or cardiovascular risk factors prior to hospitalisation with COVID-19 and compared with controls with neither. Full recovery was determined by the response to a patient-perceived evaluation of full recovery from COVID-19 in the context of physical, physiological and cognitive determinants of health., Results: From a total population of 2545 patients (38.8% women), 472 (18.5%) and 1355 (53.2%) had CVD or cardiovascular risk factors, respectively. Compared with controls (n=718), patients with CVD and cardiovascular risk factors were older and more likely to have had severe COVID-19. Full recovery was significantly lower at 12 months in patients with CVD (adjusted OR (aOR) 0.62, 95% CI 0.43 to 0.89) and cardiovascular risk factors (aOR 0.66, 95% CI 0.50 to 0.86)., Conclusion: Patients with CVD or cardiovascular risk factors had a delayed recovery at 12 months following hospitalisation with COVID-19. Targeted interventions to reduce the impact of COVID-19 in patients with cardiovascular disease remain an unmet need., Trail Registration Number: ISRCTN10980107., Competing Interests: Competing interests: KK is chair of the ethnicity subgroup of the UK Scientific Advisory Group for Emergencies (SAGE) and is a member of SAGE. KK (Chair) and RE are members of the Long COVID Epidemiological Research Group that reports to the CMO. CB is an author of the COVID-19 rapid guideline: managing the long-term effects of COVID-19 NICE guideline (NG188) https://www.nice.org.uk/guidance/ng188/history. CB is a member of the NHS National Services Scotland Long COVID group and his employer, the University of Glasgow, holds a research agreement with AstraZeneca and Somalogic for research in COVID-19. AJM is an employee of AstraZeneca., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY. Published by BMJ.)

Objective: Long COVID can include impaired cognition ('brain fog'; a term encompassing multiple symptoms) and mental health conditions. We performed a systematic review and meta-analysis to estimate their prevalence and to explore relevant factors associated with the incidence of impaired cognition and mental health conditions., Methods: Searches were conducted in Medline and PsycINFO to cover the start of the pandemic until August 2023. Included studies reported prevalence of mental health conditions and brain fog in adults with long COVID after clinically-diagnosed or PCR-confirmed SARS-CoV-2 infection., Findings: 17 studies were included, reporting 41,249 long COVID patients. Across all timepoints (3-24 months), the combined prevalence of mental health conditions and brain fog was 20·4% (95% CI 11·1%-34·4%), being lower among those previously hospitalised than in community-managed patients(19·5 vs 29·7% respectively; p = 0·047). The odds of mental health conditions and brain fog increased over time and when validated instruments were used. Odds of brain fog significantly decreased with increasing vaccination rates (p = ·000)., Conclusions: Given the increasing prevalence of mental health conditions and brain fog over time, preventive interventions and treatments are needed. Research is needed to explore underlying mechanisms that could inform further research in development of effective treatments. The reduced risk of brain fog associated with vaccination emphasizes the need for ongoing vaccination programs., Competing Interests: Declaration of competing interest Unless otherwise stated, funding for this project was paid to author institutions. In addition, CFC has had recent or current involvement with grants from the British Medical Association (CANDO Study), EU Horizon (EMPOWER Study), the Netherlands Organisation for Health Research and Development (Regional systems intervention for suicide prevention (SUPREMOCOL) in Noord -Brabant, the Netherlands), and NIHR HS&DR (Frequent Users of the Emergency Department: Improving and Standardising Services-a mixed methods study). CFC has received royalties for books on Psychiatry, an honorarium payment related to a lecture at the Big Questions in Neuroscience Annual meeting from Janssen UK, and has received travel and accommodation in the UK for a lecture from The Lloyd Register Foundation. CFC is an International member of the Scientific Advisory Board on the IMPACT in South Asia Research project, funded by the NIHR Global Health Program. KK is a past Chair of the Ethnicity Subgroup of the UK Scientific Advisory Group for Emergencies (SAGE) and a past Member of SAGE. KK is supported by the National Institute for Health Research (NIHR) Applied Research Collaboration East Midlands (ARC EM) and the NIHR Leicester Biomedical Research Centre (BRC). MG is part-funded by NIHR applied Research Collaboration North West Coast. HM has consulted for Astra Zeneca on covid vaccines and monoclonal therapies. HM has accepted lecture fees and conference support from Astra Zeneca relating to covid vaccines and monoclonal therapies. GYHL is a consultant and speaker for BMS/Pfizer, Boehringer Ingelheim, Daiichi-Sankyo, Anthos; no fees are received personally. DW holds an NIHR Advanced Fellowship to study hospital acquired pneumonia; this is held at University of Liverpool. CLW receives support from Applied Research Collaboration (ARCNWC): NIHR ARC NWC, PARticipation And engagement in Life and LEisure activities foLlowing stroke (PARALLEL): developing of a complex intervention: NIHR ARC NWC Mental Health Early Career Researcher Development Fellowship, NIHR HTA (EASE: Evaluating Antidepressants for emotionaliSm after strokE: A multi-centre, randomised, double-blind, placebo-controlled trial to establish the effect(s) of administration of sertraline (50 mg once daily for Six Months) in people with a recent stroke and post-stroke emotionalism; Should we use post-operative antibiotics following surgery for patients with mandible fractures? The MANTRA trial (MANdibular TRauma and Antibiotic use); Acceptability and feasibility of using the Virtual Engagement Rehabilitation Assistant (VERA) for community-based neurological rehabilitation). CLW receives support from NIHR Palliative and End of Life Care Research Partnerships for Living well and Dying Well in the last year of life for older people in rural and remote communities across the UK, and from NIHR Programme Grants for Applied Research for PREPARE: imPRoving End of life care Practice in stroke cARE. CLW is a member of Data Monitoring and Ethics Committees (Clinical and cost-effectiveness of a personalised health promotion intervention enabling independence in older people with mild frailty (‘HomeHealth’): A Randomised Controlled Trial; The Metoclopramide for Avoiding Pneumonia after Stroke (MAPS-2) Trial: a single-blind, randomised controlled trial of metoclopramide for the prevention of pneumonia in patients with dysphagia after an acute stroke), a Study Steering Committee 7 - Predicting AF after Cardiac Surgery - the PARADISE Score A Clinical Prediction Rule for Post-operative Atrial Fibrillation in Patients Undergoing Cardiac Surgery, and sat on a Trial Steering Committee - COVID NURSE: evaluation of the effects of a COVID-specific fundamental nursing care protocol compared to care as usual on experience of care for non-invasively ventilated patients in hospital with the SARS-CoV-2 virus: a randomised controlled trial. DJC has received investigator-initiated research funding, conference and/or consultancy fees and support for attending meetings/travel from NovoNordisk, Astra Zeneca and Ipsen. NW is Deputy Chair NIHR HTA Programme Funding Committee (Commissioned Research); payments are paid to institution. NW is GP partner in Llanfairfechan Group Practices; drawings are made to NW. AB has had recent or current involvement with NIHR, BMA, Astra Zeneca and UKRI research grants. AB is an unpaid Trustee for the South Asian Health Foundation. All other authors have no COIs to report., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background: Older people with frailty are at risk of harm from immobility or isolation, yet data about how COVID-19 lockdowns affected them are limited. Falls and fractures are easily measurable adverse outcomes correlated with frailty. We investigated whether English hospital admission rates for falls and fractures varied from the expected trajectory during the COVID-19 pandemic, and how these varied by frailty status., Methods: NHS England Hospital Episode Statistics Admitted Patient Care data were analysed for observed versus predicted outcome rates for 24 January 2020 to 31 December 2021. An auto-regressive integrated moving average time-series model was trained using falls and fracture incidence data from 2013 to 2018 and validated using data from 2019. Models included national and age-, sex- and region-stratified forecasts. Outcome measures were hospital admissions for falls, fractures, and falls and fractures combined. Frailty was defined using the Hospital Frailty Risk Score., Results: 144,148,915 pre-pandemic hospital admissions were compared with 42,267,318 admissions after pandemic onset. For the whole population, falls and fracture rates were below predicted for the first period of national lockdown, followed by a rapid return to rates close to predicted. Thereafter, rates followed expected trends. For people living with frailty, however, falls and fractures increased above expected rates during periods of national lockdown and remained elevated throughout the study period. Effects of frailty were independent of age., Conclusions: People living with frailty experienced increased fall and fracture rates above expected during and following periods of national lockdown. These remained persistently elevated throughout the study period., (© The Author(s) 2024. Published by Oxford University Press on behalf of the British Geriatrics Society.)

Objectives: This study aims to determine how workplace experiences of National Health Service (NHS) staff varied by ethnicity during the COVID-19 pandemic and how these experiences are associated with mental and physical health at the time of the study., Methods: An online Inequalities Survey was conducted by the Tackling Inequalities and Discrimination Experiences in Health Services study in collaboration with NHS CHECK. This Inequalities Survey collected measures relating to workplace experiences (such as personal protective equipment (PPE), risk assessments, redeployments and discrimination) as well as mental health (Patient Health Questionnaire (PHQ-9), Generalised Anxiety Disorder 7 (GAD-7)), and physical health (PHQ-15) from NHS staff working in the 18 trusts participating with the NHS CHECK study between February and October 2021 (N=4622)., Results: Regression analysis of this cross-sectional data revealed that staff from black and mixed/other ethnic groups had greater odds of experiencing workplace harassment (adjusted OR (AOR) 2.43 (95% CI 1.56 to 3.78) and 2.38 (95% CI 1.12 to 5.07), respectively) and discrimination (AOR 4.36 (95% CI 2.73 to 6.96) and 3.94 (95% CI 1.67 to 9.33), respectively) compared with white British staff. Staff from black ethnic groups also had greater odds than white British staff of reporting PPE unavailability (AOR 2.16 (95% CI 1.16 to 4.00)). Such workplace experiences were associated with negative physical and mental health outcomes, though this association varied by ethnicity. Conversely, understanding employment rights around redeployment, being informed about and having the ability to inform redeployment decisions were associated with lower odds of poor physical and mental health., Conclusions: Structural changes to the way staff from ethnically minoritised groups are supported, and how their complaints are addressed by leaders within the NHS are urgently required., Competing Interests: Competing interests: KK is member of SAGE and Chair of the SAGE Ethnicity Subgroup. KK also chaired the group that developed the NHS Risk Assessment Framework. Other authors have no competing interests., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY. Published by BMJ.)

The COVID-19 pandemic triggered disruptions to health care and lifestyles that could conceivably impact diabetes management. We set out to identify the impact of disruptions caused by COVID-19 on clinical outcomes in people with diabetes. We performed a systematic review of the available literature in the MEDLINE and OVID databases from Jan 1, 2020, to June 7, 2023, and included 138 studies (n>1 000 000 people). All but five studies were judged to be at some risk of bias. All studies compared prepandemic with pandemic periods. All-cause mortality (six studies) and diabetes-related mortality (13 studies) showed consistent increases, and most studies indicated increases in sight loss (six studies). In adult and mixed samples, data generally suggested no difference in diabetic ketoacidosis frequency or severity, whereas in children and adolescents most studies showed increases with some due to new-onset diabetes (69 studies). Data suggested decreases in hospital admissions in adults but increases in diabetes-related admissions to paediatric intensive care units (35 studies). Data were equivocal on diabetic foot ulcer presentations (nine studies), emergency department admissions (nine studies), and overall amputation rates (20 studies). No studies investigated renal failure. Where reported, the impact was most pronounced for females, younger people, and racial and ethnic minority groups. Further studies are needed to investigate the longer-term impact of the pandemic and the on potential differential impacts, which risk further exacerbating existing inequalities within people with diabetes., Competing Interests: Declaration of interests SS reports receiving grants from Sanofi, AstraZeneca, Novo Nordisk, Boehringer Ingelheim, and Servier; speaker honoraria from Boehringer Ingelheim, Lilly, MSD, Novartis, Novo Nordisk, Janssen, Amgen, Sanofi, AstraZeneca, Abbott, and Menarini; advisory board honoraria from Boehringer Ingelheim, Lilly, Novo Nordisk, AstraZeneca, and Abbott; and support for attending meetings or travel from AstraZeneca, Abbott, and Menarini. KK reports acting as a consultant or speaker for or receiving grants for investigator-initiated studies from AstraZeneca, Abbott, Amgen, Bayer, Novartis, Novo Nordisk, Roche, Servier, Sanofi-Aventis, Lilly, MSD, Boehringer Ingelheim, Oramed Pharmaceuticals, and Applied Therapeutics; and being chair of the Scientific Advisory Group for Emergencies Ethnicity Subgroup. All other authors declare no competing interests., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Objectives: Many reverse transcription polymerase chain reaction (RT-PCR) methods exist that can detect SARS-CoV-2 RNA in different matrices. RT-PCR is highly sensitive, although viral RNA may be detected long after active infection has taken place. SARS-CoV-2 proteins have shorter detection windows hence their detection might be more meaningful. Given salivary droplets represent a main source of transmission, we explored the detection of viral RNA and protein using four different detection platforms including SISCAPA peptide immunoaffinity liquid chromatography-mass spectrometry (SISCAPA-LC-MS) using polyclonal capture antibodies., Methods: The SISCAPA-LC MS method was compared to RT-PCR, RT-loop-mediated isothermal amplification (RT-LAMP), and a lateral flow rapid antigen test (RAT) for the detection of virus material in the drool saliva of 102 patients hospitalised after infection with SARS-CoV-2. Cycle thresholds (Ct) of RT-PCR ( E gene) were compared to RT-LAMP time-to-positive (TTP) ( NE and Orf1a genes), RAT optical densitometry measurements (test line/control line ratio) and to SISCAPA-LC-MS for measurements of viral protein., Results: SISCAPA-LC-MS showed low sensitivity (37.7 %) but high specificity (89.8 %). RAT showed lower sensitivity (24.5 %) and high specificity (100 %). RT-LAMP had high sensitivity (83.0 %) and specificity (100.0 %). At high initial viral RNA loads (<20 Ct), results obtained using SISCAPA-LC-MS correlated with RT-PCR (R 2 0.57, p-value 0.002)., Conclusions: Detection of SARS-CoV-2 nucleoprotein in saliva was less frequent than the detection of viral RNA. The SISCAPA-LC-MS method allowed processing of multiple samples in <150 min and was scalable, enabling high throughput., (© 2023 Walter de Gruyter GmbH, Berlin/Boston.)

Competing Interests: KK and AR are supported by the National Institute for Health Research (NIHR) Applied Research Collaboration East Midlands (and the NIHR Leicester Biomedical Research Centre. KK is chair and AR a secretariat of the UK National Long Covid Research Working Group. KK was chair of the Ethnicity Subgroup of the UK Scientific Advisory Group for Emergencies (SAGE) and is a member of SAGE.

Background: Restrictions implemented by governments during the coronavirus disease 2019 (COVID-19) pandemic affected people's eating habits and physical activity. We investigated the effect of COVID-19 lockdowns and restrictions on body mass index (BMI) and weight in a UK population, according to BMI class, sex, age and ethnicity., Methods: This retrospective observational cohort study used the Clinical Practice Research Datalink AURUM database. Baseline spanned from 22 March 2017-22 March 2020, and the follow-up lockdown period was from 23 March 2020 (start of the lockdown in the UK) to 13 March 2021. The descriptive analysis included individuals with ≥ 1 valid BMI/weight measurements during both the baseline and follow-up periods, while the model-based analysis comprised individuals with ≥ 1 valid measurement(s) during baseline. Results were stratified by baseline BMI category, sex, age and ethnicity., Results: In the descriptive analysis (n = 273,529), most individuals did not change BMI category post-lockdown (66.4-83.3%). A greater proportion of women (12.6%) than men (9.5%) moved up BMI categories post-lockdown. Compared with older groups, a higher proportion of individuals < 45 years old increased post-lockdown BMI category. The model-based analysis (n = 938,150) revealed consistent trends, where changes in body weight and BMI trajectories pre- and post-lockdown were observed for women and for individuals < 45 years., Conclusion: During COVID-19 restrictions, women and young individuals were more likely than other groups to increase BMI category and weight post-lockdown., Competing Interests: Declaration of Competing Interest Katherine Byrne and Ricardo Reynoso are employees of Novo Nordisk and hold shares. Kamlesh Khunti is supported by the National Institute for Health Research (NIHR) Applied Research Collaboration East Midlands and has acted as a consultant or speaker for, or has received grants for investigator-initiated studies from, AstraZeneca, Bayer, Berlin-Chemie AG/Menarini Group, Boehringer Ingelheim, Janssen, Lilly, Merck Sharp & Dohme, Napp Pharmaceuticals, Novartis, Novo Nordisk and Sanofi-Aventis. Thomas Yates is supported by the NIHR Leicester Biomedical Research Centre and has received investigator-initiated funding for obesity related research from AstraZeneca. Other authors declare no conflicts of interest., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Objectives: To estimate the risk of Long COVID by socioeconomic deprivation and to further examine the inequality by sex and occupation., Design: We conducted a retrospective population-based cohort study using data from the ONS COVID-19 Infection Survey between 26 April 2020 and 31 January 2022. This is the largest nationally representative survey of COVID-19 in the UK with longitudinal data on occupation, COVID-19 exposure and Long COVID., Setting: Community-based survey in the UK., Participants: A total of 201,799 participants aged 16 to 64 years and with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection., Main Outcome Measures: The risk of Long COVID at least 4 weeks after SARS-CoV-2 infection by index of multiple deprivation (IMD) and the modifying effects of socioeconomic deprivation by sex and occupation., Results: Nearly 10% ( n  = 19,315) of participants reported having Long COVID. Multivariable logistic regression models, adjusted for a range of variables (demographic, co-morbidity and time), showed that participants in the most deprived decile had a higher risk of Long COVID (11.4% vs. 8.2%; adjusted odds ratio (aOR): 1.46; 95% confidence interval (CI): 1.34, 1.59) compared to the least deprived decile. Significantly higher inequalities (most vs. least deprived decile) in Long COVID existed in healthcare and patient-facing roles (aOR: 1.76; 95% CI: 1.27, 2.44), in the education sector (aOR: 1.68; 95% CI: 1.31, 2.16) and in women (aOR: 1.56; 95% CI: 1.40, 1.73) than men (aOR: 1.32; 95% CI: 1.15, 1.51)., Conclusions: This study provides insights into the heterogeneous degree of inequality in Long COVID by deprivation, sex and occupation. These findings will help inform public health policies and interventions in incorporating a social justice and health inequality lens.

Background: Concerns have been raised that antipsychotic drug prescribing, which has been associated with increased mortality in people with dementia, might have increased during the COVID-19 pandemic due to social restrictions imposed to limit the spread of SARS-CoV-2. We used multisource, routinely collected health-care data from Wales, UK to investigate prescribing and mortality variations in people with dementia before and during the COVID-19 pandemic., Methods: In this retrospective cohort study, we used individual-level, anonymised, population-scale linked health data to identify adults aged 60 years and older with a diagnosis of dementia in Wales, UK. We used the CVD-COVID-UK initiative to access Welsh routinely collected electronic health record data from the Secure Anonymised Information Linkage (SAIL) Databank. Patients who were alive and registered with a SAIL general practice on Jan 1, 2016, and who received a dementia diagnosis before the age of 60 years and before or during the study period were included. We explored antipsychotic drug prescribing rate changes over 67 months, between Jan 1, 2016, and Aug 1, 2021, overall and stratified by age and dementia subtype. We used time-series analyses to examine all-cause and myocardial infarction and stroke mortality over the study period and identified the leading causes of death in people with dementia between Jan 1, 2020, and Aug 1, 2021., Findings: Of 3 106 690 participants in SAIL between Jan 1, 2016 and Aug 1, 2021, 57 396 people (35 148 [61·2%] women and 22 248 [38·8%] men) met inclusion criteria for this study and contributed 101 428 person-years of follow-up. Of the 57 396 people with dementia, 11 929 (20·8%) were prescribed an antipsychotic drug at any point during follow-up. Accounting for seasonality, antipsychotic drug prescribing increased during the second half of 2019 and throughout 2020. However, the absolute difference in prescribing rates was small, ranging from 1253 prescriptions per 10 000 person-months in March, 2019, to 1305 per 10 000 person-months in September, 2020. All-cause mortality and stroke mortality increased throughout 2020, while myocardial infarction mortality declined. From Jan 1, 2020, to Aug 1, 2021, 1286 (17·1%) of 7508 participants who died had COVID-19 recorded as the underlying cause of death., Interpretation: During the COVID-19 pandemic, antipsychotic drug prescribing in people with dementia in the UK increased slightly; however, it is unlikely that this was solely related to the pandemic and this increase was unlikely to be a major factor in the substantial increase in mortality during 2020. The long-term increase in antipsychotic drug prescribing in younger people and in those with Alzheimer's disease warrants further investigation using resources with access to more granular clinical data. Although deprescribing antipsychotic medications remains an essential aspect of dementia care, the results of this study suggest that changes in prescribing and deprescribing practices as a result of the COVID-19 pandemic are not required., Funding: British Heart Foundation (via the British Heart Foundation Data Science Centre led by Health Data Research UK), and the Scottish Neurological Research Fund., Competing Interests: Declaration of interests CLMS reports a £10 million research grant from 2020 to 2024 to enable set-up of the British Heart Foundation Data Science Centre within Health Data Research UK, the UK's institute for health data science, which as part of its activities has worked with Secure Anonymised Information Linkage Wales (including a small investment of about £130 000 to enable access to the data relevant to this study); and is the Director of the British Heart Foundation Data Science Centre. CS was a co-investigator on a grant paid by the Benter Foundation to the University of Edinburgh, Edinburgh, UK, for dementia research. All other authors declare no competing interests., (Copyright © 2023 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Background In the past few decades, diabetes-related cardiovascular mortality has been steadily declining. However, the impact of the COVID19 pandemic on this trend has not been previously defined. Methods and Results Diabetes-related cardiovascular mortality data were extracted for each year between 1999 and 2020 from the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (WONDER) database. Regression analysis was used to calculate the trend in the 2 decades before the pandemic (1999-2019) and thereby estimate the excess cardiovascular mortality in 2020. There was a 29.2% fall in the diabetes-related cardiovascular age-adjusted mortality rate between 1999 to 2019, largely driven by a 41% decrease in ischemic heart disease deaths. In comparison to 2019, there was an overall 15.5% increase in the diabetes-related cardiovascular age-adjusted mortality rate in the first year of the pandemic, mainly due to a 14.1% rise in ischemic heart disease deaths. Younger patients (under 55 years) and the Black population experienced the greatest increase in diabetes-related cardiovascular age-adjusted mortality rate (24.0% and 25.3%, respectively). Trend analysis estimated 16 009 excess diabetes-related cardiovascular deaths in 2020, with the majority due to ischemic heart disease (8504). Black and Hispanic or Latino populations had at least one-fifth of their 2020 diabetes-related cardiovascular age-adjusted mortality rate as excess deaths (22.3% and 20.2%, respectively). Conclusions There was a sharp rise in diabetes-related cardiovascular mortality during the first pandemic year. Black, Hispanic or Latino, and young people showed the largest increases in diabetes-related cardiovascular mortality. Targeted health policies could help address the disparities observed in this analysis.

The SARS-CoV-2 pandemic has had an unprecedented effect on global health, mortality and healthcare provision. Diabetes has emerged as a key disease entity over the pandemic period, influencing outcomes from COVID-19 but also a tantalising hypothesis that the virus itself may be inducing diabetes. An uptick in diabetes cases over the pandemic has been noted for both type 1 diabetes (in children) and type 2 diabetes but understanding how this increase in incidence relates to the pandemic is challenging. It remains unclear whether indirect effects of the pandemic on behaviour, lifestyle and health have contributed to the increase; whether the virus itself has somehow mediated new-onset diabetes or whether other factors such as stress hyperglycaemic of steroid treatment during COVID-19 infection have played a roll. Within the myriad possibilities are some real challenges in interpreting epidemiological data, assigning diabetes type and understanding what in vitro data are telling us. In this review article we address the issue of newly-diagnosed diabetes during the pandemic, reviewing both epidemiological and basic science data and bringing together both strands of this emerging story., (Copyright © 2023. Published by Elsevier Ltd.)

Aims: To investigate characteristics of people hospitalized with coronavirus-disease-2019 (COVID-19) and diabetic ketoacidosis (DKA) or hyperosmolar hyperglycaemic state (HHS), and to identify risk factors for mortality and intensive care admission., Materials and Methods: Retrospective cohort study with anonymized data from the Association of British Clinical Diabetologists nationwide audit of hospital admissions with COVID-19 and diabetes, from start of pandemic to November 2021. The primary outcome was inpatient mortality. DKA and HHS were adjudicated against national criteria. Age-adjusted odds ratios were calculated using logistic regression., Results: In total, 85 confirmed DKA cases, and 20 HHS, occurred among 4073 people (211 type 1 diabetes, 3748 type 2 diabetes, 114 unknown type) hospitalized with COVID-19. Mean (SD) age was 60 (18.2) years in DKA and 74 (11.8) years in HHS (p < .001). A higher proportion of patients with HHS than with DKA were of non-White ethnicity (71.4% vs 39.0% p = .038). Mortality in DKA was 36.8% (n = 57) and 3.8% (n = 26) in type 2 and type 1 diabetes respectively. Among people with type 2 diabetes and DKA, mortality was lower in insulin users compared with non-users [21.4% vs. 52.2%; age-adjusted odds ratio 0.13 (95% CI 0.03-0.60)]. Crude mortality was lower in DKA than HHS (25.9% vs. 65.0%, p = .001) and in statin users versus non-users (36.4% vs. 100%; p = .035) but these were not statistically significant after age adjustment., Conclusions: Hospitalization with COVID-19 and adjudicated DKA is four times more common than HHS but both associate with substantial mortality. There is a strong association of previous insulin therapy with survival in type 2 diabetes-associated DKA., (© 2023 The Authors. Diabetes, Obesity and Metabolism published by John Wiley & Sons Ltd.)

Introduction: There are limited data on the outcomes of COVID-19 risk assessment in healthcare workers (HCWs) or the association of ethnicity, other sociodemographic and occupational factors with risk assessment outcomes., Methods: We used questionnaire data from UK-REACH (UK Research study into Ethnicity And COVID-19 outcomes in Healthcare workers), an ethnically diverse, nationwide cohort of UK HCWs. We derived four binary outcomes: (1) offered a risk assessment; (2) completed a risk assessment; (3) working practices changed as a result of the risk assessment; (4) wanted changes to working practices after risk assessment but working practices did not change.We examined the association of ethnicity, other sociodemographic/occupational factors and actual/perceived COVID-19 risk variables on our outcomes using multivariable logistic regression., Results: 8649 HCWs were included in total. HCWs from ethnic minority groups were more likely to report being offered a risk assessment than white HCWs, and those from Asian and black ethnic groups were more likely to report having completed an assessment if offered. Ethnic minority HCWs had lower odds of reporting having their work change as a result of risk assessment. Those from Asian and black ethnic groups were more likely to report no changes to their working practices despite wanting them.Previous SARS-CoV-2 infection was associated with lower odds of being offered a risk assessment and having adjustments made to working practices., Discussion: We found differences in risk assessment outcomes by ethnicity, other sociodemographic/occupational factors and actual/perceived COVID-19 risk factors. These findings are concerning and warrant further research using actual (rather than reported) risk assessment outcomes in an unselected cohort., Competing Interests: Competing interests: KK is Director of the University of Leicester Centre for Black Minority Ethnic Health, Trustee of the South Asian Health Foundation and Chair of the Ethnicity Subgroup of the UK Government Scientific Advisory Group for Emergencies (SAGE). MP reports grants from Sanofi, grants and personal fees from Gilead Sciences and personal fees from QIAGEN, outside the submitted work., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY. Published by BMJ.)

Objectives: To derive and validate risk prediction algorithms (QCOVID4) to estimate the risk of covid-19 related death and hospital admission in people with a positive SARS-CoV-2 test result during the period when the omicron variant of the virus was predominant in England, and to evaluate performance compared with a high risk cohort from NHS Digital., Design: Cohort study., Setting: QResearch database linked to English national data on covid-19 vaccinations, SARS-CoV-2 test results, hospital admissions, and cancer and mortality data, 11 December 2021 to 31 March 2022, with follow-up to 30 June 2022., Participants: 1.3 million adults in the derivation cohort and 0.15 million adults in the validation cohort, aged 18-100 years, with a positive test result for SARS-CoV-2 infection., Main Outcome Measures: Primary outcome was covid-19 related death and secondary outcome was hospital admission for covid-19. Risk equations with predictor variables were derived from models fitted in the derivation cohort. Performance was evaluated in a separate validation cohort., Results: Of 1 297 922 people with a positive test result for SARS-CoV-2 infection in the derivation cohort, 18 756 (1.5%) had a covid-19 related hospital admission and 3878 (0.3%) had a covid-19 related death during follow-up. The final QCOVID4 models included age, deprivation score and a range of health and sociodemographic factors, number of covid-19 vaccinations, and previous SARS-CoV-2 infection. The risk of death related to covid-19 was lower among those who had received a covid-19 vaccine, with evidence of a dose-response relation (42% risk reduction associated with one vaccine dose and 92% reduction with four or more doses in men). Previous SARS-CoV-2 infection was associated with a reduction in the risk of covid-19 related death (49% reduction in men). The QCOVID4 algorithm for covid-19 explained 76.0% (95% confidence interval 73.9% to 78.2%) of the variation in time to covid-19 related death in men with a D statistic of 3.65 (3.43 to 3.86) and Harrell's C statistic of 0.970 (0.962 to 0.979). Results were similar for women. QCOVID4 was well calibrated. QCOVID4 was substantially more efficient than the NHS Digital algorithm for correctly identifying patients at high risk of covid-19 related death. Of the 461 covid-19 related deaths in the validation cohort, 333 (72.2%) were in the QCOVID4 high risk group and 95 (20.6%) in the NHS Digital high risk group., Conclusion: The QCOVID4 risk algorithm, modelled from data during the period when the omicron variant of the SARS-CoV-2 virus was predominant in England, now includes vaccination dose and previous SARS-CoV-2 infection, and predicted covid-19 related death among people with a positive test result. QCOVID4 more accurately identified individuals at the highest levels of absolute risk for targeted interventions than the approach adopted by NHS Digital. QCOVID4 performed well and could be used for targeting treatments for covid-19 disease., Competing Interests: Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/disclosure-of-interest/ and declare support from the National Institute for Health and Care Research (NIHR), the John Fell Oxford University Press Research Fund, Cancer Research UK, and Oxford Wellcome Institutional Strategic Support Fund for the submitted work; JH-C reports grants from NIHR Biomedical Research Centre, Oxford, John Fell Oxford University Press Research Fund, Cancer Research UK, through the Cancer Research UK Oxford Centre, Oxford Wellcome Institutional Strategic Support Fund, and other research councils, during the conduct of the study; JH-C is an unpaid director of QResearch, a not-for-profit organisation which is a partnership between the University of Oxford and EMIS Health who supplied the QResearch database used for this work; JH-C is a founder and shareholder of ClinRisk and was its medical director until 31 May 2019. ClinRisk produces open and closed source software to implement clinical risk algorithms (outside this work) into clinical computer systems; JH-C was chair of the NERVTAG (New and Emerging Respiratory Virus Threats Advisory Group) risk stratification subgroup and a member of SAGE (Scientific Advisory Group for Emergencies) covid-19 groups and the NHS group advising on prioritisation of use of monoclonal antibodies in covid-19 infection; CACC reports receiving personal fees from ClinRisk, outside this work and was a member of the NERVTAG risk stratification subgroup; KK is supported by NIHR Applied Research Collaboration East Midlands (ARC-EM) and the NIHR Biomedical Research Centre; KK is chair of the ethnic subgroup of UK SAGE and a member of SAGE; AS has received research grants from NIHR, Medical Research Council, Health Data Research UK, Central Statistics Office, National Childcare Scheme, and GSK for covid-19 work, and has provided advice for AstraZeneca’s Thrombotic Thrombocytopenic Taskforce and the UK and Scottish Government covid-19 advisory groups (roles unremunerated); no financial relationships with any organizations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work., (© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Although morbidity and mortality from COVID-19 have been widely reported, the indirect effects of the pandemic beyond 2020 on other major diseases and health service activity have not been well described., Methods and Results: Analyses used national administrative electronic hospital records in England, Scotland, and Wales for 2016-21. Admissions and procedures during the pandemic (2020-21) related to six major cardiovascular conditions [acute coronary syndrome (ACS), heart failure (HF), stroke/transient ischaemic attack (TIA), peripheral arterial disease (PAD), aortic aneurysm (AA), and venous thromboembolism(VTE)] were compared with the annual average in the pre-pandemic period (2016-19). Differences were assessed by time period and urgency of care.In 2020, there were 31 064 (-6%) fewer hospital admissions [14 506 (-4%) fewer emergencies, 16 560 (-23%) fewer elective admissions] compared with 2016-19 for the six major cardiovascular diseases (CVDs) combined. The proportional reduction in admissions was similar in all three countries. Overall, hospital admissions returned to pre-pandemic levels in 2021. Elective admissions remained substantially below expected levels for almost all conditions in all three countries [-10 996 (-15%) fewer admissions]. However, these reductions were offset by higher than expected total emergency admissions [+25 878 (+6%) higher admissions], notably for HF and stroke in England, and for VTE in all three countries. Analyses for procedures showed similar temporal variations to admissions., Conclusion: The present study highlights increasing emergency cardiovascular admissions during the pandemic, in the context of a substantial and sustained reduction in elective admissions and procedures. This is likely to increase further the demands on cardiovascular services over the coming years., (© The Author(s) 2022. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Recent health policies in the United Kingdom (UK) and internationally have focussed on digitisation of healthcare. We examined UK policies for evidence of government action addressing health inequalities and digital health, using cardiometabolic disease as an exemplar. Using a systematic search methodology, we identified 87 relevant policy documents published between 2010 and 2022. We found increasing emphasis on digital health, including for prevention, diagnosis and management of cardiometabolic disease. Several policies also focused on tackling health inequalities and improving digital access. The COVID-19 pandemic amplified inequalities. No policies addressed ethnic inequalities in digital health for cardiometabolic disease, despite high prevalence in minority ethnic communities. Our findings suggest that creating opportunities for digital inclusion and reduce longer-term health inequalities, will require future policies to focus on: the heterogeneity of ethnic groups; cross-sectoral disadvantages which contribute to disease burden and digital accessibility; and disease-specific interventions which lend themselves to culturally tailored solutions., (© 2023. The Author(s).)

Introduction: Older people were at particular risk of morbidity and mortality during COVID-19. Consequently, they experienced formal (externally imposed) and informal (self-imposed) periods of social isolation and quarantine. This is hypothesised to have led to physical deconditioning, new-onset disability and frailty. Disability and frailty are not routinely collated at population level but are associated with increased risk of falls and fractures, which result in hospital admissions. First, we will examine incidence of falls and fractures during COVID-19 (January 2020-March 2022), focusing on differences between incidence over time against expected rates based on historical data, to determine whether there is evidence of new-onset disability and frailty. Second, we will examine whether those with reported SARS-CoV-2 were at higher risk of falls and fractures., Methods and Analysis: This study uses the Office for National Statistics (ONS) Public Health Data Asset, a linked population-level dataset combining administrative health records with sociodemographic data of the 2011 Census and National Immunisation Management System COVID-19 vaccination data for England. Administrative hospital records will be extracted based on specific fracture-centric International Classification of Diseases-10 codes in years preceding COVID-19 (2011-2020). Historical episode frequency will be used to predict expected admissions during pandemic years using time series modelling, if COVID-19 had not occurred. Those predicted admission figures will be compared with actual admissions to assess changes in hospital admissions due to public health measures comprising the pandemic response. Hospital admissions in prepandemic years will be stratified by age and geographical characteristics and averaged, then compared with pandemic year admissions to assess more granular changes. Risk modelling will assess risk of experiencing a fall, fracture or frail fall and fracture, if they have reported a positive case of COVID-19. The combination of these techniques will provide insight into changes in hospital admissions from the COVID-19 pandemic., Ethics and Dissemination: This study has approval from the National Statistician's Data Ethics Advisory Committee (NSDEC(20)12). Results will be made available to other researchers via academic publication and shared via the ONS website., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Introduction: At the start of the COVID-19 pandemic there was an urgent need to identify individuals at highest risk of severe outcomes, such as hospitalisation and death following infection. The QCOVID risk prediction algorithms emerged as key tools in facilitating this which were further developed during the second wave of the COVID-19 pandemic to identify groups of people at highest risk of severe COVID-19 related outcomes following one or two doses of vaccine., Objectives: To externally validate the QCOVID3 algorithm based on primary and secondary care records for Wales, UK., Methods: We conducted an observational, prospective cohort based on electronic health care records for 1.66m vaccinated adults living in Wales on 8th December 2020, with follow-up until 15th June 2021. Follow-up started from day 14 post vaccination to allow the full effect of the vaccine., Results: The scores produced by the QCOVID3 risk algorithm showed high levels of discrimination for both COVID-19 related deaths and hospital admissions and good calibration (Harrell C statistic: ≥ 0.828)., Conclusion: This validation of the updated QCOVID3 risk algorithms in the adult vaccinated Welsh population has shown that the algorithms are valid for use in the Welsh population, and applicable on a population independent of the original study, which has not been previously reported. This study provides further evidence that the QCOVID algorithms can help inform public health risk management on the ongoing surveillance and intervention to manage COVID-19 related risks., Competing Interests: KK is Chair of the Ethnicity Subgroup of the UK Scientific Advisory Group for Emergencies (SAGE) and Member of SAGE. AS is a member of the Scottish Government Chief Medical Officer’s COVID-19 Advisory Group, the Scottish Government’s Standing Committee on Pandemic Preparedness, the UK Government’s New and Emerging Respiratory Virus Threats Advisory Group (NERVTAG) Risk Stratification Subgroup, the Department of Health and Social Care’s COVID-19 Therapeutics Modelling Group and was a member of Astra-Zeneca’s COVID-19 Strategic Thrombocytopenia Taskforce. All AS’ roles are unfunded. JHC is a member of SAGE subgroups and chair of the NERVTAG subgroup on risk stratification and several DHSC therapeutics modelling advisory groups. RAL is a member of the Welsh Government COVID-19 Technical Advisory Group., (Copyright: © 2023 Lyons et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

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., (© 2023 by the American Diabetes Association.)

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 (HbA 1c 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., (© 2022 The Authors. Diabetic Medicine published by John Wiley & Sons Ltd on behalf of Diabetes UK.)

Background: The COVID-19 pandemic has highlighted health disparities affecting ethnic minority communities. There is growing concern about the lack of diversity in clinical trials. This study aimed to assess the representation of ethnic groups in UK-based COVID-19 randomised controlled trials (RCTs)., Methods: A systematic review and meta-analysis were undertaken. A search strategy was developed for MEDLINE (Ovid) and Google Scholar (1st January 2020-4th May 2022). Prospective COVID-19 RCTs for vaccines or therapeutics that reported UK data separately with a minimum of 50 participants were eligible. Search results were independently screened, and data extracted into proforma. Percentage of ethnic groups at all trial stages was mapped against Office of National Statistics (ONS) statistics. Post hoc DerSimonian-Laird random-effects meta-analysis of percentages and a meta-regression assessing recruitment over time were conducted. Due to the nature of the review question, risk of bias was not assessed. Data analysis was conducted in Stata v17.0. A protocol was registered (PROSPERO CRD42021244185)., Results: In total, 5319 articles were identified; 30 studies were included, with 118,912 participants. Enrolment to trials was the only stage consistently reported (17 trials). Meta-analysis showed significant heterogeneity across studies, in relation to census-expected proportions at study enrolment. All ethnic groups, apart from Other (1.7% [95% CI 1.1-2.8%] vs ONS 1%) were represented to a lesser extent than ONS statistics, most marked in Black (1% [0.6-1.5%] vs 3.3%) and Asian (5.8% [4.4-7.6%] vs 7.5%) groups, but also apparent in White (84.8% [81.6-87.5%] vs 86%) and Mixed 1.6% [1.2-2.1%] vs 2.2%) groups. Meta-regression showed recruitment of Black participants increased over time (p = 0.009)., Conclusions: Asian, Black and Mixed ethnic groups are under-represented or incorrectly classified in UK COVID-19 RCTs. Reporting by ethnicity lacks consistency and transparency. Under-representation in clinical trials occurs at multiple levels and requires complex solutions, which should be considered throughout trial conduct. These findings may not apply outside of the UK setting., (© 2023. The Author(s).)

Several studies have reported associations between COVID-19 vaccination and risk of cardiac diseases, especially in young people; the impact on mortality, however, remains unclear. We use national, linked electronic health data in England to assess the impact of COVID-19 vaccination and positive SARS-CoV-2 tests on the risk of cardiac and all-cause mortality in young people (12 to 29 years) using a self-controlled case series design. Here, we show there is no significant increase in cardiac or all-cause mortality in the 12 weeks following COVID-19 vaccination compared to more than 12 weeks after any dose. However, we find an increase in cardiac death in women after a first dose of non mRNA vaccines. A positive SARS-CoV-2 test is associated with increased cardiac and all-cause mortality among people vaccinated or unvaccinated at time of testing., (© 2023. Crown.)

Background: Despite generally high coronavirus disease 2019 (COVID-19) vaccination rates in the UK, vaccination hesitancy and lower take-up rates have been reported in certain ethnic minority communities., Methods: We used vaccination data from the National Immunisation Management System (NIMS) linked to the 2011 Census and individual health records for subjects aged ≥40 years (n = 24 094 186). We estimated age-standardized vaccination rates, stratified by ethnic group and key sociodemographic characteristics, such as religious affiliation, deprivation, educational attainment, geography, living conditions, country of birth, language skills and health status. To understand the association of ethnicity with lower vaccination rates, we conducted a logistic regression model adjusting for differences in geographic, sociodemographic and health characteristics. ResultsAll ethnic groups had lower age-standardized rates of vaccination compared with the white British population, whose vaccination rate of at least one dose was 94% (95% CI: 94%-94%). Black communities had the lowest rates, with 75% (74-75%) of black African and 66% (66-67%) of black Caribbean individuals having received at least one dose. The drivers of these lower rates were partly explained by accounting for sociodemographic differences. However, modelled estimates showed significant differences remained for all minority ethnic groups, compared with white British individuals., Conclusions: Lower COVID-19 vaccination rates are consistently observed amongst all ethnic minorities., (© The Author(s) 2022. Published by Oxford University Press on behalf of Faculty of Public Health.)

Background: Heterogeneous studies have demonstrated ethnic inequalities in the risk of SARS-CoV-2 infection and adverse COVID-19 outcomes. This study evaluates the association between ethnicity and COVID-19 outcomes in two large population-based cohorts from England and Canada and investigates potential explanatory factors for ethnic patterning of severe outcomes., Methods: We identified adults aged 18 to 99 years in the QResearch primary care (England) and Ontario (Canada) healthcare administrative population-based datasets (start of follow-up: 24th and 25th Jan 2020 in England and Canada, respectively; end of follow-up: 31st Oct and 30th Sept 2020, respectively). We harmonised the definitions and the design of two cohorts to investigate associations between ethnicity and COVID-19-related death, hospitalisation, and intensive care (ICU) admission, adjusted for confounders, and combined the estimates obtained from survival analyses. We calculated the 'percentage of excess risk mediated' by these risk factors in the QResearch cohort., Results: There were 9.83 million adults in the QResearch cohort (11,597 deaths; 21,917 hospitalisations; 2932 ICU admissions) and 10.27 million adults in the Ontario cohort (951 deaths; 5132 hospitalisations; 1191 ICU admissions). Compared to the general population, pooled random-effects estimates showed that South Asian ethnicity was associated with an increased risk of COVID-19 death (hazard ratio: 1.63, 95% CI: 1.09-2.44), hospitalisation (1.53; 1.32-1.76), and ICU admission (1.67; 1.23-2.28). Associations with ethnic groups were consistent across levels of deprivation. In QResearch, sociodemographic, lifestyle, and clinical factors accounted for 42.9% (South Asian) and 39.4% (Black) of the excess risk of COVID-19 death., Conclusion: International population-level analyses demonstrate clear ethnic inequalities in COVID-19 risks. Policymakers should be cognisant of the increased risks in some ethnic populations and design equitable health policy as the pandemic continues., (© 2023. The Author(s).)

Background: Post-viral syndromes (PVS), including Long COVID, are symptoms sustained from weeks to years following an acute viral infection. Non-pharmacological treatments for these symptoms are poorly understood. This review summarises the evidence for the effectiveness of non-pharmacological treatments for PVS., Methods: We conducted a systematic review to evaluate the effectiveness of non-pharmacological interventions for PVS, as compared to either standard care, alternative non-pharmacological therapy, or placebo. The outcomes of interest were changes in symptoms, exercise capacity, quality of life (including mental health and wellbeing), and work capability. We searched five databases (Embase, MEDLINE, PsycINFO, CINAHL, MedRxiv) for randomised controlled trials (RCTs) published between 1 January 2001 to 29 October 2021. The relevant outcome data were extracted, the study quality was appraised using the Cochrane risk-of-bias tool, and the findings were synthesised narratively., Findings: Overall, five studies of five different interventions (Pilates, music therapy, telerehabilitation, resistance exercise, neuromodulation) met the inclusion criteria. Aside from music-based intervention, all other selected interventions demonstrated some support in the management of PVS in some patients., Interpretation: In this study, we observed a lack of robust evidence evaluating the non-pharmacological treatments for PVS, including Long COVID. Considering the prevalence of prolonged symptoms following acute viral infections, there is an urgent need for clinical trials evaluating the effectiveness and cost-effectiveness of non-pharmacological treatments for patients with PVS., Registration: The study protocol was registered with PROSPERO [CRD42021282074] in October 2021 and published in BMJ Open in 2022.

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., (© 2022. The Author(s).)

Major ethnic disparities in diabetes care, especially for intermediate outcomes and diabetes complications, were evident prior to the coronavirus disease 2019 (COVID-19) pandemic. Diabetes is a risk factor for severe COVID-19, and the combination of these ethnic disparities in diabetes care and outcomes may have contributed to the inequity in COVID-19 outcomes for people with diabetes. Overall, ethnic minority populations have suffered disproportionate rates of COVID-19 hospitalization and mortality. Results from the limited number of studies of COVID-19 in ethnic minority populations with diabetes are mixed, but there is some suggestion that rates of hospitalization and mortality are higher than those of White populations. Reasons for the higher incidence and severity of COVID-19-related outcomes in minority ethnic groups are complex and have been shown to be due to differences in comorbid conditions (e.g., diabetes), exposure risk (e.g., overcrowded living conditions or essential worker jobs), and access to treatment (e.g., health insurance status and access to tertiary care medical centers), which all relate to long-standing structural inequities that vary by ethnicity. While guidelines and approaches for diabetes self-management and outpatient and inpatient care during the pandemic have been published, few have recommended addressing wider structural issues. As we now plan for the recovery and improved surveillance and risk factor management, it is imperative that primary and specialist care services urgently address the disproportionate impact the pandemic has had on ethnic minority groups. This should include a focus on the larger structural barriers in society that put ethnic minorities with diabetes at potentially greater risk for poor COVID-19 outcomes., (© 2023 by the American Diabetes Association.)

Background: The CVD-COVID-UK consortium was formed to understand the relationship between COVID-19 and cardiovascular diseases through analyses of harmonised electronic health records (EHRs) across the four UK nations. Beyond COVID-19, data harmonisation and common approaches enable analysis within and across independent Trusted Research Environments. Here we describe the reproducible harmonisation method developed using large-scale EHRs in Wales to accommodate the fast and efficient implementation of cross-nation analysis in England and Wales as part of the CVD-COVID-UK programme. We characterise current challenges and share lessons learnt., Methods: Serving the scope and scalability of multiple study protocols, we used linked, anonymised individual-level EHR, demographic and administrative data held within the SAIL Databank for the population of Wales. The harmonisation method was implemented as a four-layer reproducible process, starting from raw data in the first layer. Then each of the layers two to four is framed by, but not limited to, the characterised challenges and lessons learnt. We achieved curated data as part of our second layer, followed by extracting phenotyped data in the third layer. We captured any project-specific requirements in the fourth layer., Results: Using the implemented four-layer harmonisation method, we retrieved approximately 100 health-related variables for the 3.2 million individuals in Wales, which are harmonised with corresponding variables for > 56 million individuals in England. We processed 13 data sources into the first layer of our harmonisation method: five of these are updated daily or weekly, and the rest at various frequencies providing sufficient data flow updates for frequent capturing of up-to-date demographic, administrative and clinical information., Conclusions: We implemented an efficient, transparent, scalable, and reproducible harmonisation method that enables multi-nation collaborative research. With a current focus on COVID-19 and its relationship with cardiovascular outcomes, the harmonised data has supported a wide range of research activities across the UK., (© 2023. The Author(s).)

Background: Ethnic minority groups in England have been disproportionately affected by the COVID-19 pandemic and have lower vaccination rates than the White British population. We examined whether ethnic differences in COVID-19 mortality in England have continued since the vaccine rollout and to what extent differences in vaccination rates contributed to excess COVID-19 mortality after accounting for other risk factors., Methods: We conducted a retrospective, population-based cohort study of 28.8 million adults aged 30-100 years in England. Self-reported ethnicity was obtained from the 2011 Census. The outcome was death involving COVID-19 during the second (8 December 2020 to 12 June 2021) and third wave (13 June 2021 to 1 December 2021). We calculated hazard ratios (HRs) for death involving COVID-19, sequentially adjusting for age, residence type, geographical factors, sociodemographic characteristics, pre-pandemic health, and vaccination status., Results: Age-adjusted HRs of death involving COVID-19 were elevated for most ethnic minority groups during both waves, particularly for groups with lowest vaccination rates (Bangladeshi, Pakistani, Black African, and Black Caribbean). HRs were attenuated after adjusting for geographical factors, sociodemographic characteristics, and pre-pandemic health. Further adjusting for vaccination status substantially reduced residual HRs for Black African, Black Caribbean, and Pakistani groups in the third wave. Fully adjusted HRs only remained elevated for the Bangladeshi group (men: 2.19 [95% CI 1.72-2.78]; women: 2.12 [1.58-2.86]) and Pakistani men (1.24 [1.06-1.46])., Conclusions: Lower COVID-19 vaccination uptake in several ethnic minority groups may drive some of the differences in COVID-19 mortality compared to White British. Public health strategies to increase vaccination uptake in ethnic minority groups would help reduce inequalities in COVID-19 mortality, which have remained substantial since the start of the vaccination campaign., (© 2023. Crown.)

How the Coronavirus Disease 2019 (COVID-19) pandemic has affected prevention and management of cardiovascular disease (CVD) is not fully understood. In this study, we used medication data as a proxy for CVD management using routinely collected, de-identified, individual-level data comprising 1.32 billion records of community-dispensed CVD medications from England, Scotland and Wales between April 2018 and July 2021. Here we describe monthly counts of prevalent and incident medications dispensed, as well as percentage changes compared to the previous year, for several CVD-related indications, focusing on hypertension, hypercholesterolemia and diabetes. We observed a decline in the dispensing of antihypertensive medications between March 2020 and July 2021, with 491,306 fewer individuals initiating treatment than expected. This decline was predicted to result in 13,662 additional CVD events, including 2,281 cases of myocardial infarction and 3,474 cases of stroke, should individuals remain untreated over their lifecourse. Incident use of lipid-lowering medications decreased by 16,744 patients per month during the first half of 2021 as compared to 2019. By contrast, incident use of medications to treat type 2 diabetes mellitus, other than insulin, increased by approximately 623 patients per month for the same time period. In light of these results, methods to identify and treat individuals who have missed treatment for CVD risk factors and remain undiagnosed are urgently required to avoid large numbers of excess future CVD events, an indirect impact of the COVID-19 pandemic., (© 2023. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Aim: To provide a detailled analysis of the microvascular burden in patients with diabetes hopitalized for COVD-19., Materials and Methods: We analysed data from the French CORONADO initiative and the UK Association of British Clinical Diabetologists (ABCD) COVID-19 audit, two nationwide multicentre studies, and the AMERICADO, a multicentre study conducted in New York area. We assessed the association between risk of all-cause death during hospital stay and the following microvascular complications in patients with diabetes hospitalized for COVID-19: diabetic retinopathy and/or diabetic kidney disease and/or history of diabetic foot ulcer., Results: Among 2951 CORONADO, 3387 ABCD COVID-19 audit and 9327 AMERICADO participants, microvascular diabetic complications status was ascertained for 1314 (44.5%), 1809 (53.4%) and 7367 (79.0%) patients, respectively: 1010, 1059 and 1800, respectively, had ≥1 severe microvascular complication(s) and 304, 750 and 5567, respectively, were free of any complications. The patients with isolated diabetic kidney disease had an increased risk of all-cause death during hospital stay: odds ratio [OR] 2.53 (95% confidence interval [CI] 1.66-3.83), OR 1.24 (95% CI 1.00-1.56) and OR 1.66 (95% CI 1.40-1.95) in the CORONADO, the ABCD COVID-19 national audit and the AMERICADO studies, respectively. After adjustment for age, sex, hypertension and cardiovascular disease (CVD), compared to those without microvascular complications, patients with microvascular complications had an increased risk of all-cause death during hospital stay in the CORONADO, the ABCD COVID-19 diabetes national audit and the AMERICADO studies: adjusted OR ( adj OR) 2.57 (95% CI 1.69-3.92), adj OR 1.22 (95% CI 1.00-1.52) and adj OR 1.33 (95% CI 1.15-1.53), respectively. In meta-analysis of the three studies, compared to patients free of complications, those with microvascular complications had an unadjusted OR for all-cause death during hospital stay of 2.05 (95% CI 1.42-2.97), which decreased to 1.62 (95% CI 1.19-2.119) after adjustment for age and sex, and to 1.50 (1.12-2.02) after hypertension and CVD were further added to the model., Conclusion: Microvascular burden is associated with an increased risk of death in patients hospitalized for COVID-19., (© 2022 The Authors. Diabetes, Obesity and Metabolism published by John Wiley & Sons Ltd.)

Objectives: To use national, pre- and post-pandemic electronic health records (EHR) to develop and validate a scenario-based model incorporating baseline mortality risk, infection rate (IR) and relative risk (RR) of death for prediction of excess deaths., Design: An EHR-based, retrospective cohort study., Setting: Linked EHR in Clinical Practice Research Datalink (CPRD); and linked EHR and COVID-19 data in England provided in NHS Digital Trusted Research Environment (TRE)., Participants: In the development (CPRD) and validation (TRE) cohorts, we included 3.8 million and 35.1 million individuals aged ≥30 years, respectively., Main Outcome Measures: One-year all-cause excess deaths related to COVID-19 from March 2020 to March 2021., Results: From 1 March 2020 to 1 March 2021, there were 127,020 observed excess deaths. Observed RR was 4.34% (95% CI, 4.31-4.38) and IR was 6.27% (95% CI, 6.26-6.28). In the validation cohort, predicted one-year excess deaths were 100,338 compared with the observed 127,020 deaths with a ratio of predicted to observed excess deaths of 0.79., Conclusions: We show that a simple, parsimonious model incorporating baseline mortality risk, one-year IR and RR of the pandemic can be used for scenario-based prediction of excess deaths in the early stages of a pandemic. Our analyses show that EHR could inform pandemic planning and surveillance, despite limited use in emergency preparedness to date. Although infection dynamics are important in the prediction of mortality, future models should take greater account of underlying conditions.