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Purpose The rate of cataract surgery in Outer North East London (ONEL) is significantly higher than the standardised admission rate (SAR) for England. Financial pressures have forced cost savings by restricting cataract operations, aiming for 22% reduction through new clinical acceptance criteria for the region since April 2011. This involves: 1. Best corrected distance visual acuity 6/10 or worse in the better eye AND Impaired lifestyle due to cataract: OR 2. Severe glare, diplopia or anisometropia >/= 1.5 D Exceptions include: • Significant posterior subcapsular lens opacity despite good vision • If surgery is needed to help co‐manage conditions such as glaucoma or for the view of the retina in patients with diabetic retinopathy Methods Retrospective audit of cataract surgery from Aug 2010 ‐ Dec 2011. Medisoft electronic database query identified patients with VA > 6/9 for case‐note review to ascertain reasons for (non/)compliance with cataract booking criteria. Results 1084 cataract operations were performed. Median age was 73.5 years. n=34 eyes with pre‐op VA 6/9 or better; pre‐April 2011 (9 cases) vs post‐April 2011 (25 cases). Case‐note review revealed: • Glare (8) / Anisometropia (3): 11 • Posterior Subcapsular cataract: 4 • Co‐management of other pathology: 23 Glaucoma (15), Diabetic Retinopathy (7), ARMD (1) • Not valid: 2 Conclusion Rationing must be balanced with individual clinical needs. 99.8% of cataract operations met the new restricted criteria. This sample is an underestimate as not all cataract operations are registered on the Medisoft database. A re‐audit in 6‐8 months would establish compliance and feasibility as policies are tightened. [ABSTRACT FROM AUTHOR]

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.)

Objectives: To classify older adults into clusters based on accumulating long-term conditions (LTC) as trajectories, characterise clusters and quantify their associations with all-cause mortality., Design: We conducted a longitudinal study using the English Longitudinal Study of Ageing over 9 years (n=15 091 aged 50 years and older). Group-based trajectory modelling was used to classify people into clusters based on accumulating LTC over time. Derived clusters were used to quantify the associations between trajectory memberships, sociodemographic characteristics and all-cause mortality by conducting regression models., Results: Five distinct clusters of accumulating LTC trajectories were identified and characterised as: 'no LTC' (18.57%), 'single LTC' (31.21%), 'evolving multimorbidity' (25.82%), 'moderate multimorbidity' (17.12%) and 'high multimorbidity' (7.27%). Increasing age was consistently associated with a larger number of LTCs. Ethnic minorities (adjusted OR=2.04; 95% CI 1.40 to 3.00) were associated with the 'high multimorbidity' cluster. Higher education and paid employment were associated with a lower likelihood of progression over time towards an increased number of LTCs. All the clusters had higher all-cause mortality than the 'no LTC' cluster., Conclusions: The development of multimorbidity in the number of conditions over time follows distinct trajectories. These are determined by non-modifiable (age, ethnicity) and modifiable factors (education and employment). Stratifying risk through clustering will enable practitioners to identify older adults with a higher likelihood of worsening LTC over time to tailor effective interventions to prevent mortality., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY. Published by BMJ.)

We compare the impact of the first two waves of the COVID-19 pandemic on risk of age-standardized mortality by sex, UK country, and English region. Each wave is defined as lasting 26 weeks and are consecutive beginning in 2020 week 11. The expected rate is estimated from 2015 to 2019 mean and the projected mortality trend from the same period are used to estimate excess mortality. By both measures, excess mortality was highest and lowest in regions of England, London and the South-West, respectively. Excess mortality was consistently higher for males than females., (© The Author(s) 2023. Published by Oxford University Press on behalf of the European Public Health Association.)

Introduction: Effective communication can help optimise healthcare interactions and patient outcomes. However, few interventions have been tested clinically, subjected to cost-effectiveness analysis or are sufficiently brief and well-described for implementation in primary care. This paper presents the protocol for determining the effectiveness and cost-effectiveness of a rigorously developed brief eLearning tool, EMPathicO, among patients with and without musculoskeletal pain., Methods and Analysis: A cluster randomised controlled trial in general practitioner (GP) surgeries in England and Wales serving patients from diverse geographic, socioeconomic and ethnic backgrounds. GP surgeries are randomised (1:1) to receive EMPathicO e-learning immediately, or at trial end. Eligible practitioners (eg, GPs, physiotherapists and nurse practitioners) are involved in managing primary care patients with musculoskeletal pain. Patient recruitment is managed by practice staff and researchers. Target recruitment is 840 adults with and 840 without musculoskeletal pain consulting face-to-face, by telephone or video. Patients complete web-based questionnaires at preconsultation baseline, 1 week and 1, 3 and 6 months later. There are two patient-reported primary outcomes: pain intensity and patient enablement. Cost-effectiveness is considered from the National Health Service and societal perspectives. Secondary and process measures include practitioner patterns of use of EMPathicO, practitioner-reported self-efficacy and intentions, patient-reported symptom severity, quality of life, satisfaction, perceptions of practitioner empathy and optimism, treatment expectancies, anxiety, depression and continuity of care. Purposive subsamples of patients, practitioners and practice staff take part in up to two qualitative, semistructured interviews., Ethics Approval and Dissemination: Approved by the South Central Hampshire B Research Ethics Committee on 1 July 2022 and the Health Research Authority and Health and Care Research Wales on 6 July 2022 (REC reference 22/SC/0145; IRAS project ID 312208). Results will be disseminated via peer-reviewed academic publications, conference presentations and patient and practitioner outlets. If successful, EMPathicO could quickly be made available at a low cost to primary care practices across the country., Trial Registration Number: ISRCTN18010240., Competing Interests: Competing interests: All authors have completed the ICMJE uniform disclosure form at http://www.icmje.org/disclosure-of-interest/anddeclare: financial support for the submitted work from the NIHR; CDM is Director of the NIHR School for Primary Care Research; HA has received research grants from NIHR and Research Council of Norway, payment for delivering lecture to GPs in training about remote consultations, travel expenses to attend Scientific Foundation Board meeting; HA is chair of a steering committee at University of Leeds, member of advisory boards at Imperial College London and University of Manchester, and vice-chair of the Scientific Foundation Board Royal College of General Practitioners; HA is Officer at Prof Andrew Beggs Ltd. No other relationships or activities that could appear to have influenced the submitted work., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY. Published by BMJ.)

Background: Metabolic profiling (the extensive measurement of circulating metabolites across multiple biological pathways) is increasingly employed in clinical care. However, there is little evidence on the benefit of metabolic profiling as compared with established atherosclerotic cardiovascular disease (CVD) risk scores., Methods: UK Biobank is a prospective study of 0.5 million participants, aged 40-69 at recruitment. Analyses were restricted to 74 780 participants with metabolic profiling (measured using nuclear magnetic resonance) and without CVD at baseline. Cox regression was used to compare model performance before and after addition of metabolites to QRISK3 (an established CVD risk score used in primary care in England); analyses derived three models, with metabolites selected by association significance or by employing two different machine learning approaches., Results: We identified 5097 incident CVD events within the 10-year follow-up. Harrell's C-index of QRISK3 was 0.750 (95% CI 0.739 to 0.763) for women and 0.706 (95% CI 0.696 to 0.716) for men. Adding selected metabolites did not significantly improve measures of discrimination in women (Harrell's C-index of three models are 0.759 (0.747 to 0.772), 0.759 (0.746 to 0.770) and 0.759 (0.748 to 0.771), respectively) or men (0.710 (0.701 to 0.720), 0.710 (0.700 to 0.719) and 0.710 (0.701 to 0.719), respectively), and neither did it improve reclassification or calibration., Conclusion: This large-scale study applied both conventional and machine learning approaches to assess the potential benefit of metabolic profiling to well-established CVD risk scores. However, there was no evidence that metabolic profiling improved CVD risk prediction in this population., Competing Interests: Competing interests: SL reports grants from the Medical Research Council (MRC) and research funding from the US Centers for Disease Control and Prevention Foundation (with support from Amgen) and from the World Health Organization during the conduct of the study. The Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU) receives research grants from industry that are governed by University of Oxford contracts that protect its independence and has a staff policy of not taking personal payments from industry; further details can be found at https://www.ndph.ox.ac.uk/files/about/ndph-independence-of-research-policy-jun-20.pdf. All other authors declared no conflict of interest., (© Author(s) (or their employer(s)) 2023. No commercial re-use. See rights and permissions. Published by BMJ.)

Background and Aims: We aimed to evaluate the life expectancy following the first cardiovascular disease (CVD) event by type 2 diabetes (T2D) status and ethnicity., Methods and Results: We used the Clinical Practice Research Datalink database in England (UK), linked to the Hospital Episode Statistics information, to identify individuals with and without T2D who survived a first CVD event between 1st Jan 2007 and 31st Dec 2017; subsequent death events were extracted from the Office for National Statistics database. Ethnicity was categorised as White, South Asian (SA), Black, or other. Flexible parametric survival models were used to estimate survival and predict life expectancy. 59,939 individuals with first CVD event were included: 7596 (12.7%) with T2D (60.9% men; mean age at event: 69.7 years [63.2 years in SA, 65.9 in Black, 70.2 in White]) and 52,343 without T2D (56.7% men; 65.9 years [54.7 in Black, 58.2 in SA, 66.3 in White]). Accounting for potential confounders (sex, deprivation, lipid-lowering medication, current smoking, and pre-existing hypertension), comparing individuals with vs without T2D the mortality rate was 53% higher in White (hazard ratio [HR]: 1.53 [95% CI: 1.44, 1.62]), corresponding to a potential loss of 3.87 (3.30, 4.44) life years at the age of 50 years in individuals with T2D. No evidence of a difference in life expectancy was observed in individuals of SA (HR: 0.82 [0.52, 1.29]; -1.36 [-4.58, 1.86] life years), Black (HR: 1.26 [0.59, 2.70]; 1.21 [-2.99, 5.41] life years); and other (HR: 1.64 [0.80, 3.39]; 3.89 [-2.28, 9.99] life years) ethnic group., Conclusion: Following a CVD event, T2D is associated with a different prognosis and life years lost among ethnic groups., Competing Interests: Declaration of competing interest Professor Khunti is the National Lead for multiple long-term conditions for National Institute for Health Research Applied Research Collaboration (NIHR ARC). Professor Khunti has acted as a consultant, speaker or received grants for investigator-initiated studies for Astra Zeneca, Abbott, Amgen, Bayer, Novartis, Novo Nordisk, Roche, Servier, Sanofi-Aventis, Lilly and Merck Sharp & Dohme, Boehringer Ingelheim, Oramed Pharmaceuticals and Applied Therapeutics. Dr Zaccardi is a speaker fees from Napp Pharmaceuticals and Boehringer Ingelheim. Professor Davies has acted as a consultant, advisory board member and speaker for Novo Nordisk, Sanofi-Aventis, Lilly, Merck Sharp & Dohme, Boehringer Ingelheim, AstraZeneca and Janssen, an advisory board member for Servier and Gilead Sciences Ltd and as a speaker for Napp Pharmaceuticals, Mitsubishi Tanabe Pharma Corporation and Takeda Pharmaceuticals International Inc. Professor Davies has received grants in support of investigator and investigator-initiated trials from Novo Nordisk, Sanofi-Aventis, Lilly, Boehringer Ingelheim, AstraZeneca and Janssen. All other authors have no conflict of interest., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

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.)

Estimating real-world vaccine effectiveness is vital to assessing the coronavirus disease 2019 (COVID-19) vaccination program and informing the ongoing policy response. However, estimating vaccine effectiveness using observational data is inherently challenging because of the nonrandomized design and potential for unmeasured confounding. We used a regression discontinuity design to estimate vaccine effectiveness against COVID-19 mortality in England using the fact that people aged 80 years or older were prioritized for the vaccine rollout. The prioritization led to a large discrepancy in vaccination rates among people aged 80-84 years compared with those aged 75-79 at the beginning of the vaccination campaign. We found a corresponding difference in COVID-19 mortality but not in non-COVID-19 mortality, suggesting that our approach appropriately addressed the issue of unmeasured confounding factors. Our results suggest that the first vaccine dose reduced the risk of COVID-19 death by 52.6% (95% confidence limits: 15.7, 73.4) in those aged 80 years, supporting existing evidence that a first dose of a COVID-19 vaccine had a strong protective effect against COVID-19 mortality in older adults. The regression discontinuity model's estimate of vaccine effectiveness is only slightly lower than those of previously published studies using different methods, suggesting that these estimates are unlikely to be substantially affected by unmeasured confounding factors., (© Crown copyright 2022.)

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.)

Obesity and ethnicity are known risk factors for COVID-19 outcomes, but their combination has not been extensively examined. We investigate the association between body mass index (BMI) and COVID-19 mortality across different ethnic groups using linked national Census, electronic health records and mortality data for adults in England from the start of pandemic (January 2020) to December 2020. There were 30,067 (0.27%), 1,208 (0.29%), 1,831 (0.29%), 845 (0.18%) COVID-19 deaths in white, Black, South Asian and other ethnic minority groups, respectively. Here we show that BMI was more strongly associated with COVID-19 mortality in ethnic minority groups, resulting in an ethnic risk of COVID-19 mortality that was dependant on BMI. The estimated risk of COVID-19 mortality at a BMI of 40 kg/m 2 in white ethnicities was equivalent to the risk observed at a BMI of 30.1 kg/m 2 , 27.0 kg/m 2 , and 32.2 kg/m 2 in Black, South Asian and other ethnic minority groups, respectively., (© 2022. The Author(s).)

Ethnic minorities have experienced disproportionate COVID-19 mortality rates in the UK and many other countries. We compared the differences in the risk of COVID-19 related death between ethnic groups in the first and second waves the of COVID-19 pandemic in England. We also investigated whether the factors explaining differences in COVID-19 death between ethnic groups changed between the two waves. Using data from the Office for National Statistics Public Health Data Asset, a linked dataset combining the 2011 Census with primary care and hospital records and death registrations, we conducted an observational cohort study to examine differences in the risk of death involving COVID-19 between ethnic groups in the first wave (from 24th January 2020 until 31st August 2020) and the first part of the second wave (from 1st September to 28th December 2020). We estimated age-standardised mortality rates (ASMR) in the two waves stratified by ethnic groups and sex. We also estimated hazard ratios (HRs) for ethnic-minority groups compared with the White British population, adjusted for geographical factors, socio-demographic characteristics, and pre-pandemic health conditions. The study population included over 28.9 million individuals aged 30-100 years living in private households. In the first wave, all ethnic minority groups had a higher risk of COVID-19 related death compared to the White British population. In the second wave, the risk of COVID-19 death remained elevated for people from Pakistani (ASMR: 339.9 [95% CI: 303.7-376.2] and 166.8 [141.7-191.9] deaths per 100,000 population in men and women) and Bangladeshi (318.7 [247.4-390.1] and 127.1 [91.1-171.3] in men and women) background but not for people from Black ethnic groups. Adjustment for geographical factors explained a large proportion of the differences in COVID-19 mortality in the first wave but not in the second wave. Despite an attenuation of the elevated risk of COVID-19 mortality after adjusting for sociodemographic characteristics and health status, the risk was substantially higher in people from Bangladeshi and Pakistani background in both the first and the second waves. Between the first and second waves of the pandemic, the reduction in the difference in COVID-19 mortality between people from Black ethnic background and people from the White British group shows that ethnic inequalities in COVID-19 mortality can be addressed. The continued higher rate of mortality in people from Bangladeshi and Pakistani background is alarming and requires focused public health campaign and policy changes., (© 2021. Crown.)

Objective: To estimate the proportion of ethnic inequalities explained by living in a multi-generational household., Design: Causal mediation analysis., Setting: Retrospective data from the 2011 Census linked to Hospital Episode Statistics (2017-2019) and death registration data (up to 30 November 2020)., Participants: Adults aged 65 years or over living in private households in England from 2 March 2020 until 30 November 2020 (n=10,078,568)., Main Outcome Measures: Hazard ratios were estimated for COVID-19 death for people living in a multi-generational household compared with people living with another older adult, adjusting for geographic factors, socioeconomic characteristics and pre-pandemic health., Results: Living in a multi-generational household was associated with an increased risk of COVID-19 death. After adjusting for confounding factors, the hazard ratios for living in a multi-generational household with dependent children were 1.17 (95% confidence interval [CI] 1.06-1.30) and 1.21 (95% CI 1.06-1.38) for elderly men and women. The hazard ratios for living in a multi-generational household without dependent children were 1.07 (95% CI 1.01-1.13) for elderly men and 1.17 (95% CI 1.07-1.25) for elderly women. Living in a multi-generational household explained about 11% of the elevated risk of COVID-19 death among elderly women from South Asian background, but very little for South Asian men or people in other ethnic minority groups., Conclusion: Elderly adults living with younger people are at increased risk of COVID-19 mortality, and this is a contributing factor to the excess risk experienced by older South Asian women compared to White women. Relevant public health interventions should be directed at communities where such multi-generational households are highly prevalent.

Introduction: Recent evidence suggests that influenza vaccination may offer protection against COVID-19 severity. Our aim was to quantify the association between influenza vaccination status and risk of hospitalisation or all-cause mortality in people diagnosed with COVID-19., Methods: A retrospective cohort study using routinely collected health records from patients registered to a General Practitioner (GP) practice in South West England within the Electronic Care and Health Information Analytics database. The cohort included 6921 people with COVID-19 during the first wave of the pandemic (1 January-31 July 2020). Data on influenza vaccination, hospitalisation and all-cause mortality were ascertained through linked clinical and demographic records. We applied propensity score methods (stabilised inverse probability of treatment weight) to quantify the association between influenza vaccination status and COVID-19 outcomes (hospitalisation or all-cause mortality)., Results: 2613 (38%) participants received an influenza vaccination between 1 January 2019 and COVID-19 diagnosis. Receipt of influenza vaccination was associated with a significantly lower odds of hospitalisation or all-cause mortality (adjusted OR: 0.85, 95% CI 0.75 to 0.97, p=0.02), and 24% reduced odds of all-cause mortality (adjusted OR: 0.76, 95% CI 0.64 to 0.90)., Discussion: Influenza vaccination was associated with a 15%-24% lower odds of severe COVID-19 outcomes. The current UK influenza vaccination programme needs urgent expansion as an integral component of the ongoing response plans to the COVID-19 pandemic., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ.)