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AbstractObjectiveTo estimate associations between covid-19 vaccination and long covid symptoms in adults with SARS-CoV-2 infection before vaccination.DesignObservational cohort study.SettingCommunity dwelling population, UK.Participants28 356 participants in the Office for National Statistics COVID-19 Infection Survey aged 18-69 years who received at least one dose of an adenovirus vector or mRNA covid-19 vaccine after testing positive for SARS-CoV-2 infection.Main outcome measurePresence of long covid symptoms at least 12 weeks after infection over the follow-up period 3 February to 5 September 2021.ResultsMean age of participants was 46 years, 55.6% (n=15 760) were women, and 88.7% (n=25 141) were of white ethnicity. Median follow-up was 141 days from first vaccination (among all participants) and 67 days from second vaccination (83.8% of participants). 6729 participants (23.7%) reported long covid symptoms of any severity at least once during follow-up. A first vaccine dose was associated with an initial 12.8% decrease (95% confidence interval −18.6% to −6.6%, P<0.001) in the odds of long covid, with subsequent data compatible with both increases and decreases in the trajectory (0.3% per week, 95% confidence interval −0.6% to 1.2% per week, P=0.51). A second dose was associated with an initial 8.8% decrease (95% confidence interval −14.1% to −3.1%, P=0.003) in the odds of long covid, with a subsequent decrease by 0.8% per week (−1.2% to −0.4% per week, P<0.001). Heterogeneity was not found in associations between vaccination and long covid by sociodemographic characteristics, health status, hospital admission with acute covid-19, vaccine type (adenovirus vector or mRNA), or duration from SARS-CoV-2 infection to vaccination.ConclusionsThe likelihood of long covid symptoms was observed to decrease after covid-19 vaccination and evidence suggested sustained improvement after a second dose, at least over the median follow-up of 67 days. Vaccination may contribute to a reduction in the population health burden of long covid, although longer follow-up is needed.

Atrial fibrillation (AF) is the most common sustained heart arrhythmia. However, as many cases are asymptomatic, a large proportion of patients remain undiagnosed until serious complications arise. Efficient, cost-effective detection of the undiagnosed may be supported by risk-prediction models relating patient factors to AF risk. However, there exists a need for an implementable risk model that is contemporaneous and informed by routinely collected patient data, reflecting the real-world pathology of AF. This study sought to develop and evaluate novel and conventional statistical and machine learning models for risk-predication of AF. This was a retrospective, cohort study of adults (aged ≥30 years) without a history of AF, listed on the Clinical Practice Research Datalink, from January 2006 to December 2016. Models evaluated included published risk models (Framingham, ARIC, CHARGE-AF), machine learning models, which evaluated baseline and time-updated information (neural network, LASSO, random forests, support vector machines), and Cox regression. Analysis of 2,994,837 individuals (3.2% AF) identified time-varying neural networks as the optimal model achieving an AUROC of 0.827 vs. 0.725, with number needed to screen of 9 vs. 13 patients at 75% sensitivity, when compared with the best existing model CHARGE-AF. The optimal model confirmed known baseline risk factors (age, previous cardiovascular disease, antihypertensive medication usage) and identified additional time-varying predictors (proximity of cardiovascular events, body mass index (both levels and changes), pulse pressure, and the frequency of blood pressure measurements). The optimal time-varying machine learning model exhibited greater predictive performance than existing AF risk models and reflected known and new patient risk factors for AF.

The global evidence on the risk of symptoms of Long Covid in general populations infected with SARS-CoV-2 compared to uninfected comparator/control populations remains unknown. We conducted a systematic literature search using multiple electronic databases from January 1, 2022, to August 1, 2024. Included studies had ≥100 people with confirmed or self-reported COVID-19 at ≥28 days following infection onset, and an uninfected comparator/control group. Results were summarised descriptively and meta-analyses were conducted to derive pooled risk ratio estimates. 50 studies totaling 14,661,595 people were included. In all populations combined, there was an increased risk of a wide range of 39 out of 40 symptoms in those infected with SARS‑CoV‑2 compared to uninfected controls. The symptoms with the highest pooled relative risks were loss of smell (RR 4.31; 95% CI 2.66, 6.99), loss of taste (RR 3.71; 95% CI 2.22, 7.26), poor concentration (RR 2.68; 95% CI 1.66, 4.33), impaired memory (RR 2.53; 95% CI 1.82, 3.52), and hair loss/alopecia (RR 2.38; 95% CI 1.69, 3.33). This evidence synthesis, of 50 controlled studies with a cumulative participant count exceeding 14 million people, highlights a significant risk of diverse long-term symptoms in individuals infected with SARS-CoV-2, especially among those who were hospitalised. Estimating the risk of long COVID is challenging because many of its symptoms are associated with other conditions. Here, the authors conduct a systematic review and meta-analysis of studies that estimate long COVID risk while accounting for background symptoms using comparator control populations.

ObjectiveTo examine inequalities in COVID-19 vaccination rates among elderly adults in England.DesignCohort study.SettingPeople living in private households and communal establishments in England.Participants6 655 672 adults aged ≥70 years (mean 78.8 years, 55.2% women) who were alive on 15 March 2021.Main outcome measuresHaving received the first dose of a vaccine against COVID-19 by 15 March 2021. We calculated vaccination rates and estimated unadjusted and adjusted ORs using logistic regression models.ResultsBy 15 March 2021, 93.2% of people living in England aged 70 years and over had received at least one dose of a COVID-19 vaccine. While vaccination rates differed across all factors considered apart from sex, the greatest disparities were seen between ethnic and religious groups. The lowest rates were in people of black African and black Caribbean ethnic backgrounds, where only 67.2% and 73.8% had received a vaccine, with adjusted odds of not being vaccinated at 5.01 (95% CI 4.86 to 5.16) and 4.85 (4.75 to 4.96) times greater than the white British group. The proportion of individuals self-identifying as Muslim and Buddhist who had received a vaccine was 79.1% and 84.1%, respectively. Older age, greater area deprivation, less advantaged socioeconomic position (proxied by living in a rented home), being disabled and living either alone or in a multigenerational household were also associated with higher odds of not having received the vaccine.ConclusionResearch is now urgently needed to understand why disparities exist in these groups and how they can best be addressed through public health policy and community engagement.

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.

Abstract Aims At present, the clinical burden of hypokalaemia and hyperkalaemia among European heart failure patients, and relationships between serum potassium and adverse clinical outcomes in this population, is not well characterized. The aim of this study was to investigate associations between mortality, major adverse cardiac events, and renin–angiotensin–aldosterone system inhibitor (RAASi) discontinuation across serum potassium levels, in a UK cohort of incident heart failure patients. Methods and results This was a retrospective observational cohort study of newly diagnosed heart failure patients listed in the Clinical Practice Research Datalink, with a first record of heart failure (index date) between 2006 and 2015. Hypokalaemia and hyperkalaemia episodes were defined as the number of serum potassium measurements exceeding each threshold (<3.5, ≥5.0, ≥5.5, and ≥6.0 mmol/L), without such a measurement in the preceding 7 days. Risk equations developed using Poisson generalized estimating equations were utilized to estimate adjusted incident rate ratios (IRRs) relating serum potassium and clinical outcomes (death, major adverse cardiac event, and RAASi discontinuation). Among 21,334 eligible heart failure patients, 1969 (9.2%), 7648 (35.9%), 2725 (12.8%), and 763 (3.6%) experienced episodes of serum potassium <3.5, ≥5.0, ≥5.5, and ≥6.0 mmol/L, respectively. The adjusted IRRs for mortality exhibited a U-shaped association pattern with serum potassium. Relative to the reference category (4.5 to <5.0 mmol/L), adjusted IRRs for mortality were estimated as 1.98 (95% confidence interval: 1.69–2.33), 1.23 (1.12–1.36), 1.35 (1.14–1.60), and 3.02 (2.28–4.02), for patients with serum potassium <3.5, ≥5.0 to <5.5, ≥5.5 to <6.0, and ≥6.0 mmol/L, respectively. The adjusted IRRs for major adverse cardiac events demonstrated a non-statistically significant relationship with serum potassium. Discontinuation of RAASi therapy exhibited a J-shaped trend in association with serum potassium. Compared with the reference category (4.5 to <5.0 mmol/L), adjusted IRRs were estimated as 1.07 (0.89–1.28) in patients with serum potassium <3.5 mmol/L, increasing to 1.32 (1.14–1.53) and 2.19 (1.63–2.95) among those with serum potassium ≥5.5 to <6.0 and ≥6.0 mmol/L, respectively. Conclusions In UK patients with new onset heart failure, both hypokalaemia and hyperkalaemia were associated with increased mortality risk, and hyperkalaemia was associated with increased likelihood of RAASi discontinuation. Our results demonstrate the potential importance of serum potassium monitoring for heart failure outcomes and management.

Background To address a current paucity of European data, this study developed equations to predict risks of mortality, major adverse cardiac events (MACE) and renin angiotensin-aldosterone system inhibitor (RAASi) discontinuation using time-varying serum potassium and other covariates, in a UK cohort of chronic kidney disease (CKD) patients. Methods This was a retrospective observational study of adult CKD patients listed on the Clinical Practice Research Datalink, with a first record of CKD (stage 3a–5, pre-dialysis) between 2006 and 2015. Patients with heart failure at index were excluded. Risk equations developed using Poisson Generalized Estimating Equations were utilised to estimate adjusted incident rate ratios (IRRs) between serum potassium and adverse outcomes, and identify other predictive clinical factors. Results Among 191,964 eligible CKD patients, 86,691 (45.16%), 30,629 (15.96%) and 9440 (4.92%) experienced at least one hyperkalaemia episode, when defined using serum potassium concentrations 5.0–< 5.5 mmol/L, 5.5–< 6.0 mmol/L and ≥ 6.0 mmol/L, respectively. Relative to the reference category (4.5 to < 5.0 mmol/L), adjusted IRRs for mortality and MACE exhibited U-shaped associations with serum potassium, with age being the most important predictor of both outcomes ( P  < 0.0001). A J-shaped association between serum potassium and RAASi discontinuation was observed; estimated glomerular filtration rate was most predictive of RAASi discontinuation ( P  < 0.0001). Conclusions Hyperkalaemia was associated with increased mortality and RAASi discontinuation risk. These risk equations represent a valuable tool to predict clinical outcomes among CKD patients; and identify those likely to benefit from strategies that treat hyperkalaemia, prevent RAASi discontinuation, and effectively manage serum potassium levels.

AbstractObjectiveTo quantify rates of organ specific dysfunction in individuals with covid-19 after discharge from hospital compared with a matched control group from the general population.DesignRetrospective cohort study.SettingNHS hospitals in England.Participants47 780 individuals (mean age 65, 55% men) in hospital with covid-19 and discharged alive by 31 August 2020, exactly matched to controls from a pool of about 50 million people in England for personal and clinical characteristics from 10 years of electronic health records.Main outcome measuresRates of hospital readmission (or any admission for controls), all cause mortality, and diagnoses of respiratory, cardiovascular, metabolic, kidney, and liver diseases until 30 September 2020. Variations in rate ratios by age, sex, and ethnicity.ResultsOver a mean follow-up of 140 days, nearly a third of individuals who were discharged from hospital after acute covid-19 were readmitted (14 060 of 47 780) and more than 1 in 10 (5875) died after discharge, with these events occurring at rates four and eight times greater, respectively, than in the matched control group. Rates of respiratory disease (P<0.001), diabetes (P<0.001), and cardiovascular disease (P<0.001) were also significantly raised in patients with covid-19, with 770 (95% confidence interval 758 to 783), 127 (122 to 132), and 126 (121 to 131) diagnoses per 1000 person years, respectively. Rate ratios were greater for individuals aged less than 70 than for those aged 70 or older, and in ethnic minority groups compared with the white population, with the largest differences seen for respiratory disease (10.5 (95% confidence interval 9.7 to 11.4) for age less than 70 years v 4.6 (4.3 to 4.8) for age ≥70, and 11.4 (9.8 to 13.3) for non-white v 5.2 (5.0 to 5.5) for white individuals).ConclusionsIndividuals discharged from hospital after covid-19 had increased rates of multiorgan dysfunction compared with the expected risk in the general population. The increase in risk was not confined to the elderly and was not uniform across ethnicities. The diagnosis, treatment, and prevention of post-covid syndrome requires integrated rather than organ or disease specific approaches, and urgent research is needed to establish the risk factors.

ObjectiveTo estimate vaccine effectiveness for preventing covid-19 related hospital admission in individuals first infected with the SARS-CoV-2 virus during pregnancy compared with those of reproductive age who were not pregnant when first infected with the virus.DesignPopulation based cohort study.SettingOffice for National Statistics Public Health Data Asset linked dataset, providing national linked census and administrative data in England, 8 December 2020 to 31 August 2021.Participants815 477 females aged 18-45 years (mean age 30.4 years) who had documented evidence of a first SARS-CoV-2 infection in the NHS Test and Trace or Hospital Episode Statistics data.Main outcome measuresHospital admission where covid-19 was recorded as the primary diagnosis. Cox proportional hazards models, adjusted for calendar time of infection, sociodemographic factors, and pre-existing health conditions related to uptake of the covid-19 vaccine and risk of severe covid-19 outcomes, were used to estimate vaccine effectiveness as the complement of the hazard ratio for hospital admission for covid-19.ResultsCompared with pregnant individuals who were not vaccinated, the adjusted rate of hospital admission for covid-19 was 77% (95% confidence interval 70% to 82%) lower for pregnant individuals who had received one dose and 83% (76% to 89%) lower for those who had received two doses of vaccine. These estimates were similar to those found in the non-pregnant group: 79% (77% to 81%) for one dose and 83% (82% to 85%) for two doses of vaccine. Among those who were vaccinated >90 days before infection, having two doses of vaccine was associated with a greater reduction in risk than one dose.ConclusionsCovid-19 vaccination was associated with reduced rates of hospital admission in pregnant individuals infected with the SARS-CoV-2 virus, and the reduction in risk was similar to that in non-pregnant individuals. Waning of vaccine effectiveness occurred more quickly after one than after two doses of vaccine.

ObjectiveTo examine sociodemographic inequalities in people with SARS-CoV-2 during the second (alpha) and third (delta) waves of the covid-19 pandemic.DesignRetrospective, population based cohort study.SettingResident population of England.Participants39 006 194 people aged 10 years and older who were enumerated in the 2011 census, registered with the NHS, and alive on 1 September 2020.Main outcome measuresAge standardised SARS-CoV-2 case rates (ie, the number of people who received a positive test result per 100 000 person weeks at risk) during the second wave (1 September 2020 to 22 May 2021) or third wave (23 May to 10 December 2021) of the pandemic. Age standardised rates were calculated by sociodemographic characteristics and adjusted rate ratios were estimated using generalised linear regression models with a Poisson distribution (models were adjusted for covariates including sex, age, geographical variables, and sociodemographic characteristics).ResultsDuring the study period, 5 767 584 people (14.8% of the study population) tested positive for SARS-CoV-2. In the second wave, the fully adjusted relative risks of having a positive test were highest for the Bangladeshi and Pakistani ethnic groups compared with the white British group, with rate ratios of 1.75 (95% confidence interval 1.73 to 1.77) and 1.69 (1.68 to 1.70), respectively. Muslim and Sikh religious groups had fully adjusted rate ratios of 1.51 (1.50 to 1.51) and 1.64 (1.63 to 1.66), respectively, compared with the Christian group. Greater area deprivation, disadvantaged socioeconomic position, living in a care home, and low English language proficiency were also associated with higher relative risk of having a positive test. However, the inequalities among groups varied over time. Being Christian, white British, without a disability, and from a more advantaged socioeconomic position were associated with increased relative risk of testing positive during the third wave.ConclusionResearch is urgently needed to understand the large sociodemographic inequalities in SARS-CoV-2 case rates in order to inform policy interventions in future waves or pandemics.