Exploring the relationship between physical activity and covid-19 infection in a young, non-hospitalized cohort in the united kingdom

201 Table 1Demographics of cohortVariableCategory/SummaryNegativePositiveOverallORP-value95%CI low95%CI high3043(79.7%)777(20.3%)3820AgeMean/SD21.19/6.7920.93/6.0721.12/6.640.9800.2580.9451.015Median (Q1-Q3)18(15, 27)19(16, 25)18(15, 27)Min-Max14-3614-3614-36BMIMean/SD23.34/4.8924.12/4.9023.48/4.831.068<.0011.0351.103Median (Q1-Q3)22.44(19.9, 25.9)23.39(20.5, 26.8)22.60(20.06, 26.03)Min-Max13.36-55.2514.40-45.9013.36-55.25SexWomen1107(36.3%)250(32.4%)1357 (35.5%)1Men1935 (63.5%)521(67.6%)2456 (64.3%)1.2020.0321.0161.421EthnicityWhite2789(91.65%)707(90.99%)3496(91.5%)Asian89(2.92%)23(2.96%)112 (2.93%)Black53(1.74%)11(1.42%)64 (1.68%)Other112(3.68%)36(4.63%)148 (3.87%)BAME vs. White1.0870.5550.8241.434Group Sedentary495(16.24%)112(14.53%)607 (15.89%)1typeRecreational1331(43.67%)302(39.17%)1633 (42.76%)0.7720.0030.6500.916Elite1222(40.09%)357(46.30%)1579 (41.35%)0.7620.0240.6020.965MET A (0 METs)440 (14.44%)105(13.62%)545(14.27%)1CategoryB (<500 MET-min/week)91(2.99%)12(1.56%)103 (2.70%)0.5540.0700.2921 049C (500-999 MET-min/week)128(4.20%)25(3.24%)153 (4.01%)0.8200.4170.5081.324D (1000-1499 MET-min/week)149(4.89%)37(4.80%)186 (4.87%)1.0780.7220.7121.633E (>1500MET-min/week)2240(73.49%)592(76.78%)2832 (74.16%)1.1220.3300.8901.414 201 Table 2The effects of demographics, physical activity, and symptoms on disease durationORp-value95%CI low95%CI highMen vs. Women0.561<0.0010.4180.753MET categoriesCATEGORY B vs. A1.4360.5490.4414.679CATEGORY C vs. A0.8650.7430.3642.056CATEGORY D vs. A0.5440.0890.2691.098CATEGORY E vs. A0.5320.0020.3560.795Recreational vs. Elite athlete1.698<0.0011.2602.288Sedentary vs. Elite athlete2.255<0.0011.4913.411Sedentary vs. recreational1.3280.185.8732.019Shortness of breath (YES vs. NO)3.558<0.0012.6144.842Chest pain (YES vs. NO)2.341<0.0011.5093.630Chest tightness (YES vs. NO)2.733<0.0011.9143.902Palpitations (YES vs. NO)3.1370.0011.5616.305 201 Figure 1The effect of the available variables on the duration of the disease in COVID-19 positive participants[Figure omitted. See PDF]Conflict of InterestNone

Socioeconomic inequalities of Long COVID: a retrospective population-based cohort study in the United Kingdom.

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.

Long COVID: Mechanismen, Risikofaktoren und Genesung

Long COVID, die lang anhaltende Krankheit und Erschöpfung, die bei einem kleinen Teil der SARS-CoV-2-Infizierten auftritt, stellt eine zunehmende Belastung für die Betroffenen und die Gesellschaft dar. Eine virtuelle Tagung der Physiological Society im Februar 2022 brachte Kliniker und Forscher zusammen, um das aktuelle Verständnis der Mechanismen, Risikofaktoren und Genesung nach Long COVID zu erörtern. In dieser Übersichtsarbeit werden die Themen behandelt, die sich aus dieser Tagung ergeben haben. Die Übersichtsarbeit befasst sich mit der Natur von Long COVID, untersucht den Zusammenhang mit anderen postviralen Erkrankungen wie der myalgischen Enzephalomyelitis/dem chronischen Erschöpfungssyndrom und zeigt auf, wie die Forschung zu Long COVID helfen kann, Patienten mit allen möglichen postviralen Syndromen besser zu unterstützen. Die Forschung zu Long COVID hat besonders rasche Fortschritte bei Bevölkerungsgruppen gemacht, die ihre körperliche Leistungsfähigkeit routinemäßig überwachen, insbesondere beim Militär und bei Leistungssportlern. In der Übersichtsarbeit wird hervorgehoben, inwiefern das hohe Niveau von Diagnose, Intervention und Erfolgskontrolle in diesen aktiven Bevölkerungsgruppen Informationen über Managementstrategien für die Allgemeinbevölkerung liefern kann. Anschließend wird untersucht, wie eine Schlüsselkomponente der Leistungsüberwachung bei diesen aktiven Bevölkerungsgruppen, das kardiopulmonale Training, Long-COVID-bedingte Veränderungen in der Physiologie aufdeckt − einschließlich Veränderungen der peripheren Muskelfunktion, der ventilatorischen Ineffizienz und der autonomen Dysfunktion. Das Wesen und die Auswirkungen der Dysautonomie werden im Zusammenhang mit dem posturalen orthostatischen Tachykardiesyndrom, der Fatigue und den Behandlungsstrategien, die darauf abzielen, der Überaktivierung des Sympathikus durch Stimulation des Vagusnervs entgegenzuwirken, erörtert. Anschließend untersuchen wir die Mechanismen, die den Symptomen von Long COVID zugrunde liegen. Dabei konzentrieren wir uns auf die gestörte Sauerstoffversorgung durch Mikrokoagulation und die Störung des zellulären Energiestoffwechsels, bevor wir Behandlungsstrategien betrachten, die direkt oder indirekt auf diese Mechanismen abzielen. Dazu gehören ein fernbetreutes Atemmuskeltraining und integrierte Versorgungspfade, die Rehabilitation und medikamentöse Interventionen mit der Erforschung des Zugangs zur Long-COVID-Versorgung in verschiedenen Bevölkerungsgruppen kombinieren. Insgesamt zeigt diese Übersichtsarbeit, wie im Rahmen der physiologischen Forschung die bei Long COVID auftretenden Veränderungen aufgedeckt werden und wie verschiedene therapeutische Strategien zur Bekämpfung dieser Erkrankung entwickelt und getestet werden.

Corrigendum to "The prevalence and long-term health effects of long Covid among hospitalised and non-hospitalised populations: a systematic review and meta-analysis".

[This corrects the article DOI: 10.1016/j.eclinm.2022.101762.].

Digital health, cardiometabolic disease and ethnicity: an analysis of United Kingdom government policies from 2010 to 2022.

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.

Severe COVID-19 outcomes by cardiovascular risk profile in England in 2020: a population-based cohort study

Background While cardiovascular disease (CVD) is a risk factor for severe COVID-19, the association between predicted cardiovascular risk and severe COVID-19 among people without diagnosed CVD is unclear. Methods We carried out historical, population-based cohort studies among adults aged 40–84 years in England using linked data from the Clinical Practice Research Datalink. Individuals were categorized into: existing CVD, raised cardiovascular risk (defined using QRISK3 score ≥10%) and low risk (QRISK3 score <10%) at 12/03/2020. We described incidence and severe outcomes of COVID-19 (deaths, intensive care unit [ICU] admissions, hospitalisations, major adverse cardiovascular events [MACE]) for each group. Among those with a COVID-19 record to 31/12/2020, we re-classified cardiovascular risk at infection and assessed the risk of severe outcomes using multivariable Cox regression with complete case analysis. We repeated analyses using hypertension to define raised cardiovascular risk. Findings Among 6,059,055 individuals, 741,913 (12.2%) had established CVD, 1,929,627 (31.8%) had a QRISK3 score ≥10% and 3,387,515 (55.9%) had a QRISK3 score <10%. Marked gradients were seen in the incidence of all severe COVID-19 outcomes by cardiovascular risk profile. Among those with COVID-19 (N = 146,760), there was a strong association between raised QRISK3 score and death: adjusted hazard ratio [aHR] 8.77 (7.62–10.10), N = 97,725, which remained present, though attenuated in age-stratified results. Risks of other outcomes were also higher among those with raised QRISK3 score: aHR 3.66 (3.18–4.21) for ICU admissions, 3.38 (3.22–3.56) for hospitalisations, 5.43 (4.44–6.64) for MACE. When raised cardiovascular risk was redefined by hypertension status, only the association with MACE remained: aHR 1.49 (1.20–1.85), N = 57,264. Interpretation Individuals without pre-existing CVD but with raised cardiovascular risk (by QRISK3 score) were more likely to experience severe COVID-19 outcomes and should be prioritised for prevention and treatment. Addressing cardiovascular risk factors could improve COVID-19 outcomes. Funding 10.13039/501100011950BMA Foundation for Medical Research/10.13039/501100000833Rosetrees Trust, 10.13039/100004440Wellcome, 10.13039/501100000274BHF.

Severe COVID-19 outcomes by cardiovascular risk profile in England in 2020: a population-based cohort study.

Background: While cardiovascular disease (CVD) is a risk factor for severe COVID-19, the association between predicted cardiovascular risk and severe COVID-19 among people without diagnosed CVD is unclear. Methods: We carried out historical, population-based cohort studies among adults aged 40-84 years in England using linked data from the Clinical Practice Research Datalink. Individuals were categorized into: existing CVD, raised cardiovascular risk (defined using QRISK3 score ≥10%) and low risk (QRISK3 score <10%) at 12/03/2020. We described incidence and severe outcomes of COVID-19 (deaths, intensive care unit [ICU] admissions, hospitalisations, major adverse cardiovascular events [MACE]) for each group. Among those with a COVID-19 record to 31/12/2020, we re-classified cardiovascular risk at infection and assessed the risk of severe outcomes using multivariable Cox regression with complete case analysis. We repeated analyses using hypertension to define raised cardiovascular risk. Findings: Among 6,059,055 individuals, 741,913 (12.2%) had established CVD, 1,929,627 (31.8%) had a QRISK3 score ≥10% and 3,387,515 (55.9%) had a QRISK3 score <10%. Marked gradients were seen in the incidence of all severe COVID-19 outcomes by cardiovascular risk profile. Among those with COVID-19 (N = 146,760), there was a strong association between raised QRISK3 score and death: adjusted hazard ratio [aHR] 8.77 (7.62-10.10), N = 97,725, which remained present, though attenuated in age-stratified results. Risks of other outcomes were also higher among those with raised QRISK3 score: aHR 3.66 (3.18-4.21) for ICU admissions, 3.38 (3.22-3.56) for hospitalisations, 5.43 (4.44-6.64) for MACE. When raised cardiovascular risk was redefined by hypertension status, only the association with MACE remained: aHR 1.49 (1.20-1.85), N = 57,264. Interpretation: Individuals without pre-existing CVD but with raised cardiovascular risk (by QRISK3 score) were more likely to experience severe COVID-19 outcomes and should be prioritised for prevention and treatment. Addressing cardiovascular risk factors could improve COVID-19 outcomes. Funding: BMA Foundation for Medical Research/Rosetrees Trust, Wellcome, BHF.

Cardiac abnormalities in Long COVID 1-year post-SARS-CoV-2 infection.

BACKGROUND: Long COVID is associated with multiple symptoms and impairment in multiple organs. Cross-sectional studies have reported cardiac impairment to varying degrees by varying methodologies. Using cardiac MR (CMR), we investigated a 12-month trajectory of abnormalities in Long COVID. OBJECTIVES: To investigate cardiac abnormalities 1-year post-SARS-CoV-2 infection. METHODS: 534 individuals with Long COVID underwent CMR (T1/T2 mapping, cardiac mass, volumes, function and strain) and multiorgan MRI at 6 months (IQR 4.3-7.3) since first post-COVID-19 symptoms. 330 were rescanned at 12.6 (IQR 11.4-14.2) months if abnormal baseline findings were reported. Symptoms, questionnaires and blood samples were collected at both time points. CMR abnormalities were defined as ≥1 of low left or right ventricular ejection fraction (LVEF), high left or right ventricular end diastolic volume, low 3D left ventricular global longitudinal strain (GLS), or elevated native T1 in ≥3 cardiac segments. Significant change over time was reported by comparison with 92 healthy controls. RESULTS: Technical success of multiorgan and CMR assessment in non-acute settings was 99.1% and 99.6% at baseline, and 98.3% and 98.8% at follow-up. Of individuals with Long COVID, 102/534 (19%) had CMR abnormalities at baseline; 71/102 had complete paired data at 12 months. Of those, 58% presented with ongoing CMR abnormalities at 12 months. High sensitivity cardiac troponin I and B-type natriuretic peptide were not predictive of CMR findings, symptoms or clinical outcomes. At baseline, low LVEF was associated with persistent CMR abnormality, abnormal GLS associated with low quality of life and abnormal T1 in at least three segments was associated with better clinical outcomes at 12 months. CONCLUSION: CMR abnormalities (left entricular or right ventricular dysfunction/dilatation and/or abnormal T1mapping), occurred in one in five individuals with Long COVID at 6 months, persisting in over half of those at 12 months. Cardiac-related blood biomarkers could not identify CMR abnormalities in Long COVID. TRIAL REGISTRATION NUMBER: NCT04369807.

Risk of death following COVID-19 vaccination or positive SARS-CoV-2 test in young people in England.

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.

Performance of digital early warning score (NEWS2) in a cardiac specialist setting: retrospective cohort study.

INTRODUCTION: Patients with cardiovascular diseases (CVD) are at significant risk of developing critical events. Early warning scores (EWS) are recommended for early recognition of deteriorating patients, yet their performance has been poorly studied in cardiac care settings. Standardisation and integrated National Early Warning Score 2 (NEWS2) in electronic health records (EHRs) are recommended yet have not been evaluated in specialist settings. OBJECTIVE: To investigate the performance of digital NEWS2 in predicting critical events: death, intensive care unit (ICU) admission, cardiac arrest and medical emergencies. METHODS: Retrospective cohort analysis. STUDY COHORT: Individuals admitted with CVD diagnoses in 2020; including patients with COVID-19 due to conducting the study during the COVID-19 pandemic. MEASURES: We tested the ability of NEWS2 in predicting the three critical outcomes from admission and within 24 hours before the event. NEWS2 was supplemented with age and cardiac rhythm and investigated. We used logistic regression analysis with the area under the receiver operating characteristic curve (AUC) to measure discrimination. RESULTS: In 6143 patients admitted under cardiac specialties, NEWS2 showed moderate to low predictive accuracy of traditionally examined outcomes: death, ICU admission, cardiac arrest and medical emergency (AUC: 0.63, 0.56, 0.70 and 0.63, respectively). Supplemented NEWS2 with age showed no improvement while age and cardiac rhythm improved discrimination (AUC: 0.75, 0.84, 0.95 and 0.94, respectively). Improved performance was found of NEWS2 with age for COVID-19 cases (AUC: 0.96, 0.70, 0.87 and 0.88, respectively). CONCLUSION: The performance of NEWS2 in patients with CVD is suboptimal, and fair for patients with CVD with COVID-19 to predict deterioration. Adjustment with variables that strongly correlate with critical cardiovascular outcomes, that is, cardiac rhythm, can improve the model. There is a need to define critical endpoints, engagement with clinical experts in development and further validation and implementation studies of EHR-integrated EWS in cardiac specialist settings.

Implementation of a digital early warning score (NEWS2) in a cardiac specialist and general hospital settings in the COVID-19 pandemic: a qualitative study.

OBJECTIVES: To evaluate implementation of digital National Early Warning Score 2 (NEWS2) in a cardiac care setting and a general hospital setting in the COVID-19 pandemic. DESIGN: Thematic analysis of qualitative semistructured interviews using the non-adoption, abandonment, scale-up, spread, sustainability framework with purposefully sampled nurses and managers, as well as online surveys from March to December 2021. SETTINGS: Specialist cardiac hospital (St Bartholomew's Hospital) and general teaching hospital (University College London Hospital, UCLH). PARTICIPANTS: Eleven nurses and managers from cardiology, cardiac surgery, oncology and intensive care wards (St Bartholomew's) and medical, haematology and intensive care wards (UCLH) were interviewed and 67 were surveyed online. RESULTS: Three main themes emerged: (1) implementing NEWS2 challenges and supports; (2) value of NEWS2 to alarm, escalate and during the pandemic; and (3) digitalisation: electronic health record (EHR) integration and automation. The value of NEWS2 was partly positive in escalation, yet there were concerns by nurses who undervalued NEWS2 particularly in cardiac care. Challenges, like clinicians' behaviours, lack of resources and training and the perception of NEWS2 value, limit the success of this implementation. Changes in guidelines in the pandemic have led to overlooking NEWS2. EHR integration and automated monitoring are improvement solutions that are not fully employed yet. CONCLUSION: Whether in specialist or general medical settings, the health professionals implementing early warning score in healthcare face cultural and system-related challenges to adopting NEWS2 and digital solutions. The validity of NEWS2 in specialised settings and complex conditions is not yet apparent and requires comprehensive validation. EHR integration and automation are powerful tools to facilitate NEWS2 if its principles are reviewed and rectified, and resources and training are accessible. Further examination of implementation from the cultural and automation domains is needed.

COVID-19 vaccination uptake amongst ethnic minority communities in England: a linked study exploring the drivers of differential vaccination rates.

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.

STIMULATE-ICP: A pragmatic, multi-centre, cluster randomised trial of an integrated care pathway with a nested, Phase III, open label, adaptive platform randomised drug trial in individuals with Long COVID: A structured protocol.

INTRODUCTION: Long COVID (LC), the persistent symptoms ≥12 weeks following acute COVID-19, presents major threats to individual and public health across countries, affecting over 1.5 million people in the UK alone. Evidence-based interventions are urgently required and an integrated care pathway approach in pragmatic trials, which include investigations, treatments and rehabilitation for LC, could provide scalable and generalisable solutions at pace. METHODS AND ANALYSIS: This is a pragmatic, multi-centre, cluster-randomised clinical trial of two components of an integrated care pathway (Coverscan™, a multi-organ MRI, and Living with COVID Recovery™, a digitally enabled rehabilitation platform) with a nested, Phase III, open label, platform randomised drug trial in individuals with LC. Cluster randomisation is at level of primary care networks so that integrated care pathway interventions are delivered as "standard of care" in that area. The drug trial randomisation is at individual level and initial arms are rivaroxaban, colchicine, famotidine/loratadine, compared with no drugs, with potential to add in further drug arms. The trial is being carried out in 6-10 LC clinics in the UK and is evaluating the effectiveness of a pathway of care for adults with LC in reducing fatigue and other physical, psychological and functional outcomes at 3 months. The trial also includes an economic evaluation which will be described separately. ETHICS AND DISSEMINATION: The protocol was reviewed by South Central-Berkshire Research Ethics Committee (reference: 21/SC/0416). All participating sites obtained local approvals prior to recruitment. Coverscan™ has UK certification (UKCA 752965). All participants will provide written consent to take part in the trial. The first participant was recruited in July 2022 and interim/final results will be disseminated in 2023, in a plan co-developed with public and patient representatives. The results will be presented at national and international conferences, published in peer reviewed medical journals, and shared via media (mainstream and social) and patient support organisations. TRIAL REGISTRATION NUMBER: ISRCTN10665760.

Multi-organ impairment and long COVID: a 1-year prospective, longitudinal cohort study.

OBJECTIVES: To determine the prevalence of organ impairment in long COVID patients at 6 and 12 months after initial symptoms and to explore links to clinical presentation. DESIGN: Prospective cohort study. PARTICIPANTS: Individuals. METHODS: In individuals recovered from acute COVID-19, we assessed symptoms, health status, and multi-organ tissue characterisation and function. SETTING: Two non-acute healthcare settings (Oxford and London). Physiological and biochemical investigations were performed at baseline on all individuals, and those with organ impairment were reassessed. MAIN OUTCOME MEASURES: Primary outcome was prevalence of single- and multi-organ impairment at 6 and 12 months post COVID-19. RESULTS: A total of 536 individuals (mean age 45 years, 73% female, 89% white, 32% healthcare workers, 13% acute COVID-19 hospitalisation) completed baseline assessment (median: 6 months post COVID-19); 331 (62%) with organ impairment or incidental findings had follow-up, with reduced symptom burden from baseline (median number of symptoms 10 and 3, at 6 and 12 months, respectively). Extreme breathlessness (38% and 30%), cognitive dysfunction (48% and 38%) and poor health-related quality of life (EQ-5D-5L < 0.7; 57% and 45%) were common at 6 and 12 months, and associated with female gender, younger age and single-organ impairment. Single- and multi-organ impairment were present in 69% and 23% at baseline, persisting in 59% and 27% at follow-up, respectively. CONCLUSIONS: Organ impairment persisted in 59% of 331 individuals followed up at 1 year post COVID-19, with implications for symptoms, quality of life and longer-term health, signalling the need for prevention and integrated care of long COVID.Trial Registration: ClinicalTrials.gov Identifier: NCT04369807.

Using national electronic health records for pandemic preparedness: validation of a parsimonious model for predicting excess deaths among those with COVID-19-a data-driven retrospective cohort study.

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.

Long COVID: mechanisms, risk factors and recovery.

NEW FINDINGS: What is the topic of this review? The emerging condition of long COVID, its epidemiology, pathophysiological impacts on patients of different backgrounds, physiological mechanisms emerging as explanations of the condition, and treatment strategies being trialled. The review leads from a Physiological Society online conference on this topic. What advances does it highlight? Progress in understanding the pathophysiology and cellular mechanisms underlying Long COVID and potential therapeutic and management strategies. ABSTRACT: Long COVID, the prolonged illness and fatigue suffered by a small proportion of those infected with SARS-CoV-2, is placing an increasing burden on individuals and society. A Physiological Society virtual meeting in February 2022 brought clinicians and researchers together to discuss the current understanding of long COVID mechanisms, risk factors and recovery. This review highlights the themes arising from that meeting. It considers the nature of long COVID, exploring its links with other post-viral illnesses such as myalgic encephalomyelitis/chronic fatigue syndrome, and highlights how long COVID research can help us better support those suffering from all post-viral syndromes. Long COVID research started particularly swiftly in populations routinely monitoring their physical performance - namely the military and elite athletes. The review highlights how the high degree of diagnosis, intervention and monitoring of success in these active populations can suggest management strategies for the wider population. We then consider how a key component of performance monitoring in active populations, cardiopulmonary exercise training, has revealed long COVID-related changes in physiology - including alterations in peripheral muscle function, ventilatory inefficiency and autonomic dysfunction. The nature and impact of dysautonomia are further discussed in relation to postural orthostatic tachycardia syndrome, fatigue and treatment strategies that aim to combat sympathetic overactivation by stimulating the vagus nerve. We then interrogate the mechanisms that underlie long COVID symptoms, with a focus on impaired oxygen delivery due to micro-clotting and disruption of cellular energy metabolism, before considering treatment strategies that indirectly or directly tackle these mechanisms. These include remote inspiratory muscle training and integrated care pathways that combine rehabilitation and drug interventions with research into long COVID healthcare access across different populations. Overall, this review showcases how physiological research reveals the changes that occur in long COVID and how different therapeutic strategies are being developed and tested to combat this condition.

Model-based estimation of burden of COVID-19 with disability-adjusted life years and value of statistical life in West Bengal, India.

OBJECTIVES: The COVID-19 pandemic has posed unprecedented challenges to health systems and populations, particularly in India. Comprehensive, population-level studies of the burden of disease could inform planning, preparedness and policy, but are lacking in India. In West Bengal, India, we conducted a detailed analysis of the burden caused by COVID-19 from its onset to 7 January 2022. SETTING: Open-access, population-level and administrative data sets for West Bengal were used. PRIMARY AND SECONDARY OUTCOME MEASURES: Disability-adjusted life years (DALYs), years of potential productive life lost (YPPLL), cost of productivity lost (CPL: premature mortality and absenteeism), years of potential life lost (YPLL), premature years of potential life lost, working years of potential life lost (WYPLL) and value of statistical life (VSL) were estimated across scenarios (21 for DALY and 3 each for YPLL and VSL) to evaluate the effects of different factors. RESULTS: COVID-19 had a higher impact on the elderly population with 90.2% of deaths arising from people aged above 45. In males and females, respectively, DALYs were 190 568.1 and 117 310.0 years, YPPLL of the productive population was 28 714.7 and 16 355.4 years, CPL due to premature mortality was INR3 198 259 615.6 and INR583 397 335.1 and CPL due to morbidity was INR2 505 568 048.4 and INR763 720 886.1. For males and females, YPLL ranged from 189 103.2 to 272 787.5 years and 117 925.5 to 169 712.0 years for lower to higher age limits, and WYPLL was 54 333.9 and 30 942.2 years. VSL (INR million) for the lower, midpoint and upper life expectancies was 883 330.8; 882 936.4; and 880 631.3, respectively. Vaccination was associated with reduced mortality. CONCLUSIONS: The losses incurred due to COVID-19 in terms of the computed estimates in West Bengal revealed a disproportionately higher impact on the elderly and males. Analysis of various age-gender subgroups enhances localised and targeted policymaking to minimise the losses for future pandemics.

Cardiovascular Risk Factors and Clinical Outcomes among Patients Hospitalized with COVID-19: Findings from the World Heart Federation COVID-19 Study.

Background and aims: Limited data exist on the cardiovascular manifestations and risk factors in people hospitalized with COVID-19 from low- and middle-income countries. This study aims to describe cardiovascular risk factors, clinical manifestations, and outcomes among patients hospitalized with COVID-19 in low, lower-middle, upper-middle- and high-income countries (LIC, LMIC, UMIC, HIC). Methods: Through a prospective cohort study, data on demographics and pre-existing conditions at hospital admission, clinical outcomes at hospital discharge (death, major adverse cardiovascular events (MACE), renal failure, neurological events, and pulmonary outcomes), 30-day vital status, and re-hospitalization were collected. Descriptive analyses and multivariable log-binomial regression models, adjusted for age, sex, ethnicity/income groups, and clinical characteristics, were performed. Results: Forty hospitals from 23 countries recruited 5,313 patients with COVID-19 (LIC = 7.1%, LMIC = 47.5%, UMIC = 19.6%, HIC = 25.7%). Mean age was 57.0 (±16.1) years, male 59.4%, pre-existing conditions included: hypertension 47.3%, diabetes 32.0%, coronary heart disease 10.9%, and heart failure 5.5%. The most frequently reported cardiovascular discharge diagnoses were cardiac arrest (5.5%), acute heart failure (3.8%), and myocardial infarction (1.6%). The rate of in-hospital deaths was 12.9% (N = 683), and post-discharge 30 days deaths was 2.6% (N = 118) (overall death rate 15.1%). The most common causes of death were respiratory failure (39.3%) and sudden cardiac death (20.0%). The predictors of overall mortality included older age (≥60 years), male sex, pre-existing coronary heart disease, renal disease, diabetes, ICU admission, oxygen therapy, and higher respiratory rates (p < 0.001 for each). Compared to Caucasians, Asians, Blacks, and Hispanics had almost 2-4 times higher risk of death. Further, patients from LIC, LMIC, UMIC versus. HIC had 2-3 times increased risk of death. Conclusions: The LIC, LMIC, and UMIC's have sparse data on COVID-19. We provide robust evidence on COVID-19 outcomes in these countries. This study can help guide future health care planning for the pandemic globally.