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1.
Nat Med ; 29(1): 219-225, 2023 01.
Article in English | MEDLINE | ID: covidwho-2185962

ABSTRACT

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.


Subject(s)
COVID-19 , Cardiovascular Diseases , Diabetes Mellitus, Type 2 , Hypertension , Humans , Cardiovascular Diseases/epidemiology , Cardiovascular Diseases/prevention & control , Cardiovascular Diseases/diagnosis , Diabetes Mellitus, Type 2/complications , Diabetes Mellitus, Type 2/drug therapy , Diabetes Mellitus, Type 2/epidemiology , Pandemics/prevention & control , COVID-19/epidemiology , Hypertension/complications , Hypertension/drug therapy , Hypertension/epidemiology , Risk Factors
2.
J Thorac Dis ; 14(4): 851-856, 2022 Apr.
Article in English | MEDLINE | ID: covidwho-1798612

ABSTRACT

Background: During COVID-19 pandemic, people who developed pneumonia and needed supplemental oxygen, where treated with low-flow oxygen therapy systems and non-invasive methods, including oxygen therapy using high flow nasal cannula (HFNC) and the application of bi-level or continuous positive airway pressure (BiPAP or CPAP). We aimed to investigate the outcomes of critical COVID-19 patients treated with HFNC and unveil predictors of HFNC failure. Methods: We retrospectively enrolled patients admitted to COVID-19 wards and treated with HFNC for COVID-19-related severe hypoxemic respiratory failure. The primary outcome of this study was treatment failure, such as the composite of intubation or death during hospital stay. The association between treatment failure and clinical features was evaluated using logistic regression models. Results: One hundred thirty-two patients with a median (IQR) PaO2/FiO2 ratio 96 (63-173) mmHg at HFNC initiation were studied. Overall, 45.4% of the patients were intubated. Hospital mortality was 31.8%. Treatment failure (intubation or death) occurred in 50.75% and after adjustment for age, gender, Charlson Comorbidity index (CCI) score and National Early Warning Score 2 (NEWS2) score on admission and PaO2/FiO2 ratio and acute respiratory distress syndrome (ARDS) severity at the time of HFNO initiation, it was significantly associated with the presence of dyspnea [adjusted OR 2.48 (95% CI: 1.01-6.12)], and higher Urea serum levels [adjusted OR 1.25 (95% CI: 1.03-1.51) mg/dL]. Conclusions: HFNC treatment was successful in almost half of the patients with severe COVID-19-related acute hypoxemic respiratory failure (AHRF). The presence of dyspnea and high serum Urea levels on admission are closely related to HFNC failure.

3.
Heart ; 108(12): 923-931, 2022 05 25.
Article in English | MEDLINE | ID: covidwho-1741654

ABSTRACT

OBJECTIVE: To evaluate antithrombotic (AT) use in individuals with atrial fibrillation (AF) and at high risk of stroke (CHA2DS2-VASc score ≥2) and investigate whether pre-existing AT use may improve COVID-19 outcomes. METHODS: Individuals with AF and CHA2DS2-VASc score ≥2 on 1 January 2020 were identified using electronic health records for 56 million people in England and were followed up until 1 May 2021. Factors associated with pre-existing AT use were analysed using logistic regression. Differences in COVID-19-related hospitalisation and death were analysed using logistic and Cox regression in individuals with pre-existing AT use versus no AT use, anticoagulants (AC) versus antiplatelets (AP), and direct oral anticoagulants (DOACs) versus warfarin. RESULTS: From 972 971 individuals with AF (age 79 (±9.3), female 46.2%) and CHA2DS2-VASc score ≥2, 88.0% (n=856 336) had pre-existing AT use, 3.8% (n=37 418) had a COVID-19 hospitalisation and 2.2% (n=21 116) died, followed up to 1 May 2021. Factors associated with no AT use included comorbidities that may contraindicate AT use (liver disease and history of falls) and demographics (socioeconomic status and ethnicity). Pre-existing AT use was associated with lower odds of death (OR=0.92, 95% CI 0.87 to 0.96), but higher odds of hospitalisation (OR=1.20, 95% CI 1.15 to 1.26). AC versus AP was associated with lower odds of death (OR=0.93, 95% CI 0.87 to 0.98) and higher hospitalisation (OR=1.17, 95% CI 1.11 to 1.24). For DOACs versus warfarin, lower odds were observed for hospitalisation (OR=0.86, 95% CI 0.82 to 0.89) but not for death (OR=1.00, 95% CI 0.95 to 1.05). CONCLUSIONS: Pre-existing AT use may be associated with lower odds of COVID-19 death and, while not evidence of causality, provides further incentive to improve AT coverage for eligible individuals with AF.


Subject(s)
Atrial Fibrillation , COVID-19 , Stroke , Aged , Anticoagulants/adverse effects , Atrial Fibrillation/complications , Atrial Fibrillation/drug therapy , Atrial Fibrillation/epidemiology , COVID-19/epidemiology , Female , Fibrinolytic Agents , Humans , Risk Assessment , Risk Factors , Stroke/etiology , Warfarin
4.
Clin Med (Lond) ; 21(6): e620-e628, 2021 Nov.
Article in English | MEDLINE | ID: covidwho-1551859

ABSTRACT

Patients and public have sought mortality risk information throughout the pandemic, but their needs may not be served by current risk prediction tools. Our mixed methods study involved: (1) systematic review of published risk tools for prognosis, (2) provision and patient testing of new mortality risk estimates for people with high-risk conditions and (3) iterative patient and public involvement and engagement with qualitative analysis. Only one of 53 (2%) previously published risk tools involved patients or the public, while 11/53 (21%) had publicly accessible portals, but all for use by clinicians and researchers.Among people with a wide range of underlying conditions, there has been sustained interest and engagement in accessible and tailored, pre- and postpandemic mortality information. Informed by patient feedback, we provide such information in 'five clicks' (https://covid19-phenomics.org/OurRiskCoV.html), as context for decision making and discussions with health professionals and family members. Further development requires curation and regular updating of NHS data and wider patient and public engagement.


Subject(s)
COVID-19 , Humans , Pandemics , Prognosis , SARS-CoV-2 , Surveys and Questionnaires
5.
Eur J Prev Cardiol ; 28(14): 1599-1609, 2021 12 20.
Article in English | MEDLINE | ID: covidwho-1091243

ABSTRACT

AIMS: Cardiovascular diseases (CVDs) increase mortality risk from coronavirus infection (COVID-19). There are also concerns that the pandemic has affected supply and demand of acute cardiovascular care. We estimated excess mortality in specific CVDs, both 'direct', through infection, and 'indirect', through changes in healthcare. METHODS AND RESULTS: We used (i) national mortality data for England and Wales to investigate trends in non-COVID-19 and CVD excess deaths; (ii) routine data from hospitals in England (n = 2), Italy (n = 1), and China (n = 5) to assess indirect pandemic effects on referral, diagnosis, and treatment services for CVD; and (iii) population-based electronic health records from 3 862 012 individuals in England to investigate pre- and post-COVID-19 mortality for people with incident and prevalent CVD. We incorporated pre-COVID-19 risk (by age, sex, and comorbidities), estimated population COVID-19 prevalence, and estimated relative risk (RR) of mortality in those with CVD and COVID-19 compared with CVD and non-infected (RR: 1.2, 1.5, 2.0, and 3.0).Mortality data suggest indirect effects on CVD will be delayed rather than contemporaneous (peak RR 1.14). CVD service activity decreased by 60-100% compared with pre-pandemic levels in eight hospitals across China, Italy, and England. In China, activity remained below pre-COVID-19 levels for 2-3 months even after easing lockdown and is still reduced in Italy and England. For total CVD (incident and prevalent), at 10% COVID-19 prevalence, we estimated direct impact of 31 205 and 62 410 excess deaths in England (RR 1.5 and 2.0, respectively), and indirect effect of 49 932 to 99 865 deaths. CONCLUSION: Supply and demand for CVD services have dramatically reduced across countries with potential for substantial, but avoidable, excess mortality during and after the pandemic.


Subject(s)
COVID-19 , Cardiovascular Diseases , Cardiovascular Diseases/diagnosis , Cardiovascular Diseases/epidemiology , Communicable Disease Control , Humans , Pandemics , SARS-CoV-2
7.
BMJ Open ; 10(11): e043828, 2020 11 17.
Article in English | MEDLINE | ID: covidwho-934100

ABSTRACT

OBJECTIVES: To estimate the impact of the COVID-19 pandemic on cancer care services and overall (direct and indirect) excess deaths in people with cancer. METHODS: We employed near real-time weekly data on cancer care to determine the adverse effect of the pandemic on cancer services. We also used these data, together with national death registrations until June 2020 to model deaths, in excess of background (pre-COVID-19) mortality, in people with cancer. Background mortality risks for 24 cancers with and without COVID-19-relevant comorbidities were obtained from population-based primary care cohort (Clinical Practice Research Datalink) on 3 862 012 adults in England. RESULTS: Declines in urgent referrals (median=-70.4%) and chemotherapy attendances (median=-41.5%) to a nadir (lowest point) in the pandemic were observed. By 31 May, these declines have only partially recovered; urgent referrals (median=-44.5%) and chemotherapy attendances (median=-31.2%). There were short-term excess death registrations for cancer (without COVID-19), with peak relative risk (RR) of 1.17 at week ending on 3 April. The peak RR for all-cause deaths was 2.1 from week ending on 17 April. Based on these findings and recent literature, we modelled 40% and 80% of cancer patients being affected by the pandemic in the long-term. At 40% affected, we estimated 1-year total (direct and indirect) excess deaths in people with cancer as between 7165 and 17 910, using RRs of 1.2 and 1.5, respectively, where 78% of excess deaths occured in patients with ≥1 comorbidity. CONCLUSIONS: Dramatic reductions were detected in the demand for, and supply of, cancer services which have not fully recovered with lockdown easing. These may contribute, over a 1-year time horizon, to substantial excess mortality among people with cancer and multimorbidity. It is urgent to understand how the recovery of general practitioner, oncology and other hospital services might best mitigate these long-term excess mortality risks.


Subject(s)
COVID-19/epidemiology , Models, Statistical , Neoplasms/epidemiology , Pandemics , Population Surveillance , SARS-CoV-2 , Adult , Cause of Death/trends , England/epidemiology , Female , Follow-Up Studies , Humans , Male , Middle Aged , Multimorbidity/trends , Survival Rate/trends , Time Factors
8.
PLoS One ; 15(8): e0237298, 2020.
Article in English | MEDLINE | ID: covidwho-712951

ABSTRACT

OBJECTIVES: We aimed to model the impact of coronavirus (COVID-19) on the clinical academic response in England, and to provide recommendations for COVID-related research. DESIGN: A stochastic model to determine clinical academic capacity in England, incorporating the following key factors which affect the ability to conduct research in the COVID-19 climate: (i) infection growth rate and population infection rate (from UK COVID-19 statistics and WHO); (ii) strain on the healthcare system (from published model); and (iii) availability of clinical academic staff with appropriate skillsets affected by frontline clinical activity and sickness (from UK statistics). SETTING: Clinical academics in primary and secondary care in England. PARTICIPANTS: Equivalent of 3200 full-time clinical academics in England. INTERVENTIONS: Four policy approaches to COVID-19 with differing population infection rates: "Italy model" (6%), "mitigation" (10%), "relaxed mitigation" (40%) and "do-nothing" (80%) scenarios. Low and high strain on the health system (no clinical academics able to do research at 10% and 5% infection rate, respectively. MAIN OUTCOME MEASURES: Number of full-time clinical academics available to conduct clinical research during the pandemic in England. RESULTS: In the "Italy model", "mitigation", "relaxed mitigation" and "do-nothing" scenarios, from 5 March 2020 the duration (days) and peak infection rates (%) are 95(2.4%), 115(2.5%), 240(5.3%) and 240(16.7%) respectively. Near complete attrition of academia (87% reduction, <400 clinical academics) occurs 35 days after pandemic start for 11, 34, 62, 76 days respectively-with no clinical academics at all for 37 days in the "do-nothing" scenario. Restoration of normal academic workforce (80% of normal capacity) takes 11, 12, 30 and 26 weeks respectively. CONCLUSIONS: Pandemic COVID-19 crushes the science needed at system level. National policies mitigate, but the academic community needs to adapt. We highlight six key strategies: radical prioritisation (eg 3-4 research ideas per institution), deep resourcing, non-standard leadership (repurposing of key non-frontline teams), rationalisation (profoundly simple approaches), careful site selection (eg protected sites with large academic backup) and complete suspension of academic competition with collaborative approaches.


Subject(s)
Betacoronavirus , Biomedical Research/methods , Coronavirus Infections/epidemiology , Pneumonia, Viral/epidemiology , COVID-19 , Coronavirus Infections/virology , Delivery of Health Care/methods , England/epidemiology , Follow-Up Studies , Health Personnel/organization & administration , Health Workforce/organization & administration , Humans , Models, Statistical , Pandemics , Pneumonia, Viral/virology , Prospective Studies , Public Health/methods , SARS-CoV-2
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