Atrial fibrillation (AF) is an important risk factor for ischaemic stroke, and AF incidence is expected to increase. Guidelines recommend using oral anticoagulants (OACs) to prevent the development ...of stroke. However, studies have reported the frequent underuse of OACs in AF patients. The objective of this study is to describe nonvalvular atrial fibrillation (NVAF) incidence in England and assess the clinical and socioeconomic factors associated with the underprescribing of OACs.
We conducted a population-based retrospective cohort study using the UK Clinical Practice Research Datalink (CPRD) database to identify patients with NVAF aged ≥18 years and registered in English general practices between 2009 and 2019. Annual incidence rate of NVAF by age, deprivation quintile, and region was estimated. OAC prescribing status was explored for patients at risk for stroke and classified into the following: OAC, aspirin only, or no treatment. We used a multivariable multinomial logistic regression model to estimate relative risk ratios (RRRs) and 95% confidence intervals (CIs) of the factors associated with OAC or aspirin-only prescribing compared to no treatment in patients with NVAF who are recommended to take OAC. The multivariable regression was adjusted for age, sex, comorbidities, socioeconomic status, baseline treatment, frailty, bleeding risk factors, and takes into account clustering by general practice. Between 2009 and 2019, 12,517,191 patients met the criteria for being at risk of developing NVAF. After a median follow-up of 4.6 years, 192,265 patients had an incident NVAF contributing a total of 647,876 person-years (PYR) of follow-up. The overall age-adjusted incidence of NVAF per 10,000 PYR increased from 20.8 (95% CI: 20.4; 21.1) in 2009 to 25.5 (25.1; 25.9) in 2019. Higher incidence rates were observed for older ages and males. Among NVAF patients eligible for anticoagulation, OAC prescribing rose from 59.8% (95% CI: 59.0; 60.6) in 2009 to 83.2% (95% CI: 83.0; 83.4) in 2019. Several conditions were associated with lower risk of OAC prescribing: dementia RRR 0.52 (0.47; 0.59), liver disease 0.58 (0.50; 0.67), malignancy 0.74 (0.72; 0.77), and history of falls 0.82 (0.78; 0.85). Compared to white ethnicity, patients from black and other ethnic minorities were less likely to receive OAC; 0.78 (0.65; 0.94) and 0.76 (0.64; 0.91), respectively. Patients living in the most deprived areas were less likely to receive OAC 0.85 (0.79; 0.91) than patients living in the least deprived areas. Practices located in the East of England were associated with higher risk of prescribing aspirin only over no treatment than practices in London (RRR 1.22; 95% CI 1.02 to 1.45). The main limitation of this study is that these findings depends on accurate recording of conditions by health professionals and the inevitable residual confounding due to lack of data on certain factors that could be associated with under-prescribing of OACs.
The incidence of NVAF increased between 2009 and 2015, before plateauing. Underprescribing of OACs in NVAF is associated with a range of comorbidities, ethnicity, and socioeconomic factors, demonstrating the need for initiatives to reduce inequalities in the care for AF patients.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
With high transmissibility and no effective vaccine or therapy, COVID-19 is now a global pandemic. Government-coordinated efforts across the globe have focused on containment and mitigation, with ...varying degrees of success. Countries that have maintained low COVID-19 per-capita mortality rates appear to share strategies that include early surveillance, testing, contact tracing, and strict quarantine. The scale of coordination and data management required for effective implementation of these strategies has—in most successful countries—relied on adopting digital technology and integrating it into policy and health care. This Viewpoint provides a framework for the application of digital technologies in pandemic management and response, highlighting ways in which successful countries have adopted these technologies for pandemic planning, surveillance, testing, contact tracing, quarantine, and health care.
Glycemic variability is emerging as a measure of glycemic control, which may be a reliable predictor of complications. This systematic review and meta-analysis evaluates the association between HbA1c ...variability and micro- and macrovascular complications and mortality in type 1 and type 2 diabetes.
Medline and Embase were searched (2004-2015) for studies describing associations between HbA1c variability and adverse outcomes in patients with type 1 and type 2 diabetes. Data extraction was performed independently by two reviewers. Random-effects meta-analysis was performed with stratification according to the measure of HbA1c variability, method of analysis, and diabetes type.
Seven studies evaluated HbA1c variability among patients with type 1 diabetes and showed an association of HbA1c variability with renal disease (risk ratio 1.56 95% CI 1.08-2.25, two studies), cardiovascular events (1.98 1.39-2.82), and retinopathy (2.11 1.54-2.89). Thirteen studies evaluated HbA1c variability among patients with type 2 diabetes. Higher HbA1c variability was associated with higher risk of renal disease (1.34 1.15-1.57, two studies), macrovascular events (1.21 1.06-1.38), ulceration/gangrene (1.50 1.06-2.12), cardiovascular disease (1.27 1.15-1.40), and mortality (1.34 1.18-1.53). Most studies were retrospective with lack of adjustment for potential confounders, and inconsistency existed in the definition of HbA1c variability.
HbA1c variability was positively associated with micro- and macrovascular complications and mortality independently of the HbA1c level and might play a future role in clinical risk assessment.
Several countries affected by the COVID-19 pandemic have reported a substantial drop in the number of patients attending the emergency department with acute coronary syndromes and a reduced number of ...cardiac procedures. We aimed to understand the scale, nature, and duration of changes to admissions for different types of acute coronary syndrome in England and to evaluate whether in-hospital management of patients has been affected as a result of the COVID-19 pandemic.
We analysed data on hospital admissions in England for types of acute coronary syndrome from Jan 1, 2019, to May 24, 2020, that were recorded in the Secondary Uses Service Admitted Patient Care database. Admissions were classified as ST-elevation myocardial infarction (STEMI), non-STEMI (NSTEMI), myocardial infarction of unknown type, or other acute coronary syndromes (including unstable angina). We identified revascularisation procedures undertaken during these admissions (ie, coronary angiography without percutaneous coronary intervention PCI, PCI, and coronary artery bypass graft surgery). We calculated the numbers of weekly admissions and procedures undertaken; percentage reductions in weekly admissions and across subgroups were also calculated, with 95% CIs.
Hospital admissions for acute coronary syndrome declined from mid-February, 2020, falling from a 2019 baseline rate of 3017 admissions per week to 1813 per week by the end of March, 2020, a reduction of 40% (95% CI 37–43). This decline was partly reversed during April and May, 2020, such that by the last week of May, 2020, there were 2522 admissions, representing a 16% (95% CI 13–20) reduction from baseline. During the period of declining admissions, there were reductions in the numbers of admissions for all types of acute coronary syndrome, including both STEMI and NSTEMI, but relative and absolute reductions were larger for NSTEMI, with 1267 admissions per week in 2019 and 733 per week by the end of March, 2020, a percent reduction of 42% (95% CI 38–46). In parallel, reductions were recorded in the number of PCI procedures for patients with both STEMI (438 PCI procedures per week in 2019 vs 346 by the end of March, 2020; percent reduction 21%, 95% CI 12–29) and NSTEMI (383 PCI procedures per week in 2019 vs 240 by the end of March, 2020; percent reduction 37%, 29–45). The median length of stay among patients with acute coronary syndrome fell from 4 days (IQR 2–9) in 2019 to 3 days (1–5) by the end of March, 2020.
Compared with the weekly average in 2019, there was a substantial reduction in the weekly numbers of patients with acute coronary syndrome who were admitted to hospital in England by the end of March, 2020, which had been partly reversed by the end of May, 2020. The reduced number of admissions during this period is likely to have resulted in increases in out-of-hospital deaths and long-term complications of myocardial infarction and missed opportunities to offer secondary prevention treatment for patients with coronary heart disease. The full extent of the effect of COVID-19 on the management of patients with acute coronary syndrome will continue to be assessed by updating these analyses.
UK Medical Research Council, British Heart Foundation, Public Health England, Health Data Research UK, and the National Institute for Health Research Oxford Biomedical Research Centre.
There are limited reports outlining the financial cost of treating cardiac implantable electronic device (CIED) infection outside the United States. This study aimed to determine the average ...treatment cost of CIED infection in a large UK tertiary referral centre and compared costs of different treatment pathways that are recognised in the management of CIED infection (early versus delayed re-implantation).
We retrospectively analysed cost and length of stay (LOS) data for consecutive patients undergoing infected CIED extraction with cardiac resynchronization therapy (CRT-D with defibrillator, CRT-P with pacemaker), implantable cardioverter-defibrillators (ICDs) and permanent pacemakers (PPMs).
Between January 2013 and March 2015, complete data was available for 84 patients (18 21.4% CRT-D, 24 28.6% ICDs and 42 50.0% PPMs). When all cases were considered the cost of infection ranged from £5,139 (PPM) to £24,318 (CRT-D). Considering different treatment strategies; 41 (48.8%) underwent CIED extraction and re-implantation during the same admission (early re-implant strategy (ER). 43 (51.2%) underwent extraction, but were then discharged home to be re-admitted for day-case re-implantation (delayed re-implant strategy (DR)). Median LOS was significantly shorter in DR compared to ER (5.0 vs. 18.0 days, p<0.001). The total cost of CIED infection episode was similar for both treatment strategies (median £14,241.48 vs. £14,741.70 including wearable defibrillator (Lifevest) and outpatient antibiotics costs, ER vs. DR; p = 0.491).
CIED infections are expensive and associated with significant health-economic burden. When all device types were considered, a DR strategy is associated with reduced LOS without an increased cost penalty.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Deaths during the COVID-19 pandemic result directly from infection and exacerbation of other diseases and indirectly from deferment of care for other conditions, and are socially and geographically ...patterned. We quantified excess mortality in regions of England and Wales during the pandemic, for all causes and for non-COVID-19-associated deaths.
Weekly mortality data for 1 January 2010 to 1 May 2020 for England and Wales were obtained from the Office of National Statistics. Mean-dispersion negative binomial regressions were used to model death counts based on pre-pandemic trends and exponentiated linear predictions were subtracted from: (i) all-cause deaths and (ii) all-cause deaths minus COVID-19 related deaths for the pandemic period (week starting 7 March, to week ending 8 May).
Between 7 March and 8 May 2020, there were 47 243 (95% CI: 46 671 to 47 815) excess deaths in England and Wales, of which 9948 (95% CI: 9376 to 10 520) were not associated with COVID-19. Overall excess mortality rates varied from 49 per 100 000 (95% CI: 49 to 50) in the South West to 102 per 100 000 (95% CI: 102 to 103) in London. Non-COVID-19 associated excess mortality rates ranged from -1 per 100 000 (95% CI: -1 to 0) in Wales (ie, mortality rates were no higher than expected) to 26 per 100 000 (95% CI: 25 to 26) in the West Midlands.
The COVID-19 pandemic has had markedly different impacts on the regions of England and Wales, both for deaths directly attributable to COVID-19 infection and for deaths resulting from the national public health response.
To describe the place and causes of acute cardiovascular death during the COVID-19 pandemic.
Retrospective cohort of adult (age ≥18 years) acute cardiovascular deaths (n=5 87 225) in England and ...Wales, from 1 January 2014 to 30 June 2020. The exposure was the COVID-19 pandemic (from onset of the first COVID-19 death in England, 2 March 2020). The main outcome was acute cardiovascular events directly contributing to death.
After 2 March 2020, there were 28 969 acute cardiovascular deaths of which 5.1% related to COVID-19, and an excess acute cardiovascular mortality of 2085 (+8%). Deaths in the community accounted for nearly half of all deaths during this period. Death at home had the greatest excess acute cardiovascular deaths (2279, +35%), followed by deaths at care homes and hospices (1095, +32%) and in hospital (50, +0%). The most frequent cause of acute cardiovascular death during this period was stroke (10 318, 35.6%), followed by acute coronary syndrome (ACS) (7 098, 24.5%), heart failure (6 770, 23.4%), pulmonary embolism (2 689, 9.3%) and cardiac arrest (1 328, 4.6%). The greatest cause of excess cardiovascular death in care homes and hospices was stroke (715, +39%), compared with ACS (768, +41%) at home and cardiogenic shock (55, +15%) in hospital.
The COVID-19 pandemic has resulted in an inflation in acute cardiovascular deaths, nearly half of which occurred in the community and most did not relate to COVID-19 infection suggesting there were delays to seeking help or likely the result of undiagnosed COVID-19.
The influence of marital status on the incidence of cardiovascular disease (CVD) and prognosis after CVD is inconclusive. We systematically reviewed the literature to determine how marital status ...influences CVD and prognosis after CVD.
A search of MEDLINE and Embase in January 2018 without language restriction was performed to identify studies that evaluated the association between marital status and risk of CVD. Search terms related to both marital status and CVD were used and included studies had to be prospective in design. The outcomes of interest were CVD, coronary heart disease (CHD) or stroke incidence and mortality. We performed random effects meta-analysis stratified by the types of population by calculating odds ratios (OR) and 95% confidence intervals (95% CI).
Our analysis included 34 studies with more than two million participants. Compared with married participants, being unmarried (never married, divorced or widowed) was associated with increased odds of CVD (OR 1.42; 95% CI 1.00 to 2.01), CHD (OR 1.16,95% CI 1.04 to 1.28), CHD death (OR 1.43,95% CI 1.28 to 1.60) and stroke death (OR 1.55,95% 1.16 to 2.08). Being divorced was associated with increased odds of CHD (P<0.001) for both men and women while widowers were more likely to develop a stroke (P<0.001). Single men and women with myocardial infarction had increased mortality (OR 1.42, 95% CI 1.14 to 1.76) compared with married participants.
Marital status appears to influence CVD and prognosis after CVD. These findings may suggest that marital status should be considered in the risk assessment for CVD and outcomes of CVD based on marital status merits further investigation.
There is limited knowledge of the scale and impact of multimorbidity for patients who have had an acute myocardial infarction (AMI). Therefore, this study aimed to determine the extent to which ...multimorbidity is associated with long-term survival following AMI.
This national observational study included 693,388 patients (median age 70.7 years, 452,896 65.5% male) from the Myocardial Ischaemia National Audit Project (England and Wales) who were admitted with AMI between 1 January 2003 and 30 June 2013. There were 412,809 (59.5%) patients with multimorbidity at the time of admission with AMI, i.e., having at least 1 of the following long-term health conditions: diabetes, chronic obstructive pulmonary disease or asthma, heart failure, renal failure, cerebrovascular disease, peripheral vascular disease, or hypertension. Those with heart failure, renal failure, or cerebrovascular disease had the worst outcomes (39.5 95% CI 39.0-40.0, 38.2 27.7-26.8, and 26.6 25.2-26.4 deaths per 100 person-years, respectively). Latent class analysis revealed 3 multimorbidity phenotype clusters: (1) a high multimorbidity class, with concomitant heart failure, peripheral vascular disease, and hypertension, (2) a medium multimorbidity class, with peripheral vascular disease and hypertension, and (3) a low multimorbidity class. Patients in class 1 were less likely to receive pharmacological therapies compared with class 2 and 3 patients (including aspirin, 83.8% versus 87.3% and 87.2%, respectively; β-blockers, 74.0% versus 80.9% and 81.4%; and statins, 80.6% versus 85.9% and 85.2%). Flexible parametric survival modelling indicated that patients in class 1 and class 2 had a 2.4-fold (95% CI 2.3-2.5) and 1.5-fold (95% CI 1.4-1.5) increased risk of death and a loss in life expectancy of 2.89 and 1.52 years, respectively, compared with those in class 3 over the 8.4-year follow-up period. The study was limited to all-cause mortality due to the lack of available cause-specific mortality data. However, we isolated the disease-specific association with mortality by providing the loss in life expectancy following AMI according to multimorbidity phenotype cluster compared with the general age-, sex-, and year-matched population.
Multimorbidity among patients with AMI was common, and conferred an accumulative increased risk of death. Three multimorbidity phenotype clusters that were significantly associated with loss in life expectancy were identified and should be a concomitant treatment target to improve cardiovascular outcomes.
ClinicalTrials.gov NCT03037255.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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