Aims The effect of the COVID-19 pandemic on care and outcomes across non-COVID-19 cardiovascular (CV) diseases is unknown. A systematic review and meta-analysis was performed to quantify the effect and investigate for variation by CV disease, geographic region, country income classification and the time course of the pandemic. Methods and results From January 2019 to December 2021, Medline and Embase databases were searched for observational studies comparing a pandemic and pre-pandemic period with relation to CV disease hospitalisations, diagnostic and interventional procedures, outpatient consultations, and mortality. Observational data were synthesised by incidence rate ratios (IRR) and risk ratios (RR) for binary outcomes and weighted mean differences for continuous outcomes with 95% confidence intervals. The study was registered with PROSPERO (CRD42021265930). A total of 158 studies, covering 49 countries and 6 continents, were used for quantitative synthesis. Most studies (80%) reported information for high-income countries (HICs). Across all CV disease and geographies there were fewer hospitalisations, diagnostic and interventional procedures, and outpatient consultations during the pandemic. By meta-regression, in low-middle income countries (LMICs) compared to HICs the decline in ST-segment elevation myocardial infarction (STEMI) hospitalisations (RR 0.79, 95% confidence interval [CI] 0.66–0.94) and revascularisation (RR 0.73, 95% CI 0.62–0.87) was more severe. In LMICs, but not HICs, in-hospital mortality increased for STEMI (RR 1.22, 95% CI 1.10–1.37) and heart failure (RR 1.08, 95% CI 1.04–1.12). The magnitude of decline in hospitalisations for CV diseases did not differ between the first and second wave. Conclusions There was substantial global collateral CV damage during the COVID-19 pandemic with disparity in severity by country income classification.
ObjectiveAtrial fibrillation (AF) is common and is associated with an increased risk of stroke. We aimed to systematically review and meta-analyse multivariable prediction models derived and/or validated in electronic health records (EHRs) and/or administrative claims databases for the prediction of incident AF in the community.MethodsOvid Medline and Ovid Embase were searched for records from inception to 23 March 2021. Measures of discrimination were extracted and pooled by Bayesian meta-analysis, with heterogeneity assessed through a 95% prediction interval (PI). Risk of bias was assessed using Prediction model Risk Of Bias ASsessment Tool and certainty in effect estimates by Grading of Recommendations, Assessment, Development and Evaluation.ResultsEleven studies met inclusion criteria, describing nine prediction models, with four eligible for meta-analysis including 9 289 959 patients. The CHADS (Congestive heart failure, Hypertension, Age>75, Diabetes mellitus, prior Stroke or transient ischemic attack) (summary c-statistic 0.674; 95% CI 0.610 to 0.732; 95% PI 0.526–0.815), CHA2DS2-VASc (Congestive heart failure, Hypertension, Age>75 (2 points), Stroke/transient ischemic attack/thromboembolism (2 points), Vascular disease, Age 65–74, Sex category) (summary c-statistic 0.679; 95% CI 0.620 to 0.736; 95% PI 0.531–0.811) and HATCH (Hypertension, Age, stroke or Transient ischemic attack, Chronic obstructive pulmonary disease, Heart failure) (summary c-statistic 0.669; 95% CI 0.600 to 0.732; 95% PI 0.513–0.803) models resulted in a c-statistic with a statistically significant 95% PI and moderate discriminative performance. No model met eligibility for inclusion in meta-analysis if studies at high risk of bias were excluded and certainty of effect estimates was ‘low’. Models derived by machine learning demonstrated strong discriminative performance, but lacked rigorous external validation.ConclusionsModels externally validated for prediction of incident AF in community-based EHR demonstrate moderate predictive ability and high risk of bias. Novel methods may provide stronger discriminative performance.Systematic review registrationPROSPERO CRD42021245093.
ObjectiveTo study the association of cardiac rehabilitation and physical activity with temporal changes in health-related quality of life (HRQoL) following acute myocardial infarction (AMI).MethodsEvaluation of the Methods and Management of Acute Coronary Events-3 is a nationwide longitudinal prospective cohort study of 4570 patients admitted with an AMI between 1 November 2011 and 17 September 2013. HRQoL was estimated using EuroQol 5-Dimension-3 Level Questionnaire at hospitalisation, 30 days, and 6 and 12 months following hospital discharge. The association of cardiac rehabilitation and self-reported physical activity on temporal changes in HRQoL was quantified using inverse probability of treatment weighting propensity score and multilevel regression analyses.ResultsCardiac rehabilitation attendees had higher HRQoL scores than non-attendees at 30 days (mean EuroQol 5-Visual Analogue Scale (EQ-VAS) scores: 71.0 (SD 16.8) vs 68.6 (SD 19.8)), 6 months (76.0 (SD 16.4) vs 70.2 (SD 19.0)) and 12 months (76.9 (SD 16.8) vs 70.4 (SD 20.4)). Attendees who were physically active ≥150 min/week had higher HRQoL scores compared with those who only attended cardiac rehabilitation at 30 days (mean EQ-VAS scores: 79.3 (SD 14.6) vs 70.2 (SD 17.0)), 6 months (82.2 (SD 13.9) vs 74.9 (SD 16.7)) and 12 months (84.1 (SD 12.1) vs 75.6 (SD 17.0)). Cardiac rehabilitation and self-reported physical activity of ≥150 min/week were each positively associated with temporal improvements in HRQoL (coefficient: 2.12 (95% CI 0.68 to 3.55) and 4.75 (95% CI 3.16 to 6.34), respectively).ConclusionsCardiac rehabilitation was independently associated with temporal improvements in HRQoL at up to 12 months following hospitalisation, with such changes further improved in patients who were physically active.
Background Multimorbidity is prevalent for people with myocardial infarction (MI), yet previous studies investigated single-health conditions in isolation. We identified patterns of multimorbidity in MI survivors and their associations with changes in HRQoL. Methods In this national longitudinal cohort study, we analysed data from 9566 admissions with MI from 77 National Health Service hospitals in England between 2011 and 2015. HRQoL was measured using EuroQol 5 dimension (EQ5D) instrument and visual analogue scale (EQVAS) at hospitalisation, 6, and 12 months following MI. Latent class analysis (LCA) of pre-existing long-term health conditions at baseline was used to identify clusters of multimorbidity and associations with changes in HRQoL quantified using mixed effects regression analysis. Results Of 9566 admissions with MI (mean age of 64.1 years [SD 11.9], 7154 [75%] men), over half (5119 [53.5%] had multimorbidities. LCA identified 3 multimorbidity clusters which were severe multimorbidity (591; 6.5%) with low HRQoL at baseline (EQVAS 59.39 and EQ5D 0.62) which did not improve significantly at 6 months (EQVAS 59.92, EQ5D 0.60); moderate multimorbidity (4301; 47.6%) with medium HRQoL at baseline (EQVAS 63.08, EQ5D 0.71) and who improved at 6 months (EQVAS 71.38, EQ5D 0.76); and mild multimorbidity (4147, 45.9%) at baseline (EQVAS 64.57, EQ5D 0.75) and improved at 6 months (EQVAS 76.39, EQ5D 0.82). Patients in the severe and moderate groups were more likely to be older, women, and presented with NSTEMI. Compared with the mild group, increased multimorbidity was associated with lower EQ-VAS scores (adjusted coefficient: −5.12 [95% CI −7.04 to −3.19] and −0.98 [−1.93 to −0.04] for severe and moderate multimorbidity, respectively. The severe class was more likely than the mild class to report problems in mobility, OR 9.62 (95% confidence interval: 6.44 to 14.36), self-care 7.87 (4.78 to 12.97), activities 2.41 (1.79 to 3.26), pain 2.04 (1.50 to 2.77), and anxiety/depression 1.97 (1.42 to 2.74). Conclusions Among MI survivors, multimorbidity clustered into three distinct patterns and was inversely associated with HRQoL. The identified multimorbidity patterns and HRQoL domains that are mostly affected may help to identify patients at risk of poor HRQoL for which clinical interventions could be beneficial to improve the HRQoL of MI survivors. Trial registration ClinicalTrials.gov NCT01808027 and NCT01819103
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