Several machine learning (ML) algorithms have been increasingly utilized for cardiovascular disease prediction. We aim to assess and summarize the overall predictive ability of ML algorithms in cardiovascular diseases. A comprehensive search strategy was designed and executed within the MEDLINE, Embase, and Scopus databases from database inception through March 15, 2019. The primary outcome was a composite of the predictive ability of ML algorithms of coronary artery disease, heart failure, stroke, and cardiac arrhythmias. Of 344 total studies identified, 103 cohorts, with a total of 3,377,318 individuals, met our inclusion criteria. For the prediction of coronary artery disease, boosting algorithms had a pooled area under the curve (AUC) of 0.88 (95% CI 0.84–0.91), and custom-built algorithms had a pooled AUC of 0.93 (95% CI 0.85–0.97). For the prediction of stroke, support vector machine (SVM) algorithms had a pooled AUC of 0.92 (95% CI 0.81–0.97), boosting algorithms had a pooled AUC of 0.91 (95% CI 0.81–0.96), and convolutional neural network (CNN) algorithms had a pooled AUC of 0.90 (95% CI 0.83–0.95). Although inadequate studies for each algorithm for meta-analytic methodology for both heart failure and cardiac arrhythmias because the confidence intervals overlap between different methods, showing no difference, SVM may outperform other algorithms in these areas. The predictive ability of ML algorithms in cardiovascular diseases is promising, particularly SVM and boosting algorithms. However, there is heterogeneity among ML algorithms in terms of multiple parameters. This information may assist clinicians in how to interpret data and implement optimal algorithms for their dataset.

Background The impact of asthma diagnosis and asthma endotype on outcomes from COVID-19 infection remains unclear. Objective To describe the association between asthma diagnosis and endotype and clinical outcomes among patients diagnosed with COVID-19 infection. Methods Retrospective multicenter cohort study of outpatients and inpatients presenting to six hospitals in the Mount Sinai Health System New York metropolitan region between March 7 th to June 7 th , 2020, with COVID-19 infection, with and without a history of asthma. The primary outcome assessed was in-hospital mortality. Secondary outcomes included hospitalization, intensive care unit (ICU) admission, mechanical ventilation, and hospital length of stay. Outcomes were compared in patients with or without asthma using a multivariate Cox regression model. Outcomes stratified by blood eosinophilia count were also assessed. Results Of 10,523 patients diagnosed with COVID-19 infection, 4902 patients were hospitalized, and 468 had a diagnosis of asthma (4.4%). When adjusted for COVID-19 disease severity, comorbidities, and concurrent therapies, patients with asthma had a lower mortality [adjusted odds ratio (OR) 0.64 (0.53-0.77), p<0.001] and a lower rate of hospitalization and ICU admission [OR 0.43 (0.28-0.64) p<0.001 and OR 0.51 (0.41-0.64), p<0.001 respectively]. Those with blood eosinophils ≥200 cells/μL, both with and without asthma, had lower mortality. Conclusion Patients with asthma may be at a reduced risk of poor outcomes from COVID-19 infection. Eosinophilia, both in those with and without asthma, may be associated with reduced mortality risk.

Background Catheter ablation is increasingly employed in the management of atrial fibrillation (AF). Data regarding safety of ablation of AF is largely derived from controlled clinical trials. Objectives The aim of this study was to analyze safety and complications of AF ablation performed in a “real world” setting outside of clinical trials, and obtain insights on predictors of complications. Methods We utilized the National Inpatient Sample database, to identify all patients who underwent AF ablations between 2015 and 2017 using International Classification of Disease—Tenth revision codes. Complications were defined as per the Agency for Health Care Research and Quality Guidelines. Statistical tests including multivariate logistic regression were performed to determine predictors of complications. Results Among 14,875 cases of AF ablation between 2015 and 2017, a total of 1884 complications were identified among 1080 (7.2%) patients. Patients with complications were likely to be older and female with a higher burden of comorbidities. A 27% increase in complications was observed from 2015 to 2017, driven by an increase in pericardial complications. Multivariate regression analysis revealed that pulmonary hypertension (adjusted odds ratio [aOR]: 1.99, p = .041) and chronic kidney disease (CKD; aOR: 1.67, p = .024), were independent predictors of complications. Centers with higher procedural volumes were associated with lower complication rates. Conclusions Complication rates related to AF ablations remain substantially high. Presence of pulmonary hypertension and CKD are predictive of higher procedural complications. Furthermore, hospital procedure volume is an important factor that correlates with complication rates.

Twitter offers a potentially novel investigation line to evaluate self-perception and awareness in the context of the public health response to the coronavirus disease (COVID-19) pandemic. Studies have shown that Twitter content may provide crucial insights into the ongoing public health crisis. 1,2 However, some studies suggest that Twitter may play an important role in propagating misinformation in previous epidemics such as the Zika, Ebola, and yellow fever virus outbreaks. [3][4][5] In the COVID-19 era, scientists and clinicians use Twitter to echo scientific evidence, especially toward an academic audience. However, in nonacademic contexts, the effect of Twitter in the COVID-19 era on public perception, whether beneficial or harmful, remains unknown. We hypothesize that there may be significant variation in signals of Twitter related to COVID-19 in nonacademic contexts.We extracted all Tweets and hashtags related to COVID-19 using keywords (e.g.

BackgroundCorticosteroids are a potential therapeutic agent for patients with COVID-19 pneumonia. The RECOVERY (Randomised Trials in COVID-19 Therapy) trial provided data on the mortality benefits of corticosteroids. The study aimed to determine the association between corticosteroid use on mortality and infection rates and to define subgroups who may benefit from corticosteroids in a real-world setting.MethodsClinical data were extracted that included demographic, laboratory data and details of the therapy, including the administration of corticosteroids, azithromycin, hydroxychloroquine, tocilizumab and anticoagulation. The primary outcome was in-hospital mortality. Secondary outcomes included intensive care unit (ICU) admission and invasive mechanical ventilation. Outcomes were compared in patients who did and did not receive corticosteroids using the multivariate Cox regression model.Results4313 patients were hospitalised with COVID-19 during the study period, of whom 1270 died (29.4%). When administered within the first 7 days after admission, corticosteroids were associated with reduced mortality (OR 0.73, 95% CI 0.55 to 0.97, p=0.03) and decreased transfers to the ICU (OR 0.72, 95% CI 0.47 to 1.11, p=0.02). This mortality benefit was particularly impressive in younger patients (<65 years of age), females and those with elevated inflammatory markers, defined as C reactive protein ≥150 mg/L (p≤0.05), interleukin-6 ≥20 pg/mL (p≤0.05) or D-dimer ≥2.0 µg/L (p≤0.05). Therapy was safe with similar rates of bacteraemia and fungaemia in corticosteroid-treated and non-corticosteroid-treated patients.ConclusionIn patients hospitalised with COVID-19 pneumonia, corticosteroid use within the first 7 days of admission decreased mortality and ICU admissions with no associated increase in bacteraemia or fungaemia.

Studies evaluating fish consumption and cardiovascular disease events have shown inconsistent results. We performed a systematic review of peer-reviewed publications from an extensive query of Ovid MEDLINE, Ovid Embase, Ovid Cochrane Database of Systematic Reviews, Scopus, and Web of Science from database inception to September 2020 for observational studies that reported the association between fish consumption and cardiovascular disease events. We identified and reviewed 24 studies related to fish consumption and the effect on cardiovascular outcomes. The study population included a total of 714,526 individuals and multiple cohorts from several countries. We found that nonfried fish consumption is probably associated with a reduced risk of overall cardiovascular disease events and myocardial infarction risk. In contrast, fried fish consumption is probably associated with an increased risk of overall cardiovascular disease events and myocardial infarction risk. No studies to date have shown any significant association between fish consumption and stroke. Our analysis suggests that fish consumption may reduce cardiovascular disease events, but fried fish consumption was associated with an increased risk of cardiovascular events.

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