Artificial intelligence in cardiology: the debate continues

In 1955, when John McCarthy and his colleagues proposed their first study of artificial intelligence, they suggested that ‘every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it’. Whether that might ever be possible would depend on how we define intelligence, but what is indisputable is that new methods are needed to analyse and interpret the copious information provided by digital medical images, genomic databases, and biobanks. Technological advances have enabled applications of artificial intelligence (AI) including machine learning (ML) to be implemented into clinical practice, and their related scientific literature is exploding. Advocates argue enthusiastically that AI will transform many aspects of clinical cardiovascular medicine, while sceptics stress the importance of caution and the need for more evidence. This report summarizes the main opposing arguments that were presented in a debate at the 2021 Congress of the European Society of Cardiology. Artificial intelligence is an advanced analytical technique that should be considered when conventional statistical methods are insufficient, but testing a hypothesis or solving a clinical problem—not finding another application for AI—remains the most important objective. Artificial intelligence and ML methods should be transparent and interpretable, if they are to be approved by regulators and trusted to provide support for clinical decisions. Physicians need to understand AI methods and collaborate with engineers. Few applications have yet been shown to have a positive impact on clinical outcomes, so investment in research is essential

Framingham score and micro albuminuria: Combined future targets for primary prevention?:Combined future targets for primary prevention?

Framingham score and microalbuminuria: Combined future targets for primary prevention?BackgroundRisk assessment is the cornerstone of primary prevention of cardiovascular disease. Our objective was to evaluate the prognostic value of the Framingham score in microalbuminuric subjects without a history of cardiovascular disease and whether this risk score can predict the benefit of treatment with fosinopril or pravastatin.MethodsSubjects were randomized to fosinopril 20 mg or matching placebo, and to pravastatin 40 mg or matching placebo (mean age 51 ± 12 years, 65% men, N=830). Prediction of 10-year risk for coronary heart disease by the Framingham score was performed using the risk factor categories with LDL cholesterol.ResultsAlbuminuria was correlated with Framingham score at baseline (P < 0.001). In the population with a Framingham risk score <20%, both albuminuria and Framingham risk score were independent predictors of the primary end point. A two-fold increase of albuminuria or the Framingham risk score was associated with a hazard ratio of 1.60 (95% CI 1.10–2.31), P=0.013 and 3.00 (95% CI 1.40–6.44), P=0.005, respectively. In contrast to fosinopril, pravastatin showed a significant beneficial effect on Framingham risk score after 4 years of follow-up (P < 0.001). Furthermore, the observed absolute risk reduction in cardiovascular events was greater than calculated by the Framingham risk score.ConclusionThe Framingham score is useful in microalbuminuric subjects as a prognostic tool. In addition, when considering the risk score as a target of intervention, the beneficial effects of therapies might be underestimated. Combining the Framingham score with the level of urinary albumin excretion is suggested as a primary prevention strategy with higher efficiency

Nudging within learning health systems: next generation decision support to improve cardiovascular care

The increasing volume and richness of healthcare data collected during routine clinical practice have not yet translated into significant numbers of actionable insights that have systematically improved patient outcomes. An evidence-practice gap continues to exist in healthcare. We contest that this gap can be reduced by assessing the use of nudge theory as part of clinical decision support systems (CDSS). Deploying nudges to modify clinician behaviour and improve adherence to guideline-directed therapy represents an underused tool in bridging the evidence-practice gap. In conjunction with electronic health records (EHRs) and newer devices including artificial intelligence algorithms that are increasingly integrated within learning health systems, nudges such as CDSS alerts should be iteratively tested for all stakeholders involved in health decision-making: clinicians, researchers, and patients alike. Not only could they improve the implementation of known evidence, but the true value of nudging could lie in areas where traditional randomized controlled trials are lacking, and where clinical equipoise and variation dominate. The opportunity to test CDSS nudge alerts and their ability to standardize behaviour in the face of uncertainty may generate novel insights and improve patient outcomes in areas of clinical practice currently without a robust evidence base

Low‐Density Lipoprotein Cholesterol Attributable Cardiovascular Disease Risk Is Sex Specific

Background: Epidemiological studies show that women are generally at lower risk for cardiovascular disease than men. Here, we investigated the sex‐specific differential effect of genetically increased low‐density lipoprotein cholesterol (LDL‐C) on cardiovascular disease (CVD) and other lipid‐associated diseases. Methods and Results: This is a 2‐sample Mendelian randomization study that uses individual participant data from 425 043 participants from the UK Biobank, including 229 279 female participants. An 80‐variant LDL‐C weighted genetic score was generated. Linear and logistic regression models with interactions were used to identify differences between sex‐specific LDL‐C effects on lipids, carotid‐intima media thickness, and multiple cardiovascular outcomes such as CVD, ischemic heart disease, peripheral artery disease, heart failure, aortic valve disease, type 2 diabetes, atrial fibrillation, and aortic aneurysm and dissection. After correction for multiple testing, we observed that the genetically increased LDL‐C effect on CVD events was sex specific: per SD genetically increased LDL‐C, female participants had a higher LDL‐C increase but an attenuated CVD risk increase compared with male participants (LDL‐C: female participants 0.71 mmol/L, 95% CI, 0.70–0.72 and male participants 0.57 mmol/L, 95% CI, 0.56–0.59. P for interaction: 5.03×10−60; CVD: female participants: odds ratio [OR], 1.32; 95% CI 1.24–1.40 and male participants: OR, 1.52; 95% CI, 1.46–1.58. P for interaction: 9.88×10−5). We also observed attenuated risks for ischemic heart disease and (nominally for) heart failure in female participants, and genetically increased LDL‐C results in higher risk for aortic valve disease in female participants compared with male participants. Genetically increased LDL‐C was also associated with an attenuated carotid‐intima media thickness increase in female participants. We did not observe other significant attenuations. Sensitivity analyses with an unweighted genetic score and sex‐specific weighted genetic scores showed similar results. Conclusions: We found that genetically increased LDL‐C has a sex‐specific differential effect on the risk for cardiovascular disease, ischemic heart disease, heart failure, and aortic valve stenosis. Our observations provide evidence that LDL‐C might be a less important determinant of CVD in women compared with men, suggesting that male patients might benefit more from LDL‐C targeted therapies for CVD management than female patients and warranting investigations into the sex‐specific relative contribution of risk factors for CVD

Differences between familial and sporadic dilated cardiomyopathy : ESC EORP Cardiomyopathy & Myocarditis registry

Aims Dilated cardiomyopathy (DCM) is a complex disease where genetics interplay with extrinsic factors. This study aims to compare the phenotype, management, and outcome of familial DCM (FDCM) and non-familial (sporadic) DCM (SDCM) across Europe. Methods and results Patients with DCM that were enrolled in the prospective ESC EORP Cardiomyopathy & Myocarditis Registry were included. Baseline characteristics, genetic testing, genetic yield, and outcome were analysed comparing FDCM and SDCM; 1260 adult patients were studied (238 FDCM, 707 SDCM, and 315 not disclosed). Patients with FDCM were younger (P <0.01), had less severe disease phenotype at presentation (P <0.02), more favourable baseline cardiovascular risk profiles (P Conclusions We observed that FDCM and SDCM have significant differences at baseline but similar short-term prognosis. Whether modification of associated cardiovascular risk factors provide opportunities for treatment remains to be investigated. Our results also show a prevalent role of genetics in FDCM and a non-marginal yield in SDCM although genetic testing is largely neglected in SDCM. Limited genetic testing and heterogeneity in panels provides a scaffold for improvement of guideline adherence.Peer reviewe

Embedded point of care randomisation for evaluating comparative effectiveness questions: PROSPECTOR-critical care feasibility study protocol

INTRODUCTION: Many routinely administered treatments lack evidence as to their effectiveness. When treatments lack evidence, patients receive varying care based on the preferences of clinicians. Standard randomised controlled trials are unsuited to comparisons of different routine treatment strategies, and there remains little economic incentive for change.Integrating clinical trial infrastructure into electronic health record systems offers the potential for routine treatment comparisons at scale, through reduced trial costs. To date, embedded trials have automated data collection, participant identification and eligibility screening, but randomisation and consent remain manual and therefore costly tasks.This study will investigate the feasibility of using computer prompts to allow flexible randomisation at the point of clinical decision making. It will compare the effectiveness of two prompt designs through the lens of a candidate research question-comparing liberal or restrictive magnesium supplementation practices for critical care patients. It will also explore the acceptability of two consent models for conducting comparative effectiveness research. METHODS AND ANALYSIS: We will conduct a single centre, mixed-methods feasibility study, aiming to recruit 50 patients undergoing elective surgery requiring postoperative critical care admission. Participants will be randomised to either 'Nudge' or 'Preference' designs of electronic point-of-care randomisation prompt, and liberal or restrictive magnesium supplementation.We will judge feasibility through a combination of study outcomes. The primary outcome will be the proportion of prompts displayed resulting in successful randomisation events (compliance with the allocated magnesium strategy). Secondary outcomes will evaluate the acceptability of both prompt designs to clinicians and ascertain the acceptability of pre-emptive and opt-out consent models to patients. ETHICS AND DISSEMINATION: This study was approved by Riverside Research Ethics Committee (Ref: 21/LO/0785) and will be published on completion. TRIAL REGISTRATION NUMBER: NCT05149820

A Role for CETP TaqIB Polymorphism in Determining Susceptibility to Atrial Fibrillation: A Nested Case Control Study

Studies investigating the genetic and environmental characteristics of atrial fibrillation (AF) may provide new insights in the complex development of AF. We aimed to investigate the association between several environmental factors and loci of candidate genes, which might be related to the presence of AF. A nested case-control study within the PREVEND cohort was conducted. Standard 12 lead electrocardiograms were recorded and AF was defined according to Minnesota codes. For every case, an age and gender matched control was selected from the same population (n = 194). In addition to logistic regression analyses, the multifactor-dimensionality reduction (MDR) method and interaction entropy graphs were used for the evaluation of gene-gene and gene-environment interactions. Polymorphisms in genes from the Renin-angiotensin, Bradykinin and CETP systems were included

Digital technology and patient and public involvement (PPI) in routine care and clinical research-A pilot study

BACKGROUND: Patient and public involvement (PPI) has growing impact on the design of clinical care and research studies. There remains underreporting of formal PPI events including views related to using digital tools. This study aimed to assess the feasibility of hosting a hybrid PPI event to gather views on the use of digital tools in clinical care and research. METHODS: A PPI focus day was held following local procedures and published recommendations related to advertisement, communication and delivery. Two exemplar projects were used as the basis for discussions and qualitative and quantitative data was collected. RESULTS: 32 individuals expressed interest in the PPI day and 9 were selected to attend. 3 participated in person and 6 via an online video-calling platform. Selected written and verbal feedback was collected on two digitally themed projects and on the event itself. The overall quality and interactivity for the event was rated as 4/5 for those who attended in person and 4.5/5 and 4.8/5 respectively, for those who attended remotely. CONCLUSIONS: A hybrid PPI event is feasible and offers a flexible format to capture the views of patients. The overall enthusiasm for digital tools amongst patients in routine care and clinical research is high, though further work and standardised, systematic reporting of PPI events is required