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Guidelines recommend patients undergoing a first pacemaker implant who have even mild left ventricular (LV) impairment should receive biventricular or conduction system pacing (CSP). There is no corresponding recommendation for patients who already have a pacemaker. We conducted a meta-analysis of randomized controlled trials (RCTs) and observational studies assessing device upgrades. The primary outcome was the echocardiographic change in LV ejection fraction (LVEF). Six RCTs (randomizing 161 patients) and 47 observational studies (2644 patients) assessing the efficacy of upgrade to biventricular pacing were eligible for analysis. Eight observational studies recruiting 217 patients of CSP upgrade were also eligible. Fourteen additional studies contributed data on complications (25 412 patients). Randomized controlled trials of biventricular pacing upgrade showed LVEF improvement of +8.4% from 35.5% and observational studies: +8.4% from 25.7%. Observational studies of left bundle branch area pacing upgrade showed +11.1% improvement from 39.0% and observational studies of His bundle pacing upgrade showed +12.7% improvement from 36.0%. New York Heart Association class decreased by −0.4, −0.8, −1.0, and −1.2, respectively. Randomized controlled trials of biventricular upgrade found improvement in Minnesota Heart Failure Score (−6.9 points) and peak oxygen uptake (+1.1 mL/kg/min). This was also seen in observational studies of biventricular upgrades (−19.67 points and +2.63 mL/kg/min, respectively). In studies of the biventricular upgrade, complication rates averaged 2% for pneumothorax, 1.4% for tamponade, and 3.7% for infection over 24 months of mean follow-up. Lead-related complications occurred in 3.3% of biventricular upgrades and 1.8% of CSP upgrades. Randomized controlled trials show significant physiological and symptomatic benefits of upgrading pacemakers to biventricular pacing. Observational studies show similar effects between biventricular pacing upgrade and CSP upgrade.

Background: Retrievable stents and aspiration catheters have been developed to provide more effective arterial recanalisation in acute ischaemic stroke. Aims: The aim of this analysis was to test the effect of mechanical thrombectomy on mortality and longterm neurological outcome in patients presenting with acute large-vessel anterior circulation ischaemic stroke. Methods: A structured search identified randomised controlled trials of thrombectomy (using a retrievable stent or aspiration catheter) versus control on a background of medical therapy which included intravenous thrombolysis if appropriate. The primary endpoint was disability at 90-day follow-up as assessed by the modified Rankin scale (mRS). Secondary endpoints included all-cause mortality and symptomatic intracranial haemorrhage. A Bayesian mixed-effects model was used for analysis. Results: Twelve (12) trials met the inclusion criteria, comprising a total of 1,276 patients randomised to thrombectomy and 1,282 patients to control. Randomisation to thrombectomy significantly reduced disability at 90 days (OR 0.52, 95% credible interval 0.46 to 0.61, probability(control better)2 (OR 0.44, CrI 0.37 to 0.52, pr

Aims Coronary flow reserve (CFR) assessment has proven clinical utility, but Doppler-based methods are sensitive to noise and operator bias, limiting their clinical applicability. The objective of the study is to expand the adoption of invasive Doppler CFR, through the development of artificial intelligence (AI) algorithms to automatically quantify coronary Doppler quality and track flow velocity. Methods and results A neural network was trained on images extracted from coronary Doppler flow recordings to score signal quality and derive values for coronary flow velocity and CFR. The outputs were independently validated against expert consensus. Artificial intelligence successfully quantified Doppler signal quality, with high agreement with expert consensus (Spearman’s rho: 0.94), and within individual experts. Artificial intelligence automatically tracked flow velocity with superior numerical agreement against experts, when compared with the current console algorithm [AI flow vs. expert flow bias −1.68 cm/s, 95% confidence interval (CI) −2.13 to −1.23 cm/s, P < 0.001 with limits of agreement (LOA) −4.03 to 0.68 cm/s; console flow vs. expert flow bias −2.63 cm/s, 95% CI −3.74 to −1.52, P < 0.001, 95% LOA −8.45 to −3.19 cm/s]. Artificial intelligence yielded more precise CFR values [median absolute difference (MAD) against expert CFR: 4.0% for AI and 7.4% for console]. Artificial intelligence tracked lower-quality Doppler signals with lower variability (MAD against expert CFR 8.3% for AI and 16.7% for console). Conclusion An AI-based system, trained by experts and independently validated, could assign a quality score to Doppler traces and derive coronary flow velocity and CFR. By making Doppler CFR more automated, precise, and operator-independent, AI could expand the clinical applicability of coronary microvascular assessment.

There have been no studies comparing clinical outcomes of physiology-guided revascularization in patients with unprotected left main coronary disease (ULMD) between percutaneous coronary intervention (PCI) vs. coronary artery bypass grafting (CABG). The aim of this study was to assess the long-term clinical outcomes between PCI and CABG of patients with physiologically significant ULMD. From an international multicenter registry of ULMD patients interrogated with instantaneous wave-free ratio (iFR), we analyzed data from 151 patients (85 PCI vs. 66 CABG) who underwent revascularization according to the cutoff value of iFR ≤ 0.89. Propensity score matching was employed to adjust for baseline clinical characteristics. The primary endpoint was a composite of all-cause death, non-fatal myocardial infarction, and ischemia-driven target lesion revascularization. The secondary endpoints were the individual components of the primary endpoint. Mean age was 66.6 (± 9.2) years, 79.2% male. Mean SYNTAX score was 22.6 (± 8.4) and median iFR was 0.83 (IQR 0.74–0.87). After performing propensity score matching analysis, 48 patients treated with CABG were matched to those who underwent PCI. At a median follow-up period of 2.8 years, the primary endpoint occurred in 8.3% in PCI group and 20.8% in CABG group, respectively (HR 3.80; 95% CI 1.04–13.9; p = 0.043). There was no difference in each component of the primary event (p > 0.05 for all). Within the present study, iFR-guided PCI was associated with lower cardiovascular events rate in patients with ULMD and intermediate SYNTAX score, as compared to CABG. Graphical abstract State-of-the-art PCI vs. CABG for ULMD. Study design and primary endpoint in patients with physiologically significant ULMD. MACE was defined as the composite of all-cause death, non-fatal myocardial infarction, and target lesion revascularization. The blue line denotes the PCI arm, and the red line denotes the CABG arm. PCI was associated with significantly lower risk of MACE than CABG. CABG: coronary artery bypass grafting; iFR: instantaneous wave-free ratio; MACE: major adverse cardiovascular events; PCI: percutaneous coronary intervention; ULMD: unprotected left main coronary artery disease.

Background The efficacy of renal denervation has been controversial, but the procedure has now undergone several placebo-controlled trials. New placebo-controlled trial data has recently emerged, with longer follow-up of one trial and the full report of another trial (which constitutes 27% of the total placebo-controlled trial data). We therefore sought to evaluate the effect of renal denervation on ambulatory and office blood pressures in patients with hypertension. Methods We systematically identified all blinded placebo-controlled randomized trials of catheter-based renal denervation for hypertension. The primary efficacy outcome was ambulatory systolic blood pressure change relative to placebo. A random-effects meta-analysis was performed. Results 6 studies randomizing 1232 patients were eligible. 713 patients were randomized to renal denervation and 519 to placebo. Renal denervation significantly reduced ambulatory systolic blood pressure (−3.52 mmHg; 95% CI −4.94 to −2.09; p < 0.0001), ambulatory diastolic blood pressure (−1.93 mmHg; 95% CI −3.04 to −0.83, p = 0.0006), office systolic blood pressure size (−5.10 mmHg; 95% CI −7.31 to −2.90, p < 0.0001) and office diastolic pressure (effect size −3.11 mmHg; 95% CI −4.43 to −1.78, p < 0.0001). Adverse events were rare and not more common with denervation. Conclusions The totality of blinded, randomized placebo-controlled data shows that renal denervation is safe and provides genuine reduction in blood pressure for at least 6 months post-procedure. If this effect continues in the long term, renal denervation might provide a life-long 10% relative risk reduction in major adverse cardiac events and 7.5% relative risk reduction in all-cause mortality.

Objectives The authors performed an updated meta-analysis of randomized placebo-controlled trials of renal denervation and specifically compared the effect of renal denervation in patients...

Aims Sodium-glucose cotransporter 2 (SGLT-2) inhibitors have now been evaluated for the treatment of heart failure in several placebo-controlled randomized controlled trials (RCTs) across various ejection fraction ranges, but these trials were powered for composite outcomes rather than individual clinical endpoints. We therefore performed a meta-analysis to assess their safety and efficacy on all-cause mortality, cardiovascular mortality, and heart failure hospitalizations. Methods and results We performed a prospectively registered random-effects meta-analysis of all RCTs comparing SGLT-2 inhibitors to placebo in patients with heart failure. The pre-specified primary endpoint was all-cause mortality. Secondary endpoints included cardiovascular mortality, heart failure hospitalizations, and the composite of cardiovascular mortality or heart failure hospitalization. Four trials with 15 684 patients were eligible. The SGLT-2 inhibitor tested was empagliflozin in two trials, dapagliflozin in one trial, and sotagliflozin in one trial. The weighted-mean follow-up was 20.0 months. The hazard ratio (HR) for all-cause mortality was 0.91, 95% confidence interval (CI) 0.82–1.01, P = 0.071. There was a 12% reduction in cardiovascular mortality (HR 0.88, 95% CI 0.79 to 0.97, P = 0.012), and a 30% reduction in heart failure hospitalization (HR 0.70, 95% CI 0.64 to 0.77, P Conclusion SGLT-2 inhibitors significantly reduced cardiovascular mortality and heart failure hospitalizations in patients with heart failure. The effect appears consistent across three drugs studied in four trials. SGLT-2 inhibitors should become standard care for patients with heart failure.

PURPOSE: To develop an artificial intelligence (AI) solution for automated segmentation and analysis of joint cardiac MRI short-axis T1 and T2 mapping. MATERIALS AND METHODS: In this retrospective study, a joint T1 and T2 mapping sequence was used to acquire 4240 maps from 807 patients across two hospitals between March and November 2020. Five hundred nine maps from 94 consecutive patients were assigned to a holdout testing set. A convolutional neural network was trained to segment the endocardial and epicardial contours with use of an edge probability estimation approach. Training labels were segmented by an expert cardiologist. Predicted contours were processed to yield mapping values for each of the 16 American Heart Association segments. Network segmentation performance and segment-wise measurements on the testing set were compared with those of two experts on the holdout testing set. The AI model was fully integrated using open-source software to run on MRI scanners. RESULTS: A total of 3899 maps (92%) were deemed artifact-free and suitable for human segmentation. AI segmentation closely matched that of each expert (mean Dice coefficient, 0.82 ± 0.07 [SD] vs expert 1 and 0.86 ± 0.06 vs expert 2) and compared favorably with interexpert agreement (Dice coefficient, 0.84 ± 0.06 for expert 1 vs expert 2). AI-derived segment-wise values for native T1, postcontrast T1, and T2 mapping correlated with expert-derived values (R(2) = 0.96, 0.98, and 0.87, respectively, vs expert 1, and 0.97, 0.99, and 0.92 vs expert 2) and fell within the range of interexpert reproducibility (R(2) = 0.97, 0.99, and 0.90, respectively). The AI model has since been deployed at two hospitals, enabling automated inline analysis. CONCLUSION: Automated inline analysis of joint T1 and T2 mapping allows accurate segment-wise tissue characterization, with performance equivalent to that of human experts. Keywords: MRI, Neural Networks, Cardiac, Heart Supplemental material is available for this article. © RSNA, 2022

Learning objectives Machine learning (ML) is a revolution in computer science and is set to change the face of cardiology practice. In ML, humans no longer need to convert an understanding of a problem into a stepwise algorithmic solution; instead, the computer learns to solve a task for itself. While ML can seem intimidating, the underlying principles build on familiar and established techniques. The recent revolution that made ML so effective, however, was the recognition that numerous sequential layers of simple arithmetic, termed neural networks, become surprisingly effective at solving difficult problems. This ‘deep learning’ has been startlingly effective across a variety of problems, and a particular type, the convolutional neural network (CNN) has revolutionised image analysis. CNNs are inspired by the human visual cortex and have been used successfully in cardiology to process data that are one-dimensional (1D) (ECGs, pressure waveforms), two-dimensional (2D) (X-rays, MRIs) and three-dimensional (3D) (echocardiography videos, cardiac magnetic resonance cine videos and CT volumes). We are now entering the stage where these CNNs’ performances are starting to equal that of cardiologists in some domains.1 2 In this review, we will cover the basics of ML, before explaining the workings of neural networks, and particularly CNNs. ML will play an increasing role in medical practice and, as with any diagnostic test or piece of medical equipment, an understanding of these systems will better equip medical staff to interpret these systems’ results. The first chapter in an ML textbook is often made up of topics that a decade ago would have been called ‘statistics’. A simple example that we commonly encounter in cardiology is the formula for predicting …

Aims Contemporary 2nd-generation thin-strut drug-eluting stents (DES) are considered standard of care for revascularization of patients undergoing percutaneous coronary intervention. A previous meta-analysis of 10 randomized controlled trials (RCTs) with 11 658 patients demonstrated a 16% reduction in the 1-year risk of target lesion failure (TLF) with ultrathin-strut DES compared with conventional 2nd-generation thin-strut DES. Whether this benefit is sustained longer term is not known, and newer trial data may inform these relative outcomes. We therefore sought to perform an updated systematic review and meta-analysis of RCTs comparing clinical outcomes with ultrathin-strut DES (≤70 µm strut thickness) with conventional 2nd-generation thin-strut DES. Methods and results We performed a random-effects meta-analysis of all RCTs comparing ultrathin-strut DES to conventional 2nd-generation thin-strut DES. The pre-specified primary endpoint was long-term TLF, a composite of cardiac death, myocardial infarction (MI), or clinically driven target lesion revascularization (CD-TLR). Secondary endpoints included the components of TLF, stent thrombosis (ST), and all-cause death. There were 16 eligible trials in which 20 701 patients were randomized. The weighted mean follow-up duration was 2.5 years. Ultrathin-strut DES were associated with a 15% reduction in long-term TLF compared with conventional 2nd-generation thin-strut DES [relative risk (RR) 0.85, 95% confidence interval (CI) 0.76–0.96, P = 0.008] driven by a 25% reduction in CD-TLR (RR 0.75, 95% CI 0.62–0.92, P = 0.005). There were no significant differences between stent types in the risks of MI, ST, cardiac death, or all-cause mortality. Conclusions At a mean follow-up of 2.5 years, ultrathin-strut DES reduced the risk of TLF, driven by less CD-TLR compared with conventional 2nd-generation thin-strut DES, with similar risks of MI, ST, cardiac death, and all-cause mortality.

One of the most feared complications of transcatheter aortic valve implantation (TAVI) is stroke, with increased mortality and disability observed in patients suffering a stroke after TAVI. There has been no significant decline in stroke rates seen over the last 5 years; attention has therefore been given to strategies for cerebral embolic protection. With the emergence of new randomized trial data, we sought to perform an updated systematic review and meta-analysis to examine the effect of cerebral embolic protection during TAVI both on clinical outcomes and on neuroimaging parameters. We performed a random-effects meta-analysis of randomized clinical trials of cerebral embolic protection during TAVI. The primary end point was the risk of stroke. The risk of stroke was not significantly different with the use of cerebral embolic protection: relative risk (RR) 0.88, 95% confidence interval (CI) 0.57 to 1.36, p = 0.566. Nor was there a significant reduction in the risk of disabling stroke, non-disabling stroke or death. There was no significant difference in total lesion volume on MRI with cerebral embolic protection: mean difference -74.94, 95% CI -174.31 to 24.4, p = 0.139. There was also not a significant difference in the number of new ischemic lesions on MRI: mean difference -2.15, 95% -5.25 to 0.96, p = 0.176, although there was significant heterogeneity for the neuroimaging outcomes. In conclusion, cerebral embolic protection during TAVI is safe but there is no evidence of a statistically significant benefit on clinical outcomes or neuroimaging parameters.

Aims Accurately determining atrial arrhythmia mechanisms from a 12-lead electrocardiogram (ECG) can be challenging. Given the high success rate of cavotricuspid isthmus (CTI) ablation, identification of CTI-dependent typical atrial flutter (AFL) is important for treatment decisions and procedure planning. We sought to train a convolutional neural network (CNN) to classify CTI-dependent AFL vs. non-CTI dependent atrial tachycardia (AT), using data from the invasive electrophysiology (EP) study as the gold standard. Methods and results We trained a CNN on data from 231 patients undergoing EP studies for atrial tachyarrhythmia. A total of 13 500 five-second 12-lead ECG segments were used for training. Each case was labelled CTI-dependent AFL or non-CTI-dependent AT based on the findings of the EP study. The model performance was evaluated against a test set of 57 patients. A survey of electrophysiologists in Europe was undertaken on the same 57 ECGs. The model had an accuracy of 86% (95% CI 0.77–0.95) compared to median expert electrophysiologist accuracy of 79% (range 70–84%). In the two thirds of test set cases (38/57) where both the model and electrophysiologist consensus were in agreement, the prediction accuracy was 100%. Saliency mapping demonstrated atrial activation was the most important segment of the ECG for determining model output. Conclusion We describe the first CNN trained to differentiate CTI-dependent AFL from other AT using the ECG. Our model matched and complemented expert electrophysiologist performance. Automated artificial intelligence-enhanced ECG analysis could help guide treatment decisions and plan ablation procedures for patients with organized atrial arrhythmias.

Background His-bundle pacing (HBP) has emerged as an alternative to conventional ventricular pacing because of its ability to deliver physiological ventricular activation. Pacing at the His bundle produces different electrocardiographic (ECG) responses: selective His-bundle pacing (S-HBP), non-selective His bundle pacing (NS-HBP), and myocardium-only capture (MOC). These 3 capture types must be distinguished from each other, which can be challenging and time-consuming even for experts. Objective The purpose of this study was to use artificial intelligence (AI) in the form of supervised machine learning using a convolutional neural network (CNN) to automate HBP ECG interpretation. Methods We identified patients who had undergone HBP and extracted raw 12-lead ECG data during S-HBP, NS-HBP, and MOC. A CNN was trained, using 3-fold cross-validation, on 75% of the segmented QRS complexes labeled with their capture type. The remaining 25% was kept aside as a testing dataset. Results The CNN was trained with 1297 QRS complexes from 59 patients. Cohen kappa for the neural network’s performance on the 17-patient testing set was 0.59 (95% confidence interval 0.30 to 0.88; P, Graphical abstract

BACKGROUND The per-vessel level impact of physiological pattern of disease on the discordance between fractional flow reserve (FFR) and instantaneous wave-free ratio (iFR) has not been clarified.Methods and Results:Using the AJIP registry, vessels with FFR/iFR discordance (133/671 [19.8%]) were analyzed. In the left anterior descending artery (LAD), physiologically diffuse disease, as assessed by pressure-wire pullback, was associated with FFR-/iFR+ (83.3% [40/48]), while physiologically focal disease was associated with FFR+/iFR- (57.4% [31/54]), significantly (P

Speckle tracking is the most prominent technique used to estimate the regional movement of the heart based on echocardiograms. In this study, we propose an optimised-based block matching algorithm to perform speckle tracking iteratively. The proposed technique was evaluated using a publicly available synthetic echocardiographic dataset with known ground-truth from several major vendors and for healthy/ischaemic cases. The results were compared with the results from the classic (standard) two-dimensional block matching. The proposed method presented an average displacement error of 0.57 pixels, while classic block matching provided an average error of 1.15 pixels. When estimating the segmental/regional longitudinal strain in healthy cases, the proposed method, with an average of 0.32 ± 0.53, outperformed the classic counterpart, with an average of 3.43 ± 2.84. A similar superior performance was observed in ischaemic cases. This method does not require any additional ad hoc filtering process. Therefore, it can potentially help to reduce the variability in the strain measurements caused by various post-processing techniques applied by different implementations of the speckle tracking. Graphical Abstract Standard block matching versus proposed iterative block matching approach.

Aims The optimal method of revascularization for patients with left main coronary artery disease (LMCAD) is controversial. Coronary artery bypass graft surgery (CABG) has traditionally been considered the gold standard therapy, and recent randomized trials comparing CABG with percutaneous coronary intervention (PCI) with drug-eluting stents (DES) have reported conflicting outcomes. We, therefore, performed a systematic review and updated meta-analysis comparing CABG to PCI with DES for the treatment of LMCAD. Methods and results We systematically identified all randomized trials comparing PCI with DES vs. CABG in patients with LMCAD. The primary efficacy endpoint was all-cause mortality. Secondary endpoints included cardiac death, myocardial infarction (MI), stroke, and unplanned revascularization. All analyses were by intention-to-treat. There were five eligible trials in which 4612 patients were randomized. The weighted mean follow-up duration was 67.1 months. There were no significant differences between PCI and CABG for the risk of all-cause mortality [relative risk (RR) 1.03, 95% confidence interval (CI) 0.81–1.32; P = 0.779] or cardiac death (RR 1.03, 95% CI 0.79–1.34; P = 0.817). There were also no significant differences in the risk of stroke (RR 0.74, 95% CI 0.35–1.50; P = 0.400) or MI (RR 1.22, 95% CI 0.96–1.56; P = 0.110). Percutaneous coronary intervention was associated with an increased risk of unplanned revascularization (RR 1.73, 95% CI 1.49–2.02; P Conclusion The totality of randomized clinical trial evidence demonstrated similar long-term mortality after PCI with DES compared with CABG in patients with LMCAD. Nor were there significant differences in cardiac death, stroke, or MI between PCI and CABG. Unplanned revascularization procedures were less common after CABG compared with PCI. These findings may inform clinical decision-making between cardiologists, surgeons, and patients with LMCAD.

OBJECTIVE To investigate the prevalence of Escherichia coli contamination and E coli virulence gene signatures consistent with known E coli pathotypes in commercially available conventional diets and raw-meat–based diets (RMBDs). SAMPLE 40 diets in total (19 conventionally cooked kibble or canned diets and 21 RMBDs) obtained from retail stores or online distributors. PROCEDURES Each diet was cultured for E coli contamination in 3 separate container locations using standard microbiological techniques. Further characterization of E coli isolates was performed by polymerase chain reaction-based pathotype and virulence gene analysis. RESULTS Conventional diets were negative in all culture based testing. In RMBDs, bacterial contamination was similar to previous reports in the veterinary literature, with 66% (14/21) of the RMBDs having positive cultures for E coli. Among the 191 confirmed E coli isolates from these diets, 31.9% (61/191) were positive for virulence genes. Categorized by pathotype, isolates presumptively belonging to the neonatal meningitis E coli pathotype (15.7% [30/191]) were the most common, followed by enterohemorrhagic E coli (10.5% [20/191]), enteropathogenic E coli (5.8% [11/191]), uropathogenic E coli (2.1% [4/191]), and diffusely adherent E coli (1.6% [3/191]). CLINICAL RELEVANCE The results of this study reaffirmed the bacteriologic risks previously associated with RMBDs. Furthermore, potential zoonotic concerns associated with identified pathotypes in these diets may have significant consequences for owners in the animals’ home environment. Potential risk associated with bacterial contamination should be addressed in animals fed RMBDs.

Transcatheter aortic valve replacement (TAVR) is the treatment of choice for patients with severe aortic stenosis who are at a moderate or higher surgical risk. Stroke is a recognised and serious complication of TAVR, and it is important to identify patients at higher stroke risk. This study aims to discover if aortic valve calcium score calculated from pre-TAVR computed tomography is associated with acute stroke in TAVR patients.We conducted a retrospective, observational cohort study of 433 consecutive patients undergoing TAVR between January 2017 and December 2019 at the Hammersmith Hospital.This cohort had a median age of 83 years (interquartile range, 78-87), and 52.7% were male. Fifty-two patients (12.0%) had a history of previous stroke or transient ischemic attack. Median aortic valve calcium score was 2145 (interquartile range, 1427-3247) Agatston units. Twenty-two patients had a stroke up to the time of discharge (5.1%). In a logistic regression model, aortic valve calcium score was significantly associated with acute stroke (odds ratio [OR], 1.26; 95% confidence interval [CI], 1.01-1.53;Aortic valve calcium score from pre-TAVR computed tomography is an independent risk factor for acute stroke in the TAVR population. This is an additional clinical value of the pre-TAVR aortic valve calcium score and should be considered when discussing periprocedural stroke risk.

Disruptive events within a country can have global repercussions, creating a need for the anticipation and planning of these events. Crystal Cube (CC) is a novel approach to forecasting disruptive ...

Background and purpose Artificial intelligence (AI) has the potential to greatly improve efficiency and reproducibility of quantification in echocardiography, but to gain widespread use it must both meet expert standards of excellence and have a transparent methodology. We developed an online platform to enable multiple collaborators to annotate medical images for training and validating neural networks. Methods Using our online collaborative platform 9 expert echocardiographers labelled 2056 images that comprised the training dataset. They labelled the four points from where the standard parasternal long axis (PLAX) measurements (interventricular septum, posterior wall, left ventricular dimension) would be made. Using these labelled images we trained a 2d convolutional neural network to replicate these labels. Separately, we curated an external validation dataset of the systolic and diastolic frames of 100 PLAX acquisitions. Each of these images were labelled twice by 13 different experts, and the average of the 26 measurements was taken as the consensus standard. We then compared the individual experts and the AI measurements on the external validation dataset to the consensus standard, and calculated the precision standard deviation (SD) of the signed differences from the consensus standard. Results For diastolic septum thickness, the AI had a precision SD of 1.8 mm (ICC 0.81; 95% CI 0.73 to 0.97), compared with 2.0 mm for the individual experts (ICC 0.64; 95% CI 0.57 to 0.72). For diastolic posterior wall thickness, the AI had a precision SD 1.4 mm (ICC 0.54; 95% CI 0.38 to 0.66), and the individual experts 2.2 mm (ICC 0.37; 95% CI 0.29 to 0.46). The AI's precision SD for left ventricular internal dimension was 3.5 mm (ICC 0.93, 95% CI 0.90 to 0.94), and for individual experts was 4.4mm (ICC 0.82, 95% CI 0.78 to 0.95). Both the experts and AI performed better in diastole than systole (precision SD AI 2.5mm vs 4.3mm, p Conclusions AI trained by a group of echocardiography experts was able to perform PLAX measurements which matched the reference standard more closely than any individual expert's own measurements. This open, collaborative approach may be a model for the development of AI that is explainable to, and trusted by clinicians. Funding Acknowledgement Type of funding sources: Public grant(s) – National budget only. Main funding source(s): NIHR Imperil BRC ITMATDr Howard was additionally funded by Wellcome. Online collaborative platformResults of AI and experts

Background Left ventricular longitudinal strain has been reported to deliver reproducibility, sensitivity and prognostic value over and above ejection fraction. However, it currently relies on uninspectable proprietary algorithms and suffers from a lack of widespread clinical use. Uptake may be improved by increasing user trust through greater transparency. Purpose We therefore developed a machine-learning based method, trained, and validated with accredited experts from our AI Echocardiography Collaborative. We make the dataset, code, and trained network freely available under an open-source license. Methods AI enables strain to be calculated without relying on speckle tracking by directly locating key points and borders across frames. Strain can then be calculated as the fractional shortening of the left ventricular perimeter. We first curated a dataset of 7523 images, including 2587 apical four chamber, each labelled by a single expert from our collaboration of 17 hospitals, using our online platform (Figure 1). Using both this dataset and a semi-supervised approach, we trained a 3d convolutional neural network to identify the annulus, apex, and the endocardial border throughout the cardiac cycle. Separately, we constructed an external validation dataset of 100 apical 4 chamber video-loops. The systolic and diastolic frame were identified, and each image was separately labelled by 11 experts. From these labels we then derived the expert consensus strain for each of the 100 video loops. These experts also ordered all 100 echocardiograms by their visual grading of left ventricular longitudinal function. Finally, a single expert calculated strain using two different proprietary commercial packages (A and B). Results Consensus strain measurements (obtained by averaging individual assessments by the 11 experts) across the 100 cases ranged from −4% to −27%, with strong correlations with the individual experts and machine methods (Figure 2). Using each cases' consensus across experts as the gold standard, median error from consensus was 3.1% for individual experts, 3.4% for Propriety A, 2.6% for Proprietary B, 2.6% for our AI. Using the visual grading of longitudinal strain as the reference, the 11 individual experts and 4 machine methods each showed significant correlation: coefficients ranged from 0.55 to 0.69 for experts, and for Proprietary A was 0.68, Proprietary B 0.69, and our AI 0.69. Conclusions Our open-source, vendor-independent AI-based strain measure automatically produces values that agree with expert consensus, as strongly as the individual experts do. It also agrees with the subjective visual ranking by longitudinal function. Our open-source AI strain performs at least as well as closed-source speckle-based approaches, and may enable increased clinical and research use of longitudinal strain. Funding Acknowledgement Type of funding sources: Public grant(s) – National budget only. Main funding source(s): NIHR Imperial BRC ITMAT.Dr Howard was additionally funded by Wellcome. Figure 1. Collaborative online platformFigure 2. Correlations between strain methods

N-of-1 Trial of a Statin, Placebo, or No Treatment Patients who had discontinued statins because of side effects received four bottles of a statin, four bottles of placebo, and four empty bottles, ...

Under current Federal Information Security Management Act of 2002 (FISMA) requirements, all new federal IT programs and modernization efforts using blockchain must meet National Institute of Standards and Technology (NIST) cryptographic standards. This article evaluates four major blockchain technologies-Ethereum, Hyperledger Fabric, R3's Corda, and Multichain-to determine their level of NIST compliance.

Objectives: This study developed a neural network to perform automated pressure waveform analysis and allow real-time accurate identification of damping. Background: Damping of aortic pressure during coronary angiography must be identified to avoid serious complications and make accurate coronary physiology measurements. There are currently no automated methods to do this, and so identification of damping requires constant monitoring, which is prone to human error. Methods: The neural network was trained and tested versus core laboratory expert opinions derived from 2 separate datasets. A total of 5,709 aortic pressure waveforms of individual heart beats were extracted and classified. The study developed a recurrent convolutional neural network to classify beats as either normal, showing damping, or artifactual. Accuracies were reported using the opinions of 2 independent core laboratories. Results: The neural network was 99.4% accurate (95% confidence interval: 98.8% to 99.6%) at classifying beats from the testing dataset when judged against the opinions of the internal core laboratory. It was 98.7% accurate (95% confidence interval: 98.0% to 99.2%) when judged against the opinions of an external core laboratory not involved in neural network training. The neural network was 100% sensitive, with no beats classified as damped misclassified, with a specificity of 99.8%. The positive predictive and negative predictive values were 98.1% and 99.5%. The 2 core laboratories agreed more closely with the neural network than with each other. Conclusions: Arterial waveform analysis using neural networks allows rapid and accurate identification of damping. This demonstrates how machine learning can assist with patient safety and the quality control of procedures.

Supplemental Digital Content is available in the text., Background: Physiological assessment with pressure wire pullback can characterize coronary artery disease (CAD) with a focal or diffuse pattern. However, the clinical relevance of this distinction is unknown. We use data from the ORBITA trial (Objective Randomised Blinded Investigation With Optimal Medical Therapy of Angioplasty in Stable Angina) to test if the pattern of CAD predicts the placebo-controlled efficacy of percutaneous coronary intervention (PCI) on stress echocardiography ischemia and symptom end points. Methods: One hundred sixty-four patients in ORBITA underwent blinded instantaneous wave-free ratio (iFR) pullback assessment before randomization. Focal disease was defined as a ≥0.03 iFR unit drop within 15 mm, rather than over a longer distance. Analyses were performed using regression modeling. Results: In the PCI arm (n=85), 48 were focal and 37 were diffuse. In the placebo arm (n=79), 35 were focal and 44 were diffuse. Focal stenoses were associated with significantly lower fractional flow reserve (FFR) and iFR values than diffusely diseased vessels (mean FFR and iFR, focal 0.60±0.15 and 0.65±0.24, diffuse 0.78±0.10 and 0.88±0.08, respectively, P

The authors performed an updated meta-analysis of randomized placebo-controlled trials of renal denervation and specifically compared the effect of renal denervation in patients taking medications and in those not taking medications.Renal denervation has now undergone several blinded placebo-controlled trials, covering the spectrum from patients with drug-resistant hypertension to those not yet taking antihypertensive medications.All blinded placebo-controlled randomized trials of catheter-based renal sympathetic denervation for hypertension were systematically identified, and a random-effects meta-analysis was performed. The primary efficacy outcome was the change in ambulatory systolic blood pressure beyond the effect of the placebo procedure. Analysis was stratified by whether there was background antihypertensive medication use.There were 7 eligible trials, totaling 1,368 patients. Denervation significantly reduced ambulatory systolic (mean difference -3.61 mm Hg; 95% CI: -4.89 to -2.33 mm Hg; P 0.0001), ambulatory diastolic (-1.85 mm Hg; 95% CI: -2.78 to -0.92 mm Hg; P 0.0001), office systolic (-5.86 mm Hg; 95% CI: -7.77 to -3.94 mm Hg; P 0.0001), and office diastolic (-3.63 mm Hg; 95% CI: -4.77 to -2.50; P 0.0001) blood pressure. There was no evidence that the use of concomitant antihypertensive medication had a significant impact on the effect of denervation on any of these endpoints (PThe randomized placebo-controlled trials show consistently that renal denervation provides significant reduction in ambulatory and office blood pressure. Although the magnitude of benefit, about 4/2 mm Hg, is modest, it is similar between patients on background antihypertensive medications and those who are not. Denervation could therefore be a useful strategy at various points for patients who are not willing to add antihypertensive agents. Whether the effect changes with time is currently unknown.

Funding Acknowledgements Type of funding sources: None. Background Cardiovascular magnetic resonance (CMR) is a key diagnostic investigation in acute myocarditis (1) and permits quantification of late gadolinium enhancement (LGE) and myocardial oedema. Follow-up CMR imaging is recommended to check for persistence of scar and oedema (2). Persistent late gadolinium enhancement is associated with a worse prognosis (3). It is not known whether all patients require follow-up scanning or whether the initial scan can provide useful information to identify which patients need convalescent assessment. Purpose In this study we considered whether extent of troponin elevation, extent of T2 elevation and initial late gadolinium enhancement burden predicted long-term late gadolinium enhancement at follow-up. Methods Index and follow-up CMR scans of consecutive patients presenting with a diagnosis of acute myocarditis between 2019 and 2020 across three hospitals were included. Inclusion criteria were: follow-up scan within 9 months of the index scan, CMR with LGE imaging and T2 mapping, and acute myocarditis being the primary diagnosis of the index scan. Myocardial T2 values in the area affected by myocarditis and percentage of LV myocardium showing late enhancement (using a threshold-based full height half width or manual region of interest strategy) were extracted. Results 20 patients were included in the study (80% male; mean age 37 years). Mean interval between the index and follow-up scan was 4.1 months. Peak troponin level during the acute illness was not associated with the proportion of LV myocardium affected by LGE in the index scan (R^2 Conclusions The extent of troponin elevation and initial CMR phenotype was not a good predictor of the burden of long-term late gadolinium enhancement. Although most cases showed improvement in LGE scar burden between index and follow-up imaging, neither peak troponin level during the acute episode, nor T2 values at the first CMR scan were predictive of initial or change in scar burden. Serial CMR assessment is required to identify those patients who have residual long-term scarring.

Background: The mechanisms underlying atrial fibrillation (AF) remain controversial. We developed Representation of Electrical Tracking or Origin-Mapping to characterize activation wavefronts by direction and uniformity, accumulating data as an orbital plot and analyzed as frequency histograms. We applied this technique to patients undergoing AF ablation to determine if AF activation is random. Methods: Patients undergoing persistent AF ablation were recruited, and an AFocusII was positioned at multiple left atrial locations and kept steady for 1 minute to collect electrograms. The AFocusII was returned to the original site and position after >10 minutes for a repeat 1-minute data collection. Data were exported to custom Representation of Electrical Tracking or Origin-Mapping software, and 30 seconds consecutive time windows at each location were studied using frequency histograms of wavefronts. R50 (the range in degrees containing 50% of the total activation) was used as a method to enable statistical comparisons of activation patterns. Electrogram characterization into categories of complex fractionated atrial electrograms by Ensite Precision was subjected to similar analysis. Results: Consecutive 30 seconds segments were studied at 161 locations in 18 pts. Mean overlap between frequency histograms was 79.5%±7.7 (95% CI, 78.3–80.7). Nine patients underwent delayed mapping at the same location, and mean overlap between the first 30 seconds and >10 minute interval was 73%±11.8 and 71.9%±13.6 for consecutive 30-second segments. Stability was confirmed using R50 (Bland-Altman mean difference: 0.87°; limits of agreement: −34.0 to 36.0; r =0.005; P =0.95). A greater variance in R50 was observed between different locations within a patient than the variance within the same locations (intraclass correlation=0.765; P P r =0.36, P Conclusions: There appears to be preferential activation patterns during persistent AF indicating spatiotemporal stability. This has important implication to our mechanistic understanding of persistent AF.

Funding Acknowledgements Type of funding sources: Public Institution(s). Main funding source(s): British Heart Foundation Background Cardiac resynchronization therapy delivered via biventricular pacing is thought to improve haemodynamic function through resynchronization of ventricular activation. Biventricular pacing also improves ventricular filling by shortening atrioventricular delay. Quantifying the relative contributions of these two mechanisms requires atrioventricular delay to be altered while left bundle branch block is preserved. This occurs when the His bundle is paced at an output below the left bundle branch block correction threshold. Purpose We performed His bundle pacing with preservation of left bundle branch block to measure the relative contributions of atrioventricular delay shortening and ventricular resynchronisation to the overall haemodynamic benefit of biventricular pacing. Methods Patients with left bundle branch block referred for conventional cardiac resynchronization therapy with biventricular pacing were recruited. Using a high precision, beat-by-beat systolic blood pressure assessment protocol, we assessed the haemodynamic effects of biventricular pacing and temporary His bundle pacing with left bundle branch block preservation at a full range of atrioventricular delays. We used non-invasive epicardial mapping (ECGI) to assess left ventricular activation time. Left bundle branch block preservation was defined as Results In 19 patients, His bundle pacing with preservation of left bundle branch block produced a peak systolic blood pressure improvement of 5.1mmHg (95% confidence interval: 2.2 to 8.0, p = 0.0013) compared to AAI pacing. In 16 of these patients, biventricular pacing was performed and produced a peak systolic blood pressure improvement of 7.1mmHg (3.8 to 10.4, p Conclusion Biventricular pacing in left bundle branch block improves haemodynamic function through ventricular resynchronization and shortening of atrioventricular delay. The majority of benefit appears to be produced by atrioventricular delay shortening. When left bundle branch block is not corrected, His bundle pacing may still produce considerable haemodynamic improvement through this mechanism. Abstract Figure.

Funding Acknowledgements Type of funding sources: Private grant(s) and/or Sponsorship. Main funding source(s): NIHR Imperial Biomedical Research Centre Introduction Implantable Cardioverter-Defibrillators (ICDs) cannot distinguish between ventricular tachycardia (VT) with haemodynamic compromise from haemodynamically tolerated VT to ensure that therapies are delivered only when necessary. Currently, unnecessary therapies are reduced by longer duration thresholds and higher rate thresholds. This can result in ICDs withholding or delaying therapies during haemodynamically compromising VT while potentially still providing therapies during rapid or prolonged VT that is haemodynamically well tolerated. Laser doppler perfusion monitoring (LDPM) allows assessment of peripheral blood flow as a surrogate for haemodynamic status. We have previously demonstrated that laser doppler perfusion signals, analysed using an electro-mechanical coupling algorithm (SafeShock), can reliably identify loss of perfusion during ventricular fibrillation (VF), as well as discriminate VF from simulated lead fractures and T wave over-sensing. The utility of LDPM signals in VT, however, has not been established. Purpose In this study we assessed the utility of LDPM using the SafeShock algorithm to discriminate haemodynamically tolerated VT from VT with haemodynamic compromise. Methods Recruited participants underwent a rapid ventricular pacing protocol to simulate VT at different rates. Pacing was performed using the right ventricular lead of an implanted pacing device or a temporary pacing wire in the right ventricular apex. 3-lead ECG, blood pressure (either invasively using a radial artery catheter or non-invasively using beat-by-beat finometry) and LDPM signal were continuously recorded during the protocol. LDPM signals during simulated VT were analysed using the SafeShock electro-mechanical algorithm and compared to blood pressure change from baseline intrinsic rhythm to simulated VT. Results We obtained 588 recordings of simulated VT in 56 patients at rates of 100 bpm, 120 bpm, 140 bpm, 160 bpm, 180 bpm and 200 bpm. Percentage change in systolic blood pressure from baseline to VT correlated with LDPM-derived perfusion value during VT (Spearman’s Rho = 0.7786, p < 0.0001). Using a cut-off of 5 units, perfusion value predicted a 20% drop in systolic blood pressure in VT with an accuracy of 89.4% (sensitivity 94.8%, specificity 83.6%, p value Conclusions Peripheral perfusion measurements, analysed using an electro-mechanical algorithm, can accurately discriminate haemodynamically tolerated VT from VT with haemodynamic compromise. ICDs with integrated LDPM sensors and algorithms could make therapy decisions based on the circulatory status of patients with arrhythmias not just rate and duration parameters. This could reduce unnecessary therapies while facilitating prompt treatment of compromising arrhythmias. Abstract Figure 1

Funding Acknowledgements Type of funding sources: Public Institution(s). Main funding source(s): British Heart Foundation Background: His bundle pacing can be achieved in two ways selective His bundle pacing, where the His bundle is captured alone, and non-selective His bundle pacing, where local myocardium is also captured resulting a pre-excited ECG appearance. We assessed the impact of this ventricular pre-excitation on left and right ventricular dys-synchrony. Methods We recruited patients who displayed both selective and non-selective His bundle pacing. We performed non-invasive epicardial electrical mapping to determine left and right ventricular activation times and patterns. Results In the primary analysis (n = 20, all patients), non-selective His bundle pacing did not prolong LVAT compared to select His bundle pacing by a pre-specified non-inferiority margin of 10ms (LVAT prolongation: -5.5ms, 95% confidence interval (CI): -0.6 to -10.4, non-inferiority p In patients with narrow intrinsic QRS (n = 6), non-selective His bundle pacing preserved left ventricular activation time (-2.9ms, 95%CI: -9.7 to 4.0, p = 0.331) but prolonged QRS duration (31.4ms, 95%CI: 22.0 to 40.7, p = 0.0003) and mean right ventricular activation time (16.8ms, 95%CI: -5.3 to 38.9, p = 0.108) compared to selective His bundle pacing. Activation pattern of the left ventricular surface was unchanged between selective and non-selective His bundle pacing. Non-selective His bundle pacing produced early basal right ventricular activation, which was not observed with selective His bundle pacing. Conclusions Compared to selective His bundle pacing, local myocardial capture during non-selective His bundle pacing produces right ventricular pre-excitation resulting in prolongation of QRS duration. However, non-selective His bundle pacing preserves the left ventricular activation time and pattern of selective His bundle pacing. When choosing between selective and non-selective His bundle pacing, left ventricular dyssynchrony is not an important factor. Abstract Figure: Selective vs Non-Selective HBP

Funding Acknowledgements Type of funding sources: Public Institution(s). Main funding source(s): British Heart Foundation Imperial Centre of Research Excellence Background/Introduction ECG algorithms for identifying accessory pathway (AP) locations are inaccurate and difficult to use. Human expert interpretation is poorly reproducible. Artificial intelligence (AI) techniques such as machine learning can improve accuracy in classification tasks by eschewing theory-driven predictions. More reproducible and accurate AP localisation could shorten procedure time and personalise ablation consent. Purpose We developed a neural network to perform AP localisation using 12-lead ECGs. Its decision-making process was analysed to enable explainability of the neural network. Methods A convolutional neural network was trained on raw, digital, intra-procedural 12-lead ECGs of patients with manifest APs who underwent successful ablation. ECGs were labelled with AP locations as left-sided, septal or right-sided using procedure reports, fluoroscopy and electro-anatomical maps. Accuracy of the neural network was assessed via 4-fold cross-validation and was compared to the Arruda algorithm. Five cardiologists were also assessed for their accuracy in determining locations in sub-groups of cases. The neural network was retrospectively analysed to identify areas of ECGs most influential to its predictions using importance mapping. Results In 156 cases, accuracy of the neural network (92.9%) was significantly higher than the Arruda algorithm (76.9%; p The figure shows (A) architecture of the neural network, (B) accuracy of the neural network, Arruda algorithm and five cardiologists, (*, p = 0.05 – 0.01; **, p = 0.01 – 0.001; ***, p = 0.001 - 0.0001; ****, p Conclusion AI ECG interpretation allows accurate, reproducible prediction of AP locations, superior to conventional algorithms and human interpretation. Although AI decision-making is thought of as a ‘black box’, explanation visualisation techniques such as importance mapping allow humans to understand aspects of how a neural network make decisions. A prospectively validated neural network could be integrated into clinical practice to improve pre-procedural AP localisation. Abstract Figure. Summary of results

Background Guidelines recommend dual antiplatelet therapy (DAPT) after transcatheter aortic valve replacement (TAVR) but guidelines predate the publication of the largest randomized trial. There have been few trials in the field to date, and with a small number of total patients; pooling their results may therefore be helpful. Methods We systematically identified all randomized trials comparing SAPT to DAPT after TAVR. The primary endpoint was the risk of major bleeding. Secondary endpoints included all bleeding, life-threatening bleeding, stroke, myocardial infarction, death and cardiac death. Results Four trials, randomizing 1086 participants, were eligible (541 randomized to SAPT and 545 randomized to DAPT). The weighted mean follow-up was 9.1 months. The risk of major bleeding was significantly increased after DAPT (relative risk (RR) 2.36, 95% confidence interval (CI) 1.27 to 4.40, P = 0.007). There was a similar increased risk for all bleeding (RR 1.65, 95% CI 1.24 to 2.19, P < 0.001), although not for life-threatening bleeding (RR 1.44, 95% CI 0.74 to 2.77, P = 0.282). There were no significant differences in the risk of stroke, myocardial infarction (MI), death or cardiac death. There was no heterogeneity observed for any endpoint (I2 = 0.0%). Conclusions DAPT after TAVR is associated with an increased risk of major bleeding and all bleeding. There is no evidence of a significant difference between DAPT or SAPT for the risks of stroke, MI, death or cardiac death. However, the total number of patients randomized is small and the duration of follow-up is short. Larger scale randomized trials with longer follow-up are required to assess for any potential differences in ischemic endpoints or mortality.

Background Physiology-guided treatment strategy improves clinical outcomes of patients with coronary artery disease. However, it has not been fully evaluated whether such guideline-based strategy is useful for patients with diffuse coronary artery disease as well, which is known to be one of the major factors affecting morbidity and mortality. Purpose The aim of this study was to clarify clinical outcomes of patients with diffuse coronary artery disease whose treatment strategy was based on coronary physiology. Methods From an international multicentre registry of iFR-pullback, consecutive 1067 patients (1185 vessels) with stable angina were included in whom coronary lesions were deferred or revascularized according to the iFR cutoff: 0.89. The physiological pattern of disease was classified according to the iFR-pullback recording as predominantly physiologically diffuse (n=463) or predominantly physiologically focal (n=722). Major adverse cardiovascular events (MACEs), defined as a composite of cardiac death, non-fatal myocardial infarction, and ischemia-driven target lesion revascularization during follow-up period, were compared between diffuse and focal groups, in both deferred and revascularized groups, respectively. Results Mean age was 67.1±10.7 years and 75.8% of patients were men. Median iFR was 0.88 (interquartile range: 0.80 to 0.92). At a median follow-up period of 18 months, no significant differences in MACEs were found between diffuse and focal groups, in both iFR-based deferred and revascularized groups. In the deferred group (n=480), MACEs occurred in 6.9% patients (15/217) in the diffuse group and 8.0% patients (21/263) in the focal group (p=0.44). In the revascularized group (n=705), MACEs occurred in 8.9% patients (22/246) in the diffuse group and 7.2% patients (33/459) in the focal group (p=0.49). Conclusions Despite potentially higher risks in patients with diffuse coronary artery disease, clinical outcomes of those patients were comparable to those of patients without diffuse disease, as long as treatment strategy was based on the physiology guidance, which is globally recommended by international guidelines. Funding Acknowledgement Type of funding source: None

Background Beta-blockers are widely used for many cardiovascular conditions; however, their efficacy in contemporary clinical practice remains uncertain. Methods We performed a prospectively designed, umbrella review of meta-analyses of randomised controlled trials (RCTs) investigating the evidence of beta-blockers in the contemporary management of coronary artery disease (CAD), heart failure (HF), patients undergoing surgery or hypertension (registration: PROSPERO CRD42016038375). We searched MEDLINE, EMBASE and the Cochrane Library from inception until December 2018. Outcomes were analysed as beta-blockers versus control for all-cause mortality, myocardial infarction (MI), incident HF or stroke. Two independent investigators abstracted the data, assessed the quality of the evidence and rated the certainty of evidence. Results We identified 98 meta-analyses, including 284 unique RCTs and 1,617,523 patient-years of follow-up. In CAD, 12 meta-analyses (93 RCTs, 103,481 patients) showed that beta-blockers reduced mortality in analyses before routine reperfusion, but there was a lack of benefit in contemporary studies where ≥ 50% of patients received thrombolytics or intervention. Beta-blockers reduced incident MI at the expense of increased HF. In HF with reduced ejection fraction, 34 meta-analyses (66 RCTs, 35,383 patients) demonstrated a reduction in mortality and HF hospitalisation with beta-blockers in sinus rhythm, but not in atrial fibrillation. In patients undergoing surgery, 23 meta-analyses (89 RCTs, 19,211 patients) showed no effect of beta-blockers on mortality for cardiac surgery, but increased mortality in non-cardiac surgery. In non-cardiac surgery, beta-blockers reduced MI after surgery but increased the risk of stroke. In hypertension, 27 meta-analyses (36 RCTs, 260,549 patients) identified no benefit versus placebo, but beta-blockers were inferior to other agents for preventing mortality and stroke. Conclusions Beta-blockers substantially reduce mortality in HF patients in sinus rhythm, but for other conditions, clinicians need to weigh up both benefit and potential risk.