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1. The arrhythmic substrate of hypertrophic cardiomyopathy using ECG imaging

Author: Ji-Jian Chow, Kevin M. W. Leong, Matthew Shun-Shin, Sian Jones, Oliver P. Guttmann, Saidi A. Mohiddin, Pier Lambiase, Perry M. Elliott, Julian O. M. Ormerod, Michael Koa-Wing, David Lefroy, Phang Boon Lim, Nicholas W. F. Linton, Fu Siong Ng, Norman A. Qureshi, Zachary I. Whinnett, Nicholas S. Peters, Darrel P. Francis, Amanda M. Varnava, and Prapa Kanagaratnam
Subjects: hypertrophic cardiomyopathy, sudden death, electrocardiographic imaging, implantable defibrillator, risk stratification, Physiology, QP1-981
Abstract: Introduction: Patients with hypertrophic cardiomyopathy (HCM) are at risk for lethal ventricular arrhythmia, but the electrophysiological substrate behind this is not well-understood. We used non-invasive electrocardiographic imaging to characterize patients with HCM, including cardiac arrest survivors.Methods: HCM patients surviving ventricular fibrillation or hemodynamically unstable ventricular tachycardia (n = 17) were compared to HCM patients without a personal history of potentially lethal arrhythmia (n = 20) and a pooled control group with structurally normal hearts. Subjects underwent exercise testing by non-invasive electrocardiographic imaging to estimate epicardial electrophysiology.Results: Visual inspection of reconstructed epicardial HCM maps revealed isolated patches of late activation time (AT), prolonged activation-recovery intervals (ARIs), as well as reversal of apico-basal trends in T-wave inversion and ARI compared to controls (p < 0.005 for all). AT and ARI were compared between groups. The pooled HCM group had longer mean AT (60.1 ms vs. 52.2 ms, p < 0.001), activation dispersion (55.2 ms vs. 48.6 ms, p = 0.026), and mean ARI (227 ms vs. 217 ms, p = 0.016) than structurally normal heart controls. HCM ventricular arrhythmia survivors could be differentiated from HCM patients without a personal history of life-threatening arrhythmia by longer mean AT (63.2 ms vs. 57.4 ms, p = 0.007), steeper activation gradients (0.45 ms/mm vs. 0.36 ms/mm, p = 0.011), and longer mean ARI (234.0 ms vs. 221.4 ms, p = 0.026). A logistic regression model including whole heart mean activation time and activation recovery interval could identify ventricular arrhythmia survivors from the HCM cohort, producing a C statistic of 0.76 (95% confidence interval 0.72–0.81), with an optimal sensitivity of 78.6% and a specificity of 79.8%.Discussion: The HCM epicardial electrotype is characterized by delayed, dispersed conduction and prolonged, dispersed activation-recovery intervals. Combination of electrophysiologic measures with logistic regression can improve differentiation over single variables. Future studies could test such models prospectively for risk stratification of sudden death due to HCM.
Published: 2024
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2. Automated echocardiographic left ventricular dimension assessment in dogs using artificial intelligence: Development and validation

Author: Catherine C. Stowell, Valeria Kallassy, Beth Lane, Jonathan Abbott, Kieran Borgeat, David Connolly, Oriol Domenech, Joanna Dukes‐McEwan, Luca Ferasin, Josefa Fernández Del Palacio, Chris Linney, Jose Novo Matos, Ilaria Spalla, Nuala Summerfield, Tommaso Vezzosi, James P. Howard, Matthew J. Shun‐Shin, Darrel P. Francis, and Virginia Luis Fuentes
Subjects: artificial intelligence, echocardiography, vendor‐neutral, Veterinary medicine, SF600-1100
Abstract: Abstract Background Artificial intelligence (AI) could improve accuracy and reproducibility of echocardiographic measurements in dogs. Hypothesis A neural network can be trained to measure echocardiographic left ventricular (LV) linear dimensions in dogs. Animals Training dataset: 1398 frames from 461 canine echocardiograms from a single specialist center. Validation: 50 additional echocardiograms from the same center. Methods Training dataset: a right parasternal 4‐chamber long axis frame from each study, labeled by 1 of 18 echocardiographers, marking anterior and posterior points of the septum and free wall. Validation Dataset End‐diastolic and end‐systolic frames from 50 studies, annotated twice (blindly) by 13 experts, producing 26 measurements of each site from each frame. The neural network also made these measurements. We quantified its accuracy as the deviation from the expert consensus, using the individual‐expert deviation from consensus as context for acceptable variation. The deviation of the AI measurement away from the expert consensus was assessed on each individual frame and compared with the root‐mean‐square‐variation of the individual expert opinions away from that consensus. Results For the septum in end‐diastole, individual expert opinions deviated by 0.12 cm from the consensus, while the AI deviated by 0.11 cm (P = .61). For LVD, the corresponding values were 0.20 cm for experts and 0.13 cm for AI (P = .65); for the free wall, experts 0.20 cm, AI 0.13 cm (P
Published: 2024
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3. Quality assurance of late gadolinium enhancement cardiac magnetic resonance images: a deep learning classifier for confidence in the presence or absence of abnormality with potential to prompt real-time image optimization

Author: Sameer Zaman, Kavitha Vimalesvaran, Digby Chappell, Marta Varela, Nicholas S. Peters, Hunain Shiwani, Kristopher D. Knott, Rhodri H. Davies, James C. Moon, Anil A. Bharath, Nick WF Linton, Darrel P. Francis, Graham D. Cole, and James P. Howard
Subjects: Late gadolinium enhancement, Artificial intelligence, Deep learning, Neural networks, Efficiency, Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract: Background: Late gadolinium enhancement (LGE) of the myocardium has significant diagnostic and prognostic implications, with even small areas of enhancement being important. Distinguishing between definitely normal and definitely abnormal LGE images is usually straightforward, but diagnostic uncertainty arises when reporters are not sure whether the observed LGE is genuine or not. This uncertainty might be resolved by repetition (to remove artifact) or further acquisition of intersecting images, but this must take place before the scan finishes. Real-time quality assurance by humans is a complex task requiring training and experience, so being able to identify which images have an intermediate likelihood of LGE while the scan is ongoing, without the presence of an expert is of high value. This decision-support could prompt immediate image optimization or acquisition of supplementary images to confirm or refute the presence of genuine LGE. This could reduce ambiguity in reports. Methods: Short-axis, phase-sensitive inversion recovery late gadolinium images were extracted from our clinical cardiac magnetic resonance (CMR) database and shuffled. Two, independent, blinded experts scored each individual slice for “LGE likelihood” on a visual analog scale, from 0 (absolute certainty of no LGE) to 100 (absolute certainty of LGE), with 50 representing clinical equipoise. The scored images were split into two classes—either “high certainty” of whether LGE was present or not, or “low certainty.” The dataset was split into training, validation, and test sets (70:15:15). A deep learning binary classifier based on the EfficientNetV2 convolutional neural network architecture was trained to distinguish between these categories. Classifier performance on the test set was evaluated by calculating the accuracy, precision, recall, F1-score, and area under the receiver operating characteristics curve (ROC AUC). Performance was also evaluated on an external test set of images from a different center. Results: One thousand six hundred and forty-five images (from 272 patients) were labeled and split at the patient level into training (1151 images), validation (247 images), and test (247 images) sets for the deep learning binary classifier. Of these, 1208 images were “high certainty” (255 for LGE, 953 for no LGE), and 437 were “low certainty”. An external test comprising 247 images from 41 patients from another center was also employed. After 100 epochs, the performance on the internal test set was accuracy = 0.94, recall = 0.80, precision = 0.97, F1-score = 0.87, and ROC AUC = 0.94. The classifier also performed robustly on the external test set (accuracy = 0.91, recall = 0.73, precision = 0.93, F1-score = 0.82, and ROC AUC = 0.91). These results were benchmarked against a reference inter-expert accuracy of 0.86. Conclusion: Deep learning shows potential to automate quality control of late gadolinium imaging in CMR. The ability to identify short-axis images with intermediate LGE likelihood in real-time may serve as a useful decision-support tool. This approach has the potential to guide immediate further imaging while the patient is still in the scanner, thereby reducing the frequency of recalls and inconclusive reports due to diagnostic indecision.
Published: 2024
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4. Automating quality control in cardiac magnetic resonance: Artificial intelligence for discriminative assessment of planning and motion artifacts and real-time reacquisition guidance

Author: Hoi C. Cheung, Kavitha Vimalesvaran, Sameer Zaman, Michalis Michaelides, Matthew J. Shun-Shin, Darrel P. Francis, Graham D. Cole, and James P. Howard
Subjects: Artificial intelligence, Machine learning, Cardiac magnetic resonance, Quality control, Quality assessment, Convolutional neural networks, Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract: Background: Accurate measurements from cardiovascular magnetic resonance (CMR) images require precise positioning of scan planes and elimination of motion artifacts from arrhythmia or breathing. Unidentified or incorrectly managed artifacts degrade image quality, invalidate clinical measurements, and decrease diagnostic confidence. Currently, radiographers must manually inspect each acquired image to confirm diagnostic quality and decide whether reacquisition or a change in sequences is warranted. We aimed to develop artificial intelligence (AI) to provide continuous quality scores across different quality domains, and from these, determine whether cines are clinically adequate, require replanning, or warrant a change in protocol. Methods: A three-dimensional convolutional neural network was trained to predict cine quality graded on a continuous scale by a level 3 CMR expert, focusing separately on planning and motion artifacts. It incorporated four distinct output heads for the assessment of image quality in terms of (a, b, c) 2-, 3- and 4-chamber misplanning, and (d) long- and short-axis arrhythmia/breathing artifact. Backpropagation was selectively performed across these heads based on the labels present for each cine. Each image in the testing set was reported by four level 3 CMR experts, providing a consensus on clinical adequacy. The AI's assessment of image quality and ability to identify images requiring replanning or sequence changes were evaluated with Spearman’s rho and the area under receiver operating characteristic curve (AUROC), respectively. Results: A total of 1940 cines across 1387 studies were included. On the test set of 383 cines, AI-judged image quality correlated strongly with expert judgment, with Spearman’s rho of 0.84, 0.84, 0.81, and 0.81 for 2-, 3- and 4-chamber planning quality and the extent of arrhythmia or breathing artifacts, respectively. The AI also showed high efficacy in flagging clinically inadequate cines (AUROC 0.88, 0.93, and 0.93 for identifying misplanning of 2-, 3- and 4-chamber cines, and 0.90 for identifying movement artifacts). Conclusion: AI can assess distinct domains of CMR cine quality and provide continuous quality scores that correlate closely with a consensus of experts. These ratings could be used to identify cases where reacquisition is warranted and guide corrective actions to optimize image quality, including replanning, prospective gating, or real-time imaging.
Published: 2024
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5. Ventricular Conduction Stability Noninvasively Identifies an Arrhythmic Substrate in Survivors of Idiopathic Ventricular Fibrillation

Author: Ji‐Jian Chow, Kevin M. W. Leong, Matthew J. Shun‐Shin, Julian O. M. Ormerod, Michael Koa‐Wing, David C. Lefroy, Phang Boon Lim, Nicholas W. F. Linton, Fu Siong Ng, Norman A. Qureshi, Zachary I. Whinnett, Nicholas S. Peters, Darrel P. Francis, Amanda M. Varnava, and Prapa Kanagaratnam
Subjects: exercise testing, idiopathic ventricular fibrillation, myocardial ischemia, premature ventricular complex, Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract: Background Idiopathic ventricular fibrillation (VF) is a diagnosis of exclusion following normal cardiac investigations. We sought to determine if exercise‐induced changes in electrical substrate could distinguish patient groups with various ventricular arrhythmic pathophysiological conditions and identify patients susceptible to VF. Methods and Results Computed tomography and exercise testing in patients wearing a 252‐electrode vest were combined to determine ventricular conduction stability between rest and peak exercise, as previously described. Using ventricular conduction stability, conduction heterogeneity in idiopathic VF survivors (n=14) was compared with those surviving VF during acute ischemia with preserved ventricular function following full revascularization (n=10), patients with benign ventricular ectopy (n=11), and patients with normal hearts, no arrhythmic history, and negative Ajmaline challenge during Brugada family screening (Brugada syndrome relatives; n=11). Activation patterns in normal subjects (Brugada syndrome relatives) are preserved following exercise, with mean ventricular conduction stability of 99.2±0.9%. Increased heterogeneity of activation occurred in the idiopathic VF survivors (ventricular conduction stability: 96.9±2.3%) compared with the other groups combined (versus 98.8±1.6%; P=0.001). All groups demonstrated periodic variation in activation heterogeneity (frequency, 0.3–1 Hz), but magnitude was greater in idiopathic VF survivors than Brugada syndrome relatives or patients with ventricular ectopy (7.6±4.1%, 2.9±2.9%, and 2.8±1.2%, respectively). The cause of this periodicity is unknown and was not replicable by introducing exercise‐induced noise at comparable frequencies. Conclusions In normal subjects, ventricular activation patterns change little with exercise. In contrast, patients with susceptibility to VF experience activation heterogeneity following exercise that requires further investigation as a testable manifestation of underlying myocardial abnormalities otherwise silent during routine testing.
Published: 2023
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6. The impact of artificial intelligence on clinical education: perceptions of postgraduate trainee doctors in London (UK) and recommendations for trainers

Author: Maya Banerjee, Daphne Chiew, Keval T. Patel, Ieuan Johns, Digby Chappell, Nick Linton, Graham D. Cole, Darrel P. Francis, Jo Szram, Jack Ross, and Sameer Zaman
Subjects: Artificial intelligence, Machine learning, Medical education, Clinical training, Special aspects of education, LC8-6691, Medicine
Abstract: Abstract Background Artificial intelligence (AI) technologies are increasingly used in clinical practice. Although there is robust evidence that AI innovations can improve patient care, reduce clinicians’ workload and increase efficiency, their impact on medical training and education remains unclear. Methods A survey of trainee doctors’ perceived impact of AI technologies on clinical training and education was conducted at UK NHS postgraduate centers in London between October and December 2020. Impact assessment mirrored domains in training curricula such as ‘clinical judgement’, ‘practical skills’ and ‘research and quality improvement skills’. Significance between Likert-type data was analysed using Fisher’s exact test. Response variations between clinical specialities were analysed using k-modes clustering. Free-text responses were analysed by thematic analysis. Results Two hundred ten doctors responded to the survey (response rate 72%). The majority (58%) perceived an overall positive impact of AI technologies on their training and education. Respondents agreed that AI would reduce clinical workload (62%) and improve research and audit training (68%). Trainees were skeptical that it would improve clinical judgement (46% agree, p = 0.12) and practical skills training (32% agree, p
Published: 2021
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7. Why Do I Get Side Effects? Personalized (N-of-1) Trials for Statin Intolerance and the Nocebo Effect

Author: James Philip Howard, Frances A. Wood, and Darrel P. Francis
Subjects: Electronic computers. Computer science, QA75.5-76.95
Published: 2022
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8. Discriminating electrocardiographic responses to His-bundle pacing using machine learning

Author: Ahran D. Arnold, MBBS, James P. Howard, MB BChir, Aiswarya Gopi, BSc, Cheng Pou Chan, BSc, Nadine Ali, BMBCh, Daniel Keene, MBChB, PhD, Matthew J. Shun-Shin, BMBCh, PhD, Yousif Ahmad, BMBS, PhD, Ian J. Wright, BSc, Fu Siong Ng, MBBS, PhD, Nick W.F. Linton, MBBS, PhD, Prapa Kanagaratnam, MB BChir, PhD, Nicholas S. Peters, MBBS, MD, FHRS, Daniel Rueckert, PhD, Darrel P. Francis, MB BChir, MD, and Zachary I. Whinnett, BMBS, PhD
Subjects: Artificial intelligence, Conduction system pacing, Electrocardiography, His-bundle pacing, Machine learning, Neural networks, Diseases of the circulatory (Cardiovascular) system, RC666-701, Medical technology, R855-855.5
Abstract: 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
Published: 2020
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9. Beta-blocker efficacy across different cardiovascular indications: an umbrella review and meta-analytic assessment

Author: Oliver J. Ziff, Monica Samra, James P. Howard, Daniel I. Bromage, Frank Ruschitzka, Darrel P. Francis, and Dipak Kotecha
Subjects: Systematic review, Coronary artery disease, Heart failure, Hypertension, Perioperative, Meta-analysis, Medicine
Abstract: Abstract 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.
Published: 2020
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10. Inadvertent QRS prolongation by an optimization device-based algorithm in patients with cardiac resynchronization therapy

Author: Kamil Sedláček, Rostislav Polášek, Helena Jansová, Domenico Grieco, Pavel Kučera, Josef Kautzner, Darrel P. Francis, and Dan Wichterle
Subjects: Medicine, Science
Abstract: Background Device-based algorithms offer the potential for automated optimization of cardiac resynchronization therapy (CRT), but the process for accepting them into clinical use is currently still ad-hoc, rather than based on pre-clinical and clinical testing of specific features of validity. We investigated how the QuickOpt-guided VV delay (VVD) programming performs against the clinical and engineering heuristic of QRS complex shortening by CRT. Methods A prospective, 2-center study enrolled 37 consecutive patients with CRT. QRS complex duration (QRSd) was assessed during intrinsic atrioventricular conduction, synchronous biventricular pacing, and biventricular pacing with QuickOpt-proposed VVD. The measurements were done manually by electronic calipers in signal-averaged and magnified 12-lead QRS complexes. Results Native QRSd was 174 ± 22 ms. Biventricular pacing with empiric AVD and synchronous VVD resulted in QRSd 156 ± 20 ms, a significant narrowing from the baseline QRSd by 17 ± 27 ms, P = 0.0003. In 36 of 37 patients, the QuickOpt algorithm recommended left ventricular preexcitation with VVD of 42 ± 18 ms (median 40 ms; interquartile range 30–55 ms, P Conclusions QuickOpt algorithm systematically favours a left-preexcitation VVD which translates into a significant prolongation of the QRSd compared to synchronous biventricular pacing. There is no reason to believe that a manipulation that systematically widens QRSd should be considered to optimize physiology. Device-based CRT optimization algorithms should undergo systematic mechanistic pre-clinical evaluation in various scenarios before they are tested in large clinical studies.
Published: 2022

11. The Placebo-Controlled Effect of Percutaneous Coronary Intervention on Exercise Induced Changes in Anti-Malondialdehyde-LDL Antibody Levels in Stable Coronary Artery Disease: A Substudy of the ORBITA Trial

Author: Adam Hartley, Matthew Shun-Shin, Mikhail Caga-Anan, Christopher Rajkumar, Alexandra N. Nowbar, Michael Foley, Darrel P. Francis, Dorian O. Haskard, Ramzi Y. Khamis, and Rasha K. Al-Lamee
Subjects: atherosclerosis, percutaneous coronary intervention (PCI), exercise, LDL-cholesterol, oxidised LDL (oxLDL), malondialdehyde-modified LDL (MDA-LDL), Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract: Aim: Malondialdehyde-modified low-density lipoprotein (MDA-LDL) forms a significant component of oxidised LDL. The effects of exercise on levels of MDA-LDL and anti-MDA-LDL antibodies are not well-understood. Furthermore, it is not known whether these can be modified in patients with coronary artery disease by percutaneous coronary intervention (PCI).Methods: The Objective Randomised Blinded Investigation with optimal medical Therapy of Angioplasty in stable angina (ORBITA) trial was the first blinded, multi-centre randomised trial of PCI vs. placebo procedure for angina relief. Serum samples were available at four time-points: pre-randomisation pre- (P1) and post- (P2) exercise and post-randomisation (6-weeks following the PCI or placebo procedure), pre- (P3) and post- (P4) exercise. ELISAs were performed using laboratory-developed assays for MDA-LDL (adjusted for Apolipoprotein B) and anti-MDA-LDL antibodies.Results: One hundred ninety-six of the 200 patients (age 66.1 [SD 8.99] years, 28% female) with severe single vessel coronary artery disease suitable for PCI enrolled in the ORBITA trial had blood available for analysis. With exercise at pre-randomisation (P2–P1) there was no significant change in adjusted MDA-LDL (−0.001, 95% CI −0.004 to 0.001; p = 0.287); however, IgG and IgM anti-MDA-LDL significantly declined (−0.022, 95% CI −0.029 to −0.014, p < 0.0001; −0.016, 95% CI −0.024 to −0.008, p = 0.0002, respectively). PCI did not have a significant impact on either the pre-exercise values (P3 controlling for P1) of MDA-LDL (p = 0.102), IgG (p = 0.444) or IgM anti-MDA-LDL (p = 0.909). Nor did PCI impact the exercise induced changes in these markers (P4 controlling for P1, P2, and P3) for MDA-LDL (p = 0.605), IgG (p = 0.725) or IgM anti-MDA-LDL (p = 0.171). Pre-randomisation ischaemia on stress echo did not impact these interactions.Conclusions: Exercise results in an acute reduction in anti-oxLDL antibodies in patients with severe single vessel coronary disease, possibly indicating an induction in homoeostatic clearance via the innate immune system. However, PCI did not ameliorate this effect.
Published: 2021
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12. Achieving optimal adherence to medical therapy by telehealth: Findings from the ORBITA medication adherence sub‐study

Author: David Thompson, Rasha Al‐Lamee, Michael Foley, Hakim M. Dehbi, Simon Thom, Justin E. Davies, Darrel P. Francis, Prashanth Patel, Pankaj Gupta, and ORBITA Investigators
Subjects: cardiovascular diseases, chromatography, liquid, coronary artery disease, medication adherence, therapeutics, Therapeutics. Pharmacology, RM1-950
Abstract: Abstract Introduction The ORBITA trial of percutaneous coronary intervention (PCI) versus a placebo procedure for patients with stable angina was conducted across six sites in the United Kingdom via home monitoring and telephone consultations. Patients underwent detailed assessment of medication adherence which allowed us to measure the efficacy of the implementation of the optimization protocol and interpretation of the main trial endpoints. Methods Prescribing data were collected throughout the trial. Self‐reported adherence was assessed, and urine samples collected at pre‐randomization and at follow‐up for direct assessment of adherence using high‐performance liquid chromatography with tandem mass spectrometry (HPLC MS/MS). Results Self‐reported adherence was >96% for all drugs in both treatment groups at both stages. The percentage of samples in which drug was detected at pre‐randomization and at follow‐up in the PCI versus placebo groups respectively was: clopidogrel, 96% versus 90% and 98% versus 94%; atorvastatin, 95% versus 92% and 92% versus 91%; perindopril, 95% versus 97% and 85% versus 100%; bisoprolol, 98% versus 99% and 96% versus 97%; amlodipine, 99% versus 99% and 94% versus 96%; nicorandil, 98% versus 96% and 94% versus 92%; ivabradine, 100% versus 100% and 100% versus 100%; and ranolazine, 100% versus 100% and 100% versus 100%. Conclusions Adherence levels were high throughout the study when quantified by self‐reporting methods and similarly high proportions of drug were detected by urinary assay. The results indicate successful implementation of the optimization protocol delivered by telephone, an approach that could serve as a model for treatment of chronic conditions, particularly as consultations are increasingly conducted online.
Published: 2021
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13. Achieving Optimal Medical Therapy: Insights From the ORBITA Trial

Author: Michael Foley, Christopher A. Rajkumar, Matthew Shun‐Shin, Sashiananthan Ganesananthan, Henry Seligman, James Howard, Alexandra N. Nowbar, Thomas R. Keeble, John R. Davies, Kare H. Tang, Robert Gerber, Peter O’Kane, Andrew S. P. Sharp, Ricardo Petraco, Iqbal S. Malik, Sukhjinder Nijjer, Sayan Sen, Darrel P. Francis, and Rasha Al‐Lamee
Subjects: adverse effects, angina, compliance/adherence, medical therapy, randomized controlled trial, Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract: Background In stable coronary artery disease, medications are used for 2 purposes: cardiovascular risk reduction and symptom improvement. In clinical trials and clinical practice, medication use is often not optimal. The ORBITA (Objective Randomised Blinded Investigation With Optimal Medical Therapy of Angioplasty in Stable Angina) trial was the first placebo‐controlled trial of percutaneous coronary intervention. A key component of the ORBITA trial design was the inclusion of a medical optimization phase, aimed at ensuring that all patients were treated with guideline‐directed truly optimal medical therapy. In this study, we report the medical therapy that was achieved. Methods and Results After enrollment into the ORBITA trial, all 200 patients entered a 6‐week period of intensive medical therapy optimization, with initiation and uptitration of risk reduction and antianginal therapy. At the prerandomization stage, the median number of antianginals established was 3 (interquartile range, 2–4). A total of 195 patients (97.5%) reached the prespecified target of ≥2 antianginals; 136 (68.0%) did not stop any antianginals because of adverse effects, and the median number of antianginals stopped for adverse effects per patient was 0 (interquartile range, 0–1). Amlodipine and bisoprolol were well tolerated (stopped for adverse effects in 4/175 [2.3%] and 9/167 [5.4%], respectively). Ranolazine and ivabradine were also well tolerated (stopped for adverse effects in 1/20 [5.0%] and 1/18 [5.6%], respectively). Isosorbide mononitrate and nicorandil were stopped for adverse effects in 36 of 172 (20.9%) and 32 of 141 (22.7%) of patients, respectively. Statins were well tolerated and taken by 191 of 200 (95.5%) patients. Conclusions In the 12‐week ORBITA trial period, medical therapy was successfully optimized and well tolerated, with few drug adverse effects leading to therapy cessation. Truly optimal medical therapy can be achieved in clinical trials, and translating this into longer‐term clinical practice should be a focus of future study. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT02062593.
Published: 2021
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14. Prognostic significance of troponin level in 3121 patients presenting with atrial fibrillation (The NIHR Health Informatics Collaborative TROP‐AF study)

Author: Amit Kaura, Ahran D. Arnold, Vasileios Panoulas, Benjamin Glampson, Jim Davies, Abdulrahim Mulla, Kerrie Woods, Joe Omigie, Anoop D. Shah, Keith M. Channon, Jonathan N. Weber, Mark R. Thursz, Paul Elliott, Harry Hemingway, Bryan Williams, Folkert W. Asselbergs, Michael O'Sullivan, Graham M. Lord, Narbeh Melikian, David C. Lefroy, Darrel P. Francis, Ajay M. Shah, Rajesh Kharbanda, Divaka Perera, Riyaz S. Patel, and Jamil Mayet
Subjects: angiography, atrial fibrillation, coronary artery disease, mortality, troponin, Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract: Background Patients presenting with atrial fibrillation (AF) often undergo a blood test to measure troponin, but interpretation of the result is impeded by uncertainty about its clinical importance. We investigated the relationship between troponin level, coronary angiography, and all‐cause mortality in real‐world patients presenting with AF. Methods and Results We used National Institute of Health Research Health Informatics Collaborative data to identify patients admitted between 2010 and 2017 at 5 tertiary centers in the United Kingdom with a primary diagnosis of AF. Peak troponin results were scaled as multiples of the upper limit of normal. A total of 3121 patients were included in the analysis. Over a median follow‐up of 1462 (interquartile range, 929–1975) days, there were 586 deaths (18.8%). The adjusted hazard ratio for mortality associated with a positive troponin (value above upper limit of normal) was 1.20 (95% CI, 1.01–1.43; P
Published: 2020
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15. Importance of the aortic reservoir in determining the shape of the arterial pressure waveform – The forgotten lessons of Frank

Author: Justin E. Davies, Nearchos Hadjiloizou, Debora Leibovich, Anura Malaweera, Jordi Alastruey-Arimon, Zachary I. Whinnett, Charlotte H. Manisty, Darrel P. Francis, Jazmin Aguado-Sierra, Rodney A. Foale, Iqbal S. Malik, Kim H. Parker, Jamil Mayet, and Alun D. Hughes
Subjects: Aortic pressure, Wave reflection, Windkessel, Aortic cushioning, Augmentation index, Specialties of internal medicine, RC581-951, Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract: It has been recognised for nearly 200 years that the human pressure waveform changes in shape with ageing and disease. The shape of the pressure waveform has been explained in terms of two fundamental models: the Windkessel (reservoir) and wave theory. In its simplest form the Windkessel model satisfactorily explains the pressure waveform in diastole but cannot model pressure changes in systole. Wave theory satisfactorily models the pressure waveform but predicts the existence of ‘self-cancelling’ forward and backward waves in diastole which are difficult to explain in biological terms. We propose that a hybrid reservoir–wave model better describes the pressure waveform and may enable assessment of aortic function from pressure measurements made at any large systemic artery.
Published: 2019
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16. Contribution of the Lung to the Genesis of Cheyne‐Stokes Respiration in Heart Failure: Plant Gain Beyond Chemoreflex Gain and Circulation Time

Author: Alberto Giannoni, Francesco Gentile, Alessandro Navari, Chiara Borrelli, Gianluca Mirizzi, Giosuè Catapano, Giuseppe Vergaro, Francesco Grotti, Monica Betta, Massimo F. Piepoli, Darrel P. Francis, Claudio Passino, and Michele Emdin
Subjects: chemoreceptor, chronic heart failure, circulation, lung, sleep apnea, Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract: Background The contribution of the lung or the plant gain (PG; ie, change in blood gases per unit change in ventilation) to Cheyne‐Stokes respiration (CSR) in heart failure has only been hypothesized by mathematical models, but never been directly evaluated. Methods and Results Twenty patients with systolic heart failure (age, 72.4±6.4 years; left ventricular ejection fraction, 31.5±5.8%), 10 with relevant CSR (24‐hour apnea‐hypopnea index [AHI] ≥10 events/h) and 10 without (AHI
Published: 2019
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17. Aortic Stiffness Is Related to the Ischemic Brain Injury Biomarker N-Methyl-D-aspartate Receptor Antibody Levels in Aortic Valve Replacement

Author: Emaddin Kidher, Vanash M. Patel, Petros Nihoyannopoulos, Jon R. Anderson, Andrew Chukwuemeka, Darrel P. Francis, Hutan Ashrafian, and Thanos Athanasiou
Subjects: Neurology. Diseases of the nervous system, RC346-429
Abstract: Background. Aortic stiffness changes the flow pattern of circulating blood causing microvascular damage to different end-organ tissues, such as brain cells. The relationship between aortic stiffness measured by pulse wave velocity (PWV) and serum ischemic brain injury biomarker N-methyl-D-aspartate receptor antibody (NR2Ab) levels in aortic valve replacement has not been assessed. Methods. Patients undergoing aortic valve replacement (AVR) for aortic stenosis (AS) had their PWV and NR2Ab serum levels measured preoperatively. We analyzed PWV and NR2Ab in two ways: (1) as continuous variables using the actual value and (2) as dichotomous variables (PWV-norm and PWV-high groups) and (NR2Ab-low and NR2Ab-high groups). Results. Fifty-six patients (71 ± 8.4 years) were included in this study. The NR2Ab level (ng/mL) was significantly higher in the PWV-high group (n=21) than in PWV-norm group (n=35; median 1.8±1.2 versus 1.2 ± 0.7, resp., P=0.003). NR2Ab level was positively associated with PWV and negatively associated with male gender. Multiple regression revealed PWV independently related to NR2Ab level, and PWV cut-off was associated with a 7.23 times increase in the likelihood of having high NR2Ab (>1.8 ng/mL). Conclusion. Higher PWV in patients with surgical aortic stenosis is associated with higher levels of the ischemic brain biomarker NR2Ab.
Published: 2014
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18. Deep Active Learning for Left Ventricle Segmentation in Echocardiography.

Author: Eman Alajrami, Preshen Naidoo, Jevgeni Jevsikov, Elisabeth S. Lane, Jamie Pordoy, Nasim Dadashi Serej, Neda Azarmehr, Fateme Dinmohammadi, Matthew J. Shun-Shin, Darrel P. Francis, and Massoud Zolgharni
Published: 2023
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19. Automated Analysis of Mitral Inflow Doppler Using Deep Neural Networks.

Author: Jevgeni Jevsikov, Elisabeth S. Lane, Eman Alajrami, Preshen Naidoo, Nasim Dadashi Serej, Neda Azarmehr, Sama Aleshaiker, Catherine C. Stowell, Matthew J. Shun-Shin, Darrel P. Francis, and Massoud Zolgharni
Published: 2023
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20. Automated multi-beat tissue Doppler echocardiography analysis using deep neural networks.

Author: Elisabeth S. Lane, Jevgeni Jevsikov, Matthew J. Shun-Shin, Niti M. Dhutia, Nasser Matoorian, Graham D. Cole, Darrel P. Francis, and Massoud Zolgharni
Published: 2023
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21. Active learning for left ventricle segmentation in echocardiography.

Author: Eman Alajrami, Tiffany Ng, Jevgeni Jevsikov, Preshen Naidoo, Patricia Fernandes, Neda Azarmehr, Fateme Dinmohammadi, Matthew J. Shun-Shin, Nasim Dadashi Serej, Darrel P. Francis, and Massoud Zolgharni
Published: 2024
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22. Automated mitral inflow Doppler peak velocity measurement using deep learning.

Author: Jevgeni Jevsikov, Tiffany Ng, Elisabeth S. Lane, Eman Alajrami, Preshen Naidoo, Patricia Fernandes, Joban S. Sehmi, Maysaa Alzetani, Camelia D. Demetrescu, Neda Azarmehr, Nasim Dadashi Serej, Catherine C. Stowell, Matthew J. Shun-Shin, Darrel P. Francis, and Massoud Zolgharni
Published: 2024
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23. Segmentation of Left Ventricle in 2D Echocardiography Using Deep Learning.

Author: Neda Azarmehr, Xujiong Ye, Stefania Sacchi, James P. Howard 0001, Darrel P. Francis, and Massoud Zolgharni
Published: 2019
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24. An optimisation-based iterative approach for speckle tracking echocardiography.

Author: Neda Azarmehr, Xujiong Ye, Joseph D. Howes, Benjamin Docking, James P. Howard 0001, Darrel P. Francis, and Massoud Zolgharni
Published: 2020
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25. ECG-based real-time arrhythmia monitoring using quantized deep neural networks: A feasibility study.

Author: Henrique De Melo Ribeiro, Ahran Arnold, James P. Howard 0001, Matthew J. Shun-Shin, Ying Zhang, Darrel P. Francis, Phang Boon Lim, Zachary Whinnett, and Massoud Zolgharni
Published: 2022
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26. Comparison of methods for delivering cardiac resynchronization therapy: an acute electrical and haemodynamic within-patient comparison of left bundle branch area, His bundle, and biventricular pacing

Author: Nadine Ali, Ahran D Arnold, Alejandra A Miyazawa, Daniel Keene, Ji-Jian Chow, Ian Little, Nicholas S Peters, Prapa Kanagaratnam, Norman Qureshi, Fu Siong Ng, Nick W F Linton, David C Lefroy, Darrel P Francis, Lim Phang Boon, Mark A Tanner, Amal Muthumala, Matthew J Shun-Shin, Graham D Cole, and Zachary I Whinnett
Subjects: Physiology (medical), Cardiology and Cardiovascular Medicine
Abstract: Aims Left bundle branch area pacing (LBBAP) is a promising method for delivering cardiac resynchronization therapy (CRT), but its relative physiological effectiveness compared with His bundle pacing (HBP) is unknown. We conducted a within-patient comparison of HBP, LBBAP, and biventricular pacing (BVP). Methods and results Patients referred for CRT were recruited. We assessed electrical response using non-invasive mapping, and acute haemodynamic response using a high-precision haemodynamic protocol. Nineteen patients were recruited: 14 male, mean LVEF of 30%. Twelve had time for BVP measurements. All three modalities reduced total ventricular activation time (TVAT), (ΔTVATHBP -43 ± 14 ms and ΔTVATLBBAP −35 ± 20 ms vs. ΔTVATBVP −19 ± 30 ms, P = 0.03 and P = 0.1, respectively). HBP produced a significantly greater reduction in TVAT compared with LBBAP in all 19 patients (−46 ± 15 ms, −36 ± 17 ms, P = 0.03). His bundle pacing and LBBAP reduced left ventricular activation time (LVAT) more than BVP (ΔLVATHBP −43 ± 16 ms, P < 0.01 vs. BVP, ΔLVATLBBAP −45 ± 17 ms, P < 0.01 vs. BVP, ΔLVATBVP −13 ± 36 ms), with no difference between HBP and LBBAP (P = 0.65). Acute systolic blood pressure was increased by all three modalities. In the 12 with BVP, greater improvement was seen with HBP and LBBAP (6.4 ± 3.8 mmHg BVP, 8.1 ± 3.8 mmHg HBP, P = 0.02 vs. BVP and 8.4 ± 8.2 mmHg for LBBAP, P = 0.3 vs. BVP), with no difference between HBP and LBBAP (P = 0.8). Conclusion HBP delivered better ventricular resynchronization than LBBAP because right ventricular activation was slower during LBBAP. But LBBAP was not inferior to HBP with respect to LV electrical resynchronization and acute haemodynamic response.
Published: 2023
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27. Effects of haemodynamically atrio‐ventricular optimized His bundle pacing on heart failure symptoms and exercise capacity: the His Optimized Pacing Evaluated for Heart Failure ( <scp>HOPE‐HF</scp> ) randomized, double‐blind, cross‐over trial

Author: Zachary I. Whinnett, Matthew J. Shun‐Shin, Mark Tanner, Paul Foley, Badri Chandrasekaran, Philip Moore, Shaumik Adhya, Norman Qureshi, Amal Muthumala, Rebecca Lane, Aldo Rinaldi, Sharad Agarwal, Francisco Leyva, Jonathan Behar, Sukh Bassi, Andre Ng, Paul Scott, Rachana Prasad, Jon Swinburn, Joseph Tomson, Amarjit Sethi, Jaymin Shah, Phang Boon Lim, Andreas Kyriacou, Dewi Thomas, Jenny Chuen, Ravi Kamdar, Prapa Kanagaratnam, Myril Mariveles, Leah Burden, Katherine March, James P. Howard, Ahran Arnold, Pugazhendhi Vijayaraman, Berthold Stegemann, Nicholas Johnson, Emanuela Falaschetti, Darrel P. Francis, John G.F. Cleland, and Daniel Keene
Subjects: Cardiology and Cardiovascular Medicine
Published: 2023
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28. Upgrading right ventricular pacemakers to biventricular pacing or conduction system pacing: a systematic review and meta-analysis

Author: Nandita Kaza, Varanand Htun, Alejandra Miyazawa, Florentina Simader, Bradley Porter, James P Howard, Ahran D Arnold, Akriti Naraen, David Luria, Michael Glikson, Carsten Israel, Darrel P Francis, Zachary I Whinnett, Matthew J Shun-Shin, and Daniel Keene
Subjects: Physiology (medical), Cardiology and Cardiovascular Medicine
Abstract: 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.
Published: 2022
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29. Contributions of Atrioventricular Delay Shortening and Ventricular Resynchronization to Hemodynamic Benefits of Biventricular Pacing

Author: Ahran D. Arnold, Matthew J. Shun-Shin, Nadine Ali, Daniel Keene, James P. Howard, Darrel P. Francis, and Zachary I. Whinnett
Published: 2023
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30. Multibeat echocardiographic phase detection using deep neural networks.

Author: Elisabeth S. Lane, Neda Azarmehr, Jevgeni Jevsikov, James P. Howard 0001, Matthew J. Shun-Shin, Graham D. Cole, Darrel P. Francis, and Massoud Zolgharni
Published: 2021
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31. Variation in optimal hemodynamic atrio‐ventricular delay of biventricular pacing with different endocardial left ventricular lead locations using precision hemodynamics

Author: Charles J. T. Butcher, Emily Cantor, Afzal Sohaib, Matthew J. Shun‐Shin, Ross Haynes, Habib Khan, Adreas Kyriacou, Rui Shi, Zhong Chen, Shouvik Haldar, John G. F. Cleland, Wajid Hussain, Vias Markides, David G. Jones, Rebecca E. Lane, Mark J. Mason, Zachary I. Whinnett, Darrel P. Francis, and Tom Wong
Subjects: Physiology (medical), Cardiology and Cardiovascular Medicine
Published: 2023
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32. Development of artificial intelligence tools for invasive Doppler-based coronary microvascular assessment

Author: Henry Seligman, Sapna B Patel, Anissa Alloula, James P Howard, Christopher M Cook, Yousif Ahmad, Guus A de Waard, Mauro Echavarría Pinto, Tim P van de Hoef, Haseeb Rahman, Mihir A Kelshiker, Christopher A Rajkumar, Michael Foley, Alexandra N Nowbar, Samay Mehta, Mathieu Toulemonde, Meng-Xing Tang, Rasha Al-Lamee, Sayan Sen, Graham Cole, Sukhjinder Nijjer, Javier Escaned, Niels Van Royen, Darrel P Francis, Matthew J Shun-Shin, and Ricardo Petraco
Subjects: General Engineering, General Earth and Planetary Sciences, General Environmental Science
Abstract: 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.
Published: 2023
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33. A randomised controlled trial to investigate the use of acute coronary syndrome therapy in patients hospitalised with COVID-19: the C19-ACS trial

Author: Prapa Kanagaratnam, Darrel P. Francis, Daniel Chamie, Clare Coyle, Alena Marynina, George Katritsis, Patricia Paiva, Matyas Szigeti, Graham Cole, David de Andrade Nunes, James Howard, Rodrigo Esper, Masood Khan, Ranjit More, Guilherme Barreto, Rafael Meneguz-Moreno, Ahran Arnold, Alexandra Nowbar, Amit Kaura, Myril Mariveles, Katherine March, Jaymin Shah, Sukhjinder Nijjer, Gregory YH. Lip, Nicholas Mills, A John Camm, Graham S. Cooke, Simon J. Corbett, Martin J. Llewelyn, Waleed Ghanima, Mark Toshner, Nicholas Peters, Ricardo Petraco, Rasha Al-Lamee, Ana Sousa Marcelino Boshoff, Margarita Durkina, Iqbal Malik, Neil Ruparelia, Victoria Cornelius, and Matthew Shun-Shin
Subjects: Hematology
Abstract: BACKGROUND: Patients hospitalised with COVID-19 suffer thrombotic complications. Risk factors for poor outcomes are shared with coronary artery disease. OBJECTIVES: To investigate efficacy of an acute coronary syndrome regimen in patients hospitalised with COVID-19 and coronary disease risk factors. PATIENTS/METHODS: A randomised controlled open-label trial across acute hospitals (UK and Brazil) added aspirin, clopidogrel, low-dose rivaroxaban, atorvastatin, and omeprazole to standard care for 28-days. Primary efficacy and safety outcomes were 30-day mortality and bleeding. The key secondary outcome was a daily clinical status (at home, in hospital, on intensive therapy unit admission, death). RESULTS: 320 patients from 9 centres were randomised. The trial terminated early due to low recruitment. At 30 days there was no significant difference in mortality (intervention: 11.5% vs control: 15%, unadjusted OR 0.73, 95%CI 0.38 to 1.41, p=0.355). Significant bleeds were infrequent and not significantly different between the arms (intervention: 1.9% vs control 1.9%, p>0.999). Using a Bayesian Markov longitudinal ordinal model, it was 93% probable that intervention arm participants were more likely to transition to a better clinical state each day (OR 1.46, 95% CrI 0.88 to 2.37, Pr(Beta>0)=93%; adjusted OR 1.50, 95% CrI 0.91 to 2.45, Pr(Beta>0)=95%) and median time to discharge home was two days shorter (95% CrI -4 to 0, 2% probability that it was worse). CONCLUSIONS: Acute coronary syndrome treatment regimen was associated with a reduction in the length of hospital stay without an excess in major bleeding. A larger trial is needed to evaluate mortality.
Published: 2023

34. Mechanical thrombectomy with retrievable stents and aspiration catheters for acute ischaemic stroke: a meta-analysis of randomised controlled trials

Author: Alexandra N. Nowbar, Matthew J. Shun-Shin, Iqbal S. Malik, Rasha Al-Lamee, George D Thornton, Iris Q. Grunwald, Henry Seligman, Darrel P. Francis, Sashiananthan Ganesananthan, James P. Howard, Michael Foley, Yousif Ahmad, Christopher Rajkumar, and Thomas R. Keeble
Subjects: medicine.medical_specialty, Catheters, medicine.medical_treatment, Brain Ischemia, Modified Rankin Scale, Ischaemic stroke, medicine, Clinical endpoint, Humans, Stroke, Ischemic Stroke, Randomized Controlled Trials as Topic, Thrombectomy, business.industry, Endovascular Procedures, Stent, Bayes Theorem, Thrombolysis, medicine.disease, Surgery, Mechanical thrombectomy, Treatment Outcome, Meta-analysis, Stents, Cardiology and Cardiovascular Medicine, business, Meta-Analysis
Abstract: 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
Published: 2022
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35. Phasic flow patterns of right versus left coronary arteries in patients undergoing clinical physiological assessment

Author: Mauro Echavarria-Pinto, Tim P. van de Hoef, Ibrahim Danad, Matthew J. Shun-Shin, Martijn Meuwissen, Christopher Cook, Martijn A. van Lavieren, Darrel P. Francis, Takayuki Warisawa, Guus A. de Waard, Paul Knaapen, Hernán Mejía-Rentería, Yousif Ahmad, Rasha Al-Lamee, Ricardo Petraco, Sukhjinder Nijjer, Christopher Rajkumar, Justin E. Davies, Alexandra N. Nowbar, Mihir Kelshiker, Javier Escaned, Sayan Sen, James P. Howard, Vitaliy Androshchuk, Henry Seligman, Niels van Royen, Jan J. Piek, Jamil Mayet, ACS - Microcirculation, ACS - Atherosclerosis & ischemic syndromes, Cardiology, Graduate School, and ACS - Heart failure & arrhythmias
Subjects: medicine.medical_specialty, stable angina, Diastole, Hyperemia, Constriction, Pathologic, Hyperaemia, Clinical Research, Internal medicine, medicine.artery, Coronary Circulation, other technique, medicine, Humans, In patient, fractional flow reserve, business.industry, Vascular damage Radboud Institute for Molecular Life Sciences [Radboudumc 16], Coronary flow reserve, Blood flow, medicine.disease, Coronary Vessels, Coronary arteries, Stenosis, medicine.anatomical_structure, Right coronary artery, Cardiology, medicine.symptom, Cardiology and Cardiovascular Medicine, business, Blood Flow Velocity
Abstract: Item does not contain fulltext BACKGROUND: Coronary blood flow in humans is known to be predominantly diastolic. Small studies in animals and humans suggest that this is less pronounced or even reversed in the right coronary artery (RCA). AIMS: This study aimed to characterise the phasic patterns of coronary flow in the left versus right coronary arteries of patients undergoing invasive physiological assessment. METHODS: We analysed data from the Iberian-Dutch-English Collaborators (IDEAL) study. A total of 482 simultaneous pressure and flow measurements from 301 patients were included in our analysis. RESULTS: On average, coronary flow was higher in diastole both at rest and during hyperaemia in both the RCA and LCA (mean diastolic-to-systolic velocity ratio [DSVR] was, respectively, 1.85±0.70, 1.76±0.58, 1.53±0.34 and 1.58±0.43 for LCA(rest), LCA(hyp), RCA(rest) and RCA(hyp), p
Published: 2022
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36. Optimizing atrio‐ventricular delay in pacemakers using potentially implantable physiological biomarkers

Author: Daniel Keene, Alejandra A Miyazawa, Monika Johal, Ahran D Arnold, Nadine Ali, Khulat A Saqi, Katherine March, Leah Burden, Darrel P Francis, Zachary I Whinnett, and Matthew J Shun‐Shin
Subjects: Pacemaker, Artificial, Heart Ventricles, Atrioventricular Node, Cardiac Pacing, Artificial, Hemodynamics, Humans, General Medicine, Cardiology and Cardiovascular Medicine, Biomarkers
Abstract: Background Hemodynamically optimal atrioventricular (AV) delay can be derived by echocardiography or beat-by-beat blood pressure (BP) measurements, but analysis is labor intensive. Laser Doppler perfusion monitoring measures blood flow and can be incorporated into future implantable cardiac devices. We assess whether laser Doppler can be used instead of BP to optimize AV delay. Methods Fifty eight patients underwent 94 AV delay optimizations with biventricular or His-bundle pacing using laser Doppler and simultaneous noninvasive beat-by-beat BP. Optimal AV delay was defined using a curve of hemodynamic response to switching from AAI (reference state) to DDD (test state) at several AV delays (40–320 ms), with automatic quality control checking precision of the optimum. Five subsequent patients underwent an extended protocol to test the impact of greater numbers of alternations on optimization quality. Results 55/94 optimizations passed quality control resulting in an optimal AV delay on laser Doppler similar to that derived by BP (median absolute deviation 12 ms). An extended protocol with increasing number of replicates consistently improved quality and reduced disagreement between laser Doppler and BP optima. With only five replicates, no optimization passed quality control, and the median absolute deviation would be 29 ms. These improved progressively until at 50 replicates, all optimizations passed quality control and the median absolute deviation was only 13 ms. Conclusions Laser Doppler perfusion produces hemodynamic optima equivalent to BP. Quality control can be automatic. Adding more replicates, consistently improves quality. Future implantable devices could use such methods to dynamically and reliably optimize AV delays.
Published: 2022
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37. Randomized Blinded Placebo-Controlled Trials of Renal Sympathetic Denervation for Hypertension: A Meta-Analysis

Author: Matthew J. Shun-Shin, James P. Howard, Yousif Ahmad, Darrel P. Francis, Rasha Al-Lamee, Christopher J. Kane, Christopher Cook, Daniel Keene, Ahran D. Arnold, and Graham D. Cole
Subjects: Relative risk reduction, Blood Pressure, 030204 cardiovascular system & hematology, Kidney, Placebo, law.invention, 03 medical and health sciences, 0302 clinical medicine, Randomized controlled trial, law, Humans, Medicine, 030212 general & internal medicine, Sympathectomy, 1102 Cardiorespiratory Medicine and Haematology, Antihypertensive Agents, Randomized Controlled Trials as Topic, Denervation, business.industry, General Medicine, Meta-analysis, Treatment Outcome, Blood pressure, Cardiovascular System & Hematology, Renal sympathetic denervation, Anesthesia, Hypertension, Ambulatory, Renal denervation, Cardiology and Cardiovascular Medicine, business
Abstract: 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.
Published: 2022
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38. Advanced heart failure in adult congenital heart disease: the role of renal dysfunction in management and outcomes

Author: Kaushiga Krishnathasan, Konstantinos Dimopoulos, Neill Duncan, Piera Ricci, Alexander Kempny, Isma Rafiq, Michael A Gatzoulis, Ee Ling Heng, Sarah Blakey, Claudia Montanaro, Sonya V Babu-Narayan, Darrel P Francis, Wei Li, and Andrew Constantine
Subjects: Epidemiology, Cardiology and Cardiovascular Medicine
Abstract: Aims Previous studies in adult congenital heart disease (CHD) have demonstrated a link between renal dysfunction and mortality. However, the prognostic significance of renal dysfunction in CHD and decompensated heart failure (HF) remains unclear. We sought to assess the association between renal dysfunction and outcomes in adults with CHD presenting to our centre with acute HF between 2010 and 2021. Methods and results This retrospective analysis focused on the association between renal dysfunction, pre-existing and on admission, and outcomes during and after the index hospitalization. Chronic kidney disease (CKD) was defined as an estimated glomerular filtration rate Conclusion Adult patients with CHD admitted with acute HF are a high-risk cohort. CKD is common and triples the risk of death/transplantation/VAD. An expert multidisciplinary approach is essential for optimizing outcomes.
Published: 2023
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39. Left bundle branch pacing with and without anodal capture: impact on ventricular activation pattern and acute hemodynamics

Author: Nadine Ali, Khulat Saqi, Ahran D. Arnold, Alejandra A.Miyazawa, Daniel Keene, Ji-Jian Chow, Ian Little, Nicholas S. Peters, Prapa Kanagaratnam, Norman Qureshi, Fu Siong Ng, Nick W. F Linton, David C. Lefroy, Darrel P. Francis, PB Lim, Mark A. Tanner, Amal Muthumala, Matthew J. Shun-Shin, Graham D. Cole, and Zachary I. Whinnett
Abstract: IntroductionLeft bundle branch pacing (LBBP) can deliver physiological left ventricular activation, but typically at the cost of delayed right ventricular (RV) activation. A proposed solution is to advance RV activation through anodal capture, but there is uncertainty regarding the mechanism by which early RV activation is achieved (capture of right bundle or RV myocardial capture) and it is not known whether this produces hemodynamic benefit.MethodsWe recruited patients with LBBP leads in whom anodal capture eliminated the terminal R wave in lead V1.Ventricular activation pattern, timing and high precision acute hemodynamic response were studied during LBBP with and without anodal capture.ResultsWe recruited 21 patients, mean age 67 years, 14 were males. We measured ECG timings and hemodynamics in all patients and in 15 we also performed non-invasive mapping. Ventricular epicardial propagation maps demonstrated that right ventricular septal myocardial capture, rather than right bundle capture, was the mechanism for earlier RV activation. With anodal capture, QRS duration was shorter (116 ± 12ms versus 129 ± 14ms, p < 0.01), and total ventricular activation time was shorter (83 ± 18ms versus 90 ± 15ms, p = 0.01). This required higher outputs (3.6 ± 1.9V versus 0.6 ± 0.2V, p ConclusionLeft bundle pacing with anodal capture advances right ventricular activation as a result of stimulation of the RV septal myocardium. However, this requires higher outputs and did not improve acute hemodynamics. Aiming for anodal capture may therefore not be necessary.
Published: 2023
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40. MP-453086-3 HIS BUNDLE VS BIVENTRICULAR PACING FOR LBBB: EFFECTS ON VENTRICULAR REPOLARISATION GRADIENTS

Author: Ahran Arnold, Timothy Cheng, Ji-Jian Chow, Matthew J. Shun-Shin, Jack W. Samways, Akriti Naraen, Jagdeep S. Mohal, Mark A. Tanner, Amal G. Muthumala, Fu Siong Ng, Nick F. Linton, Prapa Kanagaratnam, Nicholas S. Peters, Darrel P. Francis, and Zachary I. Whinnett
Subjects: Physiology (medical), Cardiology and Cardiovascular Medicine
Published: 2023
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41. Renal Denervation for Hypertension

Author: Yousif Ahmad, Deepak L. Bhatt, Darrel P. Francis, and James P. Howard
Subjects: Denervation, medicine.medical_specialty, business.industry, Internal medicine, Meta-analysis, medicine, In patient, urologic and male genital diseases, Cardiology and Cardiovascular Medicine, business, Placebo
Abstract: 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...
Published: 2021
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42. Sodium-glucose cotransporter 2 inhibitors in patients with heart failure: a systematic review and meta-analysis of randomized trials

Author: Gregg W. Stone, Darrel P. Francis, James P. Howard, Yousif Ahmad, Deepak L. Bhatt, Mahesh V. Madhavan, and Raj Makkar
Subjects: Heart Failure, medicine.medical_specialty, Ejection fraction, business.industry, Health Policy, Sodium, Hazard ratio, Review, medicine.disease, Placebo, law.invention, Clinical trial, Glucose, Diabetes Mellitus, Type 2, Randomized controlled trial, law, Heart failure, Internal medicine, medicine, Clinical endpoint, Empagliflozin, Humans, Cardiology and Cardiovascular Medicine, business, Randomized Controlled Trials as Topic
Abstract: 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.
Published: 2021
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43. Effects of haemodynamically atrio-ventricular optimized His-pacing on heart failure symptoms and exercise capacity: The His Optimized Pacing Evaluated for Heart Failure (HOPE-HF) randomised, double-blind, cross-over trial

Author: Zachary I, Whinnett, Matthew J, Shun-Shin, Mark, Tanner, Paul, Foley, Badri, Chandrasekaran, Philip, Moore, Shaumik, Adhya, Norman, Qureshi, Amal, Muthumala, Rebecca, Lane, Aldo, Rinaldi, Sharad, Agarwal, Francisco, Leyva, Jonathan, Behar, Sukh, Bassi, Andre, Ng, Paul, Scott, Rachana, Prasad, Jon, Swinburn, Joseph, Tomson, Amarjit, Sethi, Jaymin, Shah, Phang Boon, Lim, Andreas, Kyriacou, Dewi, Thomas, Jenny, Chuen, Ravi, Kamdar, Prapa, Kanagaratnam, Myril, Mariveles, Leah, Burden, Katherine, March, Ahran, Arnold, Pugazhendhi, Vijayaraman, Berthold, Stegemann, Nicholas, Johnson, Emanuela, Falaschetti, Darrel P, Francis, John Gf, Cleland, and Daniel, Keene
Abstract: Excessive prolongation of PR interval impairs coupling of AV contraction, which reduces left ventricular pre-load and stroke volume, and worsens symptoms. His-bundle pacing allows AV-delay shortening while maintaining normal ventricular activation. HOPE-HF evaluated whether AV-optimized His pacing is preferable to no-pacing, in double-blind cross-over fashion, in patients with heart failure, left ventricular ejection fraction (LVEF) ≤40%, PR interval ≥200ms and either QRS ≤140ms or right BBB.Patients had atrial and His-bundle leads implanted (and an ICD lead if clinically indicated) and were randomized, to 6-months of pacing and 6-months of no-pacing utilizing a cross-over design. The primary outcome was peak oxygen uptake during symptom-limited exercise. Quality of life, LVEF and patients' holistic symptomatic preference between arms were secondary outcomes. 167 patients were randomized: 90% men, 69±10 years, QRS duration 124±26ms, PR interval 249±59ms, LVEF 33±9%. Neither peak VOHis-bundle pacing did not increase peak oxygen uptake but, under double-blind conditions, significantly improved quality of life and was symptomatically preferred by the clear majority of patients. Ventricular pacing delivered via the His bundle did not adversely impact ventricular function during the 6 months. This article is protected by copyright. All rights reserved.
Published: 2022

44. Initial Invasive or Conservative Strategy for Stable Coronary Disease

Author: Maron D. J., Hochman J. S., Reynolds H. R., Bangalore S., O'Brien S. M., Boden W. E., Chaitman B. R., Senior R., Lopez-Sendon J., Alexander K. P., Lopes R. D., Shaw L. J., Berger J. S., Newman J. D., Sidhu M. S., Goodman S. G., Ruzyllo W., Gosselin G., Maggioni A. P., White H. D., Bhargava B., Min J. K., John Mancini G. B., Berman D. S., Picard M. H., Kwong R. Y., Ali Z. A., Mark D. B., Spertus J. A., Krishnan M. N., Elghamaz A., Moorthy N., Hueb W. A., Demkow M., Mavromatis K., Bockeria O., Peteiro J., Miller T. D., Szwed H., Doerr R., Keltai M., Selvanayagam J. B., Gabriel Steg P., Held C., Kohsaka S., Mavromichalis S., Kirby R., Jeffries N. O., Harrell F. E., Rockhold F. W., Broderick S., Bruce Ferguson T., Williams D. O., Harrington R. A., Stone G. W., Rosenberg Y, ISCHEMIA Research Group: Joseph Ricci, A Tello Montoliu, A I Robero Aniorte, Abbey Mulder, Abhay A Laddu, Abhinav Goyal, Abhishek Dubey, Abhishek Goyal, Abigail Knighton, Abraham Oomman, Adam J Jaskowiak, Adam Kolodziej, Adam Witkowski, Adnan Hameed, Adriana Anesini, Afshan Hussain, Agne Juceviciene, Agne Urboniene, Agnes Jakal, Agnieszka Szramowska, Ahmad Khairuddin, Ahmed Abdel-Latif, Ahmed Adel, Ahmed Aljzeeri, Ahmed Kamal, Ahmed Talaat, Aimee Mann, Aira Contreras, Ajit Kumar, V K Kumar, Akemi Furukawa, Akshay Bagai, Akvile Smigelskaite, Alain Furber, Alain Rheault, Alaine Melanie Loehr, Alan Rosen, Albert Varga, Albertina Qelaj, Alberto Barioli, Aldo Russo, Alec Moorman, Alejandro Gisbert, Aleksandra Fratczak, Aleksandras Laucevicius, Alena Kuleshova, Alessandro Sionis, Alexander A Sirker, Alexander M Chernyavskiy, Alexandra Craft, Alexandra Vazquez, Alexandre Ciappina Hueb, Alexandre S Colafranseschi, Alexandre Schaan de Quadros, Alexandre Tognon, Ali Alghamdi, Alice Manica Muller, Aline Nogueira Rabaça, Aline Peixoto Deiro, Alison Hallam, Allegra Stone, Allison Schley, Almudena Castro, Alvaro Rabelo Ales, Amanda Germann, Amanda O'Malley, Amar Uxa, Amarachi Ojajuni, Amarino C Oliveira Jr, Amber B Hull, Ambuj Roy, Amer Zarka, Amir Janmohamed, Ammani Brown, Ammy Malinay, Amparo Martinez Monzonis, Amy J Richards, Amy Iskandrian, Amy Ollinger, Ana D Djordjevic-Dikic, Ana Fernández Martínez, Ana Gomes Almeida, Ana Paula Batista, Ana Rita Francisco, Ana S Mladenovic, Ana Santana, Anam Siddiqui, Anastasia M Kuzmina-Krutetskaya, Andras Vertes, Andre S Sousa, Andre Gabriel, André Schmidt, Andrea M Lundeen, Andrea Bartykowszki, Andrea Lorimer, Andrea Mortara, Andrea Pascual, Andreia Coelho, Andreia Rocha, Andrés García-Rincón, Andrew G Howarth, Andrew J Moriarty, Andrew Docherty, Andrew Starovoytov, Andrew Zurick, Andrzej Łabyk, Andrzej Swiatkowski, Andy Lam, Anelise Kawakami, Angela Hoye, Angela Kim, Angelique Smit, Angelo Nobre, Anil V Shah, Anja Ljubez, Anjali Anand, Ankush Sachdeva, Ann Greenberg, Ann Luyten, Ann Ostrander, Anna Di Donato, Anna Cichocka-Radwan, Anna Fojt, Anna Plachcinska, Anna Proietti, Anna Teresinska, Anne Marie Webb, Anne Cartwright, Anne Heath, Anne Mackin, Anong Amaritakomol, Anong Chaiyasri, Anoop Chauhan, Anoop Mathew, Anthony Gemignani, Anto Luigi Andres, Antonia Vega, Antonietta Hansen, Antonino Ginel Iglesias, Antonio Carlos Carvalho, Antonio Di Chiara, Antonio Serra Peñaranda, Antonio Carvalho, Antonio Colombo, Antonio Fiarresga, Anupama Rao, Aquiles Valdespino-Estrada, Araceli Boan, Areef Ishani, Ariel Diaz, Arijit Ghosh, Arintaya Prommintikul, Arline Roberts, Arnold H Seto, Arnold P Good, Arshed Quyyumi, Arthur J Labovitz, Arthur Kerner, Arturo S Campos-Santaolalla, Arunima Misra, Ashok Mukherjee, Ashok Seth, Ashraf Seedhom, Asim N Cheema, Asker Ahmed, Atul Mathur, Atul Verma, Audrey W Leong, Axel Åkerblom, Axelle Fuentes, Aynun Naher, Badhma Valaiyapathi, Baljeet Kaur, Bandula Guruge, Barbara 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Ohmart, Carmen C Beladan, Carmen Ginghina, Carol M Kartje, Caroline Alsweiler, Caroline Brown, Caroline Callison, Caroline Pinheiro, Caroline Rodgers, Caroline Spindler, Carolyn Corbett, Carrie Drum, Casey Riedberger, Catherine Bone, Catherine Fleming, Catherine Gordon, Catherine Jahrsdorfer, Catherine Lemay, Catherine Weick, Cathrine Patten, Cecilia Goletto, Cezary Kepka, Chandini Suvarna, Chang Xu, Chantale Mercure, Charle A Viljoen, Charlene Wiyarand, Charles Jia-Yin Hou, Charles Y Lui, Charles Cannan, Charles Cornet, Charlotte Pirro, Chataroon Rimsukcharoenchai, Chen Wang, Cheng-Ting Tsai, Chen-Yen Chien, Cheryl A Allardyce, Chester M Hedgepeth, Chetan Patel, Chiara Attanasio, Chih-Hsuan Yen, Chi-Ming Chow, Ching Min Er, Ching-Ching Ong, Cholenahally Nanjappa Manjunath, Chris Beck, Chris Buller, Christel Vassaliere, Christian Hamm, Christiano Caldeira, Christie Ballantyne, Christina Björklund, Christine R Hinton, Christine Bergeron, Christine Masson, Christine Roraff, Christine Shelley, Christophe Laure, Christophe Thuaire, Christopher Kinsey, Christopher McFarren, Christopher Spizzieri, Christopher Travill, Chun-Chieh Liu, Chung-Lieh Hung, Chunguang Li, Chun-Ho Yun, Chunli Xia, Ciarra Heard, Cidney Schultz, Clare Venn-Edmonds, Claudia P Hochberg, Claudia Wegmayr, Claudia Cortés, Claudia Escobar, Cláudia Freixo, Claudio T Mesquita, Clemens T Kadalie, Colin Berry, Constance Philander, Corine Thobois, Costantino Costantini, Courtney Page, Craig Atkinson, Craig Barr, Craig Paterson, Cristina Bare, Cynthia Baumann, Cynthia Burman, Dalisa Espinosa, Damien Collison, Dan Deleanu, Dan Elian, Dan Gao, Dana Oliver, Daniel P Vezina, Daniel O'Rourke, Daniele Komar, Danielle Schade, Darrel P Francis, Dastan Malaev, David A Bull, David E Winchester, David P Faxon, David Booth, David Cohen, David DeMets, David Foo, David Schlichting, David Taggart, David Waters, David Wohns, Davis Vo, Dawid Teodorczyk, Dawn Shelstad, Dawn Turnbull, Dayuan Li, Dean Kereiakes, Deborah O'Neill, Deborah Yip, Debra K Johnson, Debra Dees, Deepak L Bhatt, Deepika Gopal, Deepti Kumar, Deirdre Mattina, Deirdre Murphy, Delano R Small, Delsa K Rose, Dengke Jiang, Denis Carl Phaneuf, Denise Braganza, Denise Fine, Derek Cyr, Desiree Tobin, Diana Cukali, Diana Parra, Diane Camara, Diane Minshall Liu, Diego Adrián Vences, Diego Franca de Cunha, Dimitrios Stournaras, Dipti Patel, Dongze Li, Donna Exley, Dorit Grahl, Dragana Stanojevic, Duarte Cacela, Dwayne S G Conway, E Pinar Bermudez, Eapen Punnoose, Edgar L Tay, Edgar Karanjah, Edoardo Verna, Eduardo Hernandez-Rangel, Edward D Nicol, Edward O McFalls, Edward T Martin, Edyta Kaczmarska, Ekaterina I Lubinskaya, Elena A Demchenko, Elena Refoyo Salicio, Eli Feen, Elihú Durán-Cortés, Elisabeth M Janzen, Elise L Hannemann, Elise van Dongen, Elissa Restelli Piloto, Eliza Kaplan, Elizabeta Srbinovska Kostovska, Elizabeth Capasso-Gulve, Elizabeth Congdon, Elizabeth Ferguson, Elizaveta V Zbyshevskaya, Ellen Magedanz, Ellie Fridell, Ellis W Lader, Elvin Kedhi, Emanuela Racca, Emilie Tachot, Emily DeRosa, Encarnación Alonso-Álvarez, Eric Nicollet, Eric Peterson, Erick Alexánderson Rosas, Erick Donato Morales, Erin Orvis, Ermina Moga, Estelle Montpetit, Estevao Figueiredo, Eugene Passamani, Eugenia Nikolsky, Eunice Yeoh, Evgeniy I Kretov, Ewa Szczerba, Ewelina Wojtala, Expedito Eustáquio Ribeiro Silva, F Marin Ortuño, Fabio R Farias, Fabio Fimiani, Fabrizio Rolfo, Fa-Chang Yu, Fadi Hage, Fadi Matar, Fahim Haider Jafary, Fang Feng, Fang Liu, Fatima Ranjbaran, Fatima Rodriguez, Fausto J Pinto, Fauzia Rashid, Federica Ramani, Fei Wang, Fernanda Igansi, Filipa Silva, Filippo Ottani, Fiona Haines, Firas Al Solaiman, Flávia Egydio, Flavio Lyra, Florian Egger, Fran Farquharson, Frances Laube, Francesc Carreras Costa, Francesca de Micco, Francesca Bianchini, Francesca Pezzetta, Francesca Pietrucci, Francesco Orso, Francesco Pisano, Francis Burt, Francisca Patuleia Figueiras, Francisco Fernandez-Aviles, Francois Pierre Mongeon, Frans Van de Werf, Franziska Guenther, Fraser N Witherow, Fred Mohr, Frederico Dall'Orto, Fumiyuki Otsuka, G De La Morena, G Karthikeyan, Gabor Dekany, Gabor Kerecsen, Gabriel Galeote, Gabriel Grossmann, Gabriel Vorobiof, Gabriela Sanchez de Souza, Gabriela Guzman, Gabriela Zeballos, Gabriele Gabrielli, Gabriele Jakl-Kotauschek, Gail A Shammas, Gail Brandt, Gang Chen, Gary E Lane, Gary J Luckasen, Gautam Sharma, Gelmina Mikolaitiene, Gennie Yee, Georg Nickenig, George E Revtyak, George J Juang, Gerald Fletcher, Gerald Leonard, Gerard Patrick Devlin, Gerard Esposito, Gergely Ágoston, Gervasio Lamas, Geza Fontos, Ghada Mikhail, Gia Cobb, Gian Piero Perna, Gianpiero Leone, Giles Roditi, Gilles Barone-Rochette, Girish Mishra, Giuseppe Tarantini, Glenda Wong, Glenn S Hamroff, Glenn Rayos, Gong Cheng, Gonzalo Barge-Caballero, Goran Davidović, Goran Stankovic, Gordana Stevanovic, Grace Jingyan Wang, Grace M Young, Graceanne Wayser, Graciela Scaro, Graham S Hillis, Graham Wong, Grazyna Anna Szulczyk, Gregor Simonis, Gregory Kumkumian, Gretchen Ann Peichel, Grzegorz Gajos, Gudrun Steinmaurer, Guilherme G Rucatti, Guilherme Portugal, Guilhermina Cantinho Lopes, Guillem Pons Lladó, Gunnar Frostfelt, Gurpreet S Wander, Gurpreet Gulati, Gustavo Pucci, Hafidz Abd Hadi, Haibo Zhang, Haitao Wang, Halina Marciniak, Han Chen, Hanan Kerr, Hani Najm, Hanna Douglas, Hannah Phillips, Hao Dai, Haojian Dong, Haqeel Jamil, Harikrishnan Sivadasanpillai, Harry Suryapranata, Hassan Reda, Hayley Pomeroy, Heather Barrentine, Heather Golden, Heather Hurlburt, Heidi Wilson, Helen C Tucker, Helene Abergel, Hemalata Siddaram, Hermine Osseni, Herwig Schuchlenz, Hesong Zeng, Hicham Skali, Hilda Solomon, Hollie Horton, Holly Hetrick, Holly Little, Holly Park, Hongjie Chi, Hossam Mahrous, Howard A Levite, Hristo Pejkov, Huajun Li, Hugo Bloise-Adames, Hugo Marques, Hui Zhong, Hui-Min Zhang, Humayrah Hashim, Hung-I Yeh, Hussien El Fishawy, Ian Webb, Iftikhar Kullo, Igor O Grazhdankin, Ihab Hamzeh, Ikraam Hassan, Ikuko Ueda, Ileana L Pina, Ilona Tamasauskiene, Ilse Bouwhuis, Imran Arif, Ina Wenzelburger, Inês Zimbarra Cabrita, Ines Rodrigues, Inga H Robbins, Inga Soveri, Ingela Schnittger, Iqbal Karimullah, Ira M Dauber, Iram Rehman, Irena Peovska Mitevska, Irene Marthe Lang, Irina Subbotina, Irma Kalibataite-Rutkauskiene, Irni Yusnida, Isabel Estela Carvajal, Isabella C Palazzo, Isabelle Hogan, Isabelle Roy, Ishba Syed, Ishita Tejani, Ivan A Naryshkin, Ivana Jankovic, Iwona Niedzwiecka, J David Knight, Jacek Kusmierek, Jackie M White, Jackie Chow, Jacob Udell, Jacqueline E Tamis-Holland, Jacqueline Fannon, Jacquelyn A Quin, Jacquelyn Do, Jaekyeong Heo, Jakub Maksym, James E Davies, James H O'Keefe Jr, James J Jang, James Cha, James Harrison, James Hirsch, James Stafford, James Tatoulis, Jamie Rankin, Jan Henzel, Jan Orga, Jana Tancredi, Janaina Oliveira, Jane Burton, Jane Eckstein, Jane Marucci, Janet P Knight, Janet Blount, Janet Halliday, Janetta Kourzenkova, Janitha Raj, Jan-Malte Sinning, Jaqueline Pozzibon, Jaroslaw Drozdz, Jaroslaw Karwowski, Jason D Glover, Jason Loh Kwok, Jason T Call, Jason Linefsky, Jassira Gomes, Jati Anumpa, Javier J Garcia, Javier Courtis, Jay Meisner, K Jayakumar, Jayne Scales, Jean E Denaro, Jean Michel Juliard, Jean Ho, Jeanette K Stansborough, Jean-Michel Juliard, Jeanne Russo, Jeannette J M Schoep, Jeet Thambyrajah, Jeff Leimberger, Jeffery A Breall, Jeffrey A Kohn, Jeffrey C Milliken, Jeffrey Anderson, Jeffrey Blume, Jeffrey Kanters, Jeffrey Lorin, Jeffrey Moses, Jelena J Stepanovic, Jelena Celutkiene, Jelena Djokic, Jelena Stojkovic, Jenne M Jose, Jenne Manchery, Jennifer A Mull, Jennifer H Czerniak, Jennifer L Stanford, Jennifer Gillis, Jennifer Horst, Jennifer Isaacs, Jennifer Langdon, Jennifer Thomson, Jennifer Tomfohr, Jennifer White, Jen-Yuan Kuo, Jeremy Rautureau, Jerome Fleg, Jessica Berg, Jessica Rodriguez, Jessica Waldron, Jhina Patro, Jia Li, Jiajia Mao, Jiamin Liu, Jian'an Wang, Jianhua Li, Jianxin Zhang, Jie Qi, Jihyun Lyo, Jill Marcus, Jim Blankenship, Jing Zhang, Jingjing Liu, Jing-Yao Fan, Jiun-Yi Li, Jiwan Pradhan, Jiyan Chen, J M Rivera Caravaca, Jo Evans, Joan Garcia Picart, Joan Hecht, Joanna Jaroch, Joanna Zalewska, Joanne Kelly, Joanne Taaffe, João Reynaldo Abbud, João V Vitola, Joaquín V Peñafiel, Jocelyne Benatar, Jody Bindeman, Joe Sabik, Joel Klitch, Johann Christopher, Johannes Aspberg, John D Friedman, John F Beltrame, John F Heitner, John Joseph Graham, John R Davies, John Doan, John Kotter, John Kurian, John Mukai, John Pownall, Jolanta Sobolewska, Jon Kobashigawa, Jonathan L Goldberg, Jonathan W Bazeley, Jonathan Byrne, Jonathan Himmelfarb, Jonathan Leipsic, Jonean Thorsen, Jorge F Trejo Gutierrez, Jorge Escobedo, Jorik Timmer, José A Ortega-Ramírez, José Antonio Marin-Neto, Jose D Salas, Jose Enrique Castillo, Jose Francisco Saraiva, José J Cuenca-Castillo, Jose L Diez, José Luis Narro Villanueva, José Luiz da Vieira, José M Flores-Palacios, Jose Ramon Gonzalez, Jose Seijas Amigo, Jose Fragata, Josep Maria Padró, Josheph F X McGarvey Jr, Joseph Hannan, Joseph Sacco, Joseph Sweeny, Joseph Wiesel, Josephine D Abraham, Joshua P Loh, Joy Burkhardt, Joyce R White, Joyce Riestenberg-Smith, Judit Sebo, Judith L Meadows, Judith Wright, Judy Mae Foltz, Judy Hung, Judy Otis, Juergen Stumpf, Jui-Peng Tsai, Julia S Dionne, Julia de Aveiro Morata, Julie Bunke, Julie Morrow, Julio César Figal, Jun Fujita, Jun Jiang, Junhua Li, Junqing Yang, Juntima Euathrongchit, Jyotsna Garg, K Manjula Rani, K Preethi, Kaatje Goetschalckx, Kai Eggers, Kamalakar Surineni, Kanae Hirase, T R Kapilamoorthy, Karen Calfas, Karen Gratrix, Karen Hallett, Karen Hultberg, Karen Nugent, Karen Petrosyan, Karen Swan, Karolina Kryczka, Karolina Wojtczak-Soska, Karolina Wojtera, Karsten Lenk, Karthik Ramasamy, Katarzyna Łuczak, Katarzyna Malinowska, Kate Pointon, Kate Robb, Katherine Martin, Kathleen Claes, Kathryn Carruthers, Kathy E Siegel, Katia Drouin, Katie Fowler-Lehman, Kavita Rawat, Kay Rowe, Keiichi Fukuda, Keith A A Fox, Ken Mahaffey, Kendra Unterbrink, Kenneth Giedd, Kerrie Van Loo, Kerry Lee, Kerstin Bonin, Kevin R Bainey, Kevin T Harley, Kevin Anstrom, Kevin Chan, Kevin Croce, Kevin Landolfo, Kevin Marzo, Keyur Patel, Khaled Abdul-Nour, Khaled Alfakih, Khaled Dajani, Khaled Ziada, Khaula Baloch, Khrystyna Kushniriuk, Kian-Keong Poh, Kim F Ireland, Kim Holland, Kimberly Ann Byrne, Kimberly E Halverson, Kimberly Elmore, Kimberly Miller-Cox, Kiran Reddy, Kirsten J Quiles, Kirsty Abercrombie, Klaus Matschke, Konrad Szymczyk, Koo Hui Chan, Kotiboinna Preethi, Kozhaya Sokhon, Krissada Meemuk, Kristian Thygesen, Kristin M Salmi, Kristin Newby, Kristina Wippler, Kristine Arges, Kristine Teoh, Krystal Etherington, Krystyna Łoboz-Grudzień, Krzysztof W Reczuch, Krzysztof Bury, Krzysztof Drzymalski, Krzysztof Kukuła, Kuo-Tzu Sung, Kurt Huber, Ladda Douangvila, Lance Sullenberger, Larissa Miranda Trama, Laszlone Matics, Laura Drew, Laura Flint, Laura 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Luiz A Carvalho, Luyang Xiong, Lynette L Teo, Lynn M Neeson, Lynne Winstanley, M Barbara Srichai-Parsia, M Quintana Giner, M Sowjanya Reddy, M Valdés Chávarri, M Grazia Rossi, Maarten Simoons, Maayan Konigstein, Maciej Lesiak, Maciej Olsowka, Mafalda Selas, Magalie Corfias, Magdalena Madero Rovalo, Magdalena Łanocha, Magdalena Miller, Magdalena Misztal-Teodorczyk, Magdalena Rantinella, Magdy Abdelhamid, Magnolia Jimenez, Mahboob Alam, Mahevamma Mylarappa, Mahfouz El Shahawy, Mahmoud Mohamed, Mahmud Al-Bustami, Majo X Joseph, Malgorzata Frach, Małgorzta Celińska-Spodar, Malte Helm, Manas Chacko, Mandy Murphy, Manitha Vinod, Manjula Rani, Manu Dhawan, Manuela Mombelli, Marcel Weber, Marcello Galvani, Marcelo Jamus Rodrigues, Marcia F Dubin, Marcia F Werner Bayer, Marcin Szkopiak, Marco Antonio Monsalve, Marco Bizzaro Santos, Marco Magnoni, Marco Marini, Marco Sicuro, Marco Zenati, Marcos Valério Coimbra Resende, Marek Roik, Margalit Bentzvi, Margaret Gilsenan, Margaret Iraola, Margot C 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Jr, Matthew Budoff, Matthew Jezior, Matthew Luckie, Matthias Friedrich, Mauren P Haeffner, Maximilian Tscharre, Max-Paul Winter, Mayana Almeida, Mayil S Krishnam, Mayuri Patel, Meenakshi Mishra, Megan Manocchia, Meghana Kakade, Melanie J Munro, Melissa D Chaplin, Melissa LeFevre, Mervyn Andiapen, Michael A Gibson, Michael B Rubens, Michael C Turner, Michael D Shapiro, Michael W Lee, Michael Berlowitz, Michael Davidson, Michael Mack, Michael McDaniel, Michael Mumma, Michal Wlodarczyk, Michel G Khouri, Michel S Slama, Michele Rawlins, Michelle M Bonner, Michelle M Seib, Michelle Chang, Michelle Crowder, Michelle Dixon, Michelle Mayon, Michelle McEvoy, Michelle Yee, Miguel M Fernandes, Miguel Nobre Menezes, Miguel Souto Bayarri, Miguel Barrero, Mikhail T Torosoff, Milan R Dobric, Milan Dobric, Milica Nikola Dekleva, Milind Avdhoot Gadkari, Millie Gomez, Min Tun Kyaw, Miriam Brooks, Miroslav Stevo Martinovic, Mitchel B Lustre, Mohammad Tariq Vakani, Mohammad El-Hajjar, Mohammed Al-Amoodi, 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Paula García-González, Paulo Cury Rezende, Paulo Ricardo Caramori, Pavel S Kozlov, Pedro Canas Silva, Pedro Gabriel Melo Barros E Silva, Pedro Píccaro de Oliveira, Pedro Carvalho, Pedro Modas, Pedro Rio, Peeyush Jain, Peiyu He, Peter A McCullough, Peter H Stone, Peter M Pollak, Peter Douglass, Peter Henriksen, Peter OKane, Peter Ong, Philip Jones, Philip Rogal, Philippe Généreux, Philippe Menasche, Philippe Rheault, Phoebe Goold, Pierre Gervais, Pierre Michaud, Pilar Calvillo, Ping Chai, Piotr Jakubowski, Piotr Pruszczyk, Piotr Slomka, Piyamitr Sritara, Poay-Huan Loh, Poonam Sonawane, Pouneh Samadi, Pragnesh P Parikh, Prakash Deedwania, Pranav M Patel, Praneeth Polamuri, Pratiksha Sharma, Precilia Vasquez, Preeti Kamath, Prince Thomas, Priyadarshani Arambam, Puja K Mehta, Purvez Grant, Pushpa Naik, Qi Zhong, Qian Zhao, Qiang Zhou, Qianqian Yuan, Qin Yu, Qingxian Li, Qiulan Xie, Qiutang Zeng, R J Vindhya, R James Gerlach, Rachel King, Rada Vučić, Radmila Lyubarova, Radoslaw Pracon, 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George J Juang, Gerald Fletcher, Gerald Leonard, Gerard Patrick Devlin, Gerard Esposito, Gergely Ágoston, Gervasio Lamas, Geza Fontos, Ghada Mikhail, Gia Cobb, Gian Piero Perna, Gianpiero Leone, Giles Roditi, Gilles Barone-Rochette, Girish Mishra, Giuseppe Tarantini, Glenda Wong, Glenn S Hamroff, Glenn Rayos, Gong Cheng, Gonzalo Barge-Caballero, Goran Davidović, Goran Stankovic, Gordana Stevanovic, Grace Jingyan Wang, Grace M Young, Graceanne Wayser, Graciela Scaro, Graham S Hillis, Graham Wong, Grazyna Anna Szulczyk, Gregor Simonis, Gregory Kumkumian, Gretchen Ann Peichel, Grzegorz Gajos, Gudrun Steinmaurer, Guilherme G Rucatti, Guilherme Portugal, Guilhermina Cantinho Lopes, Guillem Pons Lladó, Gunnar Frostfelt, Gurpreet S Wander, Gurpreet Gulati, Gustavo Pucci, Hafidz Abd Hadi, Haibo Zhang, Haitao Wang, Halina Marciniak, Han Chen, Hanan Kerr, Hani Najm, Hanna Douglas, Hannah Phillips, Hao Dai, Haojian Dong, Haqeel Jamil, Harikrishnan Sivadasanpillai, Harry Suryapranata, Hassan Reda, 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Wu, Yu Kunwu, Yu Zhao, Yudong Peng, Yueh-Hung Lin, Yulan Zhao, Yumei Dong, Yunhai Zhao, Yutthaphan Wannasopha, Yvonne Taul, Zakir Sahul, Zalina Kudzoeva, Zbigniew Kalarus, Zeljko Z Markovic, Zhen Huang, Zheng Ji, Zhenyu Liu, Zhou Yue, Zhulin Zhang, Zhuxi Li, Zile Singh Meharwal, Ziliang Bai, Zixiang Yu, Zohra Huda, Zoltan Davidovits
Subjects: Male, Cardiac Catheterization, Computed Tomography Angiography, medicine.medical_treatment, Myocardial Ischemia, Coronary Disease, Coronary Artery Disease, Kaplan-Meier Estimate, 030204 cardiovascular system & hematology, Coronary Angiography, ISCHEMIA Research Group, law.invention, Angina, Coronary artery disease, 0302 clinical medicine, Randomized controlled trial, law, Cardiovascular Disease, Myocardial Revascularization, 030212 general & internal medicine, Coronary Artery Bypass, 11 Medical and Health Sciences, Cardiac catheterization, General Medicine, Middle Aged, humanities, Cardiovascular Diseases, Cardiology, Female, Human, medicine.medical_specialty, Ischemia, Article, 03 medical and health sciences, Geriatric cardiology, Percutaneous Coronary Intervention, General & Internal Medicine, Internal medicine, medicine, Humans, Angina, Unstable, Aged, business.industry, Coronary Artery Bypa, Percutaneous coronary intervention, Bayes Theorem, medicine.disease, Heart failure, Quality of Life, business
Abstract: BACKGROUND: Among patients with stable coronary disease and moderate or severe ischemia, whether clinical outcomes are better in those who receive an invasive intervention plus medical therapy than in those who receive medical therapy alone is uncertain. METHODS: We randomly assigned 5179 patients with moderate or severe ischemia to an initial invasive strategy (angiography and revascularization when feasible) and medical therapy or to an initial conservative strategy of medical therapy alone and angiography if medical therapy failed. The primary outcome was a composite of death from cardiovascular causes, myocardial infarction, or hospitalization for unstable angina, heart failure, or resuscitated cardiac arrest. A key secondary outcome was death from cardiovascular causes or myocardial infarction. RESULTS: Over a median of 3.2 years, 318 primary outcome events occurred in the invasive-strategy group and 352 occurred in the conservative-strategy group. At 6 months, the cumulative event rate was 5.3% in the invasive-strategy group and 3.4% in the conservative-strategy group (difference, 1.9 percentage points; 95% confidence interval [CI], 0.8 to 3.0); at 5 years, the cumulative event rate was 16.4% and 18.2%, respectively (difference, -1.8 percentage points; 95% CI, -4.7 to 1.0). Results were similar with respect to the key secondary outcome. The incidence of the primary outcome was sensitive to the definition of myocardial infarction; a secondary analysis yielded more procedural myocardial infarctions of uncertain clinical importance. There were 145 deaths in the invasive-strategy group and 144 deaths in the conservative-strategy group (hazard ratio, 1.05; 95% CI, 0.83 to 1.32). CONCLUSIONS: Among patients with stable coronary disease and moderate or severe ischemia, we did not find evidence that an initial invasive strategy, as compared with an initial conservative strategy, reduced the risk of ischemic cardiovascular events or death from any cause over a median of 3.2 years. The trial findings were sensitive to the definition of myocardial infarction that was used. (Funded by the National Heart, Lung, and Blood Institute and others; ISCHEMIA ClinicalTrials.gov number, NCT01471522.).
Published: 2020
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45. Automated Aortic Doppler Flow Tracing for Reproducible Research and Clinical Measurements.

Author: Massoud Zolgharni, Niti M. Dhutia, Graham D. Cole, M. Reza Bahmanyar, Siana Jones, Syed M. Afzal Sohaib, Sarah B. Tai, Keith Willson, Judith A. Finegold, and Darrel P. Francis
Published: 2014
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46. Patient-Specific Coronary Stenoses Can Be Modeled Using a Combination of OCT and Flow Velocities to Accurately Predict Hyperemic Pressure Gradients.

Author: C. A. Kousera, Sukhjinder Nijjer, Ryo Torii, R. Petraco, S. Sen, N. Foin, Alun D. Hughes, Darrel P. Francis, X. Yun Xu, and Justin E. Davies
Published: 2014
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47. Quality of Life Assessment in Trials of Revascularization for Chronic Stable Angina: Insights from ORBITA and the Implications of Blinding

Author: Alexandra N. Nowbar, Darrel P. Francis, and Rasha Al-Lamee
Subjects: Canada, medicine.medical_specialty, medicine.medical_treatment, Myocardial Infarction, Placebo, Coronary artery disease, Angina, Percutaneous Coronary Intervention, Quality of life, Internal medicine, Clinical endpoint, Humans, Medicine, Pharmacology (medical), Angina, Stable, cardiovascular diseases, Pharmacology, Nitrates, business.industry, Percutaneous coronary intervention, General Medicine, Canadian Cardiovascular Society, medicine.disease, Treatment Outcome, Conventional PCI, Quality of Life, Cardiology and Cardiovascular Medicine, business
Abstract: The main aims of therapy in chronic stable angina are to reduce the risk of myocardial infarction and death and improve symptoms and quality of life (QoL). Unblinded trials have shown that revascularization does not reduce the risk of myocardial infarction or death but does appear to improve symptoms. However, symptoms are susceptible to the placebo effect which can bias therapies to appear more effective than they are. To assess the true physical impact of a treatment on symptoms, placebo-controlled trials with patients and medical and research teams blinded to treatment allocation are necessary. Symptoms and QoL can be reported directly by the patient or indirectly by the physician. Patient-reported outcome measures in angina trials can include angina frequency, frequency of nitrate use, exercise capacity, and questionnaires such as the Seattle Angina Questionnaire (SAQ) and the generic EuroQOL-5D-5L (EQ-5D-5L) QoL questionnaire. Physician-assessed outcome measures include Canadian Cardiovascular Society Class. The Objective Randomised Blinded Investigation with Optimal Medical Therapy of Angioplasty in Stable Angina (ORBITA) trial was the first blinded placebo-controlled study investigating the role of percutaneous coronary intervention (PCI) in chronic stable angina. The trial showed a smaller than expected and not statistically significant effect of placebo-controlled PCI on the primary endpoint of change in exercise time at 6 weeks follow-up in single-vessel coronary artery disease. There was also no significant placebo-controlled treatment effect of PCI for the prespecified secondary endpoints of SAQ or EQ-5D-5L, although PCI did result in 20% more patients becoming free from angina than placebo in a non-prespecified secondary analysis. ORBITA has demonstrated the need for symptomatic and QoL effects of PCI to be studied using placebo control. Here, we describe ways of measuring QoL, the impact of the unblinded and blinded trials to date, what we have learned from ORBITA, and what is next for this common and complex condition.
Published: 2021
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48. Machine learning with convolutional neural networks for clinical cardiologists

Author: Darrel P. Francis, James P. Howard, and Wellcome Trust
Subjects: Cardiac & Cardiovascular Systems, cardiac imaging techniques, Process (engineering), Machine learning, computer.software_genre, Convolutional neural network, CLASSIFICATION, Task (project management), Machine Learning, Cardiologists, Humans, Medicine, Set (psychology), 1102 Cardiorespiratory Medicine and Haematology, Science & Technology, Artificial neural network, business.industry, Deep learning, 1103 Clinical Sciences, Variety (cybernetics), Cardiovascular System & Hematology, Face (geometry), Cardiovascular System & Cardiology, Neural Networks, Computer, Artificial intelligence, Cardiology and Cardiovascular Medicine, business, Life Sciences & Biomedicine, computer, Algorithms
Abstract: 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 …
Published: 2021
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49. Arterial pulse wave velocity in coronary arteries.

Author: Jazmin Aguado-Sierra, Kim H. Parker, Justin E. Davies, Darrel P. Francis, Alun D. Hughes, and Jamil Mayet
Published: 2006
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50. Efficient labelling for efficient deep learning: the benefit of a multiple-image-ranking method to generate high volume training data applied to ventricular slice level classification in cardiac MRI

Author: Sameer Zaman, Kavitha Vimalesvaran, James P. Howard, Digby Chappell, Marta Varela, Nicholas S. Peters, Darrel P. Francis, Anil A. Bharath, Nick W. F. Linton, and Graham D. Cole
Subjects: Artificial Intelligence, Medicine (miscellaneous)
Published: 2023
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