Long term clinical outcomes and cost-effectiveness of catheter vs thoracoscopic surgical ablation in long-standing persistent atrial fibrillation using continuous cardiac monitoring: CASA-AF randomised controlled trial.

BACKGROUND: Long-term clinical outcomes of catheter ablation (CA) compared to thoracoscopic surgical ablation (SA) to treat patients with long-standing persistent atrial fibrillation (LSPAF) are not known. OBJECTIVES: To compare long-term (36-months) clinical efficacy, quality of life and cost-effectiveness of SA and CA in LSPAF. METHODS: Participants were followed up for 3 years using implantable loop recorder (ILR) and questionnaires to assess change in quality of life. Intention-to-treat analyses were used to report the findings. RESULTS: Of 115 LSPAF patients treated, 104 (90.4%) completed 36-months follow-up (CA=57, SA=47). Following a single procedure without anti-arrhythmic drugs (AAD) 7 (12%) patients in the CA arm and 5 (11%) in the SA arm (HR 1.22, 95% CI 0.81 to 1.83, p = 0.41) were free from AF/AT ≥30 sec at 36 months. Thirty-three patients (58%) in the CA arm and 26 (55%) in the SA arm (HR 1.04, 95% CI 0.57 to 1.88, p = 0.91) had their AF/AT burden reduced by ≥75%. The overall impact on health-related quality of life was similar, with mean QALY estimates of 2.45 (95% CI 2.31 to 2.59) for CA and 2.32 (2.13 to 2.52) for SA. Estimated costs were higher for SA (mean £24,682, 95% CI £21,746 to £27,618) than for CA (mean £18,002, 95% CI £15,422 to £20,581). CONCLUSION: In symptomatic LSPAF, CA and SA were equally effective at achieving arrhythmia outcomes (freedom from AF/AT ≥30s and ≥75% burden reduction) following a single-procedure without AADs. However, SA is significantly more costly than catheter ablation.

Symptoms as a Predictor of the Placebo-Controlled Efficacy of PCI in Stable Coronary Artery Disease.

BACKGROUND: Placebo-controlled evidence from ORBITA-2 found that percutaneous cutaneous intervention (PCI) in stable coronary artery disease with little or no antianginal medication relieved angina, but residual symptoms persisted in many. The reason for this was unclear. OBJECTIVES: ; This ORBITA-2 secondary analysis investigates the relationship between presenting symptoms and disease severity (anatomic, non-invasive, and invasive ischemia) and the ability of symptoms to predict the placebo-controlled efficacy of PCI. METHODS: Pre-randomization symptom severity and nature were assessed using the ORBITA smartphone application and symptom and quality of life questionnaires including the Rose angina questionnaire. Disease severity was assessed using quantitative coronary angiography (QCA), stress echocardiography, fractional flow reserve (FFR), and instantaneous wave-free ratio (iFR). Bayesian ordinal regression was used. RESULTS: At pre-randomization, the median number of daily angina episodes was 0.8 (0.4-1.6), 64% had Rose angina, QCA diameter stenosis 61 (49-74), stress echocardiography score 1.0 (0.0-2.7), FFR 0.63 (0.49-0.75), and iFR 0.78 (0.55-0.87). There was little relationship between symptom severity and nature and disease severity: angina symptom score with QCA ordinal correlation coefficient 0.06 (95% CrI 0.00 to 0.08); stress echocardiography 0.09 (95% CrI 0.02 to 0.10); FFR 0.04 (95% CrI -0.03 to 0.07); and iFR 0.04 (95% CrI -0.01 to 0.07). However, Rose angina and guideline-based typical angina were strong predictors of placebo-controlled PCI efficacy (angina symptom score: OR 1.9, 95% CrI 1.6 to 2.1, Pr(Interaction)=99.9% and OR 1.8, 95% CrI 1.6 to 2.1, Pr(Interaction)=99.9%, respectively). CONCLUSIONS: Although symptom severity and nature were poorly associated with disease severity, the nature of symptoms powerfully predicted the placebo-controlled efficacy of PCI.

N-of-1 Trial of Angina Verification Before Percutaneous Coronary Intervention.

BACKGROUND: In stable coronary artery disease, 30% to 60% of patients remain symptomatic despite successful revascularization. Perhaps not all symptoms reported by a patient with myocardial ischemia are, in fact, angina. OBJECTIVES: This study sought to determine whether independent symptom verification using a placebo-controlled ischemic stimulus could distinguish which patients achieve greatest symptom relief from percutaneous coronary intervention (PCI). METHODS: ORBITA-STAR was a multicenter, n-of-1, placebo-controlled study in patients undergoing single-vessel PCI for stable symptoms. Participants underwent 4 episodes (60 seconds each) of low-pressure balloon occlusion across their coronary stenosis, randomly paired with 4 episodes of placebo inflation. Following each episode, patients reported the similarity of the induced symptom in comparison with their usual symptom. The similarity score ranged from -10 (placebo replicated the symptom more than balloon occlusion) to +10 (balloon occlusion exactly replicated the symptom). The primary endpoint was the ability of the similarity score to predict symptom relief with PCI. RESULTS: Fifty-one patients were recruited, aged 62.9 ± 8.6 years. The median fractional flow reserve was 0.68 (Q1-Q3: 0.57-0.79), and the instantaneous wave-free ratio was 0.80 (Q1-Q3: 0.48-0.89). The median similarity score was 3 (Q1-Q3: 0.875-5.25). The similarity score was a strong predictor of symptom improvement following PCI: a patient with an upper quartile similarity score of 5.25 was significantly more likely to have lower angina frequency at follow-up (OR: 8.01; 95% credible interval: 2.39-15.86) than a patient with a lower quartile similarity score of 0.875 (OR: 1.31; 95% credible interval: 0.71-1.99), Pr(difference) >99.9%. CONCLUSIONS: Similarity score powerfully predicted symptom improvement from PCI. These data lay the foundation for independent symptom mapping to target PCI to those patients most likely to benefit. (Systematic Trial of Angina Assessment Before Revascularization [ORBITA-STAR]; NCT04280575).

Placebo Control and Blinding in Randomized Trials of Procedural Interventions: A Systematic Review and Meta-Regression.

Importance: Unlike medications, procedural interventions are rarely trialed against placebo prior to becoming accepted in clinical practice. When placebo-controlled trials are eventually conducted, procedural interventions may be less effective than previously believed. Objective: To investigate the importance of including a placebo arm in trials of surgical and interventional procedures by comparing effect sizes from trials of the same procedure that do and do not include a placebo arm. Data Sources: Searches of MEDLINE and Embase identified all placebo-controlled trials for procedural interventions in any specialty of medicine and surgery from inception to March 31, 2019. A secondary search identified randomized clinical trials assessing the same intervention, condition, and end point but without a placebo arm for paired comparison. Study Selection: Placebo-controlled trials of anatomically site-specific procedures requiring skin incision or endoscopic techniques were eligible for inclusion; these were then matched to trials without placebo control that fell within prespecified limits of heterogeneity. Data Extraction and Synthesis: Random-effects meta-regression, with placebo and blinding as a fixed effect and intervention and end point grouping as random effects, was used to calculate the impact of placebo control for each end point. Data were analyzed from March 2019 to March 2020. Main Outcomes and Measures: End points were examined in prespecified subgroups: patient-reported or health care professional-assessed outcomes, quality of life, pain, blood pressure, exercise-related outcomes, recurrent bleeding, and all-cause mortality. Results: Ninety-seven end points were matched from 72 blinded, placebo-controlled trials (hereafter, blinded) and 55 unblinded trials without placebo control (hereafter, unblinded), including 111 500 individual patient end points. Unblinded trials had larger standardized effect sizes than blinded trials for exercise-related outcomes (standardized mean difference [SMD], 0.59; 95% CI, 0.29 to 0.89; P < .001) and quality-of-life (SMD, 0.32; 95% CI, 0.11 to 0.53; P = .003) and health care professional-assessed end points (SMD, 0.40; 95% CI, 0.18 to 0.61; P < .001). The placebo effect accounted for 88.1%, 55.2%, and 61.3% of the observed unblinded effect size for these end points, respectively. There was no significant difference between unblinded and blinded trials for patient-reported end points (SMD, 0.31; 95% CI, -0.02 to 0.64; P = .07), blood pressure (SMD, 0.26; 95% CI, -0.10 to 0.62; P = .15), all-cause mortality (odds ratio [OR], 0.23; 95% CI, -0.26 to 0.72; P = .36), pain (SMD, 0.03; 95% CI, -0.52 to 0.57; P = .91), or recurrent bleeding events (OR, -0.12; 95% CI, -1.11 to 0.88; P = .88). Conclusions and Relevance: The magnitude of the placebo effect found in this systematic review and meta-regression was dependent on the end point. Placebo control in trials of procedural interventions had the greatest impact on exercise-related, quality-of-life, and health care professional-assessed end points. Randomized clinical trials of procedural interventions may consider placebo control accordingly.

Therapeutic potential of conduction system pacing as a method for improving cardiac output during ventricular tachycardia.

BACKGROUND: Ventricular tachycardia (VT) reduces cardiac output through high heart rates, loss of atrioventricular synchrony, and loss of ventricular synchrony. We studied the contribution of each mechanism and explored the potential therapeutic utility of His bundle pacing to improve cardiac output during VT. METHODS: Study 1 aimed to improve the understanding of mechanisms of harm during VT (using pacing simulated VT). In 23 patients with left ventricular impairment, we recorded continuous ECG and beat-by-beat blood pressure measurements. We assessed the hemodynamic impact of heart rate and restoration of atrial and biventricular synchrony. Study 2 investigated novel pacing interventions during clinical VT by evaluating the hemodynamic effects of His bundle pacing at 5 bpm above the VT rate in 10 patients. RESULTS: In Study 1, at progressively higher rates of simulated VT, systolic blood pressure declined: at rates of 125, 160, and 190 bpm, -22.2%, -42.0%, and -58.7%, respectively (ANOVA p < 0.0001). Restoring atrial synchrony alone had only a modest beneficial effect on systolic blood pressure (+ 3.6% at 160 bpm, p = 0.2117), restoring biventricular synchrony alone had a greater effect (+ 9.1% at 160 bpm, p = 0.242), and simultaneously restoring both significantly increased systolic blood pressure (+ 31.6% at 160 bpm, p = 0.0003). In Study 2, the mean rate of clinical VT was 143 ± 21 bpm. His bundle pacing increased systolic blood pressure by + 14.2% (p = 0.0023). In 6 of 10 patients, VT terminated with His bundle pacing. CONCLUSIONS: Restoring atrial and biventricular synchrony improved hemodynamic function in simulated and clinical VT. Conduction system pacing could improve VT tolerability and treatment.

Coronary sinus reducer for the treatment of refractory angina (ORBITA-COSMIC): a randomised, placebo-controlled trial.

BACKGROUND: The coronary sinus reducer (CSR) is proposed to reduce angina in patients with stable coronary artery disease by improving myocardial perfusion. We aimed to measure its efficacy, compared with placebo, on myocardial ischaemia reduction and symptom improvement. METHODS: ORBITA-COSMIC was a double-blind, randomised, placebo-controlled trial conducted at six UK hospitals. Patients aged 18 years or older with angina, stable coronary artery disease, ischaemia, and no further options for treatment were eligible. All patients completed a quantitative adenosine-stress perfusion cardiac magnetic resonance scan, symptom and quality-of-life questionnaires, and a treadmill exercise test before entering a 2-week symptom assessment phase, in which patients reported their angina symptoms using a smartphone application (ORBITA-app). Patients were randomly assigned (1:1) to receive either CSR or placebo. Both participants and investigators were masked to study assignment. After the CSR implantation or placebo procedure, patients entered a 6-month blinded follow-up phase in which they reported their daily symptoms in the ORBITA-app. At 6 months, all assessments were repeated. The primary outcome was myocardial blood flow in segments designated ischaemic at enrolment during the adenosine-stress perfusion cardiac magnetic resonance scan. The primary symptom outcome was the number of daily angina episodes. Analysis was done by intention-to-treat and followed Bayesian methodology. The study is registered with ClinicalTrials.gov, NCT04892537, and completed. FINDINGS: Between May 26, 2021, and June 28, 2023, 61 patients were enrolled, of whom 51 (44 [86%] male; seven [14%] female) were randomly assigned to either the CSR group (n=25) or the placebo group (n=26). Of these, 50 patients were included in the intention-to-treat analysis (24 in the CSR group and 26 in the placebo group). 454 (57%) of 800 imaged cardiac segments were ischaemic at enrolment, with a median stress myocardial blood flow of 1·08 mL/min per g (IQR 0·77-1·41). Myocardial blood flow in ischaemic segments did not improve with CSR compared with placebo (difference 0·06 mL/min per g [95% CrI -0·09 to 0·20]; Pr(Benefit)=78·8%). The number of daily angina episodes was reduced with CSR compared with placebo (OR 1·40 [95% CrI 1·08 to 1·83]; Pr(Benefit)=99·4%). There were two CSR embolisation events in the CSR group, and no acute coronary syndrome events or deaths in either group. INTERPRETATION: ORBITA-COSMIC found no evidence that the CSR improved transmural myocardial perfusion, but the CSR did improve angina compared with placebo. These findings provide evidence for the use of CSR as a further antianginal option for patients with stable coronary artery disease. FUNDING: Medical Research Council, Imperial College Healthcare Charity, National Institute for Health and Care Research Imperial Biomedical Research Centre, St Mary's Coronary Flow Trust, British Heart Foundation.

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.

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.

Active learning for left ventricle segmentation in echocardiography.

BACKGROUND AND OBJECTIVE: Training deep learning models for medical image segmentation require large annotated datasets, which can be expensive and time-consuming to create. Active learning is a promising approach to reduce this burden by strategically selecting the most informative samples for segmentation. This study investigates the use of active learning for efficient left ventricle segmentation in echocardiography with sparse expert annotations. METHODS: We adapt and evaluate various sampling techniques, demonstrating their effectiveness in judiciously selecting samples for segmentation. Additionally, we introduce a novel strategy, Optimised Representativeness Sampling, which combines feature-based outliers with the most representative samples to enhance annotation efficiency. RESULTS: Our findings demonstrate a substantial reduction in annotation costs, achieving a remarkable 99% upper bound performance while utilising only 20% of the labelled data. This equates to a reduction of 1680 images needing annotation within our dataset. When applied to a publicly available dataset, our approach yielded a remarkable 70% reduction in required annotation efforts, representing a significant advancement compared to baseline active learning strategies, which achieved only a 50% reduction. Our experiments highlight the nuanced performance of diverse sampling strategies across datasets within the same domain. CONCLUSIONS: The study provides a cost-effective approach to tackle the challenges of limited expert annotations in echocardiography. By introducing a distinct dataset, made publicly available for research purposes, our work contributes to the field's understanding of efficient annotation strategies in medical image segmentation.

Automated mitral inflow Doppler peak velocity measurement using deep learning.

Doppler echocardiography is a widely utilised non-invasive imaging modality for assessing the functionality of heart valves, including the mitral valve. Manual assessments of Doppler traces by clinicians introduce variability, prompting the need for automated solutions. This study introduces an innovative deep learning model for automated detection of peak velocity measurements from mitral inflow Doppler images, independent from Electrocardiogram information. A dataset of Doppler images annotated by multiple expert cardiologists was established, serving as a robust benchmark. The model leverages heatmap regression networks, achieving 96% detection accuracy. The model discrepancy with the expert consensus falls comfortably within the range of inter- and intra-observer variability in measuring Doppler peak velocities. The dataset and models are open-source, fostering further research and clinical application.

Automated echocardiographic left ventricular dimension assessment in dogs using artificial intelligence: Development and validation.

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 < .01). In end-systole, there were no differences between individual expert and AI performances. CONCLUSIONS AND CLINICAL IMPORTANCE: An artificial intelligence network can be trained to adequately measure linear LV dimensions, with performance indistinguishable from that of experts.

The ability of contemporary cardiologists to judge the ischemic impact of a coronary lesion visually

BACKGROUND: Landmark trials showed that invasive pressure measurement (Fractional Flow Reserve, FFR) was a better guide to coronary stenting than visual assessment. However, present-day interventionists have benefited from extensive research and personal experience of mapping anatomy to hemodynamics. AIMS: To determine if visual assessment of the angiogram performs as well as invasive measurement of coronary physiology. METHODS: 25 interventional cardiologists independently visually assessed the single vessel coronary disease of 200 randomized participants in The Objective Randomized Blinded Investigation with optimal medical Therapy of Angioplasty in stable angina trial (ORBITA). They gave a visual prediction of the FFR and Instantaneous Wave-free Ratio (iFR), denoted vFFR and viFR respectively. Each judged each lesion on 2 occasions, so that every lesion had 50 vFFR, and 50 viFR assessments. The group consensus visual estimates (vFFR-group and viFR-group) and individual cardiologists' visual estimates (vFFR-individual and viFR-individual) were tested alongside invasively measured FFR and iFR for their ability to predict the placebo-controlled reduction in stress echo ischemia with stenting. RESULTS: Placebo-controlled ischemia improvement with stenting was predicted by vFFR-group (p < 0.0001) and viFR-group (p < 0.0001), vFFR-individual (p < 0.0001) and viFR-individual (p < 0.0001). There were no significant differences between the predictive performance of the group visual estimates and their invasive counterparts: p = 0.53 for vFFR vs FFR and p = 0.56 for viFR vs iFR. CONCLUSION: Visual assessment of the angiogram by contemporary experts, provides significant additional information on the amount of ischaemia which can be relieved by placebo-controlled stenting in single vessel coronary artery disease.

The ability of contemporary cardiologists to judge the ischemic impact of a coronary lesion visually.

BACKGROUND: Landmark trials showed that invasive pressure measurement (Fractional Flow Reserve, FFR) was a better guide to coronary stenting than visual assessment. However, present-day interventionists have benefited from extensive research and personal experience of mapping anatomy to hemodynamics. AIMS: To determine if visual assessment of the angiogram performs as well as invasive measurement of coronary physiology. METHODS: 25 interventional cardiologists independently visually assessed the single vessel coronary disease of 200 randomized participants in The Objective Randomized Blinded Investigation with optimal medical Therapy of Angioplasty in stable angina trial (ORBITA). They gave a visual prediction of the FFR and Instantaneous Wave-free Ratio (iFR), denoted vFFR and viFR respectively. Each judged each lesion on 2 occasions, so that every lesion had 50 vFFR, and 50 viFR assessments. The group consensus visual estimates (vFFR-group and viFR-group) and individual cardiologists' visual estimates (vFFR-individual and viFR-individual) were tested alongside invasively measured FFR and iFR for their ability to predict the placebo-controlled reduction in stress echo ischemia with stenting. RESULTS: Placebo-controlled ischemia improvement with stenting was predicted by vFFR-group (p < 0.0001) and viFR-group (p < 0.0001), vFFR-individual (p < 0.0001) and viFR-individual (p < 0.0001). There were no significant differences between the predictive performance of the group visual estimates and their invasive counterparts: p = 0.53 for vFFR vs FFR and p = 0.56 for viFR vs iFR. CONCLUSION: Visual assessment of the angiogram by contemporary experts, provides significant additional information on the amount of ischaemia which can be relieved by placebo-controlled stenting in single vessel coronary artery disease.

Catheter Ablation for Ventricular Tachycardia After MI: A Reconstructed Individual Patient Data Meta-analysis of Randomised Controlled Trials.

Background: The prognostic impact of ventricular tachycardia (VT) catheter ablation is an important outstanding research question. We undertook a reconstructed individual patient data meta-analysis of randomised controlled trials comparing ablation to medical therapy in patients developing VT after MI. Methods: We systematically identified all trials comparing catheter ablation to medical therapy in patients with VT and prior MI. The prespecified primary endpoint was reconstructed individual patient assessment of all-cause mortality. Prespecified secondary endpoints included trial-level assessment of all-cause mortality, VT recurrence or defibrillator shocks and all-cause hospitalisations. Prespecified subgroup analysis was performed for ablation approaches involving only substrate modification without VT activation mapping. Sensitivity analyses were performed depending on the proportion of patients with prior MI included. Results: Eight trials, recruiting a total of 874 patients, were included. Of these 874 patients, 430 were randomised to catheter ablation and 444 were randomised to medical therapy. Catheter ablation reduced all-cause mortality compared with medical therapy when synthesising individual patient data (HR 0.63; 95% CI [0.41-0.96]; p=0.03), but not in trial-level analysis (RR 0.91; 95% CI [0.67-1.23]; p=0.53; I2=0%). Catheter ablation significantly reduced VT recurrence, defibrillator shocks and hospitalisations compared with medical therapy. Sensitivity analyses were consistent with the primary analyses. Conclusion: In patients with postinfarct VT, catheter ablation reduces mortality.

A Placebo-Controlled Trial of Percutaneous Coronary Intervention for Stable Angina.

BACKGROUND: Percutaneous coronary intervention (PCI) is frequently performed to reduce the symptoms of stable angina. Whether PCI relieves angina more than a placebo procedure in patients who are not receiving antianginal medication remains unknown. METHODS: We conducted a double-blind, randomized, placebo-controlled trial of PCI in patients with stable angina. Patients stopped all antianginal medications and underwent a 2-week symptom assessment phase before randomization. Patients were then randomly assigned in a 1:1 ratio to undergo PCI or a placebo procedure and were followed for 12 weeks. The primary end point was the angina symptom score, which was calculated daily on the basis of the number of angina episodes that occurred on a given day, the number of antianginal medications prescribed on that day, and clinical events, including the occurrence of unblinding owing to unacceptable angina or acute coronary syndrome or death. Scores range from 0 to 79, with higher scores indicating worse health status with respect to angina. RESULTS: A total of 301 patients underwent randomization: 151 to the PCI group and 150 to the placebo group. The mean (±SD) age was 64±9 years, and 79% were men. Ischemia was present in one cardiac territory in 242 patients (80%), in two territories in 52 patients (17%), and in three territories in 7 patients (2%). In the target vessels, the median fractional flow reserve was 0.63 (interquartile range, 0.49 to 0.75), and the median instantaneous wave-free ratio was 0.78 (interquartile range, 0.55 to 0.87). At the 12-week follow-up, the mean angina symptom score was 2.9 in the PCI group and 5.6 in the placebo group (odds ratio, 2.21; 95% confidence interval, 1.41 to 3.47; P<0.001). One patient in the placebo group had unacceptable angina leading to unblinding. Acute coronary syndromes occurred in 4 patients in the PCI group and in 6 patients in the placebo group. CONCLUSIONS: Among patients with stable angina who were receiving little or no antianginal medication and had objective evidence of ischemia, PCI resulted in a lower angina symptom score than a placebo procedure, indicating a better health status with respect to angina. (Funded by the National Institute for Health and Care Research Imperial Biomedical Research Centre and others; ORBITA-2 ClinicalTrials.gov number, NCT03742050.).

Left bundle branch pacing with and without anodal capture: impact on ventricular activation pattern and acute haemodynamics.

AIMS: Left bundle branch pacing (LBBP) can deliver physiological left ventricular activation, but typically at the cost of delayed right ventricular (RV) activation. Right ventricular activation can be advanced through anodal capture, but there is uncertainty regarding the mechanism by which this is achieved, and it is not known whether this produces haemodynamic benefit. METHODS AND RESULTS: We 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 haemodynamic response were studied during LBBP with and without anodal capture. We recruited 21 patients with a mean age of 67 years, of whom 14 were males. We measured electrocardiogram timings and haemodynamics in all patients, and in 16, we also performed non-invasive mapping. Ventricular epicardial propagation maps demonstrated that RV septal myocardial capture, rather than right bundle capture, was the mechanism for earlier RV activation. With anodal capture, QRS duration and total ventricular activation times were shorter (116 ± 12 vs. 129 ± 14 ms, P < 0.01 and 83 ± 18 vs. 90 ± 15 ms, P = 0.01). This required higher outputs (3.6 ± 1.9 vs. 0.6 ± 0.2 V, P < 0.01) but without additional haemodynamic benefit (mean difference -0.2 ± 3.8 mmHg compared with pacing without anodal capture, P = 0.2). CONCLUSION: Left bundle branch pacing with anodal capture advances RV activation by stimulating the RV septal myocardium. However, this requires higher outputs and does not improve acute haemodynamics. Aiming for anodal capture may therefore not be necessary.

Development of artificial intelligence tools for invasive Doppler-based coronary microvascular assessment.

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.

How robust are recommended waiting times to pacing after cardiac surgery that are derived from observational data?

AIMS: For bradycardic patients after cardiac surgery, it is unknown how long to wait before implanting a permanent pacemaker (PPM). Current recommendations vary and are based on observational studies. This study aims to examine why this variation may exist. METHODS AND RESULTS: We conducted first a study of patients in our institution and second a systematic review of studies examining conduction disturbance and pacing after cardiac surgery. Of 5849 operations over a 6-year period, 103 (1.8%) patients required PPM implantation. Only pacing dependence at implant and time from surgery to implant were associated with 30-day pacing dependence. The only predictor of regression of pacing dependence was time from surgery to implant. We then applied the conventional procedure of receiver operating characteristic (ROC) analysis, seeking an optimal time point for decision-making. This suggested the optimal waiting time was 12.5 days for predicting pacing dependence at 30 days for all patients (area under the ROC curve (AUC) 0.620, P = 0.031) and for predicting regression of pacing dependence in patients who were pacing-dependent at implant (AUC 0.769, P < 0.001). However, our systematic review showed that recommended optimal decision-making time points were strongly correlated with the average implant time point of those individual studies (R = 0.96, P < 0.001). We further conducted modelling which revealed that in any such study, the ROC method is strongly biased to indicate a value near to the median time to implant as optimal. CONCLUSION: When commonly used automated statistical methods are applied to observational data with the aim of defining the optimal time to pacing after cardiac surgery, the suggested answer is likely to be similar to the average time to pacing in that cohort.

Septal scar as a barrier to left bundle branch area pacing.

BACKGROUND: The use of left bundle branch area pacing (LBBAP) for bradycardia pacing and cardiac resynchronization is increasing, but implants are not always successful. We prospectively studied consecutive patients to determine whether septal scar contributes to implant failure. METHODS: Patients scheduled for bradycardia pacing or cardiac resynchronization therapy were prospectively enrolled. Recruited patients underwent preprocedural scar assessment by cardiac MRI with late gadolinium enhancement imaging. LBBAP was attempted using a lumenless lead (Medtronic 3830) via a transeptal approach. RESULTS: Thirty-five patients were recruited: 29 male, mean age 68 years, 10 ischemic, and 16 non-ischemic cardiomyopathy. Pacing indication was bradycardia in 26% and cardiac resynchronization in 74%. The lead was successfully deployed to the left ventricular septum in 30/35 (86%) and unsuccessful in the remaining 5/35 (14%). Septal late gadolinium enhancement was significantly less extensive in patients where left septal lead deployment was successful, compared those where it was unsuccessful (median 8%, IQR 2%-18% vs. median 54%, IQR 53%-57%, p < .001). CONCLUSIONS: The presence of septal scar appears to make it more challenging to deploy a lead to the left ventricular septum via the transeptal route. Additional implant tools or alternative approaches may be required in patients with extensive septal scar.

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.

Background: Getting the most value from expert clinicians' limited labelling time is a major challenge for artificial intelligence (AI) development in clinical imaging. We present a novel method for ground-truth labelling of cardiac magnetic resonance imaging (CMR) image data by leveraging multiple clinician experts ranking multiple images on a single ordinal axis, rather than manual labelling of one image at a time. We apply this strategy to train a deep learning (DL) model to classify the anatomical position of CMR images. This allows the automated removal of slices that do not contain the left ventricular (LV) myocardium. Methods: Anonymised LV short-axis slices from 300 random scans (3,552 individual images) were extracted. Each image's anatomical position relative to the LV was labelled using two different strategies performed for 5 hours each: (I) 'one-image-at-a-time': each image labelled according to its position: 'too basal', 'LV', or 'too apical' individually by one of three experts; and (II) 'multiple-image-ranking': three independent experts ordered slices according to their relative position from 'most-basal' to 'most apical' in batches of eight until each image had been viewed at least 3 times. Two convolutional neural networks were trained for a three-way classification task (each model using data from one labelling strategy). The models' performance was evaluated by accuracy, F1-score, and area under the receiver operating characteristics curve (ROC AUC). Results: After excluding images with artefact, 3,323 images were labelled by both strategies. The model trained using labels from the 'multiple-image-ranking strategy' performed better than the model using the 'one-image-at-a-time' labelling strategy (accuracy 86% vs. 72%, P=0.02; F1-score 0.86 vs. 0.75; ROC AUC 0.95 vs. 0.86). For expert clinicians performing this task manually the intra-observer variability was low (Cohen's κ=0.90), but the inter-observer variability was higher (Cohen's κ=0.77). Conclusions: We present proof of concept that, given the same clinician labelling effort, comparing multiple images side-by-side using a 'multiple-image-ranking' strategy achieves ground truth labels for DL more accurately than by classifying images individually. We demonstrate a potential clinical application: the automatic removal of unrequired CMR images. This leads to increased efficiency by focussing human and machine attention on images which are needed to answer clinical questions.

A randomized controlled trial to investigate the use of acute coronary syndrome therapy in patients hospitalized with COVID-19: the COVID-19 Acute Coronary Syndrome trial.

BACKGROUND: Patients hospitalized with COVID-19 suffer thrombotic complications. Risk factors for poor outcomes are shared with coronary artery disease. OBJECTIVES: To investigate the efficacy of an acute coronary syndrome regimen in patients hospitalized with COVID-19 and coronary disease risk factors. METHODS: A randomized controlled, open-label trial across acute hospitals (United Kingdom 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, or death). RESULTS: Three hundred twenty patients from 9 centers were randomized. The trial terminated early due to low recruitment. At 30 days, there was no significant difference in mortality (intervention vs control, 11.5% vs 15%; unadjusted odds ratio [OR], 0.73; 95% CI, 0.38-1.41; p = .355). Significant bleeds were infrequent and were not significantly different between the arms (intervention vs control, 1.9% vs 1.9%; p > .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% credible interval [CrI], 0.88-2.37; Pr [beta > 0], 93%; adjusted OR, 1.50; 95% CrI, 0.91-2.45; Pr [beta > 0], 95%) and median time to discharge to home was 2 days shorter (95% CrI, -4 to 0; 2% probability that it was worse). CONCLUSION: 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.