Insights into functional mitral regurgitation using the average pixel intensity method

Previously we introduced and validated the average pixel intensity (API) method for grading mitral regurgitation (MR) in a heterogeneous MR population. We now investigated the feasibility and added value of the API method more specifically in patients with functional MR (FMR). We consecutively enrolled 283 patients with pure FMR. Transthoracic echocardiography was performed and MR was assessed using the API method and guideline-recommended parameters, including color Doppler, vena contracta width (VCW) and proximal isovelocity surface area (PISA)-based methods. The API method had an applicability of 98% in this FMR cohort, which was significantly higher than VCW (84%) and PISA-based methods (75%). Overall, the API method had significant correlations with direct parameters of FMR severity, ejection fraction, atrial and ventricular dimensions, pulmonary pressures and New York Heart Association class. Analysis of the API dynamics during MR revealed a typical pattern with early and late systolic peaks in API and a midsystolic nadir, which matched the temporal changes of the effective regurgitant orifice (ERO) during FMR. Based on ROC curves of established FMR severity cut-offs, an API value of 125 au was considered the optimal cut-off to determine severe MR. Interestingly, this API severity cut-off is similar to the API severity cut-off for MR in degenerative MR (DMR), despite different EROA/RV cut-offs in current ESC guidelines for FMR and DMR. The API method is an easy, fast and feasible parameter for grading FMR and may complement the multiparametric assessment of FMR in daily clinical practice

Directed networks as a novel way to describe and analyze cardiac excitation : directed graph mapping

Networks provide a powerful methodology with applications in a variety of biological, technological and social systems such as analysis of brain data, social networks, internet search engine algorithms, etc. To date, directed networks have not yet been applied to characterize the excitation of the human heart. In clinical practice, cardiac excitation is recorded by multiple discrete electrodes. During (normal) sinus rhythm or during cardiac arrhythmias, successive excitation connects neighboring electrodes, resulting in their own unique directed network. This in theory makes it a perfect fit for directed network analysis. In this study, we applied directed networks to the heart in order to describe and characterize cardiac arrhythmias. Proof-of-principle was established using in-silico and clinical data. We demonstrated that tools used in network theory analysis allow determination of the mechanism and location of certain cardiac arrhythmias. We show that the robustness of this approach can potentially exceed the existing state-of-the art methodology used in clinics. Furthermore, implementation of these techniques in daily practice can improve the accuracy and speed of cardiac arrhythmia analysis. It may also provide novel insights in arrhythmias that are still incompletely understood

Feasibility and performance of a device for automatic self-detection of symptomatic acute coronary artery occlusion in outpatients with coronary artery disease : a multicentre observational study

Background Time delay between onset of symptoms and seeking medical attention is a major determinant of mortality and morbidity in patients with acute coronary artery occlusion. Response time might be reduced by reliable self-detection. We aimed to formally assess the proof-of-concept and accuracy of self-detection of acute coronary artery occlusion by patients during daily life situations and during the very early stages of acute coronary artery occlusion. Methods In this multicentre, observational study, we tested the operational feasibility, specificity, and sensitivity of our RELF method, a three-lead detection system with an automatic algorithm built into a mobile handheld device, for detection of acute coronary artery occlusion. Patients were recruited continuously by physician referrals from three Belgian hospitals until the desired sample size was achieved, had been discharged with planned elective percutaneous coronary intervention, and were able to use a smartphone; they were asked to perform random ambulatory selfrecordings for at least 1 week. A similar self-recording was made before percutaneous coronary intervention and at 60 s of balloon occlusion. Patients were clinically followed up until 1 month after discharge. We quantitatively assessed the operational feasibility with an automated dichotomous quality check of self-recordings. Performance was assessed by analysing the receiver operator characteristics of the ST difference vector magnitude. This trial is registered with ClinicalTrials.gov, number NCT02983396. Findings From Nov 18, 2016, to April 25, 2018, we enrolled 64 patients into the study, of whom 59 (92%) were eligible for self-applications. 58 (91%) of 64 (95% CI 81.0-95.6) patients were able to perform ambulatory self-recordings. Of all 5011 self-recordings, 4567 (91%) were automatically classified as successful within 1 min. In 65 balloon occlusions, 63 index tests at 60 s of occlusion in 55 patients were available. The mean specificity of daily life recordings was 0.96 (0.95-0.97). The mean false positive rate during daily life conditions was 4.19% (95% CI 3.29-5.10). The sensitivity for the target conditions was 0.87 (55 of 63; 95% CI 0.77-0.93) for acute coronary artery occlusion, 0.95 (54 of 57; 0.86-0.98) for acute coronary artery occlusion with electrocardiogram (ECG) changes, and 1.00 (35 of 35) for acute coronary artery occlusion with ECG changes and ST-segment elevation myocardial infarction criteria (STEMI). The index test was more sensitive to detect a 60 s balloon occlusion than the STEMI criteria on 12-lead ECG (87% vs 56%; p<0.0001). The proportion of total variation in study estimates due to heterogeneity between patients (I-2) was low (12.6%). The area under the receiver operator characteristics curve was 0.973 (95% CI 0.956-0.990) for acute coronary artery occlusion at different cutoff values of the magnitude of the ST difference vector. No patients died during the study. Interpretation Self-recording with our RELF device is feasible for most patients with coronary artery disease. The sensitivity and specificity for automatic detection of the earliest phase of acute coronary artery occlusion support the concept of our RELF device for patient empowerment to reduce delay and increase Survival without overloading emergency services. Copyright (C) 2019 The Author(s). Published by Elsevier Ltd

Prospective evaluation of entrainment mapping as an adjunct to new-generation high-density activation mapping systems of left atrial tachycardias

BACKGROUND Identification of atrial tachycardia (AT) mechanism remains challenging. OBJECTIVE We sought to investigate the added value of entrainment maneuvers (EM) when using new high-density activation mapping (HDAM) technologies for the identification of complex left ATs. METHODS Thirty-six consecutive complex ATs occurring after ablation of persistent atrial fibrillation were prospectively analyzed. The AT mechanism was diagnosed in 2 steps by 2 experts: (1) based on H DAM only (Coherent module, CARTO, Biosense Webster Inc., Irvine, CA) and (2) with additional analysis from EM. RESULTS EM resulted in atrial fibrillation in 1 patient, who was excluded from the analysis. Ten of 11 single loop macroreentries identified by HDAM were confirmed by EM. Only 4 of 14 double loop macroreentries identified by HDAM wereconfirmed by EM (in 10 patients, EM unmasked passive activation of one of the visual cir- cuits). One sole microreentry circuit identified by HDAM was confirmed by EM. A combination of macro- and microreentry circuits was visualized in 3 ATs using H DAM. However, EM revealed passive activation of the visual macroreentrant loop in 2 of these 3 cases. By using HDAM in 6 of 35 ATs (17%), no univocal mechanism could be identified, whereas EM finally enabled the diagnosis of 5 microreentry circuits and 1 macroreentrant AT. All the diagnoses made from EM in addition to HDAM were confirmed by ablation. CONCLUSION Entrainment maneuvers are still useful during mapping of complex left ATs, mostly to differentiate active from passive macroreentrant loops and to demonstrate microreentry circuits

Personalized assessment of the cumulative complication risk of the atrial fibrillation ablation track: The AF-TRACK calculator

Atrial fibrillation (AF) ablation strategy is associated with a non-negligible risk of complications and often requires repeat procedures (AF ablation track), implying repetitive exposure to procedural risk.The purpose of this study was to develop and validate a model to estimate individualized cumulative risk of complications in patients undergoing the AF ablation track (Atrial Fibrillation TRAck Complication risK [AF-TRACK] calculator).The model was derived from a multicenter cohort including 3762 AF ablation procedures in 2943 patients. A first regression model was fitted to predict the propensity for repeat ablation. The AF-TRACK calculator computed the risk of AF ablation track complications, considering the propensity for repeat ablation. Internal (cross-validation) and external (independent cohort) validation were assessed for discrimination capacity (area under the curve [AUC]) and goodness of fit (Hosmer-Lemeshow [HL] test).Complications (N = 111) occurred in 3.7% of patients (2.9% of procedures). Predictors included female sex, heart failure, sleep apnea syndrome, and repeat procedures. The model showed fair discrimination capacity to predict complications (AUC 0.61 [0.55-0.67]) and likelihood of repeat procedure (AUC 0.62 [0.60-0.64]), with good calibration (HL χ2 12.5; P = .13). The model maintained adequate discrimination capacity (AUC 0.67 [0.57-0.77]) and calibration (HL χ2 5.6; P = .23) in the external validation cohort. The validated model was used to create the Web-based AF-TRACK calculator.The proposed risk model provides individualized estimates of the cumulative risk of complications of undergoing the AF ablation track. The AF-TRACK calculator is a validated, easy-to-use, Web-based clinical tool to calibrate the risk-to-benefit ratio of this treatment strategy.© 2022 Heart Rhythm Society. Published by Elsevier Inc

What is going on around here? Intolerance of uncertainty predicts threat generalization

Attending to stimuli that share perceptual similarity to learned threats is an adaptive strategy. However, prolonged threat generalization to cues signalling safety is considered a core feature of pathological anxiety. One potential factor that may sustain over-generalization is sensitivity to future threat uncertainty. To assess the extent to which Intolerance of Uncertainty (IU) predicts threat generalization, we recorded skin conductance in 54 healthy participants during an associative learning paradigm, where threat and safety cues varied in perceptual similarity. Lower IU was associated with stronger discrimination between threat and safety cues during acquisition and extinction. Higher IU, however, was associated with generalized responding to threat and safety cues during acquisition, and delayed discrimination between threat and safety cues during extinction. These results were specific to IU, over and above other measures of anxious disposition. These findings highlight: (1) a critical role of uncertainty-based mechanisms in threat generalization, and (2) IU as a potential risk factor for anxiety disorder development

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries