In recent years, numerous applications for artificial intelligence (AI) in cardiology have been found, due in part to large digitized data sets and the evolution of high-performance computing. In the ...discipline of cardiac electrophysiology (EP), a number of clinical, imaging, and electrical waveform data are considered in the diagnosis, prognostication, and management of arrhythmias, which lend themselves well to automation through AI. But equally relevant, AI offers a unique opportunity to discover novel EP concepts and improve clinical care through its inherent, hierarchical tenets of self-learning. In this review we focus on the application of AI in clinical EP and summarize state-of-the art, large, clinical studies in the following key domains: (1) electrocardiogram-based arrhythmia and disease classification; (2) atrial fibrillation source detection; (3) substrate and risk assessment for atrial fibrillation and ventricular tachyarrhythmias; and (4) predicting outcomes after cardiac resynchronization therapy. Many are small, single-centre, proof-of-concept investigations, but they still show ground-breaking performance of deep learning, a subdomain of AI, which surpasses traditional statistical analysis. Larger studies, for instance classifying arrhythmias from electrocardiogram recordings, have further provided external validation of their high accuracy. Ultimately, the performance of AI is dependent on the quality of the input data and the rigour of algorithm development. The field is still nascent and several barriers will need to be overcome, including prospective validation in large, well labelled data sets and more seamless information technology-based data collection/integration, before AI can be adopted into broader clinical EP practice. This review concludes with a discussion of these challenges and future work.
Ces dernières années, de nombreuses applications relatives à l'intelligence artificielle (IA) en cardiologie ont été découvertes, en partie grâce aux vastes ensembles de données numérisées et à l'évolution du calcul haute performance. Dans la discipline de l'électrophysiologie cardiaque (EP), un certain nombre de données cliniques, d'imagerie et de types d'ondes électriques sont prises en compte dans le diagnostic, le pronostic et la prise en charge des arythmies, qui se prêtent bien à l'automatisation par l'IA. Mais de façon toute aussi pertinente, l'IA offre une occasion unique de découvrir de nouveaux concepts associés à l'EP et d'améliorer les soins cliniques grâce à ses principes inhérents et hiérarchiques d'auto-apprentissage. Dans cet article de revue, nous nous concentrons sur l'application de l'IA à l'EP clinique et synthétisons l'état de l'art, les grandes études cliniques dans les domaines clés suivants : (1) classification des arythmies et des pathologies basée sur l'électrocardiogramme; (2) détection de la source de la fibrillation auriculaire; (3) évaluation du substrat et du risque de fibrillation auriculaire et de tachyarythmie ventriculaire; et (4) prédiction du pronostic après une thérapie de resynchronisation cardiaque. Il s'agit souvent de petites études, monocentriques, de validation du concept, mais elles n'en présentent pas moins les performances révolutionnaires de l'apprentissage profond, un sous-domaine de l'IA, qui surpasse l'analyse statistique traditionnelle. Des études de plus grande envergure, portant par exemple sur la classification des arythmies à partir d'enregistrements d'électrocardiogrammes, ont fourni une validation externe de leur grande précision. En définitive, les performances de l'IA dépendent de la qualité des données d'entrée et de la rigueur du développement des algorithmes. Ce domaine en est encore à ses débuts et plusieurs obstacles devront être surmontés, notamment la validation prospective dans de grands ensembles de données bien identifiées et une collecte/intégration des données plus transparente basée sur les technologies de l'information, avant que l'IA ne puisse être adoptée plus largement dans la pratique clinique de l'EP. Cette revue se termine par une discussion sur ces défis et les développements futurs.
Patients with end-stage renal disease (ESRD) are predisposed to heart rhythm disorders resulting in significant morbidity and mortality. Bradyarrhythmia appears to be more prevalent than ventricular ...tachyarrhythmias. There is also a high incidence of sudden cardiac death (SCD) in this group of patients, which cannot be explained only by traditional cardiac risk factors. The reported incidence and prevalence of arrhythmias and SCD is quite variable mainly because of the different study populations and recording techniques. The mechanism of SCD in patients with ESRD is also not clear. Although traditionally the thinking has been that ventricular arrhythmias are the main contributor to SCD, recent studies with implantable loop recorders have highlighted the role of bradyarrhythmias. The pathophysiological processes resulting in arrhythmia and SCD in patients with ESRD are unique. Some of the risk factors, including dialysate composition, timing, and frequency, are modifiable and hence provide an option for interventions to potentially reduce SCD. In addition, there might be a relationship with the timing of dialysis with SCD tending to occur during the long interdialytic period. Patients with ESRD have a higher likelihood of requiring pacemaker implantation; however, they also have a higher risk of device-related complications. The limited data available regarding the role of the implantable cardioverter defibrillator to prevent SCD in patients with ESRD have shown conflicting results. Future research is needed to develop appropriate risk stratification tools to identify patients who will benefit from such interventions and to assess their safety and efficacy.
Les patients atteints d’insuffisance rénale en phase terminale (IRPT) sont prédisposés à des troubles du rythme cardiaque qui entraînent une augmentation considérable de la morbidité et de la mortalité. La bradyarythmie semble avoir une plus grande prévalence que les tachyarythmies ventriculaires. Dans ce groupe de patients, on note également une forte incidence de la mort subite d’origine cardiaque (MSOC), qui ne peut être expliquée que par les facteurs de risque cardiaque traditionnels. L’incidence et la prévalence des cas déclarés d’arythmies et de MSOC sont très variables principalement en raison des différentes populations étudiées et des techniques d’enregistrement. On ne connaît pas non plus le mécanisme de la MSOC chez les patients atteints d’une IRPT. Bien que traditionnellement on ait pensé que les arythmies ventriculaires contribuaient principalement à la MSOC, de récentes études sur les enregistreurs en boucle implantables ont mis en évidence le rôle des bradyarythmies. Les processus physiopathologiques qui entraînent l’arythmie et la MSOC chez les patients atteints d’une IRPT sont uniques. Certains des facteurs de risque, dont la composition, le moment et la fréquence de la dialyse, sont modifiables et, par conséquent, offrent aux interventions la possibilité de réduire la MSOC. De plus, il se pourrait qu’il existe une relation entre le moment de la dialyse et la tendance de la MSOC à survenir pendant les longues périodes interdialytiques. Les patients atteints de IRPT sont plus susceptibles d’avoir besoin de l’implantation d’un stimulateur cardiaque. Cependant, ils sont également exposés à un plus grand risque de complications liées au dispositif. Les quelques données disponibles sur le rôle du défibrillateur cardioverteur implantable dans la prévention de la MSOC des patients atteints d’une IRPT ont montré des résultats contradictoires. Des recherches ultérieures sont nécessaires à l’élaboration d’outils appropriés de stratification du risque pour déterminer les patients qui bénéficieront de ces interventions et pour évaluer leur innocuité et leur efficacité.
•A unique high throughput multiresidue analysis method for 150 pesticides in tuber matrices.•Pressurized liquid extraction provided rapid, exhaustive and semi-automatic sample preparation.•The ...optimized rapid GC–MS/MS method offered selective and sensitive analysis with LOQs of 0.1–10ng/g.•The method was equivalent to conventional QuEChERS-based methods in terms of sensitivity and throughput.
Tuber crops substantially contribute to the food security in the developing countries. Often, their cultivation involves unregulated applications of pesticides, leading to MRL non-compliances. Despite their rising currency in international trade, there exist scarcely any methods for pesticide residue analysis in these matrices. Therefore, we developed a multi-residue method for simultaneous analysis of a diverse range of pesticides in tuber crops, based on pressurized liquid extraction by ethyl acetate, followed by selective identification and quantification of the residues using GC–MS selected reaction monitoring. The method was evaluated for 150 pesticides. Results showed that their limits of quantification were 0.1–10ng/g, with recoveries of 70–120%. When compared to the conventional analytical techniques, such as QuEChERS and buffered ethyl acetate extraction, this method provided superior performance in terms of precision, and recovery of the spiked and incurred residues with similar productivity. The method holds promise for commercial and regulatory residue analysis.
Atrial fibrillation (AF), the most common arrhythmia, is a growing epidemic with substantial morbidity and economic burden. Mechanisms underlying vulnerability to AF remain poorly understood, which ...contributes to the current lack of highly effective therapies. Recognizing mechanistic subtypes of AF may guide an individualized approach to patient management. Here, we describe a family with a previously unreported syndrome characterized by early-onset AF (age <35 years), conduction disease and signs of a primary atrial myopathy. Phenotypic penetrance was complete in all mutation carriers, although complete disease expressivity appears to be age-dependent. We show that this syndrome is caused by a novel, heterozygous p.Glu11Lys mutation in the atrial-specific myosin light chain gene MYL4. In zebrafish, mutant MYL4 leads to disruption of sarcomeric structure, atrial enlargement and electrical abnormalities associated with human AF. These findings describe the cause of a rare subtype of AF due to a primary, atrial-specific sarcomeric defect.
T-wave alternans (TWA), a marker of electrical instability, can be modulated by cardiac resynchronization therapy (CRT). The relationship between TWA and heart failure response to CRT has not been ...clearly defined.
In 40-patients (age 65±11 years, left ventricular ejection-fraction LVEF 23±7%), TWA was evaluated prospectively at median of 2 months (baseline) and 8 months (follow-up) post-CRT implant. TWA-magnitude (Valt >0μV, k≥3), its duration (d), and burden (Valt ·d) were quantified in moving 128-beat segments during incremental atrial (AAI, native-TWA) and atrio-biventricular (DDD-CRT) pacing. The immediate and long-term effect of CRT on TWA was examined. Clinical response to CRT was defined as an increase in LVEF of ≥5%. Native-TWA was clinically significant (Valt ≥1.9μV, k≥3) in 68% of subjects at baseline. Compared to native-TWA at baseline, DDD-CRT pacing at baseline and follow-up reduced the number of positive TWA segments, peak-magnitude, longest-duration and peak-burden of TWA (44±5 to 33±5 to 28±4%, p = 0.02 and 0.002; 5.9±0.8 to 4.1±0.7 to 3.8±0.7μV, p = 0.01 and 0.01; 97±9 to 76±8 to 67±8sec, p = 0.004 and <0.001; and 334±65 to 178±58 to 146±54μV.sec, p = 0.01 and 0.004). In addition, the number of positive segments and longest-duration of native-TWA diminished during follow-up (44±5 to 35±6%, p = 0.044; and 97±9 to 81±9sec, p = 0.02). Clinical response to CRT was observed in 71% of patients; the reduction in DDD-CRT paced TWA both at baseline and follow-up was present only in responders (interaction p-values <0.1).
Long-term CRT reduces the prevalence and magnitude of TWA. This CRT induced beneficial electrical remodeling is a marker of clinical response after CRT.
Although QRS duration (QRSd) is an important determinant of cardiac resynchronization therapy (CRT) response, non-responder rates remain high. QRS fragmentation can also reflect electrical ...dyssynchrony. We hypothesized that quantification of abnormal QRS peaks (QRSp) would predict CRT response.
Forty-seven CRT patients (left ventricular ejection fraction = 23±7%) were prospectively studied. Digital 12-lead ECGs were recorded during native rhythm at baseline and 6 months post-CRT. For each precordial lead, QRSp was defined as the total number of peaks detected on the unfiltered QRS minus those detected on a smoothed moving average template QRS. CRT response was defined as >5% increase in left ventricular ejection fraction post-CRT.
Sixty-percent of patients responded to CRT. Baseline QRSd was similar in CRT responders and non-responders, and did not change post-CRT regardless of response. Baseline QRSp was greater in responders than non-responders (9.1±3.5 vs. 5.9±2.2, p = 0.001) and decreased in responders (9.2±3.6 vs. 7.9±2.8, p = 0.03) but increased in non-responders (5.5±2.3 vs. 7.5±2.8, p = 0.049) post-CRT. In multivariable analysis, QRSp was the only independent predictor of CRT response (Odds Ratio 95% Confidence Interval: 1.5 1.1-2.1, p = 0.01). ROC analysis revealed QRSp (area under curve = 0.80) to better discriminate response than QRSd (area under curve = 0.67). Compared to QRSd ≥150ms, QRSp ≥7 identified response with similar sensitivity but greater specificity (74 vs. 32%, p<0.05). Amongst patients with QRSd <150ms, more patients with QRSp ≥7 responded than those with QRSp <7 (75 vs. 0%, p<0.05).
Our novel automated QRSp metric independently predicts CRT response and decreases in responders. Electrical dyssynchrony assessed by QRSp may improve CRT selection and track structural remodeling, especially in those with QRSd <150ms.
The paper describes a computational study and an experimental investigation of aqueous potassium carbonate droplets in superheated steam flow for potential applications in mitigation of superheated ...geothermal steam. The computational model included the boiling point elevation due to the droplet salt concentration as well as other concentration-dependent physical properties of the salt solution. Various phenomena involved in the process, such as breakup, transport, heat transfer, boiling and coupling between droplet and steam phase were taken into account. To validate the simulation results from the model, a laboratory scale experimental setup was built and experiments were carried out for different salt solution injection concentrations upto 5.27 mol kg
−1
in superheated steam at 421 K. Results from the simulation were in accordance with experimental measurements, showing an increase in boiling point elevation with an increase in injection salt solution concentration. The temperature values obtained from the simulation are slightly higher than those measured with an average deviation of 1.5 K, which can be explained by a small degree of heat loss from the apparatus not accounted for in the model. Results from the simulation for concentration were also in accordance with the experimental measurement, showing an increase in concentration of the salt solution droplets, collected at the separator bottom. The concentration values obtained from the simulation are lower than that from the measurement with an average deviation of 20%.
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