¿Qué hay de nuevo en el diagnóstico de amiloidosis? / What is new in diagnosis of amyloidosis?

La amiloidosis siempre ha representado un desafío diagnóstico. En el año 2020, el Grupo de Estudio de Amiloidosis (GEA), confeccionó la Guía de Práctica Clínica para el Diagnóstico de Amiloidosis. Nuevas líneas de investigación se han desarrollado posteriormente. Esta revisión narrativa tiene como intención explorar el estado del arte en el diagnóstico de la amiloidosis. En pacientes con amiloidosis se recomienda la tipificación de la proteína mediante espectrometría de masa, técnica de difícil ejecución por requerir de microdisectores láser para la preparación de la muestra. Algunas publicaciones recientes proponen otros métodos para obtener la muestra de amiloide que se va a analizar, permitiendo prescindir de la microdisección. Por otra parte, en pacientes con Amiloidosis ATTR confirmada, la recomendación de secuenciar el gen amiloidogénico se encontraba destinada a los casos sospechosos de ATTR hereditaria (ATTRv,), pero actualmente esta se ha extendido a todos los pacientes sin importar la edad. En lo que respecta a los estudios complementarios orientados al diagnóstico de compromiso cardíaco, se ha propuesto el uso de la inteligencia artificial para su interpretación, permitiendo la detección temprana de la enfermedad y el correcto diagnóstico diferencial. Para el diagnóstico de neuropatía, las últimas publicaciones proponen el uso de la cadena ligera de neurofilamento sérica, que también podría resultar un indicador útil para seguimiento. Finalmente, con referencia a la amiloidosis AL, la comunidad científica se encuentra interesada en definir qué características determinan el carácter amiloidogénico de las cadenas livianas. La N-glicosilación de dichas proteínas impresiona ser uno de los determinantes en cuestión. (AU)

Amyloidosis has always represented a diagnostic challenge. In 2020, the Amyloidosis Study Group (ASG) developed the "Clinical Practice Guideline for the Diagnosis of Amyloidosis". New lines of research have subsequently emerged. This narrative review aims to explore the state of the art in the diagnosis of amyloidosis diagnosis. In patients with amyloidosis, protein typing by mass spectrometry is recommended, a technique hard to perform because it requires laser microdissection for sample preparation. Recent publications propose other methods to obtain the amyloid sample to be analyzed, making it possible to dispense with microdissection. On the other hand, in patients with confirmed TTR amyloidosis (aTTR), the recommendation to sequence the amyloidogenic gene was intended for suspected cases of hereditary aTTR but has now been extended to all patients regardless of age. (AU)

Elaboração de algoritmo para interpretação rápidadas principais arritmias cardíacas no eletrocardiograma / Algorithm Elaboration For Quick Interpretation Of The Main Heart Arrythmias In The Electrocardiogram

Objetivo: relatar a elaboração de um algoritmo para facilitar a interpretação rápida das principais arritmias cardíacas no eletrocardiograma. Método: estudo descritivo, exploratório, com abordagem qualitativa, do tipo relato de experiência, realizado mediante um projeto de intervenção em educação em saúde durante o ano de 2021. Resultados: a elaboração do algoritmo denominado Scaritmo contribuiu para sistematizar as etapas de identificação de arritmias cardíacas, favorecendo o processo didático e aprendizado dos estudantes e otimizando a interpretação rápida do eletrocardiograma. Conclusão: o uso do algoritmo Scaritmo permite a sistematização teórico-prática das etapas necessárias para a interpretação do eletrocardiograma tornando sua avaliação mais didática e assertiva pelo examinador em treinamento.(AU)

Objective: to report the development of an algorithm to facilitate the rapid interpretation of the main cardiac arrhythmias in electrocardiogram. Method: a descriptive, exploratory study with qualitative approach, of experience report type, conducted through an intervention project in health education during the year 2021. Results: The development of the algorithm called Scaritmo contributed to systematize the steps of cardiac arrhythmia identification, favoring the didactic process and student learning, and optimizing the rapid interpretation of the electrocardiogram. Conclusion: The use of the Scaritm algorithm allows the theoretical and practical systematization of the steps necessary for the interpretation of electrocardiograms, making its evaluation more didactic and assertive by the examiner in training.(AU)

Objetivo: relatar el desarrollo de un algoritmo para facilitar la interpretación rápida de las principales arritmias cardíacas en electrocardiograma. Método: estudio descriptivo, exploratorio, con abordaje cualitativo, de tipo relato de experiencia, realizado a través de un proyecto de intervención en educación para la salud durante el año 2021. Resultados: el desarrollo del algoritmo denominado Scaritmo contribuyó para sistematizar los pasos de identificación de arritmias cardíacas, favoreciendo el proceso didáctico y el aprendizaje de los alumnos y optimizando la rápida interpretación del electrocardiograma. Conclusión: El uso del algoritmo Scaritmo permite la sistematización teórica y práctica de los pasos necesarios para la interpretación del electrocardiograma, tornando su evaluación más didáctica y asertiva por el examinador en formación.(AU)

Como eu faço no Coração de Atleta: avaliação dos diferentes tipos de adaptação ao exercício / My approach to "Athlete'S Heart": evaluation of the different types of adaptation to exercise

A prática regular de esportes pode induzir adaptações no coração, sendo essa condição comumente chamada de "coração de atleta". As alterações observadas incluem dilatação das câmaras cardíacas, aumento da espessura miocárdica, melhora do enchimento ventricular, aumento da trabeculação do ventrículo esquerdo (VE), dilatação da veia cava inferior, entre outras. Essas alterações também podem ser observadas em algumas doenças cardíacas, como cardiomiopatia (CMP) dilatada, hipertrófica e outras. Dessa forma, os exames de imagem cardíaca são fundamentais na identificação dessas alterações e na diferenciação entre o "coração de atleta" e uma possível cardiopatia.(AU)

Exercise-induced adaptation may occur in amateur and professional athletes. This condition is commonly named "athlete's heart". The alterations observed include dilation of the heart chambers, increased myocardial thickness, improved ventricular filling, increased left ventricular trabeculation, dilation of the inferior vena cava, among others. These changes can also be observed in some heart diseases, such as dilated, hypertrophic and other cardiomyopathies (CMP). Thus, cardiac imaging tests are fundamental in identifying these alterations and in differentiating between "athlete's heart" and possible heart disease. (AU)

Summary of evidence for threshold setting of multi-parameter electrocardiograph monitor in intensive care unit / 中华危重病急救医学

OBJECTIVE@#To retrieve the evidence for threshold setting of multi-parameter electrocardiograph (ECG) monitors in intensive care unit (ICU), and summarize the best evidence.@*METHODS@#After literature retrieval, clinical guidelines, expert consensus, evidence summary and systematic review that met the requirements were screened. Guidelines were evaluated by the appraisal of guidelines for research and evaluation II (AGREE II), expert consensus and systematic review were evaluated by the Australian JBI evidence-based health care center authenticity evaluation tool, and evidence summary was evaluated by the CASE checklist. High-quality literature was selected to extract evidence related to the use and setup of multi-parameter ECG monitors in the ICU.@*RESULTS@#A total of 19 literatures were included, including 7 guidelines, 2 expert consensus, 8 systematic reviews, 1 evidence summary, and 1 national industry standard. After evidence extraction, translation, proofreading and summary, a total of 32 pieces of evidence were integrated. The included evidence involved the environmental preparation for the application of the ECG monitor, the electrical requirements of the ECG monitor, ECG monitor use process, ECG monitor alarm setting principles, ECG monitor alarm heart rate or heart rhythm monitoring setting, ECG monitor alarm blood pressure monitoring setting, ECG monitor alarm respiratory and blood oxygen saturation threshold setting, alarm delay warning time setting, adjusting alarm setting method, evaluating alarm setting time, improving the comfort of monitoring patients, reducing nuisance alarm report the occurrence, alarm priority processing, alarm intelligent processing and so on.@*CONCLUSIONS@#This summary of evidence involves many aspects of the setting and application of ECG monitor. According to the latest guidelines and expert consensus, it is updated and revised to guide healthcare workers to monitor patients more scientifically and safely, and aims to ensure patient safety.

An Atrial Fibrillation Classification Method Study Based on BP Neural Network and SVM / 中国医疗器械杂志

Atrial fibrillation is a common arrhythmia, and its diagnosis is interfered by many factors. In order to achieve applicability in diagnosis and improve the level of automatic analysis of atrial fibrillation to the level of experts, the automatic detection of atrial fibrillation is very important. This study proposes an automatic detection algorithm for atrial fibrillation based on BP neural network (back propagation network) and support vector machine (SVM). The electrocardiogram (ECG) segments in the MIT-BIH atrial fibrillation database are divided into 10, 32, 64, and 128 heartbeats, respectively, and the Lorentz value, Shannon entropy, K-S test value and exponential moving average value are calculated. These four characteristic parameters are used as the input of SVM and BP neural network for classification and testing, and the label given by experts in the MIT-BIH atrial fibrillation database is used as the reference output. Among them, the use of atrial fibrillation in the MIT-BIH database, the first 18 cases of data are used as the training set, and the last 7 cases of data are used as the test set. The results show that the accuracy rate of 92% is obtained in the classification of 10 heartbeats, and the accuracy rate of 98% is obtained in the latter three categories. The sensitivity and specificity are both above 97.7%, which has certain applicability. Further validation and improvement in clinical ECG data will be done in next study.

Intelligent Electrocardiogram Analysis in Medicine: Data, Methods, and Applications / 中国医学科学杂志(英文版)

Electrocardiogram (ECG) is a low-cost, simple, fast, and non-invasive test. It can reflect the heart's electrical activity and provide valuable diagnostic clues about the health of the entire body. Therefore, ECG has been widely used in various biomedical applications such as arrhythmia detection, disease-specific detection, mortality prediction, and biometric recognition. In recent years, ECG-related studies have been carried out using a variety of publicly available datasets, with many differences in the datasets used, data preprocessing methods, targeted challenges, and modeling and analysis techniques. Here we systematically summarize and analyze the ECG-based automatic analysis methods and applications. Specifically, we first reviewed 22 commonly used ECG public datasets and provided an overview of data preprocessing processes. Then we described some of the most widely used applications of ECG signals and analyzed the advanced methods involved in these applications. Finally, we elucidated some of the challenges in ECG analysis and provided suggestions for further research.

Electrocardiogram signal classification based on fusion method of residual network and self-attention mechanism / 生物医学工程学杂志

In the diagnosis of cardiovascular diseases, the analysis of electrocardiogram (ECG) signals has always played a crucial role. At present, how to effectively identify abnormal heart beats by algorithms is still a difficult task in the field of ECG signal analysis. Based on this, a classification model that automatically identifies abnormal heartbeats based on deep residual network (ResNet) and self-attention mechanism was proposed. Firstly, this paper designed an 18-layer convolutional neural network (CNN) based on the residual structure, which helped model fully extract the local features. Then, the bi-directional gated recurrent unit (BiGRU) was used to explore the temporal correlation for further obtaining the temporal features. Finally, the self-attention mechanism was built to weight important information and enhance model's ability to extract important features, which helped model achieve higher classification accuracy. In addition, in order to mitigate the interference on classification performance due to data imbalance, the study utilized multiple approaches for data augmentation. The experimental data in this study came from the arrhythmia database constructed by MIT and Beth Israel Hospital (MIT-BIH), and the final results showed that the proposed model achieved an overall accuracy of 98.33% on the original dataset and 99.12% on the optimized dataset, which demonstrated that the proposed model can achieve good performance in ECG signal classification, and possessed potential value for application to portable ECG detection devices.

An image classification method for arrhythmias based on Gramian angular summation field and improved Inception-ResNet-v2 / 生物医学工程学杂志

Arrhythmia is a significant cardiovascular disease that poses a threat to human health, and its primary diagnosis relies on electrocardiogram (ECG). Implementing computer technology to achieve automatic classification of arrhythmia can effectively avoid human error, improve diagnostic efficiency, and reduce costs. However, most automatic arrhythmia classification algorithms focus on one-dimensional temporal signals, which lack robustness. Therefore, this study proposed an arrhythmia image classification method based on Gramian angular summation field (GASF) and an improved Inception-ResNet-v2 network. Firstly, the data was preprocessed using variational mode decomposition, and data augmentation was performed using a deep convolutional generative adversarial network. Then, GASF was used to transform one-dimensional ECG signals into two-dimensional images, and an improved Inception-ResNet-v2 network was utilized to implement the five arrhythmia classifications recommended by the AAMI (N, V, S, F, and Q). The experimental results on the MIT-BIH Arrhythmia Database showed that the proposed method achieved an overall classification accuracy of 99.52% and 95.48% under the intra-patient and inter-patient paradigms, respectively. The arrhythmia classification performance of the improved Inception-ResNet-v2 network in this study outperforms other methods, providing a new approach for deep learning-based automatic arrhythmia classification.

Suxiao Jiuxin Pills Prevent Ventricular Fibrillation from Inhibiting L-type Calcium Currents CaV1.2 in vivo and in vitro / 中国结合医学杂志

OBJECTIVE@#To investigate whether Suxiao Jiuxin Pills (SJP), a Chinese herbal remedy, is an anti-ventricular fibrillation (VF) agent.@*METHODS@#VF was induced by isoproterenolol (ISO) intraperitoneal injection followed by electrical pacing in mice and rabbits. The effects of SJP on the L-type calcium channel current (CaV1.2), voltage-dependent sodium channel current (INa), rapid and slow delayed rectifier potassium channel current (IKr and IKs, respectively) were studied by whole-cell patch-clamp method. Computer simulation was implemented to incorporate the experimental data of SJP effects on the CaV1.2 current into the action potential (AP) and pseudo-electrocardiography (pseudo-ECG) models.@*RESULTS@#SJP prevented VF induction and reduced VF durations significantly in mice and rabbits. Patch-clamp experiments revealed that SJP decreased the peak amplitude of the CaV1.2 current with a half maximal concentration (IC50) value of 16.9 mg/L (SJP-30 mg/L, -32.8 ± 6.1 pA; Verapamil, -16.2 ±1.8 pA; vs. control, -234.5 ±16.7 pA, P<0.01, respectively). The steady-state activation curve, inactivation curve, and the recovery from inactivation of the CaV1.2 current were not shifted significantly. Specifically, SJP did not altered INa, IKr, and IKs currents significantly (SJP vs. control, P>0.05). Computer simulation showed that SJP-reduced CaV1.2 current shortened the AP duration, transiting VF into sinus rhythm in pseudo-ECG.@*CONCLUSION@#SJP reduced VF via inhibiting the CaV1.2 current with in vivo, in vitro, and in silico studies, which provide experimental basis for SJP anti-VF clinical application.

Anesthesia Depth Monitoring Based on Anesthesia Monitor with the Help of Artificial Intelligence / 中国医疗器械杂志

OBJECTIVE@#To use the low-cost anesthesia monitor for realizing anesthesia depth monitoring, effectively assist anesthesiologists in diagnosis and reduce the cost of anesthesia operation.@*METHODS@#Propose a monitoring method of anesthesia depth based on artificial intelligence. The monitoring method is designed based on convolutional neural network (CNN) and long and short-term memory (LSTM) network. The input data of the model include electrocardiogram (ECG) and pulse wave photoplethysmography (PPG) recorded in the anesthesia monitor, as well as heart rate variability (HRV) calculated from ECG, The output of the model is in three states of anesthesia induction, anesthesia maintenance and anesthesia awakening.@*RESULTS@#The accuracy of anesthesia depth monitoring model under transfer learning is 94.1%, which is better than all comparison methods.@*CONCLUSIONS@#The accuracy of this study meets the needs of perioperative anesthesia depth monitoring and the study reduces the operation cost.

Fetal electrocardiogram signal extraction and analysis method combining fast independent component analysis algorithm and convolutional neural network / 生物医学工程学杂志

Fetal electrocardiogram (ECG) signals provide important clinical information for early diagnosis and intervention of fetal abnormalities. In this paper, we propose a new method for fetal ECG signal extraction and analysis. Firstly, an improved fast independent component analysis method and singular value decomposition algorithm are combined to extract high-quality fetal ECG signals and solve the waveform missing problem. Secondly, a novel convolutional neural network model is applied to identify the QRS complex waves of fetal ECG signals and effectively solve the waveform overlap problem. Finally, high quality extraction of fetal ECG signals and intelligent recognition of fetal QRS complex waves are achieved. The method proposed in this paper was validated with the data from the PhysioNet computing in cardiology challenge 2013 database of the Complex Physiological Signals Research Resource Network. The results show that the average sensitivity and positive prediction values of the extraction algorithm are 98.21% and 99.52%, respectively, and the average sensitivity and positive prediction values of the QRS complex waves recognition algorithm are 94.14% and 95.80%, respectively, which are better than those of other research results. In conclusion, the algorithm and model proposed in this paper have some practical significance and may provide a theoretical basis for clinical medical decision making in the future.

Latest incidence and electrocardiographic predictors of atrial fibrillation: a prospective study from China / 中华医学杂志(英文版)

BACKGROUND@#China bears the biggest atrial fibrillation (AF) burden in the world. However, little is known about the incidence and predictors of AF. This study aimed to investigate the current incidence of AF and its electrocardiographic (ECG) predictors in general community individuals aged over 60 years in China.@*METHODS@#This was a prospective cohort study, recruiting subjects who were aged over 60 years and underwent annual health checkups from April to July 2015 in four community health centers in Songjiang District, Shanghai, China. The subjects were then followed up from 2015 to 2019 annually. Data on sociodemographic characteristics, medical history, and the resting 12-lead ECG were collected. Kaplan-Meier curve was used for showing the trends in AF incidence and calculating the predictors of AF. Associations of ECG abnormalities and AF incidence were examined using Cox proportional hazard models.@*RESULTS@#This study recruited 18,738 subjects, and 351 (1.87%) developed AF. The overall incidence rate of AF was 5.2/1000 person-years during an observation period of 67,704 person-years. Multivariable Cox regression analysis indicated age (hazard ratio [HR], 1.07; 95% confidence interval [CI]: 1.06-1.09; P < 0.001), male (HR, 1.30; 95% CI: 1.05-1.62; P = 0.018), a history of hypertension (HR, 1.55; 95% CI: 1.23-1.95; P < 0.001), a history of cardiac diseases (HR, 3.23; 95% CI: 2.34-4.45; P < 0.001), atrial premature complex (APC) (HR, 2.82; 95% CI: 2.17-3.68; P < 0.001), atrial flutter (HR, 18.68; 95% CI: 7.37-47.31; P < 0.001), junctional premature complex (JPC) (HR, 3.57; 95% CI: 1.59-8.02; P = 0.002), junctional rhythm (HR, 18.24; 95% CI: 5.83-57.07; P < 0.001), ventricular premature complex (VPC) (HR, 1.76; 95% CI: 1.13-2.75, P = 0.012), short PR interval (HR, 5.49; 95% CI: 1.36-22.19; P = 0.017), right atrial enlargement (HR, 6.22; 95% CI: 1.54-25.14; P = 0.010), and pacing rhythm (HR, 3.99; 95% CI: 1.57-10.14; P = 0.004) were independently associated with the incidence of AF.@*CONCLUSIONS@#The present incidence of AF was 5.2/1000 person-years in the studied population aged over 60 years in China. Among various ECG abnormalities, only APC, atrial flutter, JPC, junctional rhythm, short PR interval, VPC, right atrial enlargement, and pacing rhythm were independently associated with AF incidence.

Approach to bradyarrhythmias: A proposed algorithm

Bradyarrhythmias are commonly encountered in clinical practice. While there are several electrocardiographic criteria and algorithms for tachyarrhythmias, there is no algorithm for bradyarrhythmias to the best of our knowledge. In this article, we propose a diagnostic algorithm that uses simple concepts: (1) the presence or absence of P waves, (2) the relationship between the number of P waves and QRS complexes, and (3) the regularity of time intervals (PP, PR and RR intervals). We believe this straightforward, stepwise method provides a structured and thorough approach to the wide differential diagnosis of bradyarrhythmias, and in doing so, reduces misdiagnosis and mismanagement.

Association between clinical phenotypes of hypertrophic cardiomyopathy and Ca2+ gene variation gene variation / 中华心血管病杂志

Objective: To observe the association between clinical phenotypes of hypertrophic cardiomyopathy (HCM) patients and a rare calcium channel and regulatory gene variation (Ca2+ gene variation) and to compare clinical phenotypes of HCM patients with Ca2+ gene variation, a single sarcomere gene variation and without gene variation and to explore the influence of rare Ca2+ gene variation on the clinical phenotypes of HCM. Methods: Eight hundred forty-two non-related adult HCM patients diagnosed for the first time in Xijing Hospital from 2013 to 2019 were enrolled in this study. All patients underwent exon analyses of 96 hereditary cardiac disease-related genes. Patients with diabetes mellitus, coronary artery disease, post alcohol septal ablation or septal myectomy, and patients who carried sarcomere gene variation of uncertain significance or carried>1 sarcomere gene variation or carried>1 Ca2+ gene variation, with HCM pseudophenotype or carrier of ion channel gene variations other than Ca2+ based on the genetic test results were excluded. Patients were divided into gene negative group (no sarcomere or Ca2+ gene variants), sarcomere gene variation group (only 1 sarcomere gene variant) and Ca2+ gene variant group (only 1 Ca2+ gene variant). Baseline data, echocardiography and electrocardiogram data were collected for analysis. Results: A total of 346 patients were enrolled, including 170 patients without gene variation (gene negative group), 154 patients with a single sarcomere gene variation (sarcomere gene variation group) and 22 patients with a single rare Ca2+ gene variation (Ca2+ gene variation group). Compared with gene negative group, patients in Ca2+ gene variation group had higher blood pressure and higher percentage of family history of HCM and sudden cardiac death (P<0.05); echocardiographic results showed that patients in Ca2+ gene variation group had thicker ventricular septum ((23.5±5.8) mm vs. (22.3±5.7) mm, P<0.05); electrocardiographic results showed that patients in Ca2+ gene variation group had prolonged QT interval ((416.6±23.1) ms vs. (400.6±47.2) ms, P<0.05) and higher RV5+SV1 ((4.51±2.26) mv vs. (3.50±1.65) mv, P<0.05). Compared with sarcomere gene variation group, patients in Ca2+ gene variation group had later onset age and higher blood pressure (P<0.05); echocardiographic results showed that there was no significant difference in ventricular septal thickness between two groups; patients in Ca2+ gene variation group had lower percentage of left ventricular outflow tract pressure gradient>30 mmHg (1 mmHg=0.133 kPa, 22.8% vs. 48.1%, P<0.05) and the lower early diastolic peak velocity of the mitral valve inflow/early diastolic peak velocity of the mitral valve annulus (E/e') ratio ((13.0±2.5) vs. (15.9±4.2), P<0.05); patients in Ca2+ gene variation group had prolonged QT interval ((416.6±23.1) ms vs. (399.0±43.0) ms, P<0.05) and lower percentage of ST segment depression (9.1% vs. 40.3%, P<0.05). Conclusion: Compared with gene negative group, the clinical phenotype of HCM is more severe in patients with rare Ca2+ gene variation; compared with patients with sarcomere gene variation, the clinical phenotype of HCM is milder in patients with rare Ca2+ gene variation.

A single-centre experience of His bundle pacing without electrophysiological mapping system: implant success rate, safety, pacing characteristics and one-year follow up

INTRODUCTION@#Despite the challenges related to His bundle pacing (HBP), recent data suggest an improved success rate with experience. As a non-university, non-electrophysiology specialised centre in Singapore, we report our experiences in HBP using pacing system analyser alone.@*METHODS@#Data of 28 consecutive patients who underwent HBP from August 2018 to February 2019 was retrospectively obtained. The clinical and technical outcomes of these patients were compared between two timeframes of three months each. Patients were followed up for 12 months.@*RESULTS@#Immediate technical success was achieved in 21 (75.0%) patients (mean age 73.3 ± 10.7 years, 47.6% female). The mean left ventricular ejection fraction was 53.9% ± 12.1%. The indications for HBP were atrioventricular block (n = 13, 61.9%), sinus node dysfunction (n = 7, 33.3%) and upgrade from implantable cardioverter-defibrillator to His-cardiac resynchronisation therapy (n = 1, 4.8%). No significant difference was observed in baseline characteristics between Timeframe 1 and Timeframe 2. Improvements pertaining to mean fluoroscopy time were achieved between the two timeframes. There was one HBP-related complication of lead displacement during Timeframe 1. All patients with successful HBP achieved non-selective His bundle (NSHB) capture, whereas only eight patients had selective His bundle (SHB) capture. NSHB and SHB capture thresholds remained stable at the 12-month follow-up.@*CONCLUSION@#Permanent HBP is feasible and safe, even without the use of an electrophysiology recording system. This was successfully achieved in 75% of patients, with no adverse clinical outcomes during the follow-up period.