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3.
Rev. Hosp. Ital. B. Aires (En línea) ; 43(4): 209-213, dic. 2023.
Article in Spanish | LILACS, UNISALUD, BINACIS | ID: biblio-1537564

ABSTRACT

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)


Subject(s)
Humans , Amyloid Neuropathies, Familial/diagnosis , Early Diagnosis , Amyloidosis/diagnosis , Mass Spectrometry , Biopsy , Glycosylation , Artificial Intelligence , Magnetic Resonance Imaging , Sequence Analysis, DNA , Practice Guidelines as Topic , Diagnosis, Differential , Electrocardiography , High-Throughput Nucleotide Sequencing
4.
Nursing (Ed. bras., Impr.) ; 26(300): 9625-9632, ju.2023. ilus
Article in English, Portuguese | LILACS, BDENF | ID: biblio-1444206

ABSTRACT

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)


Subject(s)
Arrhythmias, Cardiac , Health Education , Electrocardiography
5.
ABC., imagem cardiovasc ; 36(1): e20230002, abr. 2023. ilus, tab
Article in Portuguese | LILACS | ID: biblio-1452586

ABSTRACT

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)


Subject(s)
Humans , Male , Female , Child , Adolescent , Adult , Cardiomyopathy, Dilated/diagnosis , Cardiomegaly, Exercise-Induced/physiology , Heart/anatomy & histology , Heart/diagnostic imaging , Echocardiography/methods , Magnetic Resonance Spectroscopy/methods , Radiography, Thoracic/methods , Echocardiography, Doppler/methods , Exercise/physiology , Electrocardiography/methods
6.
Diagn. tratamento ; 28(1): 24-28, jan-mar. 2023. ilus 7
Article in Portuguese | LILACS | ID: biblio-1413198

Subject(s)
Electrocardiography
7.
Edumecentro ; 152023.
Article in Spanish | LILACS | ID: biblio-1514099

ABSTRACT

El descubrimiento de la electrocardiografía marcó un hito para la medicina: ofreció una mejor comprensión de la fisiología cardiovascular, es una herramienta imprescindible para el diagnóstico, evaluación y estratificación pronóstica de casi la totalidad de las enfermedades cardiovasculares, y ha sido un componente insustituible de las investigaciones cardiológicas de la medicina contemporánea. Importantes investigaciones de la cátedra de Cardiología del Hospital Universitario Cardiocentro "Ernesto Guevara" la han tenido como objeto de estudio en consonancia con las directrices del sistema de salud, para su aplicación en la asistencia y la actualización de los programas de la especialidad, los que se han enriquecido con nuevas variables electrocardiográficas denominadas como "no clásicas". Es objetivo de los autores comunicar algunos resultados científicos novedosos de investigaciones relacionadas con este vetusto medio de diagnóstico, los que han sido publicadas en revistas de alto impacto.


The discovery of electrocardiography marked a milestone for medicine: it offered a better understanding of cardiovascular physiology and has been an essential tool for the diagnosis, evaluation, and prognostic stratification of almost all cardiovascular diseases, and it has been an irreplaceable component of cardiology research in contemporary medicine. Important investigations of the Cardiology professorship of the "Ernesto Guevara" University Hospital have had it as an object of study in line with the guidelines of the health system, for its application in assistance and updating of specialty programs, which have been enriched with new electrocardiographic variables called "non-classical". It is the objective of the authors to communicate some novel scientific results of investigations related to this ancient aid of diagnosis, which have been published in high-impact journals.


Subject(s)
Quality of Health Care , Cardiology , Education, Medical , Electrocardiography
8.
Braz. J. Vet. Res. Anim. Sci. (Online) ; 60: e210468, 2023. ilus, graf, tab
Article in English | LILACS, VETINDEX | ID: biblio-1518143

ABSTRACT

Rescue and recovery dogs intercalate the activity intensity developed, which also triggers significant metabolic changes in cardiac physiology. Thus, we evaluated the changes that search simulation causes in glucose, lactate, and cardiac troponin I level (cTnI) and the electrocardiographic and heart rate during the activity and recovery phase to predict the physiological adaptation to the exercise. Five healthy adult dogs from the Rescue and Recovery Service of Military Firefighters Corps were submitted to 60 minutes search operation simulation in the woods. They covered a forest area of approximately 50,000 m2. The dogs were loose and accompanied by their driver, and they could perform any physical activity. Were evaluated serum biochemical analysis of glucose, lactate, cardiac troponin I, electrocardiographic, and heart rate (rest, exercise phase, and recovery time). No changes in glucose levels, heart rate, and cardiac rhythm were detected. In comparison to baseline values, there is an increase: in lactate at the end of the exercise phase [EXER] (60'EXER), and in the recovery phase [RCT] at 30'RCT and 60'RCT, and cTnI at 60'RCT, 120'RCT, and 4hRCT. P wave duration was significantly higher at 60'EXER, 15'RCT, and 30'RCT, with no alterations in wave amplitude. QRS interval duration significantly increased at 30'RCT, and the ST segment presented a significant difference at 60'EXER, 15'RCT, and 60'RCT compared to the rest moment. The moderate alterations in lactate and cTnI and few alterations in the electrocardiographic and heart rate maintenance suggest the adaptation of rescue and recovery dogs to the type, intensity, and duration of search operation simulation performed.(AU)


Cães de busca e resgate intercalam a intensidade da atividade desenvolvida que desencadeia alterações metabólicas significativas, bem como na fisiologia cardíaca. Assim, foram avaliadas as alterações que a simulação de busca produz nos níveis de glicose, lactato, troponina I cardíaca (cTnI), bem como na frequência cardíaca e atividade eletrocardiográfica durante a fase de atividade e recuperação, a fim de predizer a adaptação fisiológica ao exercício. Cinco cães adultos saudáveis do Serviço de Resgate e Salvamento do Corpo de Bombeiros Militares foram submetidos à simulação de operação de busca de 60 minutos na mata e cobriram uma área florestal de aproximadamente 50.000 m2. Os cães estavam soltos, acompanhados pelo condutor e estavam livres para realizar qualquer tipo de atividade física. Foram avaliados os níveis séricos de glicose, lactato e troponina I cardíaca, atividade eletrocardiográfica e frequência cardíaca em repouso, na fase de exercício e no tempo de recuperação. Não foram detectadas alterações nos níveis de glicose, frequência cardíaca e ritmo cardíaco. Em comparação com os valores basais houve aumento de lactato ao final da fase de exercício [EXER] (60'EXER) e na fase de recuperação [RCT] aos 30'RCT e 60'RCT; e cTnI aos 60'RCT, 120'RCT e 4hRCT. Duração da onda P foi significativamente maior em 60'EXER, 15'RCT e 30'RCT, sem alterações na amplitude da onda. Duração do intervalo QRS teve aumento significativo em 30'RCT e o segmento ST apresentou diferença significativa em 60'EXER, 15'RCT e 60'RCT quando comparado ao basal. As alterações moderadas nos níveis de lactato e cTnI, bem como a pouca alteração na atividade eletrocardiográfica e manutenção da frequência cardíaca sugerem boa adaptação dos cães de busca e resgate ao tipo, intensidade e duração da operação de busca simulada realizada.(AU)


Subject(s)
Animals , Physical Conditioning, Animal/physiology , Dogs/physiology , Electrocardiography/veterinary , Cardiac Electrophysiology/methods , Lactic Acid/administration & dosage , Troponin I/administration & dosage
9.
Belo Horizonte; s.n; 2023. 59 p.
Thesis in Portuguese | LILACS | ID: biblio-1518900

ABSTRACT

INTRODUÇÃO: a insuficiência cardíaca (IC) é uma das três causas mais comuns de doenças cardiovasculares (DCV), grupo de enfermidades que é a principal causa de morbimortalidade no mundo. O eletrocardiograma (ECG) é um dos exames utilizados na avaliação da IC, sendo de baixo custo e amplamente acessível. Quando associado à inteligência artificial, o ECG pode ser uma poderosa ferramenta para triagem de indivíduos com maior probabilidade de IC. O objetivo foi avaliar o desempenho de um algoritmo de IA, aplicado ao ECG, para detecção de DSVE e compará-lo ao das alterações maiores ao ECG (AME), de acordo com o código de Minnesota. MÉTODOS: estudo transversal retrospectivo de acurácia diagnóstica que utilizou a população do Estudo Longitudinal da Saúde do Adulto (ELSA-Brasil). Foram avaliados 2567 indivíduos que possuíam ecocardiograma (ECO) e ECG válidos e valores de predição para disfunção sistólica do ventrículo esquerdo (DSVE) estimadas por um algoritmo de inteligência artificial (IA). A DSVE foi definida como Fração de Ejeção do Ventrículo Esquerdo (FEVE) menor que 40%, calculada utilizando o ECO. A prevalência de DSVE foi de 1,13% na população estudada (29 indivíduos). Foram calculados sensibilidade, especificidade, valor preditivo positivo (VPP), valor preditivo negativo (VPN), razão de verossimilhança positivo (RVP), razão de verossimilhança negativa (RVN), diagnostic odds ratio (DOR) para o algoritmo e para as AME. Calculou-se também a área sob a curva ROC (ASC-ROC) para o algoritmo. RESULTADOS: a população estudada possui mediana de 62 anos, sendo 47,2% do sexo masculino. A ASC-ROC do algoritmo para predição de IC foi de 0,947 (IC 95% 0,913 ­ 0,981). A sensibilidade, especificidade, VPP, VPN, RVP, RVN e DOR para o algoritmo foi de 0,690; 0,976; 0,244; 0,996; 27,6; 0,32 e 88,74, respectivamente. Para as AME foi 0,172; 0,837; 0,012; 0,989; 1,09; 0,990 e 1,07 respectivamente. CONCLUSÕES: A IA aplicada ao ECG é uma fermenta promissora para identificação de pacientes com maior probabilidade de IC e que devem ser priorizados para realização de ECO. Isso poderia aprimorar o diagnóstico de IC em nosso meio e, assim, permitir o início precoce do tratamento, com possível impacto na redução da morbidade e mortalidade.


INTRODUCTION: Heart failure (HF) is one of the three most common causes of cardiovascular diseases (CVD), which are the leading causes of morbidity and mortality worldwide. The electrocardiogram (ECG) is one of the tests used in the evaluation of HF, combining low-cost and wide accessibility. When combined with artificial intelligence, the ECG can be a powerful tool for screening individuals with a higher risk of HF. Our objective was to assess the performance of an AI algorithm applied to the ECG for the detection of left ventricular systolic dysfunction (LVSD) and compare it to the performance of major ECG abnormalities (MEA) according to the Minnesota code. METHODS: This was a retrospective cross-sectional diagnostic accuracy study using data from the Brazilian Longitudinal Study of Adult Health (ELSA-Brazil). A total of 2567 individuals with valid echocardiograms (ECO) and ECGs and probability values for left ventricular systolic dysfunction (LVSD) estimated by an artificial intelligence (AI) algorithm, were evaluated. LVSD was defined as a left ventricular ejection fraction (LVEF) less than 40%, calculated using ECO. The prevalence of LVSD was 1.13% in the studied population (29 individuals). Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR) were calculated for the algorithm and MEA. The area under the ROC curve (AUC-ROC) was also calculated for the algorithm. RESULTS: The study population had a median age of 62 years, with 47.2% being male. The AUC-ROC for the algorithm to predict HF was 0.947 (95% CI 0.913 ­ 0.981). Sensitivity, specificity, PPV, NPV, PLR, NLR, and DOR for the algorithm were 0.690, 0.976, 0.244, 0.996, 27.6, 0.32, and 88.74, respectively. For MEA, it was 0.172, 0.837, 0.012, 0.989, 1.09, 0.990, and 1.07, respectively. CONCLUSIONS: AI applied to the ECG is a promising tool for identifying patients with a higher likelihood of HF who should be prioritized for ECO. This could improve the diagnosis capacity of HF in our setting and thus enable early treatment initiation, with possible impact on reducing morbidity and mortality.


Subject(s)
Humans , Male , Female , Artificial Intelligence , Ventricular Dysfunction, Left , Electrocardiography , Heart Failure
10.
Rev. urug. cardiol ; 38(1): e302, 2023. ilus
Article in Spanish | LILACS, UY-BNMED, BNUY | ID: biblio-1522875

ABSTRACT

La amiloidosis cardíaca (AC) es una enfermedad con mal pronóstico si el tratamiento no se inicia de forma temprana, por lo que una de las asignaturas pendientes en esta enfermedad consiste en realizar un diagnóstico precoz. El electrocardiograma (ECG) es una prueba diagnóstica de bajo costo y amplia disponibilidad que nos permite sospechar esta enfermedad, dado que resulta normal en < 5% de los pacientes. El hallazgo clásico es la presencia de bajos voltajes en relación con la gran hipertrofia que se observa en las pruebas de imagen, así como el conocido patrón de pseudoinfarto. Ambos hallazgos son más frecuentes en el subtipo de amiloidosis por cadenas ligeras, que era el más frecuentemente diagnosticado en el pasado. Sin embargo, con la expansión del diagnóstico no invasivo del subtipo a transtiretina, su identificación ha crecido de forma exponencial y se convirtió en el más diagnosticado con más frecuencia en nuestro medio. Se debe prestar especial atención a todos estos hallazgos electrocardiográficos, con el fin de que esta prueba diagnóstica de sencilla obtención pueda contribuir de forma importante a la sospecha y al diagnóstico precoz de la AC.


Cardiac amyloidosis (CA) is a serious disease with a poor prognosis if treatment is not started early, so one of the pending issues in this condition is to make an early diagnosis. The electrocardiogram (EKG) is an inexpensive and widely available diagnostic test that can offer differential data when suspecting this disease, being normal in < 5% of these patients. The classic EKG finding is the presence of low voltages in relation to the large hypertrophy seen on imaging tests, as well as the well-known pseudoinfarct pattern. Both findings are more frequent in the light chain subtype of CA, which was the most frequently diagnosed in the past. However, with the growth of noninvasive diagnostic tests, the identification of the transtyretin subtype has grown exponentially, becoming the most frequently diagnosed in our setting. Special attention should be paid to all these electrocardiographic findings, so that this simple diagnostic test can make an important contribution to the early suspicion and diagnosis of CA.


A amiloidose cardíaca (AC) é uma doença grave com um mau prognóstico no caso de não se iniciar tratamento de forma precoce, pelo que a necessidade de um pronto diagnóstico é imperiosa. Quando se suspeita desta doença, o eletrocardiograma (ECG) é um teste de diagnóstico pouco dispendioso e disponível em todo o mundo, que pode fornecer dados discriminativos importantes, sendo normal em menos de 5% dos casos. O achado clássico do ECG é a presença de baixas voltagens em relação à grande hipertrofia vista na imagem, bem como o conhecido padrão de pseudoinfarte. Ambos os resultados são mais frequentes no subtipo a cadenas ligeras, o mais frequentemente diagnosticado no passado. No entanto, com o aumento dos testes de diagnóstico não-invasivos, o diagnóstico ddo subtipo a transtirretina, o mais cresceu de forma exponencial, tornando-se o mais frequentemente diagnosticado no nosso meio. Deve ser dada especial atenção a todos estes achados eletrocardiográficos já que esta prova de diagnóstico de fácil obtenção pode contribuir de forma importante para a suspeição de diagnóstico precoce de AC.


Subject(s)
Humans , Electrocardiography , Heart Diseases/diagnosis , Amyloidosis/diagnosis
11.
Braz. J. Pharm. Sci. (Online) ; 59: e23063, 2023. tab, graf
Article in English | LILACS | ID: biblio-1505837

ABSTRACT

Abstract Doxorubicin (Dox) is a medication used in the treatment of cancerous tumors and hematologic malignancies with potentially serious side effects, including the risk of cardiotoxicity. Flavonoids are plant metabolites with antioxidant properties and can be extracted from Camellia sinensis (CS). The aim of this study is to evaluate the possible cardioprotective effect of CS against injuries induced by Dox in rats. A total of 32 animals were distributed into four groups: (1) control - intraperitoneal injection (I.P.) of 0.5 mL saline weekly and 1.0 mL water by gavage daily; (2) CS - 0.5 mL saline I.P. weekly and 200 mg/kg CS by gavage daily; (3) Dox - 5.0 mg/kg Dox I.P. weekly and 1.0 mL water by gavage daily; and (4) Dox+CS -5.0 mg/kg Dox I.P. weekly and 200 mg/kg CS by gavage daily. Clinical examinations, blood profiles, electrocardiograms, echocardiograms, and histological analyses of hearts were performed over 25 days. The animals in the Dox group showed changes in body weight and in erythrogram, leukogram, electrocardiography, and echocardiography readings. However, animals from the dox+CS group had significantly less change in body weight, improved cardiac function, and showed more preserved cardiac tissue. This study demonstrated that CS prevents dox-induced cardiotoxicity, despite enhancing the cytotoxic effect on blood cells


Subject(s)
Animals , Male , Rats , Doxorubicin/administration & dosage , Camellia sinensis/adverse effects , Cardiotoxicity , Echocardiography/instrumentation , Hematologic Neoplasms/pathology , Electrocardiography/instrumentation , Antioxidants/pharmacology
12.
Med. lab ; 27(2): 111-122, 2023. Tabs
Article in Spanish | LILACS | ID: biblio-1435407

ABSTRACT

Introducción. Las emulsiones lipídicas intravenosas (ELI) son unas emulsiones grasas no tóxicas con fosfolípidos, actualmente aprobadas para su uso en el tratamiento de intoxicaciones, específicamente en las producidas por anestésicos locales. El propósito de este estudio es la caracterización del uso de ELI en pacientes mayores de 18 años, que presentaron intoxicación por sustancias y medicamentos diferentes a anestésicos locales, en un hospital de alta complejidad de la ciudad de Medellín, durante el periodo comprendido entre 2015 y 2020. Metodología. Se realizó un estudio descriptivo, retrospectivo, de casos que recibieron ELI como tratamiento para su intoxicación. Se hizo revisión de las historias clínicas de la población objeto de estudio. Se recolectó información acerca de variables sociodemográficas, clínicas y paraclínicas, y de atención. Se hizo análisis univariado de las variables de interés. Resultados. Del total de 1.966 intoxicaciones, se incluyeron 51 (2,6 %) casos de intoxicación por sustancias y medicamentos diferentes a anestésicos locales, que recibieron la terapia con ELI entre 2015 y 2020. La mediana de edad de los participantes fue de 27 años. Un 74,5 % de los participantes presentó intoxicación por medicamentos. El promedio de la dosis de ELI recibida fue de 1.036 mL en 24 horas, dosis inferior a la calculada por kilo de peso que debían recibir, de 1.149 mL en promedio. Un 86,3 % (n=44) de los casos presentaron neurotoxicidad, y 76,5 % (n=39) presentaron cardiotoxicidad. La neurotoxicidad mejoró en el 34,7 % y la cardiotoxicidad en el 59,1 % de los individuos que recibieron terapia con ELI. Conclusión. La aplicación de las ELI se hizo en personas en su mayoría intoxicadas por antipsicóticos, hombres, jóvenes; menos de la mitad tenía compromiso de la ventilación, y hubo mejoría en la cardiotoxicidad y neurotoxicidad. Hubo una diferencia entre la dosis recibida y la que debían recibir ajustada por el peso


Introduction. Intravenous lipid emulsions (IVLE) are non-toxic fatty emulsions with phospholipids, currently approved for use in the treatment of poisoning, specifically those produced by local anesthetics. The purpose of this study is to characterize the use of IVLE in patients over 18 years of age, who presented intoxication by substances and medications other than local anesthetics, in a high complexity hospital in the city of Medellín, during the period between 2015 and 2020. Methodology. A retrospective descriptive study was carried out on cases that received IVLE as a treatment for their poisoning. The clinical records of the study population were reviewed. Information was collected about sociodemographic, clinical and paraclinical variables, and care. Univariate analysis of the variables of interest was performed. Results. Of the total of 1,966 poisonings, 51 (2.6%) cases caused by substances and medications other than local anesthetics, received ELI therapy between 2015 and 2020 and were included in the study. The median age of the participants was 27 years. 74.5% of the participants presented drug poisoning. The average IVLE dose received was 1,036 mL in 24 hours, a lower dose than the one calculated per kilo of weight, which had been on average 1,149 mL. 86.3% (n=44) of the cases presented neurotoxicity, and 76.5% (n=39) presented cardiotoxicity. Neurotoxicity improved in 34.7% and cardiotoxicity in 59.1% of individuals receiving ELI therapy. Conclusion. The application of IVLE was made in people mostly poisoned by antipsychotics, men, young people, less than half had compromised ventilation, and there was improvement in cardiotoxicity and neurotoxicity. There was a difference between the dose received and the one they should have received adjusted for weight


Subject(s)
Humans , Fat Emulsions, Intravenous , Poisoning , Mortality , Neurotoxicity Syndromes , Electrocardiography , Cardiotoxicity
13.
Journal of Biomedical Engineering ; (6): 51-59, 2023.
Article in Chinese | WPRIM | ID: wpr-970673

ABSTRACT

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.


Subject(s)
Algorithms , Neural Networks, Computer , Electrocardiography , Databases, Factual , Fetus
14.
Chinese Medical Journal ; (24): 313-321, 2023.
Article in English | WPRIM | ID: wpr-970080

ABSTRACT

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.


Subject(s)
Humans , Male , Middle Aged , Aged , Atrial Fibrillation/epidemiology , Prospective Studies , Incidence , Atrial Flutter/complications , Risk Factors , China/epidemiology , Electrocardiography
15.
Annals of the Academy of Medicine, Singapore ; : 96-99, 2023.
Article in English | WPRIM | ID: wpr-970016

ABSTRACT

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.


Subject(s)
Humans , Bradycardia/therapy , Algorithms , Diagnosis, Differential , Electrocardiography
16.
Chinese Critical Care Medicine ; (12): 643-650, 2023.
Article in Chinese | WPRIM | ID: wpr-982647

ABSTRACT

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.


Subject(s)
Humans , Clinical Alarms , Australia , Intensive Care Units , Arrhythmias, Cardiac , Electrocardiography , Monitoring, Physiologic
17.
Chinese Journal of Medical Instrumentation ; (6): 258-263, 2023.
Article in Chinese | WPRIM | ID: wpr-982224

ABSTRACT

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.


Subject(s)
Humans , Atrial Fibrillation/diagnosis , Support Vector Machine , Heart Rate , Algorithms , Neural Networks, Computer , Electrocardiography
18.
Chinese Medical Sciences Journal ; (4): 38-48, 2023.
Article in English | WPRIM | ID: wpr-981589

ABSTRACT

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.


Subject(s)
Humans , Arrhythmias, Cardiac/diagnosis , Electrocardiography/methods , Algorithms
19.
Journal of Biomedical Engineering ; (6): 474-481, 2023.
Article in Chinese | WPRIM | ID: wpr-981565

ABSTRACT

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.


Subject(s)
Humans , Electrocardiography , Algorithms , Cardiovascular Diseases , Databases, Factual , Neural Networks, Computer
20.
Journal of Biomedical Engineering ; (6): 465-473, 2023.
Article in Chinese | WPRIM | ID: wpr-981564

ABSTRACT

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.


Subject(s)
Humans , Arrhythmias, Cardiac/diagnostic imaging , Cardiovascular Diseases , Algorithms , Databases, Factual , Electrocardiography
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