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PURPOSE: This study aimed to develop a Quality of Life (QOL) assessment scale for older patients with Neuro-co-Cardiological Diseases (NCCD) and to evaluate the reliability and validity of the scale. METHOD: The study participants were derived from the Elderly Individuals with NCCD Registered Cohort Study (EINCCDRCS), a multicenter registry of patients with NCCD. The preliminary testing of the questionnaire was conducted among 10 older individuals aged 65 years and older who had NCCD and were recruited from the registry. Other patients who met the inclusion criteria participated in the field testing. After verifying the unidimensionality, local independence, and monotonicity assumptions of the scale, we employed the Rasch model within Item Response Theory framework to assess the quality of the scale through methods including internal consistency, criterion validity, Wright map, and item functioning differential. Subsequently, we assessed the construct validity of the scale by combining exploratory factor analysis with confirmatory factor analysis. RESULTS: Based on well-validated scales such as the short-form WHOQOL-OLD, HeartQOL, IQCODE, and SF-36, an original Neuro-co-Cardiological Diseases Quality of Life scale (NCCDQOL) was developed. 196 individuals from the EINCCDRCS were included in the study, with 10 participating in the preliminary testing and 186 in the field testing. Based on the results of the preliminary testing, the original questionnaire was refined through item deletion and adjustment, resulting in an 11-item NCCDQOL questionnaire. The Rasch analysis of the field testing data led to the removal of 21 misfitting individuals. The NCCDQOL demonstrated a four-category structure, achieved by combining two response categories. This structure aligned with the assumptions of unidimensionality, local independence, and monotonicity. The NCCDQOL also exhibited good validity and reliability. CONCLUSION: The revised NCCDQOL questionnaire demonstrated good reliability and validity in the Rasch model, indicating promising potential for clinical application.
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Calidad de Vida , Humanos , Calidad de Vida/psicología , Anciano , Masculino , Femenino , Encuestas y Cuestionarios/normas , Estudios de Cohortes , Anciano de 80 o más Años , Enfermedades del Sistema Nervioso/psicología , Enfermedades del Sistema Nervioso/diagnóstico , Cardiopatías/psicología , Cardiopatías/diagnóstico , Reproducibilidad de los Resultados , Sistema de Registros , ComorbilidadRESUMEN
BACKGROUND: Ball thrombus is rare and life-threatening. The correct diagnosis and timely management are key to improving patient prognosis. Here, we present a case report and literature review of ball thrombus. CASE PRESENTATION: A 75-year-old woman presented to our outpatient clinic because of palpitations and chest distress for 8 months. She was diagnosed mitral stenosis, and transthoracic echocardiography (TTE) showed a round mass attached to the left atrial (LA) wall. Before anesthesia induction, TTE found that the mass has dropped from the LA wall, and was spinning in the LA causing intermittent obstruction of the valve. Anesthesia induction was then carried out under TTE monitoring, and transesophageal echocardiograph found another mass in the LA appendage after intubation. She underwent LA mass removal and mitral valve replacement, and was discharged uneventfully. Histopathology confirmed the diagnosis of thrombus. Our literature review identified 19 cases of ball thrombus between 2015 and 2024. The average age was 54.8 (range 3-88) years. Heart failure was present as the initial symptom in 11 cases, and most patients had mitral valve disease or concomitant with atrial fibrillation. 12 cases received surgery, and 7 received medical treatment only. 2 deaths occurred, one due to the obstruction of left ventricular inflow tract and the other due to the worsening of heart failure. CONCLUSION: Ball thrombus is rare in clinical settings. Urgent thrombectomy should be performed as soon as possible, and echocardiography can be used for real-time monitoring during surgery.
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Trombosis , Humanos , Femenino , Anciano , Trombosis/diagnóstico por imagen , Trombosis/cirugía , Estenosis de la Válvula Mitral/cirugía , Estenosis de la Válvula Mitral/diagnóstico por imagen , Ecocardiografía Transesofágica/métodos , Ecocardiografía , Implantación de Prótesis de Válvulas Cardíacas , Cardiopatías/diagnósticoRESUMEN
Early diagnosis of heart disease is crucial, as it's one of the leading causes of death globally. Machine learning algorithms can be a powerful tool in achieving this goal. Therefore, this article aims to increase the accuracy of predicting heart disease using machine learning algorithms. Five classification models are explored: eXtreme Gradient Boosting (XGBC), Random Forest Classifier (RFC), Decision Tree Classifier (DTC), K-Nearest Neighbors Classifier (KNNC), and Logistic Regression Classifier (LRC). Additionally, four optimizers are evaluated: Slime mold Optimization Algorithm, Forest Optimization Algorithm, Pathfinder algorithm, and Giant Armadillo Optimization. To ensure robust model selection, a feature selection technique utilizing k-fold cross-validation is employed. This method identifies the most relevant features from the data, potentially improving model performance. The top three performing models are then coupled with the optimization algorithms to potentially enhance their generalizability and accuracy in predicting heart failure. In the final stage, the shortlisted models (XGBC, RFC, and DTC) were assessed using performance metrics like accuracy, precision, recall, F1-score, and Matthews Correlation Coefficient (MCC). This rigorous evaluation identified the XGGA hybrid model as the top performer, demonstrating its effectiveness in predicting heart failure. XGGA achieved impressive metrics, with an accuracy, precision, recall, and F1-score of 0.972 in the training phase, underscoring its robustness. Notably, the model's predictions deviated by less than 5.5 % for patients classified as alive and by less than 1.2 % for those classified as deceased compared to the actual outcomes, reflecting minimal error and high predictive reliability. In contrast, the DTC base model was the least effective, with an accuracy of 0.840 and a precision of 0.847. Overall, the optimization using the GAO algorithm significantly enhanced the performance of the models, highlighting the benefits of this approach.
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Algoritmos , Aprendizaje Automático , Humanos , Cardiopatías/diagnóstico , Valor Predictivo de las Pruebas , Masculino , Femenino , Persona de Mediana Edad , AncianoRESUMEN
BACKGROUND: High cognitive reserve (CR) has been related to lower dementia risk, but its association with heart disease (HD) is unknown. We aimed to explore the relation of CR to HD and cardiac structure and function. METHODS AND RESULTS: Within the UK Biobank, 349 907 HD-free participants were followed up. A composite CR indicator involving education/occupation attainment/television viewing time/confiding frequency/social connection frequency/variety of leisure activities was generated, and further categorized into low/moderate/high levels. Incident HD, including coronary HD, cardiac arrhythmia, and heart failure, was ascertained on the basis of medical records. During the follow-up, a subsample (n=31 182) underwent cardiac magnetic resonance imaging to assess ventricular structure and function. Data were analyzed using Cox regression, Laplace regression, and linear regression. Compared with low CR, the hazard ratio and 95% CI of any HD for high CR was 0.78 (0.75-0.80) (including 0.68 [0.66-0.71] for coronary HD, 0.91 [0.87-0.95] for cardiac arrhythmia, and 0.63 [0.58-0.68] for heart failure). Furthermore, high CR was associated with delayed HD onset by 1.59 (95% CI, 1.37-1.82) years compared with low CR. In cardiac magnetic resonance imaging data analysis, compared with low CR, high CR was associated with larger left ventricular end-diastolic volume (ß, 0.13 [95% CI, 0.09-0.17]), left ventricular end-systolic volume (ß, 0.05 [95% CI, 0.01-0.10]), left ventricular stroke volume (ß, 0.16 [95% CI, 0.12-0.21]), and left ventricular ejection fraction (ß, 0.08 [95% CI, 0.03-0.13]). CONCLUSIONS: High CR is associated with favorable HD health. Our findings suggest that the beneficial effect of CR is not limited to dementia but also HD.
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Reserva Cognitiva , Función Ventricular Izquierda , Humanos , Masculino , Femenino , Persona de Mediana Edad , Anciano , Estudios Longitudinales , Reserva Cognitiva/fisiología , Reino Unido/epidemiología , Función Ventricular Izquierda/fisiología , Cardiopatías/fisiopatología , Cardiopatías/epidemiología , Cardiopatías/diagnóstico , Volumen Sistólico/fisiología , Imagen por Resonancia Magnética , Incidencia , Adulto , Factores de Riesgo , Medición de Riesgo , Remodelación Ventricular/fisiología , Insuficiencia Cardíaca/fisiopatología , Insuficiencia Cardíaca/epidemiología , Insuficiencia Cardíaca/diagnósticoRESUMEN
BACKGROUND: Accumulating evidence suggests that cardiac findings after stroke are an important, yet understudied, manifestation of brain-heart interactions. Our aim was to investigate and compare cardiac findings after different cerebrovascular events (acute ischemic stroke, transient ischemic attack, and hemorrhagic stroke). METHODS AND RESULTS: There were 7113 patients screened who were treated between December 2013 and December 2020 at the University Hospital Zurich for ischemic stroke, transient ischemic attack, and hemorrhagic stroke. Seven hundred twenty-one patients without evidence of previous cardiac disease or presumed cardioembolic origin of their cerebrovascular disease and with at least 1 cardiac checkup were included. Clinical reports from the year following disease onset were screened for new cardiac findings, which were categorized as arrhythmia/electrocardiographic changes, myocardial alterations, valvular abnormalities, and coronary perfusion insufficiency. Differences in proportions of findings among groups were analyzed using the Pearson χ2 test or Fisher exact test. ECG changes were observed in 81.7% (n=474) of patients with ischemic stroke, 71.4% (n=70) of patients with transient ischemic attack, and 55.8% (n=24) of patients with hemorrhagic stroke (P<0.001). Myocardial alterations occurred often in all 3 groups (60.9% ischemic stroke [n=353], 59.2% transient ischemic attack [n=58], 44.2% hemorrhagic stroke [n=19]; P=0.396). CONCLUSIONS: Cardiac findings are frequent in patients with cerebrovascular disease, even without prior cardiac problems or suspected cardiac cause. Similarities, especially between patients with ischemic stroke and transient ischemic attack, were observed. Our data suggest that all patients with acute cerebrovascular events should receive thorough workup searching for cardiac manifestations.
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Accidente Cerebrovascular Hemorrágico , Ataque Isquémico Transitorio , Accidente Cerebrovascular Isquémico , Humanos , Masculino , Femenino , Anciano , Persona de Mediana Edad , Accidente Cerebrovascular Isquémico/etiología , Accidente Cerebrovascular Isquémico/fisiopatología , Accidente Cerebrovascular Isquémico/diagnóstico , Ataque Isquémico Transitorio/fisiopatología , Ataque Isquémico Transitorio/etiología , Ataque Isquémico Transitorio/diagnóstico , Accidente Cerebrovascular Hemorrágico/epidemiología , Accidente Cerebrovascular Hemorrágico/diagnóstico , Electrocardiografía , Cardiopatías/fisiopatología , Cardiopatías/etiología , Cardiopatías/diagnóstico , Estudios Retrospectivos , Anciano de 80 o más Años , Suiza/epidemiología , Factores de Riesgo , Trastornos Cerebrovasculares/fisiopatología , Trastornos Cerebrovasculares/etiología , Trastornos Cerebrovasculares/diagnósticoRESUMEN
The clinical significance of B-type natriuretic peptide (BNP) and N-terminal pro-B-type natriuretic peptide (NT-proBNP) in pediatric patients remains an area of evolving understanding, particularly regarding their utility in the presence or absence of pre-existing heart conditions. While clear cutoff values and established roles in heart failure are understood in adult patients, pediatric norms vary with age, complicating interpretation. Notably, the emergence of multi-system inflammatory syndrome in children (MIS-C) has highlighted the importance of these markers not only in the detection of acute heart failure but also as a marker of disease severity and even as a differential diagnosis tool. This review summarizes current knowledge on the utility of BNP and NT-proBNP in pediatric patients. Their unique physiology, including circulation and compensation mechanisms, likely influence BNP and NT-proBNP release, potentially even in non-heart failure states. Factors such as dynamic volemic changes accompanying inflammatory diseases in children may contribute. Thus, understanding the nuanced roles of BNP and NT-proBNP in pediatric populations is crucial for the accurate diagnosis, management, and differentiation of cardiac and non-cardiac conditions.
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Biomarcadores , Insuficiencia Cardíaca , Péptido Natriurético Encefálico , Fragmentos de Péptidos , Humanos , Péptido Natriurético Encefálico/sangre , Péptido Natriurético Encefálico/metabolismo , Niño , Fragmentos de Péptidos/sangre , Biomarcadores/sangre , Insuficiencia Cardíaca/sangre , Insuficiencia Cardíaca/metabolismo , Insuficiencia Cardíaca/diagnóstico , Cardiopatías/sangre , Cardiopatías/metabolismo , Cardiopatías/diagnóstico , Síndrome de Respuesta Inflamatoria Sistémica/sangre , Síndrome de Respuesta Inflamatoria Sistémica/diagnóstico , Relevancia ClínicaRESUMEN
Heart Rate Variability (HRV) refers to the capability of the heart rhythm to vary at different times, typically reflecting the regulation of the heart by the autonomic nervous system. In recent years, with advancements in Electrocardiogram (ECG) signal processing technology, HRV features reflect various aspects of cardiac activity, such as variability in heart rate, cardiac health status, and responses. We extracted key features of HRV and used them to develop and evaluate an automatic recognition model for cardiac diseases. Consequently, we proposed the HRV Heart Disease Recognition (HHDR) method, employing the Spectral Magnitude Quantification (SMQ) technique for feature extraction. Firstly, the HRV signals are extracted through electrocardiogram signal processing. Then, by analyzing parts of the HRV signal within various frequency ranges, the SMQ method extracts rich features of partial information. Finally, the Random Forest (RF) classification computational method is employed to classify the extracted information, achieving efficient and accurate cardiac disease recognition. Experimental results indicate that this method surpasses current technologies in recognizing cardiac diseases, with an average accuracy rate of 95.1% for normal/diseased classification, and an average accuracy of 84.8% in classifying five different disease categories. Thus, the proposed HHDR method effectively utilizes the local information of HRV signals for efficient and accurate cardiac disease recognition, providing strong support for cardiac disease research in the medical field.
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Algoritmos , Electrocardiografía , Cardiopatías , Frecuencia Cardíaca , Procesamiento de Señales Asistido por Computador , Humanos , Electrocardiografía/métodos , Frecuencia Cardíaca/fisiología , Cardiopatías/fisiopatología , Cardiopatías/diagnósticoRESUMEN
RATIONALE: Alcoholic cardiomyopathy (ACM) is associated with various cardiac complications, but the development of isolated right atrial (RA) thrombus without deep vein thrombosis is rare and presents diagnostic challenges. PATIENT CONCERNS: A 53-year-old Hispanic male presented with shortness of breath, chills, cough, bilateral lower extremity edema, and distended abdomen. DIAGNOSES: The patient was diagnosed with ACM, liver cirrhosis, and a large RA thrombus. Initial transthoracic echocardiography showed severe left ventricular systolic dysfunction but failed to detect the RA mass. Subsequent computed tomography scan and transesophageal echocardiography revealed a large oval mass in the RA, measuring 40 mm × 22 mm × 18 mm. INTERVENTIONS: The patient received guideline-directed medical therapy for heart failure and anticoagulation with enoxaparin. He underwent cardiac catheterization for mechanical thrombectomy, which was minimally successful. OUTCOMES: The patient's condition was managed with the prescribed interventions. Regular follow-up was planned to assess thrombolysis. LESSONS: RA thrombosis is an uncommon complication of ACM. A multimodal imaging approach, with a low threshold for transesophageal echocardiography, is crucial in evaluating patients with ACM who present with cardiac complications. This approach enables accurate diagnosis and management of rare conditions like isolated RA thrombosis.
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Cardiomiopatía Alcohólica , Atrios Cardíacos , Trombosis , Humanos , Masculino , Persona de Mediana Edad , Trombosis/etiología , Trombosis/diagnóstico por imagen , Atrios Cardíacos/diagnóstico por imagen , Cardiomiopatía Alcohólica/complicaciones , Cardiomiopatía Alcohólica/diagnóstico , Ecocardiografía Transesofágica/métodos , Cardiopatías/etiología , Cardiopatías/diagnóstico , Cateterismo Cardíaco/métodos , Trombectomía/métodosRESUMEN
Myocardial remodelling, entailing cellular and molecular changes in the different components of the cardiac tissue in response to damage, underlies the morphological and structural changes leading to cardiac remodelling, which in turn contributes to cardiac dysfunction and disease progression. Since cardiac tissue is not available for histomolecular diagnosis, surrogate markers are needed for evaluating myocardial remodelling as part of the clinical management of patients with cardiac disease. In this setting, circulating biomarkers, a component of the liquid biopsy, provide a promising approach for the fast, affordable and scalable screening of large numbers of patients, allowing the detection of different pathological features related to myocardial remodelling, aiding in risk stratification and therapy monitoring. However, despite the advances in the field and the identification of numerous potential candidates, their implementation in clinical practice beyond natriuretic peptides and troponins is mostly lacking. In this review, we will discuss some biomarkers related to alterations in the main cardiac tissue compartments (cardiomyocytes, extracellular matrix, endothelium and immune cells) which have shown potential for the assessment of cardiovascular risk, cardiac remodelling and therapy effects. The hurdles and challenges for their translation into clinical practice will also be addressed.
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Biomarcadores , Remodelación Ventricular , Humanos , Biomarcadores/sangre , Remodelación Ventricular/fisiología , Miocardio/patología , Miocardio/metabolismo , Cardiopatías/sangre , Cardiopatías/diagnóstico , Cardiopatías/terapia , Cardiopatías/fisiopatologíaRESUMEN
BACKGROUND: Cardiac autonomic neuropathy (CAN) in diabetes mellitus (DM) is independently associated with cardiovascular (CV) events and CV death. Diagnosis of this complication of DM is time-consuming and not routinely performed in the clinical practice, in contrast to fundus retinal imaging which is accessible and routinely performed. Whether artificial intelligence (AI) utilizing retinal images collected through diabetic eye screening can provide an efficient diagnostic method for CAN is unknown. METHODS: This was a single center, observational study in a cohort of patients with DM as a part of the Cardiovascular Disease in Patients with Diabetes: The Silesia Diabetes-Heart Project (NCT05626413). To diagnose CAN, we used standard CV autonomic reflex tests. In this analysis we implemented AI-based deep learning techniques with non-mydriatic 5-field color fundus imaging to identify patients with CAN. Two experiments have been developed utilizing Multiple Instance Learning and primarily ResNet 18 as the backbone network. Models underwent training and validation prior to testing on an unseen image set. RESULTS: In an analysis of 2275 retinal images from 229 patients, the ResNet 18 backbone model demonstrated robust diagnostic capabilities in the binary classification of CAN, correctly identifying 93% of CAN cases and 89% of non-CAN cases within the test set. The model achieved an area under the receiver operating characteristic curve (AUCROC) of 0.87 (95% CI 0.74-0.97). For distinguishing between definite or severe stages of CAN (dsCAN), the ResNet 18 model accurately classified 78% of dsCAN cases and 93% of cases without dsCAN, with an AUCROC of 0.94 (95% CI 0.86-1.00). An alternate backbone model, ResWide 50, showed enhanced sensitivity at 89% for dsCAN, but with a marginally lower AUCROC of 0.91 (95% CI 0.73-1.00). CONCLUSIONS: AI-based algorithms utilising retinal images can differentiate with high accuracy patients with CAN. AI analysis of fundus images to detect CAN may be implemented in routine clinical practice to identify patients at the highest CV risk. TRIAL REGISTRATION: This is a part of the Silesia Diabetes-Heart Project (Clinical-Trials.gov Identifier: NCT05626413).
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Aprendizaje Profundo , Neuropatías Diabéticas , Valor Predictivo de las Pruebas , Humanos , Masculino , Femenino , Persona de Mediana Edad , Anciano , Neuropatías Diabéticas/diagnóstico , Neuropatías Diabéticas/fisiopatología , Neuropatías Diabéticas/diagnóstico por imagen , Neuropatías Diabéticas/etiología , Reproducibilidad de los Resultados , Retinopatía Diabética/diagnóstico , Retinopatía Diabética/diagnóstico por imagen , Retinopatía Diabética/epidemiología , Interpretación de Imagen Asistida por Computador , Sistema Nervioso Autónomo/fisiopatología , Sistema Nervioso Autónomo/diagnóstico por imagen , Fondo de Ojo , Cardiopatías/diagnóstico por imagen , Cardiopatías/diagnóstico , Adulto , Inteligencia ArtificialRESUMEN
Chemotherapy has markedly improved cancer outcomes, yet cancer therapy-related cardiac dysfunction (CTRCD) poses a significant challenge, affecting around 10% of patients. CTRCD can be asymptomatic or present with heart failure symptoms. Multimodality imaging, particularly echocardiography, remains pivotal for monitoring cardiac function. Potential biomarkers for CTRCD assessment include troponin and B-type natriuretic peptide. Pharmacological interventions, such as dexrazoxane, angiotensin-converting enzyme inhibitors, and statins, play a crucial role in primary prevention and mitigating cardiotoxicity alongside cardiac rehabilitation programs. Thus, a comprehensive approach is essential for optimal cardiac recovery and improved patient outcomes.
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Antineoplásicos , Cardiotoxicidad , Cardiopatías , Neoplasias , Recuperación de la Función , Humanos , Neoplasias/tratamiento farmacológico , Antineoplásicos/efectos adversos , Cardiopatías/fisiopatología , Cardiopatías/inducido químicamente , Cardiopatías/diagnóstico , Cardiopatías/diagnóstico por imagen , Cardiopatías/terapia , Cardiopatías/prevención & control , Resultado del Tratamiento , Factores de Riesgo , Rehabilitación Cardiaca , Biomarcadores/sangreRESUMEN
BACKGROUND: Cardiac screening of elite athletes is widely recommended by Australasian sporting federations, but data are not structured to be shared. Data are lacking from underrepresented groups to inform ECG interpretation guidelines. The ARENA (Australasian Registry of Screening ECGs in National Athletes) project is a retrospective and prospective, multicenter, longitudinal, observational registry of athlete cardiac screening results and outcomes. The aim is to create a repository to improve our understanding of the diagnoses and outcomes of screening. METHODS: Participating sports that conduct cardiac screening of athletes will contribute data. This includes an initial collection (retrospective data, waiver of consent) and future prospective data (opt-out consent). Data include sex, age, sport/event, screening date, ECG findings, cardiac test results, follow-up details, sport participation status, cardiac diagnoses, and major cardiovascular outcomes defined as sudden cardiac arrest/death, cardiac syncope or implanted cardioverter defibrillator shock, cardiac hospitalization, and arrhythmias requiring intervention. Comparisons will be made between diagnoses, outcomes, and ECG features and analyzed by sport and sex. The ARENA project was developed in collaboration with sporting bodies, team physicians, and players association representatives and endorsed by the Australasian College of Sport & Exercise Physicians and Sports Medicine Australia. CONCLUSIONS: The ARENA project will provide a long-term international data repository to improve our understanding of ECG interpretation, cardiac screening and diagnoses, and the prevalence of cardiovascular outcomes in screened athletes. A unique aim is to address evidence gaps in underrepresented athlete groups, specifically female athletes and Indigenous populations. Results will inform screening policies and guidelines.
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Atletas , Muerte Súbita Cardíaca , Electrocardiografía , Tamizaje Masivo , Sistema de Registros , Humanos , Femenino , Masculino , Estudios Prospectivos , Tamizaje Masivo/métodos , Muerte Súbita Cardíaca/epidemiología , Muerte Súbita Cardíaca/prevención & control , Estudios Retrospectivos , Australia/epidemiología , Cardiopatías/diagnóstico , Cardiopatías/epidemiología , Proyectos de Investigación , Adulto , Estudios LongitudinalesRESUMEN
Internet of things (IoT) is utilized to enhance conventional health care systems in several ways, including patient's disease monitoring. The data gathered by IoT devices is very beneficial to medical facilities and patients. The data needs to be secured against unauthorized modifications because of security and privacy concerns. Conversely, a variety of procedures are offered by block chain technology to safeguard data against modifications. Block chain-based IoT-based health care monitoring is thus a fascinating technical advancement that may aid in easing security and privacy problems associated withthe collection of data during patient monitoring. In this work, we present an ensemble classification-based monitoring system with a block-chain as the foundation for an IoT health care model. Initially, data generation is done by considering the diseases including chronic obstructive pulmonary disease (COPD), lung cancer, and heart disease. The IoT health care data is then preprocessed using enhanced scalar normalization. The preprocessed data was used to extract features such as mutual information (MI), statistical features, adjusted entropy, and raw features. The total classified result is obtained by averaging deep maxout, improved deep convolutional network (IDCNN), and deep belief network (DBN) ensemble classification. Finally, decision-making is done by doctors to suggest treatment based on the classified results from the ensemble classifier. The ensemble model scored the greatest accuracy (95.56%) with accurate disease classification at a learning percentage of 60% compared to traditional classifiers such as neural network (NN) (89.08%), long short term memory (LSTM) (80.63%), deep belief network (DBN) (79.78%) and GT based BSS algorithm (89.08%).
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Internet de las Cosas , Humanos , Monitoreo Fisiológico/métodos , Enfermedad Pulmonar Obstructiva Crónica/diagnóstico , Redes Neurales de la Computación , Algoritmos , Neoplasias Pulmonares/diagnóstico , Atención a la Salud , Cardiopatías/diagnósticoRESUMEN
Aim: Evaluation of the performance of ChatGPT-4.0 in providing prediagnosis and treatment plans for cardiac clinical cases by expert cardiologists. Methods: 20 cardiology clinical cases developed by experienced cardiologists were divided into two groups according to preparation methods. Cases were reviewed and analyzed by the ChatGPT-4.0 program, and analyses of ChatGPT were then sent to cardiologists. Eighteen expert cardiologists evaluated the quality of ChatGPT-4.0 responses using Likert and Global quality scales. Results: Physicians rated case difficulty (median 2.00), revealing high ChatGPT-4.0 agreement to differential diagnoses (median 5.00). Management plans received a median score of 4, indicating good quality. Regardless of the difficulty of the cases, ChatGPT-4.0 showed similar performance in differential diagnosis (p: 0.256) and treatment plans (p: 0.951). Conclusion: ChatGPT-4.0 excels at delivering accurate management and demonstrates its potential as a valuable clinical decision support tool in cardiology.
Have you ever wondered if an artificial intelligence (AI) program could help doctors figure out what the problem is when someone has heart complaints? Our research examined this by testing an AI program called ChatGPT-4.0 on clinical cases. We wanted to see if it could help doctors by giving good advice on what might be wrong with patients who have heart issues and what should be done to help them. To test this, we used ChatGPT-4.0 to look at 20 different stories about patients with heart problems. These stories were made to cover a variety of common heart conditions faced by heart doctors. Then, we asked 18 heart doctors to check if the advice from ChatGPT-4.0 was good and made sense. What we found was quite interesting! Most of the time, the doctors agreed that the computer gave good advice on what might be wrong with the patients and how to help them. This means that this smart computer program could be a helpful tool for doctors, especially when they are trying to figure out tricky heart problems. But, it's important to say that computers like ChatGPT-4.0 are not ready to replace doctors. They are tools that can offer suggestions. Doctors still need to use their knowledge and experience to make the final call on what's best for their patients. In simple terms, our study shows that with more development and testing, AI like ChatGPT-4.0 could be a helpful assistant to doctors in treating heart disease, making sure patients get the best care possible.
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Cardiología , Humanos , Cardiología/métodos , Femenino , Masculino , Diagnóstico Diferencial , Persona de Mediana Edad , Toma de Decisiones Clínicas/métodos , Cardiopatías/diagnóstico , Cardiopatías/terapiaAsunto(s)
Miositis , Humanos , Estudios Retrospectivos , Masculino , Femenino , Persona de Mediana Edad , Miositis/diagnóstico , Adulto , Anciano , Cardiopatías/diagnóstico , Cardiopatías/etiologíaRESUMEN
In the last decade, an incredible improvement has been made in elucidating the genetic bases of cardiomyopathies. Here we report the impact of either the European Society of Cardiology (ESC) guidelines or the use of whole exome sequencing (WES) in terms of a number of variants of uncertain significance (VUS) and missed diagnoses in a series of 260 patients affected by inherited cardiac disorders. Samples were analyzed using a targeted gene panel of 128 cardiac-related genes and/or WES in a subset of patients, with a three-tier approach. Analyzing (i) only a subset of genes related to the clinical presentation, strictly following the ESC guidelines, 20.77% positive test were assessed. The incremental diagnostic rate for (ii) the whole gene panel, and (iii) the WES was 4.71% and 11.67%, respectively. The diverse analytical approaches increased the number of VUSs and incidental findings. Indeed, the use of WES highlights that there is a small percentage of syndromic conditions that standard analysis would not have detected. Moreover, the use of targeted sequencing coupled with "narrow" analytical approach prevents the detection of variants in actionable genes that could allow for preventive treatment. Our data suggest that genetic testing might aid clinicians in the diagnosis of inheritable cardiac disorders.
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Secuenciación del Exoma , Pruebas Genéticas , Humanos , Pruebas Genéticas/métodos , Pruebas Genéticas/normas , Femenino , Masculino , Adulto , Cardiopatías/genética , Cardiopatías/diagnóstico , Persona de Mediana Edad , Cardiología/normas , Cardiología/métodos , Europa (Continente) , Predisposición Genética a la Enfermedad , Adolescente , Anciano , Adulto Joven , Niño , Guías de Práctica Clínica como Asunto , Exoma/genética , Preescolar , Cardiomiopatías/genética , Cardiomiopatías/diagnósticoRESUMEN
AIMS: Direct oral anticoagulants (DOACs) are increasingly used off-label to treat patients with left ventricular thrombus (LVT). We analysed available meta-data comparing DOACs and vitamin K antagonists (VKAs) for efficacy and safety. METHODS: We conducted a systematic search and meta-analysis of observational and randomized data comparing DOACs vs. VKAs in patients with LVT. Endpoints of interest were stroke or systemic embolism, thrombus resolution, all-cause death, and a composite bleeding endpoint. Estimates were pooled using a random-effects model meta-analysis, and their robustness was investigated using sensitivity and influential analyses. RESULTS: We identified 22 articles (18 observational studies, 4 small randomized clinical trials) reporting on a total of 3587 patients (2489 VKA vs. 1098 DOAC therapy). The pooled estimates for stroke or systemic embolism [odds ratio (OR): 0.81; 95% confidence interval (CI): 0.57, 1.15] and thrombus resolution (OR: 1.12; 95% CI: 0.86, 1.46) were comparable, and there was low heterogeneity overall across the included studies. The use of DOACs was associated with lower odds of all-cause death (OR: 0.65; 95% CI: 0.46, 0.92) and a composite bleeding endpoint (OR: 0.67; 95% CI: 0.47, 0.97). A risk of bias was evident particularly for observational reports, with some publication bias suggested in funnel plots. CONCLUSION: In this comprehensive analysis of mainly observational data, the use of DOACs was not associated with a significant difference in stroke or systemic embolism, or thrombus resolution, compared with VKA therapy. The use of DOACs was associated with a lower rate of all-cause death and fewer bleeding events. Adequately sized randomized clinical trials are needed to confirm these findings, which could allow a wider adoption of DOACs in patients with LVT.
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Cardiopatías , Hemorragia , Trombosis , Humanos , Administración Oral , Trombosis/mortalidad , Trombosis/tratamiento farmacológico , Trombosis/prevención & control , Trombosis/diagnóstico , Hemorragia/inducido químicamente , Resultado del Tratamiento , Factores de Riesgo , Cardiopatías/mortalidad , Cardiopatías/diagnóstico , Cardiopatías/tratamiento farmacológico , Cardiopatías/complicaciones , Anticoagulantes/efectos adversos , Anticoagulantes/administración & dosificación , Ventrículos Cardíacos/efectos de los fármacos , Femenino , Medición de Riesgo , Masculino , Accidente Cerebrovascular/mortalidad , Accidente Cerebrovascular/diagnóstico , Accidente Cerebrovascular/prevención & control , Anciano , Inhibidores del Factor Xa/efectos adversos , Inhibidores del Factor Xa/administración & dosificación , Vitamina K/antagonistas & inhibidores , Persona de Mediana EdadRESUMEN
Arterial hypertension (AH) is one of the most common pathologic conditions and uncontrolled AH is a leading risk factor for cardiovascular disease and mortality. AH chronically causes myocardial and arterial remodelling with hemodynamic changes affecting the heart and other organs, with potentially irreversible consequences leading to poor outcomes. Therefore, a proper and early treatment of AH is crucial after the diagnosis. Beyond medical treatment, physical exercise also plays a therapeutic role in reducing blood pressure, given its potential effects on sympathetic tone, renin-angiotensin-aldosterone system, and endothelial function. International scientific societies recommend physical exercise among lifestyle modifications to treat AH in the first stages of the disease. Moreover, some studies have also shown its usefulness in addition to drugs to reduce blood pressure further. Therefore, an accurate, personalized exercise prescription is recommended to optimize the prevention and treatment of hypertension. On the other hand, uncontrolled AH in athletes requires proper risk stratification and careful evaluation to practice competitive sports safely. Moreover, the differential diagnosis between hypertensive heart disease and athlete's heart is sometimes challenging and requires a careful and comprehensive interpretation in order not to misinterpret the clinical findings. The present review aims to discuss the relationship between hypertensive heart disease and physical exercise, from diagnostic tools to prevention and treatment strategies.