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Heart failure (HF) is a growing epidemic, affecting millions of people worldwide, and is a major cause of mortality, morbidity, and impaired quality of life. Traditional cardiac rehabilitation is a valuable approach to the physical and quality-of-life recovery of patients with cardiovascular disease. The innovative approach of remote monitoring through telemedicine offers a solution based on modern technologies, enabling continuous collection of health data outside the hospital environment. Remote monitoring devices present challenges that could adversely affect patient adherence, resulting in the risk of dropout. By applying a cognitive-behavioral model, we aim to identify the antecedents of dropout behavior among patients adhering to traditional cardiac rehabilitation programs and remote monitoring in order to improve the latter. Our study was conducted from October 2023 to January 2024. In the first stage, we used data from literature consultation. Subsequently, data were collected from the direct experience of 49 health workers related to both remote monitoring and traditional treatment, recruited from the authors' workplace. Results indicate that patients with cardiovascular disease tend to abandon remote monitoring programs more frequently than traditional cardiac rehabilitation therapies. It is critical to design approaches that take these barriers into account to improve adherence and patient satisfaction. This analysis identified specific antecedents to address, helping to improve current monitoring models. This is crucial to promote care continuity and to achieve self-management by patients in the future.
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Cardiovascular and neurological diseases are a major cause of mortality and morbidity worldwide. Such diseases require careful monitoring to effectively manage their progression. Artificial intelligence (AI) offers valuable tools for this purpose through its ability to analyse data and identify predictive patterns. This review evaluated the application of AI in cardiac and neurological diseases for their clinical impact on the general population. We reviewed studies on the application of AI in the neurological and cardiological fields. Our search was performed on the PubMed, Web of Science, Embase and Cochrane library databases. Of the initial 5862 studies, 23 studies met the inclusion criteria. The studies showed that the most commonly used algorithms in these clinical fields are Random Forest and Artificial Neural Network, followed by logistic regression and Support-Vector Machines. In addition, an ECG-AI algorithm based on convolutional neural networks has been developed and has been widely used in several studies for the detection of atrial fibrillation with good accuracy. AI has great potential to support physicians in interpretation, diagnosis, risk assessment and disease management.
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BACKGROUND: Heart failure is an epidemiologically relevant disease because of the aging population and widespread lifestyles that promote it. In addition to the acute event, it is possible for the disease to become chronic with periodic flare-ups. It is essential to study pathology from a diagnostic and prognostic point of view and to identify parameters for effective monitoring. In addition, heart failure is associated with multiple comorbidities, including cognitive impairment, which is monitored clinically but not through specific biomarkers in these patients. The purpose of this review is to gather the most recent scientific evidence on a few possible biomarkers previously identified for monitoring heart failure and associated cognitive impairment. METHODS: We surveyed studies inherent to a set of previously identified markers, evaluating English-language articles from the past five years conducted in adult heart failure patient populations. We used the databases PubMed, Web of Sciences, and Cochrane Library for search studies, and we considered articles published in journals with an impact factor greater than five in the publication year. RESULTS: Among the biomarkers evaluated, a concordant indication for serial measurements for heart failure monitoring emerged only for interleukin-6. For the other markers, there is still little evidence available, which is interesting but sometimes conflicting. Interesting studies have also emerged for biomarkers of cognitive decline assessed in patients with heart failure, confirming the hypotheses of the increasingly studied heart-brain correlation. CONCLUSION: Certainly, further studies in large populations are needed to identify effective biomarkers for monitoring heart failure and associated cognitive impairment.
Assuntos
Disfunção Cognitiva , Insuficiência Cardíaca , Adulto , Humanos , Idoso , Disfunção Cognitiva/diagnóstico , Insuficiência Cardíaca/complicações , Insuficiência Cardíaca/diagnóstico , Insuficiência Cardíaca/epidemiologia , Biomarcadores , Bases de Dados Factuais , Interleucina-6RESUMO
Background and Objectives: Takotsubo Syndrome (TS) constitutes one of the most recent clinical realities in modern cardiology. It is clinically similar to the acute coronary syndrome, in the absence of obstructive coronary artery disease. Case Presentation: We described a case of a female patient affected by TS and left ventricular apical thrombus. Several studies described the cardiological syndrome, overlooking the neuropsychological and psychological outcomes. We aimed to assess the advantages of an integrated, multidisciplinary and multifunctional rehabilitation. Conclusions: This specific training contributed to reducing the tolerance to frustration given by her communication's difficulty. It has favored a good therapeutic alliance and a good success of the psychotherapeutic path, guaranteeing the reduction of her anxious symptoms and an improvement in the emotive and relational status.
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Doença da Artéria Coronariana , Cardiomiopatia de Takotsubo , Trombose , Cognição , Doença da Artéria Coronariana/complicações , Feminino , Humanos , Fala , Cardiomiopatia de Takotsubo/complicações , Cardiomiopatia de Takotsubo/diagnóstico , Trombose/etiologiaRESUMO
We describe two patients in whom serious bradycardia and arterial hypotension occurred after a small intrathecal baclofen (ITB) test bolus. Both patients suffered from severe spasticity (one due to brain injury, one due to spinal cord injury). Medical history and diagnostic examinations revealed no previous cardiological problems. Ten minutes following a 50 µg ITB bolus, patient 1 developed bradycardia (58 bpm) and incomplete right branch block, lasting for 3 hours. In patient 2, a 20 µg ITB bolus was followed after 5 minutes by severe bradycardia (30 bpm) and hypotension (60/30 mmHg), without loss of consciousness, lasting for 10 minutes. Exaggerated muscle tone was alleviated in both patients after 2 hours by the applied doses. Neither patient underwent implantation of a permanent pump system, both were continued on oral baclofen. Despite numerous unremarkable repeat cardiological exams, both patients suffered fatal cardiac arrest one and two months later, respectively. Our observations suggest that ITB may herald cardiovascular dysfunction in predisposed patients. Careful cardiological examination before ITB treatment, and close monitoring during ITB testing in particular, is advised.