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  1. Article ; Online: Validation of an early vascular aging construct model for comprehensive cardiovascular risk assessment using external risk indicators for improved clinical utility: data from the EVasCu study.

    Cavero-Redondo, Iván / Saz-Lara, Alicia / Martínez-García, Irene / Otero-Luis, Iris / Martínez-Rodrigo, Arturo

    Cardiovascular diabetology

    2024  Volume 23, Issue 1, Page(s) 33

    Abstract: Background: Cardiovascular diseases (CVDs) remain a major global health concern, necessitating advanced risk assessment beyond traditional factors. Early vascular aging (EVA), characterized by accelerated vascular changes, has gained importance in ... ...

    Abstract Background: Cardiovascular diseases (CVDs) remain a major global health concern, necessitating advanced risk assessment beyond traditional factors. Early vascular aging (EVA), characterized by accelerated vascular changes, has gained importance in cardiovascular risk assessment.
    Methods: The EVasCu study in Spain examined 390 healthy participants using noninvasive measurements. A construct of four variables (Pulse Pressure, Pulse Wave Velocity, Glycated Hemoglobin, Advanced Glycation End Products) was used for clustering. K-means clustering with principal component analysis revealed two clusters, healthy vascular aging (HVA) and early vascular aging (EVA). External validation variables included sociodemographic, adiposity, glycemic, inflammatory, lipid profile, vascular, and blood pressure factors.
    Results: EVA cluster participants were older and exhibited higher adiposity, poorer glycemic control, dyslipidemia, altered vascular properties, and higher blood pressure. Significant differences were observed for age, smoking status, body mass index, waist circumference, fat percentage, glucose, insulin, C-reactive protein, diabetes prevalence, lipid profiles, arterial stiffness, and blood pressure levels. These findings demonstrate the association between traditional cardiovascular risk factors and EVA.
    Conclusions: This study validates a clustering model for EVA and highlights its association with established risk factors. EVA assessment can be integrated into clinical practice, allowing early intervention and personalized cardiovascular risk management.
    MeSH term(s) Humans ; Risk Factors ; Cardiovascular Diseases/diagnosis ; Cardiovascular Diseases/epidemiology ; Cardiovascular Diseases/etiology ; Pulse Wave Analysis ; Risk Assessment ; Heart Disease Risk Factors ; Aging ; Lipids ; Vascular Stiffness
    Chemical Substances Lipids
    Language English
    Publishing date 2024-01-13
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2093769-6
    ISSN 1475-2840 ; 1475-2840
    ISSN (online) 1475-2840
    ISSN 1475-2840
    DOI 10.1186/s12933-023-02104-y
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article: Effect of Botulinum Toxin Injections in the Treatment of Spasticity of Different Etiologies: An Umbrella Review.

    Otero-Luis, Iris / Martinez-Rodrigo, Arturo / Cavero-Redondo, Iván / Moreno-Herráiz, Nerea / Martínez-García, Irene / Saz-Lara, Alicia

    Pharmaceuticals (Basel, Switzerland)

    2024  Volume 17, Issue 3

    Abstract: Background: Spasticity is a very common neurological sequelae that significantly impacts the quality of life of patients, affecting more than 12 million people worldwide. Botulinum toxin is considered a reversible treatment for spasticity, but due to ... ...

    Abstract Background: Spasticity is a very common neurological sequelae that significantly impacts the quality of life of patients, affecting more than 12 million people worldwide. Botulinum toxin is considered a reversible treatment for spasticity, but due to the large amount of available evidence, synthesis seems necessary. Therefore, we conducted an overview of existing systematic reviews and meta-analyses to evaluate the effect of botulinum toxin injections in the treatment of spasticity of different etiologies.
    Methods: A systematic search of different databases, including Pubmed, Scopus, the Cochrane Library, and Web of Science, was performed from inception to February 2024. Standardized mean differences (SMDs) and their respective 95% confidence intervals (CIs) were calculated to assess the effect of botulinum toxin compared to that of the control treatment using the Modified Ashworth Scale (MAS). All the statistical analyses were performed using STATA 15 software.
    Results: 28 studies were included in the umbrella review. The effect of botulinum toxin injections on spasticity, as measured by the MAS, was significantly lower in all but three studies, although these studies also supported the intervention. The SMDs reported by the meta-analyses ranged from -0.98 to -0.01.
    Conclusion: Botulinum toxin injections were effective at treating spasticity of different etiologies, as indicated by the measurements on the MAS. This implies an improvement in muscle tone and, consequently, in the patient's mobility and quality of life.
    Language English
    Publishing date 2024-02-28
    Publishing country Switzerland
    Document type Journal Article ; Review
    ZDB-ID 2193542-7
    ISSN 1424-8247
    ISSN 1424-8247
    DOI 10.3390/ph17030310
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article: Development of a recommendation system and data analysis in personalized medicine: an approach towards healthy vascular ageing.

    Martinez-Rodrigo, Arturo / Castillo, Jose Carlos / Saz-Lara, Alicia / Otero-Luis, Iris / Cavero-Redondo, Iván

    Health information science and systems

    2024  Volume 12, Issue 1, Page(s) 34

    Abstract: Purpose: Understanding early vascular ageing has become crucial for preventing adverse cardiovascular events. To this respect, recent AI-based risk clustering models offer early detection strategies focused on healthy populations, yet their complexity ... ...

    Abstract Purpose: Understanding early vascular ageing has become crucial for preventing adverse cardiovascular events. To this respect, recent AI-based risk clustering models offer early detection strategies focused on healthy populations, yet their complexity limits clinical use. This work introduces a novel recommendation system embedded in a web app to assess and mitigate early vascular ageing risk, leading patients towards improved cardiovascular health.
    Methods: This system employs a methodology that calculates distances within multidimensional spaces and integrates cost functions to obtain personalized optimisation of recommendations. It also incorporates a classification system for determining the intensity levels of the clinical interventions.
    Results: The recommendation system showed high efficiency in identifying and visualizing individuals at high risk of early vascular ageing among healthy patients. Additionally, the system corroborated its consistency and reliability in generating personalized recommendations among different levels of granularity, emphasizing its focus on moderate or low-intensity recommendations, which could improve patient adherence to the intervention.
    Conclusion: This tool might significantly aid healthcare professionals in their daily analysis, improving the prevention and management of cardiovascular diseases.
    Language English
    Publishing date 2024-05-03
    Publishing country England
    Document type Journal Article
    ZDB-ID 2697647-X
    ISSN 2047-2501
    ISSN 2047-2501
    DOI 10.1007/s13755-024-00292-9
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Detection of Negative Stress through Spectral Features of Electroencephalographic Recordings and a Convolutional Neural Network.

    Martínez-Rodrigo, Arturo / García-Martínez, Beatriz / Huerta, Álvaro / Alcaraz, Raúl

    Sensors (Basel, Switzerland)

    2021  Volume 21, Issue 9

    Abstract: In recent years, electroencephalographic (EEG) signals have been intensively used in the area of emotion recognition, partcularly in distress identification due to its negative impact on physical and mental health. Traditionally, brain activity has been ... ...

    Abstract In recent years, electroencephalographic (EEG) signals have been intensively used in the area of emotion recognition, partcularly in distress identification due to its negative impact on physical and mental health. Traditionally, brain activity has been studied from a frequency perspective by computing the power spectral density of the EEG recordings and extracting features from different frequency sub-bands. However, these features are often individually extracted from single EEG channels, such that each brain region is separately evaluated, even when it has been corroborated that mental processes are based on the coordination of different brain areas working simultaneously. To take advantage of the brain's behaviour as a synchronized network, in the present work, 2-D and 3-D spectral images constructed from common 32 channel EEG signals are evaluated for the first time to discern between emotional states of calm and distress using a well-known deep-learning algorithm, such as AlexNet. The obtained results revealed a significant improvement in the classification performance regarding previous works, reaching an accuracy about 84%. Moreover, no significant differences between the results provided by the diverse approaches considered to reconstruct 2-D and 3-D spectral maps from the original location of the EEG channels over the scalp were noticed, thus suggesting that these kinds of images preserve original spatial brain information.
    MeSH term(s) Algorithms ; Brain ; Electroencephalography ; Emotions ; Neural Networks, Computer
    Language English
    Publishing date 2021-04-27
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2052857-7
    ISSN 1424-8220 ; 1424-8220
    ISSN (online) 1424-8220
    ISSN 1424-8220
    DOI 10.3390/s21093050
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Evaluation of Brain Functional Connectivity from Electroencephalographic Signals Under Different Emotional States.

    García-Martínez, Beatriz / Fernández-Caballero, Antonio / Martínez-Rodrigo, Arturo / Alcaraz, Raúl / Novais, Paulo

    International journal of neural systems

    2022  Volume 32, Issue 10, Page(s) 2250026

    Abstract: The identification of the emotional states corresponding to the four quadrants of the valence/arousal space has been widely analyzed in the scientific literature by means of multiple techniques. Nevertheless, most of these methods were based on the ... ...

    Abstract The identification of the emotional states corresponding to the four quadrants of the valence/arousal space has been widely analyzed in the scientific literature by means of multiple techniques. Nevertheless, most of these methods were based on the assessment of each brain region separately, without considering the possible interactions among different areas. In order to study these interconnections, this study computes for the first time the functional connectivity metric called cross-sample entropy for the analysis of the brain synchronization in four groups of emotions from electroencephalographic signals. Outcomes reported a strong synchronization in the interconnections among central, parietal and occipital areas, while the interactions between left frontal and temporal structures with the rest of brain regions presented the lowest coordination. These differences were statistically significant for the four groups of emotions. All emotions were simultaneously classified with a 95.43% of accuracy, overcoming the results reported in previous studies. Moreover, the differences between high and low levels of valence and arousal, taking into account the state of the counterpart dimension, also provided notable findings about the degree of synchronization in the brain within different emotional conditions and the possible implications of these outcomes from a psychophysiological point of view.
    MeSH term(s) Arousal/physiology ; Brain/physiology ; Electroencephalography ; Emotions/physiology
    Language English
    Publishing date 2022-04-23
    Publishing country Singapore
    Document type Journal Article
    ISSN 1793-6462
    ISSN (online) 1793-6462
    DOI 10.1142/S0129065722500265
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article: Editorial: Physiological computing of social cognition, volume II.

    Fernández-Caballero, Antonio / Hussain, Amir / Latorre, José Miguel / Martínez-Rodrigo, Arturo / Rodriguez-Jimenez, Roberto / Fernández-Sotos, Patricia

    Frontiers in human neuroscience

    2023  Volume 17, Page(s) 1152291

    Language English
    Publishing date 2023-02-14
    Publishing country Switzerland
    Document type Editorial
    ZDB-ID 2425477-0
    ISSN 1662-5161
    ISSN 1662-5161
    DOI 10.3389/fnhum.2023.1152291
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article: Effectiveness of Extracorporeal Shock Wave Therapy in Treatment of Spasticity of Different Aetiologies: A Systematic Review and Meta-Analysis.

    Otero-Luis, Iris / Cavero-Redondo, Iván / Álvarez-Bueno, Celia / Martinez-Rodrigo, Arturo / Pascual-Morena, Carlos / Moreno-Herráiz, Nerea / Saz-Lara, Alicia

    Journal of clinical medicine

    2024  Volume 13, Issue 5

    Abstract: ... ...

    Abstract Background
    Language English
    Publishing date 2024-02-26
    Publishing country Switzerland
    Document type Journal Article ; Review
    ZDB-ID 2662592-1
    ISSN 2077-0383
    ISSN 2077-0383
    DOI 10.3390/jcm13051323
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: Deep Support Vector Machines for the Identification of Stress Condition from Electrodermal Activity.

    Sánchez-Reolid, Roberto / Martínez-Rodrigo, Arturo / López, María T / Fernández-Caballero, Antonio

    International journal of neural systems

    2020  Volume 30, Issue 7, Page(s) 2050031

    Abstract: Early detection of stress condition is beneficial to prevent long-term mental illness like depression and anxiety. This paper introduces an accurate identification of stress/calm condition from electrodermal activity (EDA) signals. The acquisition of EDA ...

    Abstract Early detection of stress condition is beneficial to prevent long-term mental illness like depression and anxiety. This paper introduces an accurate identification of stress/calm condition from electrodermal activity (EDA) signals. The acquisition of EDA signals from a commercial wearable as well as their storage and processing are presented. Several time-domain, frequency-domain and morphological features are extracted over the skin conductance response of the EDA signals. Afterwards, a classification is undergone by using several classical support vector machines (SVMs) and deep support vector machines (D-SVMs). In addition, several binary classifiers are also compared with SVMs in the stress/calm identification task. Moreover, a series of video clips evoking calm and stress conditions have been viewed by 147 volunteers in order to validate the classification results. The highest F1-score obtained for SVMs and D-SVMs are 83% and 92%, respectively. These results demonstrate that not only classical SVMs are appropriate for classification of biomarker signals, but D-SVMs are very competitive in comparison to other classification techniques. In addition, the results have enabled drawing useful considerations for the future use of SVMs and D-SVMs in the specific case of stress/calm identification.
    MeSH term(s) Adult ; Deep Learning ; Electrodiagnosis/methods ; Galvanic Skin Response/physiology ; Humans ; Stress, Psychological/diagnosis ; Stress, Psychological/physiopathology ; Support Vector Machine ; Wearable Electronic Devices
    Language English
    Publishing date 2020-06-05
    Publishing country Singapore
    Document type Journal Article
    ISSN 1793-6462
    ISSN (online) 1793-6462
    DOI 10.1142/S0129065720500318
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: Early vascular aging as an index of cardiovascular risk in healthy adults: confirmatory factor analysis from the EVasCu study.

    Saz-Lara, Alicia / Cavero-Redondo, Iván / Pascual-Morena, Carlos / Martínez-García, Irene / Rodríguez-Gutiérrez, Eva / Lucerón-Lucas-Torres, Maribel / Bizzozero-Peroni, Bruno / Moreno-Herráiz, Nerea / Martínez-Rodrigo, Arturo

    Cardiovascular diabetology

    2023  Volume 22, Issue 1, Page(s) 209

    Abstract: Background: The concept of early vascular aging (EVA) represents a potentially beneficial model for future research into the pathophysiological mechanisms underlying the early manifestations of cardiovascular disease. For this reason, the aims of this ... ...

    Abstract Background: The concept of early vascular aging (EVA) represents a potentially beneficial model for future research into the pathophysiological mechanisms underlying the early manifestations of cardiovascular disease. For this reason, the aims of this study were to verify by confirmatory factor analysis the concept of EVA on a single factor based on vascular, clinical and biochemical parameters in a healthy adult population and to develop a statistical model to estimate the EVA index from variables collected in a dataset to classify patients into different cardiovascular risk groups: healthy vascular aging (HVA) and EVA.
    Methods: The EVasCu study, a cross-sectional study, was based on data obtained from 390 healthy adults. To examine the construct validity of a single-factor model to measure accelerated vascular aging, different models including vascular, clinical and biochemical parameters were examined. In addition, unsupervised clustering techniques (using both K-means and hierarchical methods) were used to identify groups of patients sharing similar characteristics in terms of the analysed variables to classify patients into different cardiovascular risk groups: HVA and EVA.
    Results: Our data show that a single-factor model including pulse pressure, glycated hemoglobin A1c, pulse wave velocity and advanced glycation end products shows the best construct validity for the EVA index. The optimal value of the risk groups to separate patients is K = 2 (HVA and EVA).
    Conclusions: The EVA index proved to be an adequate model to classify patients into different cardiovascular risk groups, which could be valuable in guiding future preventive and therapeutic interventions.
    MeSH term(s) Humans ; Adult ; Risk Factors ; Cardiovascular Diseases/diagnosis ; Cardiovascular Diseases/epidemiology ; Cross-Sectional Studies ; Pulse Wave Analysis ; Heart Disease Risk Factors ; Factor Analysis, Statistical ; Aging
    Language English
    Publishing date 2023-08-17
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2093769-6
    ISSN 1475-2840 ; 1475-2840
    ISSN (online) 1475-2840
    ISSN 1475-2840
    DOI 10.1186/s12933-023-01947-9
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article: Editorial: Physiological Computing of Social Cognition.

    Fernández-Caballero, Antonio / Miguel Latorre, José / Martínez-Rodrigo, Arturo / Rodriguez-Jimenez, Roberto / Hussain, Amir

    Frontiers in human neuroscience

    2019  Volume 13, Page(s) 326

    Language English
    Publishing date 2019-09-18
    Publishing country Switzerland
    Document type Editorial
    ZDB-ID 2425477-0
    ISSN 1662-5161
    ISSN 1662-5161
    DOI 10.3389/fnhum.2019.00326
    Database MEDical Literature Analysis and Retrieval System OnLINE

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