Hervás Marín, David

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    Publication
    Risk Factors for Anastomotic Leak After Colon Resection for Cancer: Multivariate Analysis and Nomogram From a Multicentric, Prospective, National Study With 3193 Patients
    (Lippincott Williams & Wilkins, 2015-08) Frasson, Matteo; Flor, Blas; Alonso Ramos, José Luis; Granero-Castro, Pablo; Hervás Marín, David; Alvarez, Miguel Angel; Garcia, Maria Jesus; Sanchez, Juan Manuel; Garcia-Granero, Eduardo; Departamento de Estadística e Investigación Operativa Aplicadas y Calidad; Escuela Politécnica Superior de Alcoy; Escuela Técnica Superior de Ingeniería Agronómica y del Medio Natural; Instituto de Instrumentación para Imagen Molecular; Takeda Pharmaceutical Company, Ltd.
    [EN] Objective: To determine pre-/intraoperative risk factors for anastomotic leak after colon resection for cancer and to create a practical instrument for predicting anastomotic leak risk. Background: Anastomotic leak is still the most dreaded complication in colorectal surgery. Many risk factors have been identified to date, but multicentric prospective studies on anastomotic leak after colon resection are lacking. Methods: Fifty-two hospitals participated in this prospective, observational study. Data of 3193 patients, operated for colon cancer with primary anastomosis without stoma, were included in a prospective online database (September 2011-September 2012). Forty-two pre-/intraoperative variables, related to patient, tumor, surgical procedure, and hospital, were analyzed as potential independent risk factors for anastomotic leak (60-day follow-up). A nomogram was created to easily predict the risk of anastomotic leak for a given patient.
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    COVID-19 outbreaks analysis in the Valencian Region of Spain in the prelude of the third wave
    (Frontiers Media S.A., 2022-11-17) Fuente Herraiz, David; Hervás Marín, David; Rebollo Pedruelo, Miguel; Conejero Casares, José Alberto; Oliver, Nuria; Departamento de Sistemas Informáticos y Computación; Instituto Universitario de Tecnologías de la Información y Comunicaciones; Departamento de Matemática Aplicada; Departamento de Estadística e Investigación Operativa Aplicadas y Calidad; Instituto Universitario de Matemática Pura y Aplicada; Escuela Politécnica Superior de Alcoy; Escuela Técnica Superior de Ingeniería Informática; Escuela Técnica Superior de Ingeniería Agronómica y del Medio Natural; Instituto Universitario Valenciano de Investigación en Inteligencia Artificial; Fundación BBVA; Generalitat Valenciana
    [EN] IntroductionThe COVID-19 pandemic has led to unprecedented social and mobility restrictions on a global scale. Since its start in the spring of 2020, numerous scientific papers have been published on the characteristics of the virus, and the healthcare, economic and social consequences of the pandemic. However, in-depth analyses of the evolution of single coronavirus outbreaks have been rarely reported. MethodsIn this paper, we analyze the main properties of all the tracked COVID-19 outbreaks in the Valencian Region between September and December of 2020. Our analysis includes the evaluation of the origin, dynamic evolution, duration, and spatial distribution of the outbreaks. ResultsWe find that the duration of the outbreaks follows a power-law distribution: most outbreaks are controlled within 2 weeks of their onset, and only a few last more than 2 months. We do not identify any significant differences in the outbreak properties with respect to the geographical location across the entire region. Finally, we also determine the cluster size distribution of each infection origin through a Bayesian statistical model. DiscussionWe hope that our work will assist in optimizing and planning the resource assignment for future pandemic tracking efforts.
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    A score model for the continuous grading of early allograft dysfunction severity
    (John Wiley & Sons, 2015-01) Pareja, Eugenia; Cortes, Miriam; Hervás Marín, David; Mir, José; Valdivieso, Andrés; Castell, Jose Vicente; Lahoz Rodríguez, Agustín Gerardo; Departamento de Estadística e Investigación Operativa Aplicadas y Calidad; Escuela Politécnica Superior de Alcoy; Escuela Técnica Superior de Ingeniería Agronómica y del Medio Natural; Ministerio de Ciencia e Innovación
    [EN] Early allograft dysfunction (EAD) dramatically influences graft and patient outcomes. A lack of consensus on an EAD definition hinders comparisons of liver transplant outcomes and management of recipients among and within centers. We sought to develop a model for the quantitative assessment of early allograft function [Model for Early Allograft Function Scoring (MEAF)] after transplantation. A retrospective study including 1026 consecutive liver transplants was performed for MEAF score development. Multivariate data analysis was used to select a small number of postoperative variables that adequately describe EAD. Then, the distribution of these variables was mathematically modeled to assign a score for each actual variable value. A model, based on easily obtainable clinical parameters (ie, alanine aminotransferase, international normalized ratio, and bilirubin) and scoring liver function from 0 to 10, was built. The MEAF score showed a significant association with patient and graft survival at 3-, 6- and 12-month follow-ups. Hepatic steatosis and age for donors; cold/warm ischemia times and postreperfusion syndrome for surgery; and intensive care unit and hospital stays, Model for End-Stage Liver Disease and Child-Pugh scores, body mass index, and fresh frozen plasma transfusions for recipients were factors associated significantly with EAD. The model was satisfactorily validated by its application to an independent set of 200 patients who underwent liver transplantation at a different center. In conclusion, a model for the quantitative assessment of EAD severity has been developed and validated for the first time. The MEAF provides a more accurate graft function assessment than current categorical classifications and may help clinicians to make early enough decisions on retransplantation benefits. Furthermore, the MEAF score is a predictor of recipient and graft survival.
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    Use of multivariate statistical methods for the analysis of metabolomic data
    (Universitat Politècnica de València, 2019-11-12) Hervás Marín, David; Lahoz Rodriguez, Agustin Gerardo; Prats Montalbán, José Manuel; Departamento de Estadística e Investigación Operativa Aplicadas y Calidad; Escuela Técnica Superior de Ingeniería Industrial; Escuela Politécnica Superior de Alcoy; Escuela Técnica Superior de Ingeniería Agronómica y del Medio Natural; Grupo de Ingeniería Estadística Multivariante GIEM
    [ES] En las últimas décadas los avances tecnológicos han tenido como consecuencia la generación de una creciente cantidad de datos en el campo de la biología y la biomedicina. A día de hoy, las así llamadas tecnologías "ómicas", como la genómica, epigenómica, transcriptómica o metabolómica entre otras, producen bases de datos con cientos, miles o incluso millones de variables. El análisis de datos ómicos presenta una serie de complejidades tanto metodoló-gicas como computacionales que han llevado a una revolución en el desarrollo de nuevos métodos estadísticos específicamente diseñados para tratar con este tipo de datos. A estas complejidades metodológicas hay que añadir que, en la mayor parte de los casos, las restricciones logísticas y/o económicas de los proyectos de investigación suelen conllevar que los tamaños muestrales en estas bases de datos con tantas variables sean muy bajos, lo cual no hace sino empeorar las dificultades de análisis, ya que se tienen muchísimas más variables que observaciones. Entre las técnicas desarrolladas para tratar con este tipo de datos podemos encontrar algunas basadas en la penalización de los coeficientes, como lasso o elastic net, otras basadas en técnicas de proyección sobre estructuras latentes como PCA o PLS y otras basadas en árboles o combinaciones de árboles como random forest. Todas estas técnicas funcionan muy bien sobre distintos datos ómicos presentados en forma de matriz (IxJ). Sin embargo, en ocasiones los datos ómicos pueden estar expandidos, por ejemplo, al tomar medidas repetidas en el tiempo sobre los mismos individuos, encontrándonos con estructuras de datos que ya no son matrices, sino arrays tridimensionales o three-way (IxJxK). En estos casos, la mayoría de las técnicas citadas pierden parte de su aplicabilidad, quedando muy pocas opciones viables para el análisis de este tipo de estructuras de datos. Una de las técnicas que sí es útil para el análisis de estructuras three-way es N-PLS, que permite ajustar modelos predictivos razonablemente precisos, así como interpretarlos mediante distintos gráficos. Sin embargo, relacionado con el problema de la escasez de tamaño muestral relativa al desorbitado número de variables, aparece la necesidad de realizar una selección de variables relacionadas con la variable respuesta. Esto es especialmente cierto en el ámbito de la biología y la biomedicina, ya que no solo se quiere poder predecir lo que va a suceder, sino entender por qué sucede, qué variables están implicadas y, a poder ser, no tener que volver a recoger los cientos de miles de variables para realizar una nueva predicción, sino utilizar unas cuantas, las más importantes, para poder diseñar kits predictivos coste/efectivos de utilidad real. Por ello, el objetivo principal de esta tesis es mejorar las técnicas existentes para el análisis de datos ómicos, específicamente las encaminadas a analizar datos three-way, incorporando la capacidad de selección de variables, mejorando la capacidad predictiva y mejorando la interpretabilidad de los resultados obtenidos. Todo ello se implementará además en un paquete de R completamente documentado, que incluirá todas las funciones necesarias para llevar a cabo análisis completos de datos three-way. El trabajo incluido en esta tesis por tanto, consta de una primera parte teórico-conceptual de desarrollo de la idea del algoritmo, así como su puesta a punto, validación y comprobación de su eficacia; de una segunda parte empírico-práctica de comparación de los resultados del algoritmo con otras metodologías de selección de variables existentes, y de una parte adicional de programación y desarrollo de software en la que se presenta todo el desarrollo del paquete de R, su funcionalidad y capacidades de análisis. El desarrollo y validación de la técnica, así como la publicación del paquete de R, ha permitido ampliar las opciones actuales para el análisis
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    Implementación de aprendizaje colaborativo, software R y evaluación orientada al aprendizaje de competencias en estudiantes de econometría
    (Editorial Universitat Politècnica de València, 2023-10-06) Hervás Marín, David; Carracedo Garnateo, Patricia; Departamento de Estadística e Investigación Operativa Aplicadas y Calidad; Centro de Investigación en Gestión e Ingeniería de Producción; Escuela Politécnica Superior de Alcoy; Escuela Técnica Superior de Ingeniería Agronómica y del Medio Natural
    [ES] En esta innovación docente se ha abordado la problemática de la falta de motivación de los alumnos del grado de dirección y administración de empresas por las asignaturas del área de estadística, así como el aprendizaje demasiado mecánico y poco aplicado que se produce en la materia. En concreto, se implementó el aprendizaje colaborativo a distintos niveles, se adoptó e implementó un sistema de evaluación orientada al aprendizaje de competencias y se adoptó el manejo de un software de programación en todos los ámbitos de la asignatura. Los resultados de la intervención se analizaron mediante el análisis estadístico de una encuesta de elaboración propia con varias preguntas de escala Likert así como con el análisis de las calificaciones de los alumnos. Los resultados muestran un alto grado de satisfacción por parte de los alumnos en todos los ámbitos evaluados mediante la encuesta.
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    NUTRARET: Effect of 2-Year Nutraceutical Supplementation on Redox Status and Visual Function of Patients With Retinitis Pigmentosa: A Randomized, Double-Blind, Placebo-Controlled Trial
    (Frontiers Media S.A., 2022-03-21) Olivares-González, Lorena; Salom, David; González-García, Emilio; Hervás Marín, David; Mejía-Chiqui, Natalia; Melero, Mar; Velasco, Sheyla; Muresan, Bianca Tabita; Campillo, Isabel; Vila-Clérigues, Nieves; Lopez-Briz, Eduardo; Merino-Torres, Juan Francisco; Millán, José María; Soriano del Castillo, José Miguel; Rodrigo, Regina; Departamento de Estadística e Investigación Operativa Aplicadas y Calidad; Escuela Politécnica Superior de Alcoy; Escuela Técnica Superior de Ingeniería Agronómica y del Medio Natural; European Social Fund; Universitat de València; Instituto de Salud Carlos III; Ministerio de Sanidad y Consumo; European Regional Development Fund; Ministerio de Economía y Competitividad; Instituto de Investigación Sanitaria La Fe
    [EN] Oxidative stress plays a major role in the pathogenesis of retinitis pigmentosa (RP). The main goal of this study was to evaluate the effect of 2-year nutritional intervention with antioxidant nutraceuticals on the visual function of RP patients. Secondly, we assessed how nutritional intervention affected ocular and systemic redox status. We carried out a randomized, double-blind, placebo-controlled study. Thirty-one patients with RP participated in the study. RP patients randomly received either a mixture of nutraceuticals (NUT) containing folic acid, vitamin B6, vitamin A, zinc, copper, selenium, lutein, and zeaxanthin or placebo daily for 2 years. At baseline and after 2-year of the nutritional supplementation, visual function, dietetic-nutritional evaluations, serum concentration of nutraceuticals, plasma and aqueous humor concentration of several markers of redox status and inflammation were assessed. Retinal function and structure were assessed by multifocal electroretinogram (mfERG), spectral domain-optical coherence tomography (SD-OCT) and automated visual field (VF) tests. Nutritional status was estimated with validated questionnaires. Total antioxidant capacity, extracellular superoxide dismutase (SOD3), catalase (CAT), and glutathione peroxidase (GPx) activities, protein carbonyl adducts (CAR) content, thiobarbituric acid reactive substances (TBARS) formation (as indicator of lipid peroxidation), metabolites of the nitric oxide (NOX) and cytokine (interleukin 6 and tumor necrosis factor alpha) concentrations were assessed by biochemical and immunological techniques in aqueous humor or/and blood. Bayesian approach was performed to determine the probability of an effect. Region of practical equivalence (ROPE) was used. At baseline, Bayesian analysis revealed a high probability of an altered ocular redox status and to a lesser extent systemic redox status in RP patients compared to controls. Twenty-five patients (10 in the treated arm and 15 in the placebo arm) completed the nutritional intervention. After 2 years of supplementation, patients who received NUT presented better retinal responses (mfERG responses) compared to patients who received placebo. Besides, patients who received NUT showed better ocular antioxidant response (SOD3 activity) and lower oxidative damage (CAR) than those who received placebo. This study suggested that long-term NUT supplementation could slow down visual impairment and ameliorate ocular oxidative stress.
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    Hemodynamic Tolerance of Virtual Reality Intradialysis Exercise Performed during the Last 30 Minutes versus the Beginning of the Hemodialysis Session
    (MDPI AG, 2023-01) García-Testal, Alicia; Martínez-Olmos, Francisco José; Gil Gómez, José Antonio; López-Tercero, Víctor; Lahoz-Cano, Laura; Hervás Marín, David; Cana-Poyatos, Alicia; García-Maset, Rafael; Royo-Maicas, Pilar; Segura-Ortí, Eva; Departamento de Sistemas Informáticos y Computación; Departamento de Estadística e Investigación Operativa Aplicadas y Calidad; Instituto Universitario de Automática e Informática Industrial; Escuela Técnica Superior de Ingeniería Industrial; Escuela Politécnica Superior de Alcoy; Escuela Técnica Superior de Ingeniería Agronómica y del Medio Natural; Fundación Renal Tomás de Osma; Universidad CEU Cardenal Herrera; Agencia Estatal de Investigación
    [EN] Background: Exercise improves the physical function of people suffering from chronic kidney disease on hemodialysis (HD). Virtual reality is a new type of intradialysis exercise that has a positive impact on physical function. Intradialysis exercise is recommended during the first 2 h, but its safety in the last part of the dialysis session is unknown. Methods: This was a pilot sub-study of a clinical trial. Several hemodynamic control variables were recorded, including blood pressure, heart rate, and intradialytic hypotensive events. These variables were recorded during three different HD sessions, one HD session at rest, another HD session with exercise during the first two hours, and one HD session with exercise during the last 30 min of dialysis. The intradialysis virtual reality exercise was performed for a maximum of 30 min. Results: During exercise sessions, there was a significant increase in heart rate (6.65 (4.92, 8.39) bpm; p < 0.001) and systolic blood pressure (6.25 (0.04,12.47) mmHg; p < 0.05). There was no difference in hemodynamic control between the sessions with exercise during the first two hours and the sessions with exercise during the last 30 min. There was no association between intra-dialytic hypotensive events at rest (five events) or exercise at any point (two vs. one event(s), respectively). Conclusion: performing exercise with virtual reality at the end of a hemodialysis session is not associated with hemodynamic instability.
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    Pain in Children and Adolescents with Spinal Muscular Atrophy: A Longitudinal Study from a Patient Registry
    (MDPI AG, 2023-12) Pitarch-Castellano, Inmaculada; Hervás Marín, David; Cattinari, Maria Grazia; Ibáñez Albert, Eugenia; López Lobato, Mercedes; Ñungo Garzón, Nancy Carolina; Rojas, Juan; Puig-Ram, Cristina; Madruga-Garrido, Marcos; Departamento de Estadística e Investigación Operativa Aplicadas y Calidad; Escuela Politécnica Superior de Alcoy; Escuela Técnica Superior de Ingeniería Agronómica y del Medio Natural
    [EN] Spinal muscular atrophy (SMA) is a devastating genetic neurodegenerative disease caused by the insufficient production of Survival Motor Neuron (SMN) protein. It presents different phenotypes with frequent contractures and dislocations, scoliosis, and pain. This study aims to report the prevalence and description of pain and how it affects daily life by analyzing a new ad hoc questionnaire. An observational study of patients under 18 years of age with SMA was conducted at two referral centers in Spain. Data were analyzed using a descriptive analysis and a Bayesian ordinal regression model to assess the association with clinical and demographic variables. Fifty-one individuals were included in this study, 27% of whom reported pain with a median duration of 5.2 years and a mean Visual Analogic Scale (VAS) score of 5. Notably, 77% were receiving disease-modifying treatment, with more than 50% receiving analgesic treatment. The Bayesian model showed that functional status, lower limb contractures, and number of visits have a high probability (>90%) of influencing pain. Thus, the prevalence of pain in the SMA population under 18 years is substantial, and its presence could be associated with lower limb contractures, better functional status, and higher RULM (Revised Upper Limb Module) scores.
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    On the Oral Microbiome of Oral Potentially Malignant and Malignant Disorders: Dysbiosis, Loss of Diversity, and Pathogens Enrichment
    (MDPI AG, 2023-02) Herreros Pomares, Alejandro; Hervás Marín, David; Bagán-Debón, Leticia; Jantus Lewintre, Eloisa; Gimeno-Cardona, Concepción; Bagan, José; Departamento de Estadística e Investigación Operativa Aplicadas y Calidad; Departamento de Biotecnología; Centro Avanzado de Microbiología Aplicada; Escuela Politécnica Superior de Alcoy; Escuela Técnica Superior de Ingeniería Agronómica y del Medio Natural; Instituto de Salud Carlos III
    [EN] The role of dysbiosis in the development and progression of oral potentially malignant disorders (OPMDs) remains largely unknown. Here, we aim to characterize and compare the oral microbiome of homogeneous leucoplakia (HL), proliferative verrucous leukoplakia (PVL), oral squamous cell carcinoma (OSCC), and OSCC preceded by PVL (PVL-OSCC). Fifty oral biopsies from HL (n = 9), PVL (n = 12), OSCC (n = 10), PVL-OSCC (n = 8), and healthy (n = 11) donors were obtained. The sequence of the V3-V4 region of the 16S rRNA gene was used to analyze the composition and diversity of bacterial populations. In the cancer patients, the number of observed amplicon sequence variants (ASVs) was lower and Fusobacteriota constituted more than 30% of the microbiome. PVL and PVL-OSCC patients had a higher abundance of Campilobacterota and lower Proteobacteria than any other group analyzed. A penalized regression was performed to determine which species were able to distinguish groups. HL is enriched in Streptococcus parasanguinis, Streptococcus salivarius, Fusobacterium periodonticum, Prevotella histicola, Porphyromonas pasteri, and Megasphaera micronuciformis; PVL is enriched in Prevotella salivae, Campylobacter concisus, Dialister pneumosintes, and Schaalia odontolytica; OSCC is enriched in Capnocytophaga leadbetteri, Capnocytophaga sputigena, Capnocytophaga gingivalis, Campylobacter showae, Metamycoplasma salivarium, and Prevotella nanceiensis; and PVL-OSCC is enriched in Lachnospiraceae bacterium, Selenomonas sputigena, and Prevotella shahii. There is differential dysbiosis in patients suffering from OPMDs and cancer. To the best of our knowledge, this is the first study comparing the oral microbiome alterations in these groups; thus, additional studies are needed.
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    Virtual Screening of Small Molecules Targeting BCL2 with Machine Learning, Molecular Docking, and MD Simulation
    (MDPI AG, 2024-05) Tondar, Abtin; Sánchez-Herrero, Sergio; Bepari, Asim Kumar; Bahmani, Amir; Calvet Liñán, Laura; Hervás Marín, David; Departamento de Estadística e Investigación Operativa Aplicadas y Calidad; Escuela Politécnica Superior de Alcoy; Escuela Técnica Superior de Ingeniería Agronómica y del Medio Natural
    [EN] This study aimed to identify potential BCL-2 small molecule inhibitors using deep neural networks (DNN) and random forest (RF), algorithms as well as molecular docking and molecular dynamics (MD) simulations to screen a library of small molecules. The RF model classified 61% (2355/3867) of molecules as 'Active'. Further analysis through molecular docking with Vina identified CHEMBL3940231, CHEMBL3938023, and CHEMBL3947358 as top-scored small molecules with docking scores of -11, -10.9, and 10.8 kcal/mol, respectively. MD simulations validated these compounds' stability and binding affinity to the BCL2 protein.