This study aims to analyze the asymmetry between both eyes of the same patient for the early diagnosis of glaucoma. Two imaging modalities, retinal fundus images and optical coherence tomographies ...(OCTs), have been considered in order to compare their different capabilities for glaucoma detection. From retinal fundus images, the difference between cup/disc ratio and the width of the optic rim has been extracted. Analogously, the thickness of the retinal nerve fiber layer has been measured in spectral-domain optical coherence tomographies. These measurements have been considered as asymmetry characteristics between eyes in the modeling of decision trees and support vector machines for the classification of healthy and glaucoma patients. The main contribution of this work is indeed the use of different classification models with both imaging modalities to jointly exploit the strengths of each of these modalities for the same diagnostic purpose based on the asymmetry characteristics between the eyes of the patient. The results show that the optimized classification models provide better performance with OCT asymmetry features between both eyes (sensitivity 80.9%, specificity 88.2%, precision 66.7%, accuracy 86.5%) than with those extracted from retinographies, although a linear relationship has been found between certain asymmetry features extracted from both imaging modalities. Therefore, the resulting performance of the models based on asymmetry features proves their ability to differentiate healthy from glaucoma patients using those metrics. Models trained from fundus characteristics are a useful option as a glaucoma screening method in the healthy population, although with lower performance than those trained from the thickness of the peripapillary retinal nerve fiber layer. In both imaging modalities, the asymmetry of morphological characteristics can be used as a glaucoma indicator, as detailed in this work.
Purpose: The aim of this study was to analyze the relevance of asymmetry features between both eyes of the same patient for glaucoma screening using optical coherence tomography. Methods: ...Spectral-domain optical coherence tomography was used to estimate the thickness of the peripapillary retinal nerve fiber layer in both eyes of the patients in the study. These measurements were collected in a dataset from healthy and glaucoma patients. Several metrics for asymmetry in the retinal nerve fiber layer thickness between the two eyes were then proposed. These metrics were evaluated using the dataset by performing a statistical analysis to assess their significance as relevant features in the diagnosis of glaucoma. Finally, the usefulness of these asymmetry features was demonstrated by designing supervised machine learning models that can be used for the early diagnosis of glaucoma. Results: Machine learning models were designed and optimized, specifically decision trees, based on the values of proposed asymmetry metrics. The use of these models on the dataset provided good classification of the patients (accuracy 88%, sensitivity 70%, specificity 93% and precision 75%). Conclusions: The obtained machine learning models based on retinal nerve fiber layer asymmetry are simple but effective methods which offer a good trade-off in classification of patients and simplicity. The fast binary classification relies on a few asymmetry values of the retinal nerve fiber layer thickness, allowing their use in the daily clinical practice for glaucoma screening.
Glaucoma is a neurodegenerative disease process that leads to progressive damage of the optic nerve to produce visual impairment and blindness. Spectral-domain OCT technology enables peripapillary ...circular scans of the retina and the measurement of the thickness of the retinal nerve fiber layer (RNFL) for the assessment of the disease status or progression in glaucoma patients. This paper describes a new approach to segment and measure the retinal nerve fiber layer in peripapillary OCT images. The proposed method consists of two stages. In the first one, morphological operators robustly detect the coarse location of the layer boundaries, despite the speckle noise and diverse artifacts in the OCT image. In the second stage, deformable models are initialized with the results of the previous stage to perform a fine segmentation of the boundaries, providing an accurate measurement of the entire RNFL. The results of the RNFL segmentation were qualitatively assessed by ophthalmologists, and the measurements of the thickness of the RNFL were quantitatively compared with those provided by the OCT inbuilt software as well as the state-of-the-art methods.
Running retraining programs focused on concurrent feedback of acceleration impacts have been demonstrated to be a good strategy to reduce running-related injuries (RRI), as well as to improve running ...economy and reduce acceleration impacts and injury running incidence. Traditionally, impacts have been registered by mean of accelerometers attached directly to the athletes, which is inaccessible to the entire population, because it requires laboratory conditions. This study investigated the validity and reliability of a new device integrated directly into the treadmill, compared to a traditional acceleration impact system. Thirty healthy athletes with no history of RRI were tested on two separate days over the instrumented treadmill (AccTrea) and simultaneously with an acceleration impact system attached to the participant (AccAthl). AccTrea was demonstrated to be a valid and reliable tool for measuring spatio-temporal parameters like step length (validity intraclass correlation coefficient (ICC) = 0.94; reliability ICC = 0.92), step time (validity ICC = 0.95; reliability ICC = 0.96), and step frequency (validity ICC = 0.95; reliability ICC = 0.96) during running. Peak acceleration impact variables showed a high reliability for the left (reliability ICC = 0.88) and right leg (reliability ICC = 0.85), and peak impact asymmetry showed a modest validity (ICC = 0.55). These results indicated that the AccTrea system is a valid and reliable way to assess spatio-temporal variables, and a reliable tool for measuring acceleration impacts during running.
Fatigue causes kinematics modifications during running, and it could be related to injuries. The aim was to identify and compare the effects of central and peripheral fatigue on angular kinematics ...and spatiotemporal parameters during running. Angular kinematics and spatiotemporal parameters were evaluated using an infrared motion capture system and were registered during 2 min treadmill running in pre- and post-fatigue states in eighteen male recreational runners. Central fatigue was induced by a 30 min running fatigue protocol on a treadmill, while peripheral fatigue in quadriceps and hamstrings muscles was induced by an isokinetic dynamometer fatigue protocol. Central fatigue increased the anterior shank oscillation during the initial contact, knee flexion during the maximum absorption, posterior shank oscillation during propulsion, and stance time (p < 0.05). Peripheral fatigue decreased ankle dorsiflexion during initial contact and increased knee flexion and posterior shank oscillation during propulsion (p < 0.05). Moreover, central fatigue increased to a greater extent the hip and knee flexion and ankle dorsiflexion during initial contact and maximum absorption as well as stance time and propulsion time (p < 0.05). These results suggested that central fatigue causes greater increases in the range of movements during the midstance than peripheral fatigue.
An increase in the popularity of running can be seen over the last decades, with a large number of injuries on it. Most of the running injuries are related to impact accelerations and are due to ...overuse. In order to reduce the risk of injury or to improve performance and health new treadmill designs have been created, as it can be the curved non-motorized treadmill. The aim of this study was to analyse impact accelerations, spatio-temporal parameters and perceptual differences while running on curved non-motorized treadmill (cNMT) compared to motorized treadmill (MT) at different speeds. Therefore, 27 recreational runners completed two tests consisting of 10 min warm-up and three bouts of 8 min running at 2.77 m/s, 3.33 m/s and self-selected speed on cNMT and MT, previously randomised. Although the surface did not influence spatio-temporal parameters, a reduction in impact accelerations, head acceleration rate (mean effect size ES = 0.86), tibia peak (mean ES = 0.45) and tibia magnitude (mean ES = 0.55), was observed while running on cNMT in comparison with running on MT. Moreover, higher heart rate (HR) (mean ES = 0.51) and rating of perceived effort (RPE) (mean ES = 0.34) were found while running on cNMT. These findings demonstrated that higher intensity training and lower impact accelerations are experimented on cNMT, what can be used by trainers and athletes while planning training sessions.
Los modelos deformables son métodos matemáticos que se utilizan para delinear los bordes o parte externa de objetos por medio de curvas, superficies o volúmenes que se deforman bajo la influencia de ...fuerzas internas y externas. Estos modelos se han utilizado ampliamente en las últimas tres décadas debido a su amplio abanico de aplicaciones en las áreas del procesamiento de imagen y la visión por computador. La principal motivación para el empleo de los modelos se fundamenta en la necesidad de disponer de herramientas fiables que permitan analizar, modelar y reconstruir conjuntos de datos. Lo obtención de estas herramientas supone un reto, puesto que deben ser capaces de recuperar información de alto nivel a partir de señales de bajo nivel, reduciendo al mínimo el impacto del ruido y otros efectos no deseados.En el enfoque original, los modelos paramétricos quedan determinados a partir de la minimización de un funcional de energía por medio de la ecuación de Euler¬Lagrange. Para la discretización de las variables espaciales se utiliza el método de elementos finitos. La forma y posición del modelo se deriva de un sistema en ecuaciones en derivadas parciales (PDE) de segundo orden, el cual se obtiene al aplicar el cálculo variacional al funcional de energía.Esta tesis doctoral presenta un nuevo enfoque de los modelos deformables paramétricos, justificando asimismo su validez. El propósito de este trabajo es extender la teoría clásica a la formulación de modelos deformables multidimensionales, trasladando al mismo tiempo la formulación y el proceso iterativo al dominio de Fourier. El interés de este nuevo enfoque reside en analizar, caracterizar y segmentar información extraída de conjuntos de datos multidimensionales mediante un procedimiento más rápido y eficiente que las aproximaciones anteriores. Adicionalmente se ha desarrollado un método para el diseño óptimo de los parámetros dinámicos del modelo, el cual se ha descrito con detalle en la tesis. Deformable models are mathematical methods used for delineating boundaries of objects by means of curves, surfaces or volumes that deform under the influence of internal and external forces. These models have been used and further developed extensively in the last three decades due to their wide range of applications in the field of image processing and computer vision. The main motivation is to provide reliable tools to analyze, model and reconstruct datasets where the challenge lies in retrieving high-level information from low-level signals while minimizing the impact of noise and other unwanted effects. In the original approach, parametric models are determined from the minimization of an energy functional by means of the Euler-Lagrange equation. Finite element method is used for spatial discretization. The shape and position of the model is governed by a second-order Partial Differential Equation system, which is obtained by applying the calculus of variations. This PhD Thesis presents a new approach of parametric deformable models and proves their validity. The aim of this work is to extend the classical theory to the formulation of general multidimensional deformable models while at the same time translating the formulation and iterative process into the Fourier domain. The goal of this approach is the analysis, characterization and segmentation of information retrieved from multidimensional datasets in a faster and more efficient way than previous approaches. In addition, a method for designing the optimal dynamic parameters of the model is appended to this new formulation.
Patients with COVID-19 may present a hypercoagulable state, with an important impact on morbidity and mortality. Because of this situation pulmonary embolism is a frequent complication during the ...course of infection. We present the case of a patient recently discharged, after admission with confirmed COVID-19, who developed a pulmonary embolism and thrombosis of a biological mitral valve prosthesis, producing valve obstruction and stenosis. After 15 days of anticoagulant treatment, resolution of the thrombus and normalisation of prosthetic valve function was observed. This case supports current recommendations of administering full-dose anticoagulation therapy to COVID-19 patients with biological heart valve prosthesis, even after the acute phase of infection.
Les patients atteints de COVID-19 présentent parfois une hypercoagulabilité, ce qui a un retentissement important sur la morbidité et la mortalité. C’est pour cette raison que l’embolie pulmonaire est une complication fréquemment observée chez les patients infectés. Nous présentons le cas d’un patient ayant récemment obtenu son congé de l’hôpital après avoir contracté la COVID-19, qui a présenté une embolie pulmonaire et une thrombose de prothèse mitrale biologique provoquant l’obstruction et la sténose de la valve. Après 15 jours d’anticoagulothérapie, la thrombose s’est résorbée et la prothèse valvulaire fonctionne de nouveau normalement. Ce cas milite en faveur des recommandations actuelles concernant l’administration d’une anticoagulothérapie à dose complète aux patients atteints de COVID-19 ayant une prothèse valvulaire biologique, même après la phase aiguë de l’infection.
We aimed to assess the prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and factors associated with seropositivity and asymptomatic coronavirus disease 2019 (COVID-19) among ...people with HIV (PWH).
This was a cross-sectional study carried out within the cohort of the Spanish HIV Research Network. Participants were consecutive PWH with plasma collected from 1st April to 30th September 2020. We determined SARS-CoV-2 antibodies (Abs) in plasma. Illness severity (NIH criteria) was assessed by a review of medical records and, if needed, participant interviews. Multivariable logistic regression analysis was used to identify predictors of seropositivity among the following variables: sex, age, country of birth, education level, comorbidities (hypertension, chronic heart disease, diabetes mellitus, non-AIDS-related cancer, chronic kidney disease, cirrhosis), route of HIV acquisition, prior AIDS, CD4+ cell count, HIV viral load, nucleoside/nucleotide reverse transcriptase inhibitor (N tRTI) backbone, type of third antiretroviral drug, and month of sample collection.
Of 1076 PWH (88.0% males, median age 43 years, 97.7% on antiretroviral therapy, median CD4+ 688 cells/mm3, 91.4% undetectable HIV viral load), SARS-CoV-2 Abs were detected in 91 PWH, a seroprevalence of 8.5% (95%CI 6.9–10.3%). Forty-five infections (45.0%) were asymptomatic. Variables independently associated with SARS-CoV-2 seropositivity were birth in Latin American countries versus Spain (adjusted odds ratio (aOR) 2.30, 95%CI 1.41–3.76, p 0.001), and therapy with tenofovir disoproxil fumarate plus emtricitabine (TDF/FTC) versus tenofovir alafenamide (TAF)/FTC as the N(t)RTI backbone (aOR 0.49, 95%CI 0.26–0.94, p 0.031).
Many SARS-CoV-2 infections among PWH were asymptomatic, and birth in Latin American countries increased the risk of SARS-CoV-2 seropositivity. Our analysis, adjusted by comorbidities and other variables, suggests that TDF/FTC may prevent SARS-CoV-2 infection among PWH.
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