Reply to the Editor—Prevalence of interatrial block during lifetime

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Interatrial block and atrial arrhythmias in centenarians: Prevalence, associations, and clinical implications

Data are lacking on the characteristics of atrial activity in centenarians, including interatrial block (IAB). The aim of this study was to describe the prevalence of IAB and auricular arrhythmias in subjects older than 100 years and to elucidate their clinical implications. We studied 80 centenarians (mean age 101.4 ± 1.5 years; 21 men) with follow-ups of 6–34 months. Of these 80 centenarians, 71 subjects (88.8%) underwent echocardiography. The control group comprised 269 septuagenarians. A total of 23 subjects (28.8%) had normal P wave, 16 (20%) had partial IAB, 21 (26%) had advanced IAB, and 20 (25.0%) had atrial fibrillation/flutter. The IAB groups exhibited premature atrial beats more frequently than did the normal P wave group (35.1% vs 17.4%; P < .001); also, other measurements in the IAB groups frequently fell between values observed in the normal P wave and the atrial fibrillation/flutter groups. These measurements included sex preponderance, mental status and dementia, perceived health status, significant mitral regurgitation, and mortality. The IAB group had a higher previous stroke rate (24.3%) than did other groups. Compared with septuagenarians, centenarians less frequently presented a normal P wave (28.8% vs 53.5%) and more frequently presented advanced IAB (26.3% vs 8.2%), atrial fibrillation/flutter (25.0% vs 10.0%), and premature atrial beats (28.3 vs 7.0%) (P < .01). Relatively few centenarians (<30%) had a normal P wave, and nearly half had IAB. Our data suggested that IAB, particularly advanced IAB, is a pre–atrial fibrillation condition associated with premature atrial beats. Atrial arrhythmias and IAB occurred more frequently in centenarians than in septuagenarians.

¿Debemos anticoagular a pacientes en alto riesgo de sufrir fibrilación auricular?

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Conservative management in very elderly patients with severe aortic stenosis: Time to change?

Despite current recommendations, a high percentage of patients with severe symptomatic aortic stenosis are managed conservatively. The aim of this study was to study symptomatic patients undergoing conservative management from the IDEAS registry, describing their baseline clinical characteristics, mortality, and the causes according to the reason for conservative management. Consecutive patients with severe aortic stenosis diagnosed at 48 centers during January 2014 were included. Baseline clinical characteristics, echocardiographic data, Charlson index, and EuroSCORE-II were registered, including vital status and performance of valve intervention during one-year follow-up. For the purpose of this substudy we assessed symptomatic patients undergoing conservative management, including them in 5 groups according to the reason for performing conservative management [I: comorbidity/frailty (128, 43.8%); II: dementia 18 (6.2%); III: advanced age 34 (11.6%); IV: patients’ refusal 62 (21.2%); and V: other reasons 50 (17.1%)]. We included 292 patients aged 81.5 ± 9 years. Patients from group I had higher Charlson index (4 ± 2.3), higher EuroSCORE-II (7.5 ± 6), and a higher overall (42.2%) and non-cardiac mortality (16.4%) than the other groups. In contrast, patients from group III had fewer comorbidities, lower EuroSCORE-II (4 ± 2.5), and low overall (20.6%) and non-cardiac mortality (5.9%). Patients with severe symptomatic aortic stenosis managed conservatively have different baseline characteristics and clinical course according to the reason for performing conservative management. A prospective assessment of comorbidity and other geriatric syndromes might contribute to improve therapeutic strategy in this clinical setting.

Existence de solution antipériodique de l’équation impulsive de Liénard avec une force Henstock-Kurzweil intégrable

Notre travail se consacre à l’étude de l’existence de solution T-anti-périodique de l’équation de Liénard dans le cas impulsif. Dans notre thèse, cette équation sera appliquée à l’équation du pendule simple, de Josephson dans la super-conductivité et enfin à l’équation de Van der Pol pour modéliser un circuit de triode à tube vide. On considérera [florin] et J des actions extérieures sur le système où [florin] est une force Lebesgue intégrable (respectivement Henstock-Kurzweil intégrable au second chapitre) et J (parfois noté I) une stimulation impulsive. En appliquant le théorème du point fixe de Banach, on obtient des théorèmes d’existence de solution au sens de fonctions généralisées soumise à un ensemble de conditions données par les bornes à priori. Ensuite, par le même théorème, la suite d’itérations G[indice supérieur n] ([théta][indice inférieur 0]) converge uniformément vers la solution [théta] à la vitesse de convergence bornée avec la première dérivée […] est de variation totale finie sur [0; 2T] et la dérivée seconde généralisée […] Lebesgue intégrable sur [0; 2T] dans le cas non impulsif. Finalement, sous les mêmes hypothèses avec [florin] Henstock-Kurzweil (HK) intégrable, nous obtiendrons des conditions qui garantissent l’existence d’une solution T-antipériodique [théta] absolument continue sur R de l’équation de Liénard, qui admet à la fois une dérivée première […] de variation bornée et la seconde dérivée généralisée […] qui est HK--intégrable dans le cas non impulsif. Comme au premier chapitre nous considérerons également le cas des instants d’impulsion [gamma][indice inférieur kappa] indépendants d’état avec [florin] HK--intégrable. À chaque fois nous donnons quelques exemples d’illustration pour appuyer nos résultats. [Certains symboles non conformes]

Índice acumulativo de riesgo (nice) como prueba diagnóstica con base en tomografía corneal por elevación en la prevención de ectasia corneal post-lasik

Antecedentes La ectasia corneal post-lasik (ECPL) es una complicación infrecuente, pero devastadora en la cirugía lasik (queratomileusis asistida con éxcimer láser) para el tratamiento de la miopía con o sin astigmatismo. Con base en la tomografía corneal por elevación por imágenes de Scheimpflug (Sistema Pentacam HR, Oculus Wetzlar, Alemania), se propone un novedoso índice acumulativo de riesgo para ser utilizado como prueba diagnóstica de tamizaje y así prevenir esta complicación. Metodología Se realizó un estudio observacional analítico, de corte transversal tipo pruebas diagnósticas, con el fin de evaluar las características operativas del índice NICE teniendo como estándar de referencia el módulo de Belin-Ambrosio (Pentacam HR) utilizando un modelo de regresión logística binaria, tablas de contingencia y estimando el área bajo la curva ROC. Resultados Se evaluaron 361 ojos de los cuales el 59,3% provenían de pacientes de sexo femenino, la edad media global fue de 30 años (RIC 11,0). El modelo logístico binario aplicado se construyó con base en cuatro variables independientes cuantitativas (K2, PAQUI, EP e I-S) y una cualitativa (SEXO), y se determinó su relación con la variable dependiente, NICE (puntaje final). Las variables predictoras fueron estadísticamente significativas clasificando adecuadamente el 92,9% de los ojos evaluados según presencia o ausencia de riesgo. El coeficiente de Nagelkerke fue de 74,4%. Conclusiones El índice acumulativo de riesgo NICE es una herramienta diagnóstica novedosa en la evaluación de candidatos a cirugía refractiva lasik para prevenir la ectasia secundaria.

Evaluación del desempeño pronóstico de dos puntajes de predicción de mortalidad a siete días en pacientes adultos oncológicos críticamente enfermos admitidos a una unidad de cuidados intensivos en Bogotá

Introducción Los sistemas de puntuación para predicción se han desarrollado para medir la severidad de la enfermedad y el pronóstico de los pacientes en la unidad de cuidados intensivos. Estas medidas son útiles para la toma de decisiones clínicas, la estandarización de la investigación, y la comparación de la calidad de la atención al paciente crítico. Materiales y métodos Estudio de tipo observacional analítico de cohorte en el que reviso las historias clínicas de 283 pacientes oncológicos admitidos a la unidad de cuidados intensivos (UCI) durante enero de 2014 a enero de 2016 y a quienes se les estimo la probabilidad de mortalidad con los puntajes pronósticos APACHE IV y MPM II, se realizó regresión logística con las variables predictoras con las que se derivaron cada uno de los modelos es sus estudios originales y se determinó la calibración, la discriminación y se calcularon los criterios de información Akaike AIC y Bayesiano BIC. Resultados En la evaluación de desempeño de los puntajes pronósticos APACHE IV mostro mayor capacidad de predicción (AUC = 0,95) en comparación con MPM II (AUC = 0,78), los dos modelos mostraron calibración adecuada con estadístico de Hosmer y Lemeshow para APACHE IV (p = 0,39) y para MPM II (p = 0,99). El ∆ BIC es de 2,9 que muestra evidencia positiva en contra de APACHE IV. Se reporta el estadístico AIC siendo menor para APACHE IV lo que indica que es el modelo con mejor ajuste a los datos. Conclusiones APACHE IV tiene un buen desempeño en la predicción de mortalidad de pacientes críticamente enfermos, incluyendo pacientes oncológicos. Por lo tanto se trata de una herramienta útil para el clínico en su labor diaria, al permitirle distinguir los pacientes con alta probabilidad de mortalidad.

Analysis of Pancreas Histological Images for Glucose Intolerance Identification using Wavelet Decomposition

Subtle structural differencescan be observed in the islets of Langer-hans region of microscopic image of pancreas cell of the rats having normal glucose tolerance and the rats having pre-diabetic(glucose intolerant)situa-tions. This paper proposes a way to automatically segment the islets of Langer-hans region fromthe histological image of rat's pancreas cell and on the basis of some morphological feature extracted from the segmented region the images are classified as normal and pre-diabetic.The experiment is done on a set of 134 images of which 56 are of normal type and the rests 78 are of pre-diabetictype. The work has two stages: primarily,segmentationof theregion of interest (roi)i.e. islets of Langerhansfrom the pancreatic cell and secondly, the extrac-tion of the morphological featuresfrom the region of interest for classification. Wavelet analysis and connected component analysis method have been used for automatic segmentationof the images. A few classifiers like OneRule, Naïve Bayes, MLP, J48 Tree, SVM etc.are used for evaluation among which MLP performed the best.

New perspectives in statistical mechanics and high-dimensional inference

The main purpose of this thesis is to go beyond two usual assumptions that accompany theoretical analysis in spin-glasses and inference: the i.i.d. (independently and identically distributed) hypothesis on the noise elements and the finite rank regime. The first one appears since the early birth of spin-glasses. The second one instead concerns the inference viewpoint. Disordered systems and Bayesian inference have a well-established relation, evidenced by their continuous cross-fertilization. The thesis makes use of techniques coming both from the rigorous mathematical machinery of spin-glasses, such as the interpolation scheme, and from Statistical Physics, such as the replica method. The first chapter contains an introduction to the Sherrington-Kirkpatrick and spiked Wigner models. The first is a mean field spin-glass where the couplings are i.i.d. Gaussian random variables. The second instead amounts to establish the information theoretical limits in the reconstruction of a fixed low rank matrix, the “spike”, blurred by additive Gaussian noise. In chapters 2 and 3 the i.i.d. hypothesis on the noise is broken by assuming a noise with inhomogeneous variance profile. In spin-glasses this leads to multi-species models. The inferential counterpart is called spatial coupling. All the previous models are usually studied in the Bayes-optimal setting, where everything is known about the generating process of the data. In chapter 4 instead we study the spiked Wigner model where the prior on the signal to reconstruct is ignored. In chapter 5 we analyze the statistical limits of a spiked Wigner model where the noise is no longer Gaussian, but drawn from a random matrix ensemble, which makes its elements dependent. The thesis ends with chapter 6, where the challenging problem of high-rank probabilistic matrix factorization is tackled. Here we introduce a new procedure called "decimation" and we show that it is theoretically to perform matrix factorization through it.

Modelling and classification with quantile-based distributions

In this work, we explore and demonstrate the potential for modeling and classification using quantile-based distributions, which are random variables defined by their quantile function. In the first part we formalize a least squares estimation framework for the class of linear quantile functions, leading to unbiased and asymptotically normal estimators. Among the distributions with a linear quantile function, we focus on the flattened generalized logistic distribution (fgld), which offers a wide range of distributional shapes. A novel naïve-Bayes classifier is proposed that utilizes the fgld estimated via least squares, and through simulations and applications, we demonstrate its competitiveness against state-of-the-art alternatives. In the second part we consider the Bayesian estimation of quantile-based distributions. We introduce a factor model with independent latent variables, which are distributed according to the fgld. Similar to the independent factor analysis model, this approach accommodates flexible factor distributions while using fewer parameters. The model is presented within a Bayesian framework, an MCMC algorithm for its estimation is developed, and its effectiveness is illustrated with data coming from the European Social Survey. The third part focuses on depth functions, which extend the concept of quantiles to multivariate data by imposing a center-outward ordering in the multivariate space. We investigate the recently introduced integrated rank-weighted (IRW) depth function, which is based on the distribution of random spherical projections of the multivariate data. This depth function proves to be computationally efficient and to increase its flexibility we propose different methods to explicitly model the projected univariate distributions. Its usefulness is shown in classification tasks: the maximum depth classifier based on the IRW depth is proven to be asymptotically optimal under certain conditions, and classifiers based on the IRW depth are shown to perform well in simulated and real data experiments.

An approach to document classification using verb-object pairs

The aim of this thesis is to present a new approach to document classification using verb-object pairs. We explore one possible strategy that uses the presence of relevant verb-object pairs in documents as features and a Naive Bayes classifier as a classifier on which the model is trained. Then, we assess the results from the case study which uses a software based on the strategy and make conclusions.