RESUMO
BACKGROUND: Chemotherapy-associated liver injury (CALI) is a matter of concern for hepatobiliary surgeons as it can entail postoperative liver failure after an extensive hepatectomy. Recent studies have taken special interest in liver function parameters which can correlate with CALI to decrease this adverse event. Therefore, the current study investigates the usefulness of splenic volume as a biomarker of CALI through a portal hypertension mechanism, in patients with colorectal liver metastases (CRLM). STUDY DESIGN: We carried out a study in patients with CRLM operated on between 2009 and 2014 in our center. All samples of healthy liver were graded for non-alcoholic fatty liver disease (NAFLD) and sinusoidal obstructive syndrome. Computarized tomography scans for spleen volumetry were analyzed for each patient at CRLM diagnosis, after neoadjuvant chemotherapy, 1 and 6 months after resection. RESULTS: A group of 65 consecutive patients with CRLM of large bowel adenocarcinoma submitted to liver resection were included. Patients receiving neoadjuvant chemotherapy had a greater spleen volume increase than those who did not receive treatment (p = 0.053), finding a statistically significant spleen growth in patients with NAFLD (p = 0.036). There was no correlation between spleen enlargement and postoperative complications or average stay. However, survival was decreased in patients with spleen growth and CALI. CONCLUSIONS: Patients who receive neoadjuvant chemotherapy for liver metastasis surgery have a greater splenic volume increase, which correlates with NAFLD and a lower survival.
Assuntos
Adenocarcinoma/terapia , Antineoplásicos/efeitos adversos , Doença Hepática Induzida por Substâncias e Drogas/patologia , Neoplasias Colorretais/patologia , Hepatectomia , Hepatopatia Veno-Oclusiva/patologia , Neoplasias Hepáticas/terapia , Hepatopatia Gordurosa não Alcoólica/patologia , Baço/diagnóstico por imagem , Adenocarcinoma/secundário , Antineoplásicos/uso terapêutico , Doença Hepática Induzida por Substâncias e Drogas/etiologia , Fígado Gorduroso/induzido quimicamente , Fígado Gorduroso/patologia , Hepatopatia Veno-Oclusiva/induzido quimicamente , Humanos , Neoplasias Hepáticas/secundário , Metastasectomia , Terapia Neoadjuvante , Hepatopatia Gordurosa não Alcoólica/induzido quimicamente , Tamanho do Órgão , Oxaliplatina/efeitos adversos , Oxaliplatina/uso terapêutico , Complicações Pós-Operatórias , Baço/patologia , Taxa de Sobrevida , Tomografia Computadorizada por Raios XRESUMO
En años recientes la sonificación de electroencefalogramas (EEG) ha sido utilizada como una alternativa para analizar señales cerebrales al convertir el EEG en audio. En este trabajo se aplica la sonificación a señales de EEG durante el habla imaginada o habla no pronunciada, con el objetivo de mejorar la clasificación automática de 5 palabras del idioma español. Para comprobarlo, se procesó la señal cerebral de 27 sujetos sanos. Estas señales fueron sonificadas para después extraer características con dos métodos diferentes: la transformada Wavelet discreta (DWT); y los coeficientes cepstrales en la escala de Mel (MFCC). Éste último comúnmente utilizado en tareas de reconocimiento de voz. Para clasificar las señales se aplicaron tres algoritmos distintos de clasificación Naive Bayes (NB), Máquina de vectores de soporte (SVM) y Random Forest (RF). Se obtuvieron resultados usando los 4 canales más cercanos a las áreas de lenguaje de Broca y Wernicke, así como también los 14 canales del dispositivo EEG utilizado. Los porcentajes de exactitud promedio para los 27 sujetos en los dos conjuntos de 4 y 14 canales usando sonificación de EEG fueron de 55.83% y 64.14% respectivamente, con lo que se logró mejorar ligeramente los porcentajes de clasificación de las palabras imaginadas respecto a no utilizar sonificación.
In recent years sonification of electroencephalograms (EEG) has been used as an alternative to analyze brain signals after converting EEG to audio. In this paper we applied the sonification to EEG signals during the imagined speech or unspoken speech, with the aim of improving the automatic classification of 5 words of Spanish. To check this, the brain signals of 27 healthy subjects were processed. These sonificated signals were processed to extract features with two different methods: discrete wavelet transform (DWT); and the Mel-frequencies cepstral coefficients (MFCC). The latter commonly used in speech recognition tasks. To classify the signals three different classification algorithms Naive Bayes (NB), Support Vector Machine (SVM) and Random Forest (RF) were applied. Results were obtained using the 4 channels closest to the language areas of Broca and Wernicke, as well as the 14 channels of the EEG device used. The percentages of average accuracy for the 27 subjects in the two sets of 4 and 14 channels using EEG sonification were 55.83% and 64.14% respectively, which are improvements in the classification rates of the imagined words compared with a scheme without sonification.
RESUMO
OBJECTIVE: The aim of this study is to measure the knowledge regarding the new sanitation water system being implemented in Dessources, a rural community in the municipality of Croix-des-Bouquets in Haiti after a two-year intervention programme. DESIGN AND METHODS: A cross-sectional epidemiologic design was used to measure the knowledge of the people in the community using a semi-structured questionnaire. Data collection followed a face-to-face interview process in all houses of the community. The instrument content validity was performed by a panel of experts followed by Cronbach's alpha test to establish the reliability of knowledge scale. In addition, association measures were done using Stata 11.0 statistical package. RESULTS: Content validity test were performed with minimum changes and an alpha of 0.74 was obtained for the scale. Response rate was 65.57% (41/60 houses); non-participants were only those who did not meet the inclusion criteria. Most of the participants (77.5%) were 21-49 years old and 85% had been living in the community for more than 20 years. Bivariate analysis showed that the people of Dessources had adequate knowledge. Significant differences, however, were found among the zones that are not in use of the new sanitary systems and among families with more than seven members per house. CONCLUSIONS: Differences found can be explained based on the Rogers theoretical diffusion of innovation model. The evaluation shows that people of Dessources in Haiti have a high knowledge regarding the new water sanitation system and provided evidence of an adequate health education programme intervention.
RESUMO
El presente trabajo tiene como objetivo interpretar las señales de EEG registradas durante la pronunciación imaginada de palabras de un vocabulario reducido, sin emitir sonidos ni articular movimientos (habla imaginada o no pronunciada) con la intención de controlar un dispositivo. Específicamente, el vocabulario permitiría controlar el cursor de la computadora, y consta de las palabras del lenguaje español: "arriba", "abajo", "izquierda", "derecha", y "seleccionar". Para ello, se registraron las señales de EEG de 27 individuos utilizando un protocolo básico para saber a priori en qué segmentos de la señal la persona imagina la pronunciación de la palabra indicada. Posteriormente, se utiliza la transformada wavelet discreta (DWT) para extraer características de los segmentos que son usados para calcular la energía relativa wavelet (RWE) en cada una de los niveles en los que la señal es descompuesta, y se selecciona un subconjunto de valores RWE provenientes de los rangos de frecuencia menores a 32 Hz. Enseguida, éstas se concatenan en dos configuraciones distintas: 14 canales (completa) y 4 canales (los más cercanos a las áreas de Broca y Wernicke). Para ambas configuraciones se entrenan tres clasificadores: Naive Bayes (NB), Random Forest (RF) y Máquina de vectores de soporte (SVM). Los mejores porcentajes de exactitud se obtuvieron con RF cuyos promedios fueron 60.11% y 47.93% usando las configuraciones de 14 canales y 4 canales, respectivamente. A pesar de que los resultados aún son preliminares, éstos están arriba del 20%, es decir, arriba del azar para cinco clases. Con lo que se puede conjeturar que las señales de EEG podrían contener información que hace posible la clasificación de las pronunciaciones imaginadas de las palabras del vocabulario reducido.
This work aims to interpret the EEG signals associated with actions to imagine the pronunciation of words that belong to a reduced vocabulary without moving the articulatory muscles and without uttering any audible sound (imagined or unspoken speech). Specifically, the vocabulary reflects movements to control the cursor on the computer, and consists of the Spanish language words: "arriba", "abajo", "izquierda", "derecha", and "seleccionar". To do this, we have recorded EEG signals from 27 subjects using a basic protocol to know a priori in what segments of the signal a subject imagines the pronunciation of the indicated word. Subsequently, discrete wavelet transform (DWT) is used to extract features from the segments. These are used to compute relative wavelet energy (RWE) in each of the levels in that EEG signal is decomposed and, it is selected a RWE values subset with the frequencies smaller than 32 Hz. Then, these are concatenated in two different configurations: 14 channels (full) and 4 channels (the channels nearest to the brain areas of Wernicke and Broca). The following three classifiers were trained using both configurations: Naive Bayes (NB), Random Forest (RF) and support vector machines (SVM). The best accuracies were obtained by RF whose averages were 60.11% and 47.93% using both configurations, respectively. Even though, the results are still preliminary, these are above 20%, this means they are more accurate than chance for five classes. Based on them, we can conjecture that the EEG signals could contain information needed for the classification of the imagined pronunciations of the words belonging to a reduced vocabulary.
RESUMO
El duodeno es una localización poco frecuente de tumores. Se presenta una serie de 11 tumores primarios de duodeno, 6 malignos y 5 benignos, tratados en nuestro servicio en los últimos 5 años. Se analiza la clínica, métodos diagnósticos, localización y anatomía-patológica, asi como el tratamiento empleado y la sobrevida de los casos. Se concluye que la cirugia radical, mediante duodenopancreatectomia, es el único tratamiento con criterio oncológico ceptable en los tumores malignos duodenales. En los tumores benignos la resección local es el tratamiento de elección