Gleason score, which has a high interobserver variability, is used to classify prostate cancer. The most recent consensus valued the tertiary Gleason pattern and recommended its use in the final score of needle biopsies (modified Gleason score). This pattern is considered to be of high prognostic value in surgical specimens. This study emphasized the evaluation of the modified score agreement in needle biopsies and in surgical specimen, as well as the interobserver variability of this score. Three pathologists evaluated the slides of needle biopsies and surgical specimens of 110 patients, reporting primary, secondary and tertiary Gleason patterns and after that, traditional and modified Gleason scores were calculated. Kappa test (K) assessed the interobserver agreement and the agreement between the traditional and modified scores of the biopsy and of the surgical specimen. Interobserver agreement in the biopsy was K = 0.36 and K = 0.35, and in the surgical specimen it was K = 0.46 and K = 0.36, for the traditional and modified scores, respectively. The tertiary Gleason grade was found in 8%, 0% and 2% of the biopsies and in 8%, 0% and 13% of the surgical specimens, according to observers 1, 2 and 3, respectively. When evaluating the agreement of the traditional and modified Gleason scores in needle biopsy with both scores of the surgical specimen, a similar agreement was found through Kappa. Contrary to what was expected, the modified Gleason score was not superior in the agreement between the biopsy score and the specimen, or in interobserver reproducibility, in this study.

The accurate characterization of spike firing rates including the determination of when changes in activity occur is a fundamental issue in the analysis of neurophysiological data. Here we describe a state-space model for estimating the spike rate function that provides a maximum likelihood estimate of the spike rate, model goodness-of-fit assessments, as well as confidence intervals for the spike rate function and any other associated quantities of interest. Using simulated spike data, we first compare the performance of the state-space approach with that of Bayesian adaptive regression splines (BARS) and a simple cubic spline smoothing algorithm. We show that the state-space model is computationally efficient and comparable with other spline approaches. Our results suggest both a theoretically sound and practical approach for estimating spike rate functions that is applicable to a wide range of neurophysiological data.

OBJETIVO: Avaliar a prevalência de casos suspeitos de transtornos mentais comuns em uma população assistida por uma equipe do Programa Saúde da Família e investigar os fatores associados à ocorrência dessa morbidade. MÉTODOS: Pesquisa de levantamento, de corte transversal. A amostra, composta por 277 sujeitos, foi obtida por meio do método de amostragem aleatória do tipo sistemática. Para a coleta de dados, foram aplicados o Self Report Questionnaire (SRQ-20) e um questionário sociodemográfico. RESULTADOS: A prevalência global de casos suspeitos de transtornos mentais comuns na população alvo foi de 43,70%. O sexo feminino apresentou uma taxa de prevalência significativamente mais elevada (48,37%), quando comparado ao sexo masculino (34,41%). A variável "renda familiar" apresentou uma relação inversa com a prevalência de transtornos mentais comuns. A análise de regressão logística indicou que apenas as variáveis "uso de medicamento" e "renda familiar" estavam associadas significativamente à suspeita de casos de transtornos mentais comuns. CONCLUSÕES: Os resultados apontaram uma elevada prevalência de transtornos mentais comuns nessa população alvo, comparativamente aos dados de outros estudos semelhantes, indicando a necessidade de um cuidado especial por parte da Atenção Primária à Saúde, em particular para as famílias caracterizadas pelos fatores associados ao transtornos mentais comuns apontados nesta investigação.