Abstract Background: Mohs micrographic surgery is worldwide used for treating skin cancers. After obtaining tumor-free margins, choosing the most appropriate type of closure can be challenging. Objectives: Our aim was to associate type of surgical reconstructions after Mohs micrographic surgery with the characteristics of the tumors as histological subtype, anatomical localization and especially number of surgical stages to achieve complete excision of the tumour. Methods: Transversal, retrospective analyses of medical records. Compilation of data such as gender, age, tumor location, histological subtype, number of stages to achieve clear margins and type of repair used. Results: A total of 975 of facial and extra-facial cases were analyzed. Linear closure was the most common repair by far (39%) and was associated with the smallest number of Mohs micrographic surgery stages. This type of closure was also more common in most histological subtypes and anatomical locations studied. Using Poisson regression model, nose defects presented 39% higher frequency of other closure types than the frequency of primary repairs, when compared to defects in other anatomic sites (p< 0.05). Tumors with two or more stages had a 28.6% higher frequency of other closure types than those operated in a single stage (p< 0.05). Study limitations: Retrospective study with limitations in obtaining information from medical records. The choice of closure type can be a personal choice. Conclusions: Primary closure should not be forgotten especially in surgical defects with fewer stages and in non-aggressive histological subtypes in main anatomic sites where Mohs micrographic surgery is performed.

Abstract Cutaneous metastases from primary internal malignancies represent 0.7-9% of patients with cancer. We report a 65-year-old female patient referred for evaluation of normochromic papules on the trunk and upper limbs that had been present for three months. A skin biopsy revealed diffuse cutaneous infiltration by small round cell tumors. Immunohistochemistry was positive for AE1/AE3, CK7, estrogen receptor and mammaglobin. The final diagnosis was cutaneous metastasis of occult breast cancer, since the solid primary tumor was not identified. The location of the primary tumor can not be determined in 5-10% of cases. In these cases, 27% are identified before the patient’s death, 57% at autopsy, and the remaining 16% can not be located.

OBJECTIVES: Dengue has become the most important endemic disease in Brazil. The Amazonian state of Roraima has one of the highest incidence rates of dengue in the country. The objective of this study was to determine whether significant temporal relationships exist between the number of reported dengue cases and short-term climate measures for the city of Boa Vista, the capital of Roraima. If such relationships exist, that suggests that it may be possible to predict dengue case numbers based on antecedent climate, thus helping develop a climate-based dengue early-warning system for Boa Vista. METHODS: Seasonal Pearson product-moment correlations were developed between 3-week running averages of daily numbers of reported dengue cases for September 1998-December 2001 and certain meteorological variables (thermal, hydroclimatic, wind, atmospheric pressure, and humidity) up to 25 weeks before. Two-sample t tests were also applied to test for statistically significant differences between samples of daily dengue cases with above-average values and samples with below-average values for three-variable meteorological combinations. These multivariate combinations consisted of the three climate measures that together explained the greatest portion of the variance in the number of dengue cases for the particular season. RESULTS: The strength of the individual averaged correlations varied from weak to moderate. The correlations differed according to the period of the year, the particular climatic variable, and the lag period between the climate indicator and the number of dengue cases. The seasonal correlations in our study showed far stronger relationships than had daily, full-year measures reported in previous studies. Two-sample t tests of multivariate meteorological combinations of atmospheric pressure, wind, and humidity values showed statistically significant differences in the number of reported dengue cases. CONCLUSIONS: Relationships between climate and dengue are best analyzed for short, relevant time periods. Climate-based multivariate temporal stochastic analyses have the potential to identify periods of elevated dengue incidence, and they should be integrated into local control programs for vector-transmitted diseases.

OBJETIVOS: El dengue se ha convertido en la enfermedad endémica más importante de Brasil. El estado amazónico de Roraima presenta una de las tasas de incidencia de dengue más elevadas de ese país. El objetivo del presente estudio fue determinar si existen relaciones temporales significativas entre el número de casos informados de dengue y las mediciones climáticas a corto plazo en la ciudad de Boa Vista, capital de Roraima. De comprobarse esa relación, existiría la posibilidad de predecir el número de casos de dengue a partir de las condiciones climáticas antecedentes, lo que contribuiría a desarrollar un sistema de aviso temprano de dengue basado en las mediciones climáticas en Boa Vista. MÉTODOS: Se calcularon coeficientes de correlación momento-producto de Pearson estacionales entre los promedios deslizantes del número informado de casos de dengue en lapsos de tres semanas entre septiembre de 1998 y diciembre de 2001 y los valores de algunas variables meteorológicas seleccionadas (temperatura, precipitaciones diarias, velocidad y dirección del viento, presión atmosférica y humedad relativa) hasta 25 semanas previas. Se aplicó la prueba de la t para dos muestras para comprobar la significación estadística de las diferencias entre las muestras de casos diarios de dengue con valores por encima del promedio y las muestras diarias con valores por debajo del promedio para las combinaciones de tres variables meteorológicas. Estas combinaciones multifactoriales consistían en tres mediciones climáticas que juntas explicaran la mayor parte de la varianza en el número de casos de dengue para una estación dada. RESULTADOS: La robustez de las correlaciones de las medias individuales fue débil o moderada. Las correlaciones difirieron según el período del año, la variable climática en cuestión y el período transcurrido entre el momento en que se midió el indicador y cuando se notificaron los casos de dengue. La correlación estacional mostró una relación mucho más fuerte que la correlación diaria durante todo el año encontrada en estudios anteriores. La prueba de la t para dos muestras aplicada a combinaciones meteorológicas con múltiples variables de los valores de presión atmosférica, viento y humedad mostraron diferencias significativas en cuanto al número de casos de dengue informados. CONCLUSIONES: Las relaciones entre el clima y el dengue se pueden analizar mejor en períodos de tiempo cortos y pertinentes. Los análisis estocásticos temporales basados en múltiples variables climáticas tienen la posibilidad de identificar períodos de elevada incidencia de dengue, por lo que se deben incorporar a los programas locales de control de vectores transmisores de enfermedades.