The Brazilian Network for HIV-1 Genotyping External Quality Control Assurance Programme

The Brazilian network for genotyping is composed of 21 laboratories that perform and analyze genotyping tests for all HIV-infected patients within the public system, performing approximately 25,000 tests per year. We assessed the interlaboratory and intralaboratory reproducibility of genotyping systems by creating and implementing a local external quality control evaluation. Plasma samples from HIV-1-infected individuals (with low and intermediate viral loads) or RNA viral constructs with specific mutations were used. This evaluation included analyses of sensitivity and specificity of the tests based on qualitative and quantitative criteria, which scored laboratory performance on a 100-point system. Five evaluations were performed from 2003 to 2008, with 64% of laboratories scoring over 80 points in 2003, 81% doing so in 2005, 56% in 2006, 91% in 2007, and 90% in 2008 (Kruskal-Wallis, p = 0.003). Increased performance was aided by retraining laboratories that had specific deficiencies. The results emphasize the importance of investing in laboratory training and interpretation of DNA sequencing results, especially in developing countries where public (or scarce) resources are used to manage the AIDS epidemic.

Use of epidemiological data as the basis for developing a medical curriculum

CONTEXT AND OBJECTIVE: Epidemiology may help educators to face the challenge of establishing content guidelines for the curricula in medical schools. The aim was to develop learning objectives for a medical curriculum from an epidemiology database. DESIGN AND SETTING: Descriptive study assessing morbidity and mortality data, conducted in a private university in São Paulo. METHODS: An epidemiology database was used, with mortality and morbidity recorded as summaries of deaths and the World Health Organization's Disability-Adjusted Life Year (DALY). The scoring took into consideration probabilities for mortality and morbidity. RESULTS: The scoring presented a classification of health conditions to be used by a curriculum design committee, taking into consideration its highest and lowest quartiles, which corresponded respectively to the highest and lowest impact on morbidity and mortality. Data from three countries were used for international comparison and showed distinct results. The resulting scores indicated topics to be developed through educational taxonomy. CONCLUSION: The frequencies of the health conditions and their statistical treatment made it possible to identify topics that should be fully developed within medical education. The classification also suggested limits between topics that should be developed in depth, including knowledge and development of skills and attitudes, regarding topics that can be concisely presented at the level of knowledge.

Subcutaneous Tissue Thickness is an Independent Predictor of Image Noise in Cardiac CT

Background: Few data on the definition of simple robust parameters to predict image noise in cardiac computed tomography (CT) exist. Objectives: To evaluate the value of a simple measure of subcutaneous tissue as a predictor of image noise in cardiac CT. Methods: 86 patients underwent prospective ECG-gated coronary computed tomographic angiography (CTA) and coronary calcium scoring (CAC) with 120 kV and 150 mA. The image quality was objectively measured by the image noise in the aorta in the cardiac CTA, and low noise was defined as noise < 30HU. The chest anteroposterior diameter and lateral width, the image noise in the aorta and the skin-sternum (SS) thickness were measured as predictors of cardiac CTA noise. The association of the predictors and image noise was performed by using Pearson correlation. Results: The mean radiation dose was 3.5 ± 1.5 mSv. The mean image noise in CT was 36.3 ± 8.5 HU, and the mean image noise in non-contrast scan was 17.7 ± 4.4 HU. All predictors were independently associated with cardiac CTA noise. The best predictors were SS thickness, with a correlation of 0.70 (p < 0.001), and noise in the non-contrast images, with a correlation of 0.73 (p < 0.001). When evaluating the ability to predict low image noise, the areas under the ROC curve for the non-contrast noise and for the SS thickness were 0.837 and 0.864, respectively. Conclusion: Both SS thickness and CAC noise are simple accurate predictors of cardiac CTA image noise. Those parameters can be incorporated in standard CT protocols to adequately adjust radiation exposure.