Tele-obstetric ultrasound: analysis of first-trimester ultrasound images transmitted in realtime

We evaluated the diagnostic quality of first-trimester ultrasound images transmitted in realtime using low-cost telecommunications. A prospective sample of fetal ultrasound images from 11 weeks to 13 weeks and six days of pregnancy was obtained from pregnant women over 18 years old. The examinations were transmitted in realtime to three independent examiners who carried out a qualitative assessment based on parameters established by the Fetal Medicine Foundation. All fetal structures could be viewed and the quality of images received by the examiners was considered normal. There were significant differences for crown-rump length and nuchal translucency in the transmitted images but the loss in definition was acceptable. Thus the quality of images transmitted via the Internet through the use of low-cost software appeared suitable for screening for chromosomal abnormalities in the first trimester of pregnancy.

Predicting smear negative pulmonary tuberculosis with classification trees and logistic regression: a cross-sectional study

Abstract Background Smear negative pulmonary tuberculosis (SNPT) accounts for 30% of pulmonary tuberculosis cases reported yearly in Brazil. This study aimed to develop a prediction model for SNPT for outpatients in areas with scarce resources. Methods The study enrolled 551 patients with clinical-radiological suspicion of SNPT, in Rio de Janeiro, Brazil. The original data was divided into two equivalent samples for generation and validation of the prediction models. Symptoms, physical signs and chest X-rays were used for constructing logistic regression and classification and regression tree models. From the logistic regression, we generated a clinical and radiological prediction score. The area under the receiver operator characteristic curve, sensitivity, and specificity were used to evaluate the model's performance in both generation and validation samples. Results It was possible to generate predictive models for SNPT with sensitivity ranging from 64% to 71% and specificity ranging from 58% to 76%. Conclusion The results suggest that those models might be useful as screening tools for estimating the risk of SNPT, optimizing the utilization of more expensive tests, and avoiding costs of unnecessary anti-tuberculosis treatment. Those models might be cost-effective tools in a health care network with hierarchical distribution of scarce resources.