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.

Qualitative SEM/EDS analysis of microleakage and apical gap formation of adhesive root-filling materials

Objective: The aim of this study was to compare the correspondence between gap formation and apical microleakage in root canals filled with epoxy resin-based (AH Plus) combined or not with resinous primer or with a dimethacrylate-based root canal sealer (Epiphany). Material and Methods: Thirty-nine lower single-rooted human premolars were filled by the lateral condensation technique (LC) and immersed in a 50-wt% aqueous silver nitrate solution at 37 degrees C (24 h). After longitudinal sectioning, epoxy resin replicas were made from the tooth specimens. Both the replicas and the specimens were prepared for scanning electron microscopy (SEM). The gaps were observed in the replicas. Apical microleakage was detected in the specimens by SEM/energy dispersive spectroscopy (SEM/EDS). The data were analyzed statistically using an Ordinal Logistic Regression model and Analysis of Correspondence (alpha=0.05). Results: Epiphany presented more regions containing gaps between dentin and sealer (p<0.05). There was correspondence between the presence of gaps and microleakage (p<0.05). Microleakage was similar among the root-filling materials (p>0.05). Conclusions: The resinous primer did not improve the sealing ability of AH Plus sealer and the presence of gaps had an effect on apical microleakage for all materials.