Influence of Polishing Systems on Surface Roughness of Composite Resins: Polishability of Composite Resins.

OBJECTIVES: The objective of this in vitro study was to compare, with a threshold value of 200 nm, the surface roughness obtained when using 12 different polishing systems on four different composite resins (microfill, nanofill, and two nanohybrids). METHODS AND MATERIALS: A total of 384 convex specimens were made using Durafill VS, Filtek Supreme Ultra, Grandio SO, and Venus Pearl. After sandblasting and finishing with a medium-grit finishing disc, initial surface roughness was measured using a surface roughness tester. Specimens were polished using 12 different polishing systems: Astropol, HiLuster Plus, D♦Fine, Diacomp, ET Illustra, Sof-Lex Wheels, Sof-Lex XT discs, Super-Snap, Enhance/Pogo, Optrapol, OneGloss and ComposiPro Brush (n=8). The final surface roughness was measured, and data were analyzed using two-way analysis of variance. Pairwise comparisons were made using protected Fisher least significant difference. RESULTS: There were statistical differences in the final surface roughness between polishing systems and between composite resins (p<0.05). The highest surface roughness was observed for all composite resins polished with OneGloss and ComposiPro Brush. Enhance/Pogo and Sof-Lex Wheels produced a mean surface roughness greater than the 200-nm threshold on Filtek Supreme Ultra, Grandio SO, and Venus Pearl. Data showed that there was an interaction between the composite resins and the polishing systems. CONCLUSIONS: A single polishing system does not perform equally with all composite resins. Except for Optrapol, multi-step polishing systems performed generally better than one-step systems. Excluding Enhance/Pogo, diamond-impregnated polishers led to lower surface roughness. Durafill VS, a microfill composite resin, may be polished more predictably with different polishers.

Analysis of incomplete multivariate data from repeated measurement experiments.

This paper analyses two sets of data that consist of repeated measurements with missing data. The missing observations always occur at the end of the series of repeated measurements. The score test for multivariate normal data is used to compare treatment groups; if the original data are not multivariate normal they are replaced by expected normal scores.