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C D Evans

Publications and source records attributed to C D Evans.

92 records · Page 6Linked to original sources

The effects of tooth preparation on pressure measured in the pulp chamber: a laboratory study.

PURPOSE: The purpose of this study was to determine pressure changes in the pulp space during tooth preparation with either diamond or tungsten carbide burs in a high-speed dental handpiece in the laboratory. MATERIALS AND METHODS: Twenty premolar teeth were collected and randomly assigned to two groups: group 1 received preparation with diamond burs and group 2 with tungsten carbide burs. The teeth were mounted on a pressure transducer and the pulp chambers were filled with saline. A 0.1-mm thickness of tooth tissue was removed from the proximal surface of each tooth, alternating dry and wet cutting, until the pulp chamber was exposed. Pressure and temperature changes were recorded during tooth preparation. RESULTS: At 0 to 1 mm of remaining dentin depth dry cutting with diamond and tungsten carbide burs generated a mean positive pulpal pressure of 12 kPa and 6 kPa, respectively. Wet cutting under the same conditions produced 0.6 kPa and 0.15 kPa, respectively. The difference between wet and dry cutting was highly significant (P < 0.001). Diamond burs produced significantly higher pressure increases than carbide burs at all levels for both wet and dry techniques (P < 0.05). When cutting farther than 2 mm from the pulp, tooth preparation created a mean 0.09-kPa pressure increase, which was not influenced by either coolant use or bur type. The temperature change was minimal during wet cutting and only minor temperature increases were recorded during dry cutting. CONCLUSION: From this laboratory study it is concluded that significant pressure changes occur in the pulp chamber during tooth preparation of extracted teeth when the remaining dentin thickness is less than 2 mm.

Body Temperature↗

A case-based learning approach to grouping cases with multiple malformations.

A case-based classification system can provide assistance to specialists in dysmorphology. This article describes a case-based model designed to assist in identification and retrospective analysis of rare types of syndromes that have proved difficult to diagnose. The primary task of diagnosis is complemented by a learning, or grouping, task. Using data sets of diagnosed cases in related categories of syndromes, we demonstrate how a case-based learning algorithm can extend the retrieval and indexing mechanisms of standard databases to provide a focus for analysis of syndrome classifications.

Abnormalities, Multiple↗