treatment of carious primary molars is always indicated especially on young children, however there is no clear guidelines precisely explain the best treatment approach treating class II carious molars with marginal breakdown (ICDAS 5). This prospective observational clinical study is aimed to assess the efficacy of three restorative techniques in treating ICDAS 5 class II lesions in primary molars: Compomer fillings [CF], preformed metal crowns performed [PMC], Pulpotomy and conventional preformed metal crowns. The secondary goal is to evaluate the impact of some cofactors on the course of treatment. Overall, 92 children (female n= 50, 54.3%; male n= 42, 25.3%, 2-9 years old; mean age= 5.9±1.9) with 166 treated teeth were included. The d3mft of the whole sample was 8.0± 3.4. The distribution of the sample according to type of treatment was CF= 53 (31.9%), PMC= 64 (38.6%) and PMC+P= 49 (29.5%). Paired t-test, non-parametric Friedman's Anova test, and decision tree analysis were used as the basis for the statistics. After 12 months, data from 75.8% (72/95) treated patients, corresponding to 63.5% (103/166) of the treated teeth (CF=42/53, 79.2 %; PMC= 38/64, 59.3%; PMC+P= 23/49, 46.9%) were available for analysis. The mean patients age was 6.8± 1.8; 32 (47%) were boys and 36 (52.9%) girls. The mean d3mft of the remaining sample was 7.8±3.35. PMC and PMC+P arms showed the highest success rates (>91%) as compared to the CF arm, which showed the lowest success rates (61.9 %), with 9/42 teeth of the CF group (21.4%) presenting with minor failures, and 7/42 teeth (16.7%) with major failures (p<0.0001). According to decision tree analysis, PMC and PMC+P had a success rate of 99 %, whereas CF had a success rate of only 69 %. some cofactors like treatment decision, plaque index (API), and tooth number, had higher impact on the tree anlysis than others like age, dmfs, and dmft values especially when treatment selection was CF. It is necessary to examine the impact of other cofactors on the outcomes of conventional fillings using a bigger sample size.
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