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Analysis of the aesthetic effect and influencing factors of digital guided implant prosthesis in the treatment of dentition defect
LIN Yong, LIU Qing, ZHANG Jun-hua, CHANG Xiao-rong, HOU Dan
2025, 34 (1):
48-53.
doi: 10.19439/j.sjos.2025.01.009
PURPOSE: To explore the aesthetic effects and influencing factors of digital guided oral implant restoration in the treatment of dentition defect. METHODS: A total of 168 patients with dentition defect who underwent digital guided dental implant restoration from May 2020 to June 2022 were selected as the experimental group, while 84 patients with dentition defect who underwent routine restoration were selected as the control group. The planting accuracy(neck distance deviation, apical distance deviation, depth deviation and angle deviation), PES score and WES score were compared. The experimental group was divided into good group (n=139) and poor group (n=29) according to the repair effect. Logistic regression analysis was used to analyze the risk factors affecting the therapeutic effect of digital-guided oral implant prosthesis in patients with denture defects, and based on the risk factors, a risk nomogram prediction model for adverse therapeutic effect in patients with denture defects was constructed. Receiver operating characteristic (ROC) curve was drawn to analyze the nomogram to predict the AUC value, sensitivity and specificity of patients with dentition defect. SPSS 22.0 software package was used for statistical analysis. RESULTS: The neck distance deviation, root tip distance deviation, depth deviation and angle deviation in the experimental group were significantly lower than those in the control group(P<0.05). The PES scores and WES scores of the experimental group were significantly higher than those of the control group 6 months after treatment (P<0.05). There was no significant difference in gender, age, implant, cause of tooth loss, history of hypertension, drinking history, implant diameter, implant length and bone increment surgery between good and poor groups(P>0.05). There were significant differences in bone mineral density(BMD), diabetes mellitus, smoking history, probe depth and gingival sulcus bleeding index(P<0.05). Logistic regression analysis showed that grade Ⅲ-Ⅳ bone mineral density(BMD), diabetes history, smoking history, gingival crevicular bleeding index ≥2 were the risk factors affecting the treatment effect of digital guided oral implant repair in patients with dental defect(P<0.05). ROC curve analysis showed that AUC of nomogram prediction model, bone mineral density of missing teeth, diabetes mellitus, smoking history and gingival sulcus bleeding index in predicting adverse treatment effect of patients with dentition defect were 0.846, 0.725, 0.487, 0.731 and 0.702; the sensitivity was 44.70%, 53.20%, 59.60% and 66.00%,the specificity was 90.20%, 92.20%, 85.60% and 76.50%, respectively. CONCLUSIONS: Digital-guided oral implant restoration has a relatively ideal effect in the treatment of dentition defects, which is conducive to improving implant accuracy and aesthetics. However, bone mineral density(BMD), diabetes history, smoking history and gingival crevicular bleeding index will affect the therapeutic effect. The prediction model based on these risk factors has a higher predictive efficacy in evaluating the therapeutic effect.
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