Abstract: PURPOSE: To construct a prediction model for implant failure in patients with dentition defect and verify its efficacy. METHODS: A total of 195 patients who underwent implant repair due to dental defect in the First People's Hospital of Pingdingshan City from March 2020 to March 2023 were selected and followed up for 1 year after discharge. According to the follow-up results, the patients were divided into implant failure group(n=25) and implant success group(n=170). The risk factors of implant failure in patients with denture defect were screened by univariate and multivariate regression analysis. A nomogram model of implant failure in patients with dental defects was constructed based on risk factors, and the predictive efficiency of the nomogram model was evaluated by Hosmer-Lemeshow test and receiver operating characteristic(ROC) curve. SPSS 26.0 software package was used for statistical analysis. RESULTS: Age≥ 60 years old, complicated with diabetes mellitus, smoking history, bad oral habits, maxillary defect, gingival creval bleeding index≥ 2, the proportion of grade Ⅲ to Ⅳ alveolar bone mineral density in the failed implantation group and the successful implantation group had significant difference (P< 0.05). There was no significant difference in sex ratio, hypertension, implantation time, implant diameter and other clinical data(P> 0.05). Logistic multivariate regression analysis results showed age≥ 60 years old (OR=1.857), diabetes mellitus (OR=1.822), history of smoking (OR=1.806), bad oral habits (OR=1.714), maxillary defect (OR=1.885), gingival crevicular bleeding index ≥ 2 (OR=1.874), alveolar bone mineral density (OR=1.869) were independent risk factors for implant failure in patients with denture defects (P< 0.05). Based on age, diabetes, smoking history, bad oral habits, maxillary defect, gingival crevicular bleeding index, and alveolar bone density, a nomogram model of implant failure risk for patients with dental defect was constructed. The results showed that the C-index was 0.905(95%CI: 0.855-0.972), and the measured value was basically consistent with the predicted value. CONCLUSIONS: The factors of implant failure in patients with dentition defect include age, diabetes, smoking history, bad oral habits, maxillary defect, gingival crevicular bleeding index, and alveolar bone mineral density. The nomogram model constructed based on this analysis has a good predictive effect on implant failure.

Key words: Dentition defect, Implant restoration, Risk factors, Nomogram model, Prediction of implant failure