预测糖尿病患者牙种植术后发生种植体周围炎风险的列线图模型建立与分析

doi:10.19439/j.sjos.2021.05.013

摘要/Abstract

摘要： 目的: 探讨糖尿病患者牙种植术后发生种植体周围炎的危险因素,并建立相关列线图预测模型。方法: 回顾性分析2016年1月—2018年12月行牙种植修复治疗的257例糖尿病患者的临床资料,采用整群随机抽样法将数据分为训练集（n=153）和验证集（n=104）。分别使用单因素和Logistic回归分析,确定糖尿病患者发生种植体周围炎的独立危险因素;同时建立相关列线图预测模型,采用Bootstrap 法对模型进行内部验证,外部验证通过验证集自抽样法完成。采用SPSS 22.0软件包对数据进行统计学分析。结果: 吸烟指数>200支/年（OR=6.364,95%CI：1.943~20.840）、HbA1c>7%（OR=4.680,95%CI：1.497~14.628）、牙周病史（OR=3.779,95%CI：1.359~10.507）、前牙区种植（OR=7.183,95%CI：2.371~21.756）、刷牙频率≤1次/d（OR=4.796,95%CI：1.471~15.637）和未定期洁治（OR=4.994,95%CI：1.745~14.295）是糖尿病患者种植牙术后发生周围炎的独立危险因素（P<0.05）。基于以上6项危险因素建立预测糖尿病患者发生种植体周围炎的列线图模型,校准曲线验证显示,训练集和验证集的预测值与实测值基本一致。ROC曲线验证显示,训练集和验证集的C指数分别为0.867和0.822,说明列线图模型具有良好的预测精准度。结论: 吸烟指数>200支/年、HbA1c>7%、牙周病史、前牙区种植、刷牙频率≤1次/d和未定期洁治是糖尿病患者发生种植体周围炎的独立危险因素,基于以上危险因素建立的列线图模型能够直观、准确预测糖尿病患者发生种植体周围炎的概率。

关键词: 糖尿病, 牙种植体, 周围炎, 列线图模型

Abstract: PURPOSE: To explore the risk factors of peri-implantitis after dental implants in diabetic patients, and establish a related nomogram prediction model. METHODS: The clinical data of diabetic patients undergoing dental implant restoration from January 2016 to December 2018 were retrospectively analyzed, and cluster random sampling method was used to divide the data into training set (n=153) and validation set (n=104). Univariate and Logistic regression were used to analyze the independent risk factors of peri-implantitis in diabetic patients. At the same time, the relevant nomogram prediction model was established, and the model was internally verified by Bootstrap method. The external verification was completed by self sampling method of verification set. SPSS 22.0 software package was used for statistical analysis. RESULTS: Smoking index>200 cigarettes(OR=6.364, 95%CI: 1.943-20.840), HbA1c>7%(OR=4.680, 95%CI: 1.497-14.628), periodontal history (OR=3.779, 95%CI: 1.359-10.507), anterior teeth implantation(OR=7.183, 95%CI: 2.371-21.756), tooth brushing frequency ≤1 time/day (OR=4.796, 95%CI: 1.471-15.637) and unscheduled cleaning (OR=4.994, 95%CI: 1.745-14.295) were independent risk factors for peri-implantitis after dental implantation in diabetic patients (P<0.05). Based on the above 6 risk factors, a nomogram model to predict the occurrence of peri-implantitis in diabetic patients was established. The calibration curve verification showed that the predicted values of the training set and the verification set were basically the same as the actual measured values, and ROC curve verification showed C-index indexes of the training set and the verification set were 0.867 and 0.822, respectively, indicating that the nomogram model had good prediction accuracy. CONCLUSIONS: Smoking index>200 cigarettes, HbA1c>7%, periodontal history, anterior dental implantation, brushing frequency ≤1 time/day and unscheduled cleaning are independent risk factors for peri-implantitis in diabetic patients based on the above risk factors. The line graph model can intuitively and accurately predict the probability of peri-implantitis in diabetic patients.

Key words: Diabetes, Dental implant, Peri-implantitis, Nomogram model

中图分类号:

R782.1

张锐, 马俊涛. 预测糖尿病患者牙种植术后发生种植体周围炎风险的列线图模型建立与分析[J]. 上海口腔医学, 2021, 30(5): 517-521.

ZHANG Rui, MA Jun-tao. Establishment of a nomogram model to predict the risk of peri-implantitis in patients with diabetes mellitus[J]. Shanghai Journal of Stomatology, 2021, 30(5): 517-521.

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