Attributable fractions, modifiable risk factors and risk stratification using a risk score for peri-implant pathology

详细信息    查看全文

• 作者：Miguel de Araú ; jo Nobre ; RDH ; MSc Epi^a ; ^b ; ^{mignobre@gmail.com} ; Antó ; nio Mano Azul ; MD^c ; Evangelista Rocha ; MD ; PhD^a ; Paulo Maló ; DDS ; PhD^b ; Francisco Salvado ; MD ; PhD^a
• 关键词：Dental implants ; Risk scores ; Pathology ; Risk factors ; Risk prediction ; Peri-implantitis ; Peri-implant pathology
• 刊名：Journal of Prosthodontic Research
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：61
• 期：1
• 页码：43-53
• 全文大小：3473 K
• 卷排序：61

文摘

This study aimed to estimate the impact of risk factors for peri-implant pathology, to identify potentially modifiable factors, and to evaluate the accuracy of the risk algorithm, risk scores and risk stratification.MethodsThis retrospective case–control study with 1275 patients (255 cases; 1020 controls) retrieved a model according to the predictors: history of Periodontitis, bacterial plaque, bleeding, bone level, lack of passive fit or non-optimal screw joint, metal-ceramic restoration, proximity to other implants/teeth, and smoking habits. Outcome measures were the attributable fraction; the positive and negative likelihood ratios at different disease cut-off points illustrated by the area under the curve statistic.ResultsSix predictors may be modified or controlled directly by either the patient or the clinician, accounting for a reduction in up to 95% of the peri-implant pathology cases. The positive and negative likelihood ratios were 9.69 and 0.13, respectively; the area under the curve was 0.96; a risk score was developed, making the complex statistical model useful to clinicians.ConclusionsBased on the results, six predictors for the incidence of peri-implant pathology can be modified to significantly improve the outcome. It was possible to stratify patients per risk category according to the risk score, providing a tool for clinicians to support their decision-making process.