Prediction models for the complication incidence and survival rate of dental implants-a systematic review and critical appraisal.

Purpose: This systematic review aims to assess the performance, methodological quality and reporting transparency in prediction models for the dental implant's complications and survival rates.

Methods: A literature search was conducted in PubMed, Web of Science, and Embase databases. Peer-reviewed studies that developed prediction models for dental implant's complications and survival rate were included. Two reviewers independently evaluated the risk of bias and reporting quality using the PROBAST and TRIPOD guidelines. The performance of the models were also compared in this study. The review followed the PRISMA guidelines and was registered with PROSPERO (CRD42019122274).

Results: The initial screening yielded 1769 publications, from which 14 studies featuring 43 models were selected. Four of the 14 studies predicted peri-implantitis as the most common outcome. Three studies predicted the marginal bone loss, two predicted suppuration of peri-implant tissue. The remaining five models predicted the implant loss, osseointergration or other complication. Common predictors included implant position, length, patient age, and a history of periodontitis. Sixteen models showed good to excellent discrimination (AUROC >0.8), but only three had undergone external validation. A significant number of models lacked model presentation. Most studies had a high or unclear risk of bias, primarily due to methodological limitation. The included studies conformed to 18-27 TRIPOD checklist items.

Conclusions: The current prediction models for dental implant complications and survival rate have limited methodological quality and external validity. There is a need for enhanced reliability, generalizability, and clinical applicability in future models.