CAD/CAM Abutments in the Esthetic Zone: A Systematic Review and Meta-Analysis of Soft Tissue Stability.
Diego LopsEugenio RomeoMagda MensiGiuseppe TroianoKhrystyna ZhurakivskaMassimo Del FabbroAntonino PalazzoloPublished in: Journal of clinical medicine (2023)
Computer-aided design and computer-aided manufacturing customized abutments are increasingly used in everyday clinical practice. Nevertheless, solid scientific evidence is currently lacking regarding their potential advantages in terms of soft tissue stability. The main aim of this systematic review and meta-analysis was to compare the soft tissue outcomes of prefabricated versus customized (CAD/CAM) abutments. The present review was registered with PROSPERO (CRD42020161875) and the protocol was developed according to the PRISMA statement. An electronic search was performed on three databases (PubMed, Embase and Cochrane Central) up to May 2023. Data extraction was followed by qualitative and quantitative analysis of the included studies. Three randomized controlled clinical trials and three controlled clinical trials (number of patients = 230; number of dental implants = 230) with a follow-up of between 12 and 36 months were included. No significant differences were observed between prefabricated versus customized (CAD/CAM) abutments regarding midfacial mucosal recession, interproximal papillae and pink aesthetic score (PES) after 12 months. Conclusion: The potential benefits of CAD/CAM abutments on soft tissues should be better clarified in future investigations. The usage of customized CAD/CAM abutments in everyday clinical practice should be based on a careful case-by-case evaluation (CRD42020161875).
Keyphrases
- soft tissue
- clinical trial
- clinical practice
- end stage renal disease
- chronic kidney disease
- open label
- phase iii
- ejection fraction
- newly diagnosed
- randomized controlled trial
- double blind
- systematic review
- peritoneal dialysis
- big data
- machine learning
- adipose tissue
- electronic health record
- high resolution
- patient reported outcomes
- deep learning
- skeletal muscle