Retrospective Analysis of Complications and Survival of Teeth Restored Following Crown Lengthening

The aim of this retrospective study was to evaluate the survival rates and complications of structurally compromised teeth restored with full-coverage crowns following crown lengthening procedure (CLP), in a postgraduate dental setting. In this retrospective study the records of patients who received surgical CLP prior to receiving full coverage crowns at X hospital between January 2011 to January 2021 were obtained and reviewed by A.AH and F.AR for possible inclusion in the study. Retrospective data were collected manually from digital records of registered patients (Dental4windows, Centaur Software Development Co Pty Ltd., Australia). All personal information is de-identified and securely stored with a study code number. The data were then organized into categories based on a pre-determined form for single crowns with CLP . The calculation of sample size was based on a 10-year survival rate of 78.4% tooth preservation after crown lengthening procedure and restorative treatment in department of periodontics and oral medicine at the school of dentistry of the university of Michigan (where p is the prevalence of crown after crown lengthening, d is the precision of the estimate, and z\_(α/2)\^2 is the quartile of the 95% confidence interval). Using the above equation and data from the aforementioned study, the sample size needed is determined to be 260 teeth. Statistical Analysis The collected data will be transferred to Statistical Package for Social Sciences (SPSS) for Windows (IBM- SPSS) version 25.0 (SPSS Inc., Chicago, IL, USA) for statistical analysis. Significance for statistical analysis will be set at P \< 0.05. Chi-square analysis will be used to measure the association strength between the frequency of both the survival of crown after crown lengthening and the complications. Kaplan-Meier will be used for analysis of the survival and Logistic regression will be used for the potential risk factors. P values \<0.05 will be considered as a statistically significant.