Comparing polynomial regression and exponential growth model in predicting recession gain based on clinical gingival recession.

BACKGROUND

Gingival recession (GR) is a common issue causing plaque accumulation, root caries, abrasion, cervical wear, and dentin hypersensitivity. Studies show a prevalence of thick and thin gingival biotypes, with no significant association between age, gender, or recession. This study aims to use polynomial regression and exponential growth models to predict recession gain based on clinical data. GR is a common issue causing plaque accumulation, root caries, abrasion, cervical wear, and dentin hypersensitivity. Studies show a prevalence of thick and thin gingival biotypes, with no significant association between age, gender, or recession. This study aims to use polynomial regression and exponential growth models to predict recession gain based on clinical data.

METHODS

The study analyzed recession coverage in upper and lower anterior teeth after connective tissue and free gingival grafting procedures from institute database. Data was preprocessed and analyzed using polynomial regression and exponential growth models. Polynomial regression allowed for nonlinear trends in recession gain, while exponential growth models provided insights into cumulative effects of specific factors on recession progression.

RESULTS

The polynomial of degree 3 with the lowest MSE of 0.0612 fit best. This shows that cubic polynomials better represent the "Days"-"Gain Width" relationship than linear or higher-degree polynomials. The exponential growth model fitted to "Post Op" data predicts an initial value of 0.7735 and a growth rate of 0.0101. This model proposes that "Post Op" measurements expand exponentially, with predicted parameters reflecting this growth.

CONCLUSIONS

Based on clinical data, this study compares polynomial regression and exponential growth models for periodontal recession gain prediction. The findings emphasize the need of proper mathematical models to better understand periodontal diseases and guide dental care prevention and treatment.