Large language model–based prediction of speech intelligibility after Vibrant Soundbridge implantation using multidimensional outcome data: Part 2 of a prospective study

Active middle ear implants (AMEIs) such as the Vibrant Soundbridge (VSB) offer an effective treatment option for patients with mixed or conductive hearing loss and large air-bone gaps, where conventional hearing rehabilitation often fails. However, postoperative outcomes-particularly speech intelligibility at 65 dB SPL in free-field (WRS_65dB)-show high interindividual variability. This study aimed to develop a predictive model for WRS_65dB based on four clinically relevant parameters: postoperative bone conduction thresholds (BC_PTA4), unaided preoperative maximum speech intelligibility (WRS_max), Vibrogram threshold (VIB_PTA4), and age. Data from 20 patients were analyzed. Spearman's correlation revealed significant associations between WRS_65dB and postoperative BC_PTA4, preoperative WRS_max, and age. Using a seven-step approach supported by GPT-4o, we developed a sigmoid-transformed linear regression model. The final model included BC_PTA4, WRS_max, and age and achieved an R² of 0.51, r = 0.71, RMSE = 6.18, and MAE = 4.67. Model performance was assessed by means of residual and outlier analysis. This model provides a transparent and clinically applicable tool for preoperative outcome estimation in VSB candidates. Further validation in larger, multicenter cohorts is needed to confirm its generalizability.