Patient response prediction with logistic regression in gastrointestinal endoscopy under midazolam-alfentanil sedation performed as well as response surface model.

BACKGROUND: Researchers have used logistic regression (LR) and non-linear response surface models (RSMs) to predict patient responses to sedation. The reduced Greco and hierarchy RSMs have proven to be more appropriate than other RSMs in gastrointestinal endoscopies using midazolam and alfentanil. In this study, we evaluate the performance of a simpler model, LR, and compared it with that of RSM.

METHODS: Thirty-three patients who received esophagogastroduodenoscopy (EGD) and colonoscopy sedation with midazolam and alfentanil were enrolled in the study. LR was performed for the EGD group and validated using the colonoscopy group. The two RSMs were performed using the same process, and performances and receiver operating characteristic (ROC) curves of the models were evaluated.

RESULTS: The native EGD LR model had an ROC curve area of 0.94. For external validation, the ROC curves were 0.92, 0.94, and 0.94 for the reduced Greco, hierarchy, and LR models, respectively. Pairwise comparison between models was not significant.

CONCLUSION: The LR model performed as well as RSM in generalizing the predicted sedative effect of midazolam and alfentanil during gastrointestinal endoscopies. LR may be used for generalization across patients experiencing procedures with similar stimulus intensities.