Predicting Local Anesthetic Success in Symptomatic Irreversible Pulpitis: A Machine Learning Study

This study will develop and internally validate three machine learning models - logistic regression, random forest, and XGBoost - to predict local anesthetic (LA) success in patients undergoing endodontic treatment for symptomatic irreversible pulpitis (SIP). A large retrospective cohort of 4,390 consecutive adult patients treated at a single center (May 2014-October 2025) is being analyzed. The dataset was frozen in October 2025 for this analysis.

NCT Number	NCT07672678
Lead Sponsor	Jamia Millia Islamia
Conditions	Pulpitis, Nerve Block, Anesthesia, Local
Enrollment	4,390 participants
Start Date	2014-05-01
Primary Completion	2025-10-16 (estimated)
Study Completion	2025-12-16 (estimated)
Updated on ClinicalTrials.gov	2026-06-29