Reinforcement Learned Automated Anesthesia Systems During Painless Abortion

This study compares the automated anesthesia systems for painless abortion (AAS-PA) with traditional anesthesia in painless abortions. It assesses intraoperative indicators (hypoxemia, injection pain, hypotension, hemodynamics, respiratory depression) and postoperative outcomes (nausea, dizziness, recovery time, satisfaction). The AAS-PA group uses AI-adjusted intravenous ciprofol based on real-time vital signs and sedation depth; the traditional group relies on manual anesthesia. The goal is to verify if AAS-PA safely manages sedation, meets painless standards, reduces adverse events, and improves experience, aiding optimized automated protocols.

NCT Number	NCT07132151
Lead Sponsor	Boston Intelligent Medical Research Center, Shenzhen United Scheme Technology Co., Ltd. Collaborators: Fujian Provincial Hospital, Shishi Hospital, Sichuan Provincial People's Hospital, First Affiliated Hospital of the Chinese People's Liberation Army Naval Medical University, The People's Hospital of Yubei District of Chongqing city, Peking University Shenzhen Hospital, People's Hospital of Zhengzhou University, Jinjiang Municipal Hospital (Shanghai Sixth People's Hospital Fujian)
Conditions	Painless Abortion, Artificial Intelligence (AI), Ciprofol
Enrollment	167 participants
Start Date	2025-09-08
Primary Completion	2025-10-08 (estimated)
Study Completion	2027-11-08 (estimated)
Updated on ClinicalTrials.gov	2025-08-20