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Construction and Clinical Validation of "Ruima Assistant," an AI System for Preanesthesia Assessment

Construction and Clinical Validation of "Ruima Assistant," an AI System for Preanesthesia Assessment

Status
Active, not recruiting
Phases
Unknown
Study type
Interventional
Source
ChiCTR
Registry ID
ChiCTR2600125476
Enrollment
Unknown
Registered
2026-05-27
Start date
2026-06-04
Completion date
Unknown
Last updated
2026-06-01

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

None

Interventions

Part 1 — System performance prospective validation arm:None
Part 2 — AI-assisted assessment arm:AI-assisted assessment
Part 2 — Conventional assessment control arm:Conventional assessment
Part 3 — Within-subject before-after arm :80 patients are randomly drawn from the same case pool and evaluated by 24 junior anesthesiologists stratified 1:1:1 by years of independent practice (n=8 eac
each case is independently evaluated by one anesthesiologist from each seniority stratum, with each anesthesiologist evaluating 10 cases. For every case, the anesthesiologist first independently draft
the system then presents the AI-alone plan for the same case, and the anesthesiologist completes and submits a revised plan under AI assistance (Physician+AI). The same 80 patients are used for within

Sponsors

The Third Affiliated Hospital of Sun Yat-sen University
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: Patient participants: 1. Elective surgical patients entering the routine preoperative assessment workflow at either of the two campuses during the study period; 2. Scheduled to receive general anesthesia, neuraxial anesthesia, peripheral nerve block, or other anesthesia requiring preoperative assessment by the anesthesiology department; 3. Complete preoperative electronic medical record available. Anesthesiologist participants: 1. Junior anesthesiologists currently practicing in the anesthesia and surgery center of the institution, in principle with <= 5 years of clinical anesthesia experience; 2. Voluntary participation with written informed consent.

Exclusion criteria

Exclusion criteria: Patient exclusion criteria: Exclude those undergoing emergency surgery, those receiving only local infiltration anesthesia without the need for systematic preoperative evaluation by the anesthesiology department, and those with critical documents or key fields missing in the electronic medical record, making it impossible to establish effective reference labels. Anesthesiologist exclusion criteria: Exclude those unwilling to participate in the study or who withdraw midway, those unable to complete the required case evaluations due to rotation arrangements during the study, and those who have been deeply involved in establishing the gold standard of this study, making it impossible to meet blinding requirements.

Design outcomes

Primary

MeasureTime frame
Information extraction F1-score;Risk-score agreement;Blinded expert total score for AI-generated anesthesia plan;Time to complete chart review and initial preoperative assessment before bedside visit;Within-subject difference in total anesthesia-plan score before vs after AI assistance;

Countries

China

Contacts

Public ContactChaojin Chen

The Third Affiliated Hospital of Sun Yat-sen University

chenchj28@mail.sysu.edu.cn+86 134 3032 2182

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Jun 11, 2026