Construction of Perioperative Medical Data Platform and Its Typical Practice to Predict Postoperative Acute Moderate to Severe Pain With Machine Learning Models

Recruiting

• Conditions: Risk Reduction; Acute Pain; Anesthesia
• Interventions: Other: No intervention

• Registration Number: NCT05569460
• Lead Sponsor: Guangdong Second Provincial General Hospital

Brief Summary

Data intelligence platform was widely used to facilitate the process of clinical research. However, a platform that integrates natural language processing (NLP) and machine learning (ML) algorithms has not been reported in perioperative medical management.

Detailed Description

Not available

Study Timeline

• Status Verified: 2022-10
• Study Start: 2022-10
• Study First Submitted: 2022-10-03
• Study First Submitted QC: 2022-10-03
• Last Update Submitted: 2022-10-03
• Study First Posted: 2022-10-06
• Last Update Posted: 2022-10-06
• Primary Completion: 2023-10
• Study Completion: 2023-12

Recruitment & Eligibility

• Status: RECRUITING
• Sex: All
• Target Recruitment: 6500

Inclusion Criteria

• Patients were included if they were above 18 years old, undergoing non-local anesthesia surgery.

Exclusion Criteria

• The basic information such gender, age, height, weight, and body mass index (BMI) were missing.
• Patients undergoing day surgery, with a history of multiple operations, or entering ICU after surgery, and losing the NRS score during movement at 24h after surgery.

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Arm && Interventions

Group	Intervention	Description
Numeric Rating Scale (NRS) score after surgery <4	No intervention	-
Numeric Rating Scale (NRS) score after surgery ≥ 4	No intervention	-

Primary Outcome Measures

Name	Time	Method
Area under the curve	April 2020 to May 2021	It measures the prediction effect of the algorithm model

Trial Locations

Locations (1)

Guangdong Second Provincial General Hospital; 🇨🇳 Guangzhou, China