Development of Synthetic Medical Data Generation Technology to Predict Postoperative Complications

Acute Kidney Injury Clinical Trial

Official title:

Development of Synthetic Medical Data Generation Technology to Predict Postoperative Complications

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT05986474
• Other study ID #: H-2102-192-1203
• Status: Completed
• Start date: March 26, 2021
• Est. completion date: March 25, 2023

Study information

• Verified date: August 2023
• Source: Seoul National University Hospital
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational [Patient Registry]

Clinical Trial Summary

<Development of synthetic medical data generation technology to predict postoperative complications> In order to develop a model for predicting the occurrence of complications after surgery, it is necessary to establish a cohort along with statistical indicators related to the occurrence of complications. This study aims to combine synthetic medical data based on actual clinical data and develop a predictive model based on synthetic medical data. This will allow researchers to conduct research only with synthetic data without dealing with actual medical data, allowing them to use and process data without legal constraints, and to create as much data as they want based on various preprocessed, standardized, and labeled raw data. Patients from three hospitals in Korea (Seoul National University Hospital, Seoul National University Bundang Hospital, Seoul Metropolitan City-Boramae Medical Center) were enrolled for the study. Medical data (both clinical and laboratory) from 410,000 patients who were conducted surgery between 2005 and 2020 were collected to evaluate the performance of the prediction model using AKI-based prediction model development and external verification. Based on the collected patient data, synthetic medical data were combined using the machine learning algorithm, and the anonymity and re-identification of the synthesized medical data were evaluated. Also, the development of AI-based prediction model using synthetic medical data and the actual medical data model were compared.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 410000
• Est. completion date: March 25, 2023
• Est. primary completion date: September 27, 2022
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

• Patients over 18 years.
• Non-cardiothoracic and non-vascular surgery from five departments (general surgery, obstetrics and gynecology (OBGY), urologic surgery, neurosurgery, and orthopedic surgery)

Exclusion Criteria:

• 1) no information of baseline (=90 days before surgery) or follow-up (=7 days after surgery) renal function
• 2) exclusive surgery, including surgeries of deceased patients or surgery that directly affect renal function (partial or total nephrectomy, kidney transplantation)
• 3) preoperative advanced kidney dysfunction, including preoperative serum creatinine (SCr) =4.0 mg/dL, baseline eGFR (estimated glomerular filtration rate) <15 mL/min/1.73 m2, preoperative kidney replacement therapy history, or AKI history within 2 weeks of surgery
• 4) surgery other than general or spinal anesthesia (local anesthesia or monitored anesthesia care)
• 5) missing covariates.

Related Conditions & MeSH terms

• Acute Kidney Injury
• Nephropathy
• Postoperative Complications

Locations

Country	Name	City	State
Korea, Republic of	Seoul National University Hospital	Seoul

Sponsors (1)

Lead Sponsor	Collaborator
Seoul National University Hospital

Country where clinical trial is conducted

Korea, Republic of, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Acute kidney injury	Surgical complication 1	After surgery, within 7 days
Primary	Acute kidney disease	Surgical complication 2	After surgery, within 3 months