Development of Synthetic Medical Data Generation Technology to Predict Postoperative Complications

NCT05986474 | Completed

• 1 other identifier: H-2102-192-1203
• Study Type: observational
• Target: 410,000
• Locations: 1 country
• Sites: 1

Brief 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.

Conditions

Acute Kidney Injury; Surgery-Complications; Nephropathy

Outcome Measures

Primary Outcomes (2)

• Acute kidney injury

  Surgical complication 1

  After surgery, within 7 days

• Acute kidney disease

  Surgical complication 2

  After surgery, within 3 months

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Patients over 18 years who underwent non-cardiothoracic and non-vascular surgery

You may qualify if:

• 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)

You may not qualify if:

• \) no information of baseline (≤90 days before surgery) or follow-up (≤7 days after surgery) renal function
• \) exclusive surgery, including surgeries of deceased patients or surgery that directly affect renal function (partial or total nephrectomy, kidney transplantation)
• \) 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
• \) surgery other than general or spinal anesthesia (local anesthesia or monitored anesthesia care)
• \) missing covariates.

Sponsors & Collaborators

• Seoul National University Hospital: lead

Study Sites (1)

Seoul National University Hospital

Seoul, South Korea

Location

Related Publications (1)

• Cho JM, Kwon S, Yang S, Park J, Jeong S, Park S, Ryu J, Kim S, Lee J, Lee JP, Yoon HJ, Kim DK, Joo KW, Kim YS, Kim K, Park M, Lee H. Acute kidney injury after non-cardiac major surgery: has it reduced? Clin Kidney J. 2024 Jun 19;17(7):sfae183. doi: 10.1093/ckj/sfae183. eCollection 2024 Jul.

  PMID: 39831175 DERIVED

MeSH Terms

Conditions

Acute Kidney Injury; Kidney Diseases

Condition Hierarchy (Ancestors)

Renal Insufficiency; Urologic Diseases; Female Urogenital Diseases; Female Urogenital Diseases and Pregnancy Complications; Urogenital Diseases; Male Urogenital Diseases

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: CROSS SECTIONAL
• Target Duration: 5 Years
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Associate Professor

Study Record Dates

• First Submitted: August 3, 2023
• First Posted: August 14, 2023
• Study Start: March 26, 2021
• Primary Completion: September 27, 2022
• Study Completion: March 25, 2023
• Last Updated: August 14, 2023

Record last verified: 2023-08

Locations

KR (1)