Establishment and data quality control of a multicenter prospective database for prevalence of abdominal complications after gastroenterological surgery.
10.3760/cma.j.cn441530-20221214-00524
- Author:
Qi WANG
1
;
Zhou Qiao WU
1
;
Zi Ning LIU
1
;
Zi Yu LI
1
;
Jia Fu JI
1
Author Information
1. Department of Gastrointestinal Surgery, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital & Institute, Beijing 100142, China.
- Publication Type:Journal Article
- MeSH:
Humans;
Prevalence;
Data Accuracy;
Postoperative Complications/etiology*;
Abdomen/surgery*;
Digestive System Surgical Procedures/adverse effects*
- From:
Chinese Journal of Gastrointestinal Surgery
2023;26(2):154-159
- CountryChina
- Language:Chinese
-
Abstract:
As the main cause of secondary operation and postoperative death, the incidence of intraperitoneal infectious complications varies significantly in different medical centers in China. Due to the lack of national data, it is not possible to assess and develop appropriate diagnosis and treatment strategies properly. To provide a high-quality data platform for complication registration and clinical research, a multicenter prospective database for the Prevalence of Abdominal Complications After GastroEnterological surgery was established. Based on the Hospital Information System (HIS)of 20 medical centers in China, the electronic case reporting form (e-CRF) listed on the website was used to collect medical information of patients undergoing gastric or colorectal cancer surgery. The data were verified by on-site auditing, and data cleaning was performed by R software. After the data cleaning, the data in the database was checked and evaluated by the principle investigators and data administrators. When all data queries and questions were corrected and answered, the database was locked to establish a multicenter prospective database for postoperative abdominal infectious complications (the PACAGE database). The PACAGE database has rich information resources and high data quality and is a good data platform for complication registration and clinical research.
