PIC,a paediatric-specific intensive care database

PIC (Paediatric Intensive Care) is a large paediatric-specific, single-centre, bilingual database comprising information relating to children admitted to critical care units at a large children’s hospital in China.
Published in Research Data
PIC,a paediatric-specific intensive care database
Like

The lack of open  clinical data have limited many researches and innovations.It’s a complicated issue that needs to balance privacy exposure and research needs.

MIMIC (Medical Information Mart for Intensive Care) is an openly available dataset developed for more than a decade and contains comprehensive clinical data associated with ~60,000 intensive care unit admissions. However, MIMIC only contains data on neonates in the NICU, comprehensive pediatric patient (age from 0 to 18 years old) data are not available in it. Children are not just small adults and often have different diseases, developmental issues, and possibly differential responses to therapies and the recovery of function. There is a lack of a freely accessible database that contains the completeness of pediatric intensive care data for researchers.

Inspired by MIMIC, we decided to build a pediatric-specific critical care database for stimulating more researchers to pay attention to children’s intensive care and improve the quality of critical care for children in December 2018. During the year, most of the team members have devoted a lot of effort, and we strive to do our best in every step especially in translation because all the lab test items, medication names, examinations and diagnoses were recorded using Chinese in our original database. We also hope that all researchers interested in relevant studies can actively participate in our work and communicate with each other. 

In our recently published paper in Scientific Data (https://doi.org/10.1038/s41597-020-0355-4), we report the release of the PIC database and methods that were used to build this database. The PIC database integrates deidentified, comprehensive clinical data of pediatric patients admitted to the Children’s Hospital of Zhejiang University School of Medicine and makes it internationally accessible to researchers under a data use agreement. This database encompasses 13,499 distinct hospital admissions from 12,881 distinct pediatric patients between 2010 and 2018. This database is notable in that it is the first freely accessible English-Chinese bilingual clinical database and as a pediatric critical care supplement to the MIMIC-III. Since the PIC is a large relational database with many different data types which cannot quickly and easily retrieve information specific to an individual patient. It is a time-consuming process for new researchers to perform joint multiple table queries to fully understand which data are useful and available. We provide a website that can easily be used to explore the PIC and visualize clinical data at the patient level (http://pic.nbscn.org/chartsview).     Researchers seeking to use the database must formally request access with the following two websites: http://pic.nbscn.org https://physionet.org/content/picdb/

The life of the database lies in continuous updates and applications. We are very happy to  get some feedbacks from the community since we publish the database on Phyisonet. Some of industries innovators want us to provide the original wave data such as ECG, the clinical data enhanced wave data will help them to improve their product dedicate for children.  We hope researchers from relevant branches find this database useful and welcome any feedback to us. At the same time, the National Children's Health and Disease Clinical Research Center will continue to advance the project to serve the development of pediatric critical care.

Please sign in or register for FREE

If you are a registered user on Research Communities by Springer Nature, please sign in

Subscribe to the Topic

Research Data
Research Communities > Community > Research Data

Related Collections

With collections, you can get published faster and increase your visibility.

Remote sensing data for changes in land use

This Collection comprises a series of articles presenting data on changes to land use in urban areas, farmland, forests, and natural environments, as determined using remote sensing techniques.

Publishing Model: Open Access

Deadline: Jan 31, 2024

Ecological data for tracking biological diversity and environmental change

This collection presents data contributions addressing topics in biodiversity and ecology.

Publishing Model: Open Access

Deadline: Jan 31, 2024