Login / Signup

INSPIRE, a publicly available research dataset for perioperative medicine.

Leerang LimHyeonhoon LeeChul-Woo JungDayeon SimXavier BorratTom J PollardLeo A CeliRoger G MarkSimon Tilma VistisenHyung-Chul Lee
Published in: Scientific data (2024)
We present the INSPIRE dataset, a publicly available research dataset in perioperative medicine, which includes approximately 130,000 surgical operations at an academic institution in South Korea over a ten-year period between 2011 and 2020. This comprehensive dataset includes patient characteristics such as age, sex, American Society of Anesthesiologists physical status classification, diagnosis, surgical procedure code, department, and type of anaesthesia. The dataset also includes vital signs in the operating theatre, general wards, and intensive care units (ICUs), laboratory results from six months before admission to six months after discharge, and medication during hospitalisation. Complications include total hospital and ICU length of stay and in-hospital death. We hope this dataset will inspire collaborative research and development in perioperative medicine and serve as a reproducible external validation dataset to improve surgical outcomes.
Keyphrases
  • intensive care unit
  • patients undergoing
  • cardiac surgery
  • healthcare
  • emergency department
  • machine learning
  • mental health
  • deep learning
  • adverse drug
  • risk factors
  • acute care