Postoperative Pulmonary Complications (PPCs) Risk Calculator for Surgical Patients Older than 65 years of Age

Utilizing Intraoperative Respiratory Dynamic Features for Developing and Validating an Explainable Machine Learning Model

  • Input variables
  • Please submit as much of the following variables as you can to receive the accurate estimates.

TT
TT
TT

No reviews yet.

Your Rating

Unit of input variables: Minimum of MP (J min-1); AUC of CRS (min*ml cmH2O-1); Longest strike above/below mean value of MP (minutes); Longest strike above/below mean value of CRS (minutes); Variance of driving pressure((cmH2O-1)2); Minimum of CRS (ml cmH2O-1); Respiratory rate (beats/minutes); Percentage of MP value exceeding 15% from the mean (%). Measurements and meanings of input variables could be found in the paper: Utilizing Intraoperative Respiratory Dynamic Features for Developing and Validating an Explainable Machine Learning Model for Postoperative Pulmonary Complications.


The predicted probability of PPCs is

This application was developed and implemented at the Department of Anesthesiology, West China Hospital, Sichuan University. Please contact peiyi.li@scu.edu.cn for model details if necessary. (Version: 1.0.1; Last Updated: 10 Jan 2024)

ICP:蜀ICP备16010396号-5-1