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Clinical Trial Summary

Although a number of clinical predictive models were developed to predict postoperative pulmonary complications, few predictive models have been used in elderly patients. In this study, the researchers aim to compare different algorithms to predict postoperative pulmonary complications in elderly patients and to assess the risk of postoperative pulmonary complications in elderly patients.


Clinical Trial Description

Postoperative pulmonary complications occur frequently, which is an important cause of death and morbidity. Age has been an important predictor of postoperative pulmonary complications. As the world's population ages, more and more older people are undergoing surgery as indications for surgery expand. In order to better assess the risk of postoperative pulmonary complications in elderly patients, we plan to use database information and different algorithms such as logistic regression, random forest, and other algorithms to build models respectively and evaluate the effects of the models. ;


Study Design


Related Conditions & MeSH terms

  • Postoperative Pulmonary Complications

NCT number NCT05671939
Study type Observational
Source Wuhan Union Hospital, China
Contact Qingping Wu, PhD
Phone 13971605283
Email wqp1968@163.com
Status Not yet recruiting
Phase
Start date January 2023
Completion date March 2023

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