Development and Validation of a Predictive Model for Postoperative Pulmonary Complications in Elderly Patients

Huazhong University of Science and Technology

Status: Enrolling

Conditions: Postoperative Pulmonary Complications

Study type: Observational

Funder types: Other

Identifiers

NCT05506163

PPC20210110

Details and patient eligibility

About

Although several clinical predictive models have been developed to predict postoperative pulmonary complications, few predictive models have been developed for elderly patients. In this study, the researchers aimed to develop a new, simplified model to assess the risk of postoperative pulmonary complications in elderly patients using perioperative database information.

Full description

Postoperative pulmonary complications occur frequently, which is an important cause of death and morbidity. Age has always been an significant predictor of postoperative pulmonary complications. With an aging population worldwide, more and more elderly people are undergoing surgery due to the expansion of surgical indications. As a result of this phenomenon, the elderly are also an important group for the prediction and intervention of postoperative pulmonary complications. In order to better assess the risk of postoperative pulmonary complications in elderly patients, we constructed a model using database information.

Enrollment: 10,000 estimated patients

Sex: All

Ages: 65+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• Age 65 years or older
• receiving invasive ventilation during general anesthesia for surgery

Exclusion criteria

• preoperative mechanical ventilation
• operations related to previous postoperative complications
• a second operation after surgery
• organ transplantation
• discharged within 24 hours after surgery
• cardiac and thoracic surgery

Trial design

10,000 participants in 2 patient groups

Training set

Description:

The whole cohort is randomly assigned to a training cohort and validation cohort.

validation set

Description:

The whole cohort is randomly assigned to a training cohort and validation cohort.