Different Algorithm Models to Predict Postoperative Pulmonary Complications in Elderly Patients

Different Algorithm Models to Predict Postoperative Pulmonary Complications in Elderly Patients

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.

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.

Inclusion Criteria:

1. Age 65 years or older
2. receiving invasive ventilation during general anesthesia for surgery

Exclusion Criteria:

1. preoperative mechanical ventilation
2. procedures related to a previous surgical complication
3. a second operation after surgery
4. organ transplantation
5. discharged within 24 hours after surgery
6. cardiac surgery