Predicting Postoperative Pulmonary Infection in Elderly Patients Undergoing Major Surgery: a Study Based on Logistic Regression and Machine Learning Models

Union Hospital, Tongji Medical College, Huazhong University of Science and Technology9,481 enrolled

Overview

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

Study Type

OBSERVATIONAL

Enrollment

9,481

Conditions

Postoperative Pulmonary Infection in Elderly Patients

Eligibility

Sex: ALLMin age: 65 Years

Medical Language ↔ Plain English

Inclusion Criteria: 1. age ≥ 65 years 2. patients who were mechanically ventilated under major surgery Exclusion Criteria: 1. preoperative tracheal intubation 2. preoperative pneumonia 3. organ transplantation 4. missing data

Locations (1)

Union Hospital, Tongji Medical College, Huazhong University of Science and Technology

Wuhan, Hubei, China

Outcomes

Primary Outcomes

the incidence of postoperative pulmonary infection during hospitalization

Time frame: through study completion, an average of 30 days