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

Status

Completed

Phases

Unknown

Study type

Observational

Source

ClinicalTrials.gov

Registry ID

NCT06491459

Enrollment

9481

Registered

2024-07-09

Start date

2024-01-01

Completion date

2024-06-01

Last updated

2024-07-09

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Postoperative Pulmonary Infection in Elderly Patients

Brief summary

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.

Interventions

None listed

Study design

Observational model

COHORT

Time perspective

RETROSPECTIVE

Eligibility

Sex/Gender

ALL

Age

65 Years to No maximum

Healthy volunteers

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

Design outcomes

Primary

Measure	Time frame	Description
the incidence of postoperative pulmonary infection during hospitalization	through study completion, an average of 30 days	the incidence of postoperative pulmonary infection during hospitalization

Countries

China

Outcome results