Different Algorithm Models to Predict Postoperative Pneumonia in Elderly Patients

Status

UNKNOWN

Phases

Unknown

Study type

Observational

Source

ClinicalTrials.gov

Registry ID

NCT05671926

Enrollment

10000

Registered

2023-01-05

Start date

2023-01-31

Completion date

2023-02-28

Last updated

2023-01-05

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

Conditions

Postoperative Pulmonary Complications

Brief summary

The researchers aim to compare different algorithms to predict postoperative pneumonia in elderly patients and to assess the risk of pneumonia in elderly patients.

Detailed description

Postoperative pneumonia is a common complication that increases the mortality and length of older patients. In order to better assess the risk of postoperative pneumonia in elderly patients, we plan to use database information and different algorithms, such as logistic regression, random forest, and other algorithms respectively to build models and evaluate the effects of the models.

Interventions

None listed

Study design

Observational model

COHORT

Time perspective

RETROSPECTIVE

Eligibility

Sex/Gender

ALL

Age

65 Years to No maximum

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 and thoracic surgery

Design outcomes

Primary

Measure	Time frame
Postoperative pulmonary complications	within one week after surgery

Secondary

Measure	Time frame
Postoperative pulmonary complications	30 days after surgery

Contacts

Primary ContactQingping Wu, PhD

wqp1968@163.com13971605283

Outcome results