- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT06218758
Prediction Model for PPCs in Patients Undergoing Lung Transplantation Using Machine Learning
Prediction Model for Postoperative Pulmonary Complications in Patients Undergoing Lung Transplantation Using Machine Learning: a Retrospective Cohort Study
Study Overview
Detailed Description
After the first report of lung transplantation in humans in 1963, rapid advancements in immunosuppressive agents since the mid-1990s have led to significant progress in both the quantity and quality of lung transplantation. In 2004, a total of 1,815 lung transplantations were reported worldwide. Patients undergoing lung transplantation are typically elderly, often experiencing not only impaired lung function but also overall instability in their health. Despite successful outcomes in lung transplantation, the occurrence of pulmonary complications after surgery can lead to deterioration or even fatal consequences.
Postoperative pulmonary complications (PPCs) can result in prolonged hospitalization, increased complications, and the need for additional treatment. Various factors are associated with the development of PPCs after lung transplantation, including age, smoking, pre-existing lung diseases (such as chronic obstructive pulmonary disease, pulmonary fibrosis, etc.), immunosuppressive drug use post-transplant, diabetes, hypertension, pulmonary hypertension, heart disease, infections, allergies, and immune disorders. The retrospective analysis of medical records of adult patients who underwent lung transplantation aims to investigate patient characteristics, anesthesia methods, intraoperative tests, and the occurrence of PPCs. The goal is to analyze the incidence and risk factors of postoperative respiratory complications and develop a predictive model through machine learning.
Study Type
Enrollment (Actual)
Contacts and Locations
Study Locations
-
-
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Yangsan, Korea, Republic of
- Pusan National University Yangsan Hospital
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Participation Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
- Adult patients 18 years of age or older who underwent lung transplantation for end-stage lung disease
Exclusion Criteria:
- None.
Study Plan
How is the study designed?
Design Details
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Postoperative pulmonary complications
Time Frame: Up to 1 year after lung transplantation
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Postoperative pulmonary complications such as pleural effusion, pneumothorax, hemothorax, chylothorax, atelectasis, pulmonary edema, acute respiratory distress syndrome, pneumonia, bronchial stenosis, pulmonary fibrosis and emphysema, postoperative tracheostomy, acute rejection occurring within the first year after lung transplantation, chronic rejection
|
Up to 1 year after lung transplantation
|
Collaborators and Investigators
Investigators
- Principal Investigator: Hee Young Kim, MD, PhD, Department of Anesthesia and Pain Medicine, School of Medicine, Pusan National University
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Actual)
Study Completion (Actual)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
- 55-2024-004
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
product manufactured in and exported from the U.S.
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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