Predicting complications after lung transplantation using machine learning
Prediction Model for Postoperative Pulmonary Complications in Patients Undergoing Lung Transplantation Using Machine Learning: a Retrospective Cohort Study
This study is trying to see if using machine learning on medical records can help predict complications after lung transplants to improve patient care.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 214 (estimated) |
| Ages | 18 Years and up |
| Sex | All |
| Sponsor | Pusan National University Yangsan Hospital Academic / other |
| Locations | 1 site (Yangsan) |
| Trial ID | NCT06218758 on ClinicalTrials.gov |
What this trial studies
This observational study aims to analyze medical records of adult patients who have undergone lung transplantation to identify risk factors associated with postoperative pulmonary complications (PPCs). By examining patient characteristics, anesthesia methods, and intraoperative tests, the study seeks to develop a predictive model using machine learning techniques. The focus is on understanding how various factors, such as age, smoking history, and pre-existing lung diseases, contribute to the incidence of PPCs. The ultimate goal is to enhance patient outcomes by predicting and potentially mitigating these complications.
Who should consider this trial
Good fit: Ideal candidates for this study are adult patients aged 18 years or older who have undergone lung transplantation for end-stage lung disease.
Not a fit: Patients who have not undergone lung transplantation or those under 18 years of age may not benefit from this study.
Why it matters
Potential benefit: If successful, this study could lead to improved prediction and management of postoperative complications in lung transplant patients, enhancing their recovery and overall outcomes.
How similar studies have performed: Other studies utilizing machine learning for predicting postoperative complications have shown promise, indicating that this approach may be effective.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * Adult patients 18 years of age or older who underwent lung transplantation for end-stage lung disease Exclusion Criteria: * None.
Where this trial is running
Yangsan
- Pusan National University Yangsan Hospital — Yangsan, Korea, Republic of (Recruiting)
Study contacts
- Principal investigator: Hee Young Kim, MD, PhD — Department of Anesthesia and Pain Medicine, School of Medicine, Pusan National University
- Study coordinator: Hee Young Kim, MD, PhD
- Email: anekhy@gmail.com
- Phone: 82-10-7641-1774
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.