Predicting lung complications in liver transplant patients using machine learning
Establishment and Evaluation of Moderate-severe Prediction Model of Pulmonary Complications in Liver Transplantation Patients Based on Machine Learning Algorithm
West China Hospital · NCT06534840
This study is testing a new way to use machine learning to predict which liver transplant patients might have serious lung problems after their surgery.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 400 (estimated) |
| Ages | 18 Years to 80 Years |
| Sex | All |
| Sponsor | West China Hospital (other) |
| Locations | 1 site (Chengdu, Sichuan) |
| Trial ID | NCT06534840 on ClinicalTrials.gov |
What this trial studies
This study aims to develop a machine learning model that predicts the risk of moderate to severe pulmonary complications in patients undergoing liver transplantation within 14 days post-surgery. By utilizing real-world preoperative and intraoperative electronic health records, the study seeks to improve upon traditional prediction models that often lack accuracy due to their reliance on limited variables and linear analysis. The goal is to create a more effective tool for identifying at-risk patients, potentially leading to better postoperative care and outcomes. This observational study will analyze a rich dataset to enhance the predictive capabilities of the model.
Who should consider this trial
Good fit: Ideal candidates for this study are adult patients aged 18 years and older who are scheduled to undergo liver transplantation.
Not a fit: Patients who are undergoing re-transplantation, multi-organ transplants, or those with severe encephalopathy may not benefit from this study.
Why it matters
Potential benefit: If successful, this study could significantly reduce the incidence of severe pulmonary complications in liver transplant patients, leading to improved recovery times and reduced healthcare costs.
How similar studies have performed: While machine learning has been successfully applied in various clinical prediction models, this specific application in predicting pulmonary complications in liver transplantation is relatively novel and has not been extensively tested.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * Adult patients (age ≥ 18 years) * Undergoing liver transplantation Exclusion Criteria: * Re-transplantation * Multi-organ transplants * Intra-operative deaths * severe encephalopathy (West Haven criteria III or IV) * Incomplete clinical data
Where this trial is running
Chengdu, Sichuan
- West China Hospital, Sichuan University — Chengdu, Sichuan, China (RECRUITING)
Study contacts
- Study coordinator: Chun ling Jiang, PhD
- Email: jiang_chunling@yahoo.com
- Phone: +8602885423593
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.
Conditions: Liver Transplantation