Clinical trial NCT06218745: Prediction Model for Postoperative AKI in Patients Undergoing Lung Transplantation Using Machine Learning
Official title: Prediction Model for Postoperative Acute Kidney Injury in Patients Undergoing Lung Transplantation Using Machine Learning: a Retrospective Cohort Study
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: Lung Transplantation
Lead sponsor: Pusan National University Yangsan Hospital
Sponsor class: OTHER
First posted: 2024-01-23
Enrollment: 214
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: RETROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Adult patients 18 years of age or older who underwent lung transplantation for end-stage lung disease

Brief summary: Since 1963, lung transplantation progress has surged due to immunosuppressive agent advancements. In 2004, 1,815 global lung transplantations were reported. Elderly recipients face impaired lung function and health instability, leading to potential respiratory complications post-surgery.

Postoperative acute renal injury (AKI) can cause temporary or chronic dysfunction, increasing hospitalization, complications, and additional treatment needs. Various factors contribute to postoperative renal dysfunction after lung transplantation, including sustained hypoperfusion, bleeding, heart failure, acute myocardial infarction, pulmonary embolism, sepsis, and medications. Retrospective analysis of adult lung transplant patients' records aims to explore characteristics, anesthesia methods, intraoperative tests, and postoperative acute renal dysfunction, analyzing incidence and risk factors to develop a machine learning predictive model.

Detailed description: Since the first report of lung transplantation in humans in 1963, there has been rapid progress in both the quantity and quality of lung transplantation, driven by the significant advancements in immunosuppressive agents since the mid-1990s. In 2004, a total of 1,815 lung transplantations were reported worldwide. Patients undergoing lung transplantation are often elderly and face not only impaired lung function but also overall health instability, leading to the potential occurrence of respiratory complications post-surgery, even with successful lung transplantation outcomes.

Postoperative acute renal injury (AKI) can result in temporary or even chronic renal dysfunction. AKI following surgery can lead to an increase in hospitalization duration, complications, and the need for additional treatment. Various factors are associated with postoperative renal dysfunction after lung transplantation, including sustained hypoperfusion, hypoperfusion related to intraoperative and postoperative bleeding, heart failure, acute myocardial infarction, pulmonary embolism, sepsis, and more. Medications related to renal dysfunction include those associated with thrombosis or embolism, such as aminoglycosides, amphotericin B, non-steroidal anti-inflammatory drugs (NSAIDs), proton-pump inhibitors, contrast agents, and others. Additionally, graft-versus-host disease is known to be related to renal dysfunction.

The retrospective analysis of medical records from adult patients who underwent lung transplantation aims to investigate patient characteristics, anesthesia methods, intraoperative tests, and the occurrence of postoperative acute renal dysfunction. The goal is to analyze the incidence and risk factors of postoperative renal dysfunction and develop a predictive model through machine learning.

Eligibility criteria: Inclusion Criteria:

* Adult patients 18 years of age or older who underwent lung transplantation for end-stage lung disease

Exclusion Criteria:

* None.

Primary outcomes:
measure: Postoperative acute kidney injury (AKI)
timeFrame: Within 48 hours after lung transplantation
Secondary outcomes:
Other outcomes:
Locations:
city: Yangsan
country: Korea, Republic of
facility: Pusan National University Yangsan Hospital
Study officials:
affiliation: Department of Anesthesia and Pain Medicine, School of Medicine, Pusan National University
name: Hee Young Kim
role: PRINCIPAL_INVESTIGATOR
References: