Deep Learning Model and Risk Factors for Tacrolimus-related Acute Kidney Injury

Qianfoshan Hospital

Status: Active, not recruiting

Conditions: AKI

Study type: Observational

Funder types: Other

Identifiers

NCT06596798

LCYX-LX-20240102

Details and patient eligibility

About

In this study, the investigators aim to develop a risk prediction model for acute kidney injury (AKI) in hospitalized patients using the calcineurin inhibitor tacrolimus. This will be achieved by mining electronic medical record data and employing explainable deep learning methods. The model will provide clinical decision support for timely intervention and treatment. Compared to traditional machine learning models, deep neural networks can extract more nuanced features from complex medical data and perform more precise pattern recognition, thereby enhancing prediction accuracy and reliability. By constructing a predictive tool based on explainable deep learning models, the investigators will better assess the association between the use of calcineurin inhibitors and AKI, explore targeted prevention strategies, and offer more precise predictions and intervention guidance to clinicians. Additionally, this research has significant socio-economic benefits and application potential. By reducing the incidence of AKI, the investigators can lower patient hospitalization duration and re-treatment costs, conserve medical resources, and improve patient quality of life. Preventive healthcare not only alleviates the physical and psychological burden on patients but also reduces the strain on the healthcare system, enhances healthcare efficiency, and promotes the rational allocation of medical resources.

Enrollment: 1,200 estimated patients

Sex: All

Ages: 18+ years old

Volunteers: Accepts Healthy Volunteers

Inclusion criteria

• Use of tacrolimus during hospitalization, with standardized therapeutic drug monitoring
• Age of 18 years or older at the time of admission
• Length of hospital stay ≥ hours
• At least two serum creatinine level tests conducted during the hospital stay

Exclusion criteria

• Stage 5 chronic kidney disease prior to admission
• Incomplete clinical data
• Serum creatinine levels consistently below 40 mmol/L during hospitalization