Research on the Risk Warning Model and Prevention Strategies for Acute Kidney Injury Associated With Cyclosporine Based on Explainable Deep Neural Networks and Therapeutic Drug Monitoring

In this study, the investigators will focus on hospitalized patients using cyclosporine and develop an acute kidney injury risk prediction model through in-depth analysis of electronic medical record data, employing interpretable deep learning methods. This model aims to provide timely decision-making support for clinicians regarding prevention and treatment. Compared to traditional machine learning models, deep neural network models can extract deeper features from complex medical data and perform more precise pattern recognition, thereby improving the accuracy and reliability of predictions. By developing a prediction tool based on interpretable deep learning models, the investigators will be able to better assess the association between the use of CNI-class immunosuppressants and acute kidney injury, explore targeted prevention strategies, and offer more accurate prediction and intervention guidance for clinicians. Additionally, this study has significant socioeconomic benefits and promising prospects for application and promotion.

Study Overview

• Status: Active, not recruiting
• Conditions: AKI; Therapeutic Drug Monitoring (TDM)

• Study Type: Observational
• Enrollment (Estimated): 1200

Contacts and Locations

Study Locations

• China
  • Jinan, China, 250117
    • The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: Yes

• Sampling Method: Non-Probability Sample

Study Population

Inpatients treated with tacrolimus or cyclosporine and monitored for therapeutic drug concentrations at three medical centers from January 2020 to December 2023, including Shandong First Medical University Affiliated Hospital, Binzhou Medical University Affiliated Hospital, and Jinan First People's Hospital.

Description

Inclusion Criteria:

1. During hospitalization, tacrolimus or cyclosporine was used, and therapeutic drug monitoring was conducted according to standard procedures.
2. Aged 18 years or older at the time of admission.
3. Length of hospital stay > 48 hours.
4. At least 2 serum creatinine tests were conducted during hospitalization.

Exclusion Criteria:

1. Chronic kidney disease stage 5 was achieved before admission.
2. Incomplete clinical data.
3. Serum creatinine levels were consistently below 40 mmol/L during hospitalization.

Study Plan

How is the study designed?

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
AKI	Acute kidney injury occurred in hospitalized patients treated with cyclosporine	From January 2020 to December 2023

Collaborators and Investigators

• Sponsor: Qianfoshan Hospital
• Investigators: Principal Investigator: Xiao Li, Qianfoshan Hospital

Study record dates

Study Major Dates

• Study Start (Actual): September 1, 2024
• Primary Completion (Estimated): September 1, 2026
• Study Completion (Estimated): December 30, 2026

Study Registration Dates

• First Submitted: September 8, 2024
• First Submitted That Met QC Criteria: September 11, 2024
• First Posted (Estimated): September 19, 2024

Study Record Updates

• Last Update Posted (Estimated): September 19, 2024
• Last Update Submitted That Met QC Criteria: September 11, 2024
• Last Verified: September 1, 2024

More Information

Terms related to this study

• Keywords: ADM; deep learning; AKI
• Additional Relevant MeSH Terms: Kidney Diseases; Urologic Diseases; Renal Insufficiency; Female Urogenital Diseases; Female Urogenital Diseases and Pregnancy Complications; Urogenital Diseases; Male Urogenital Diseases; Acute Kidney Injury
• Other Study ID Numbers: LCYX-LX-20240103

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No