Clinical Trials Directory

Trials / Completed

CompletedNCT05533619

Risk Factors and Machine Learning Model for Proton Pump Inhibitor Related Acute Kidney Injury

Analysis of Risk Factors of Proton Pump Inhibitor Related Acute Kidney Injury in Hospitalized Patients and Developments of Machine Learning Model

Status
Completed
Phase
Study type
Observational
Enrollment
30,000 (actual)
Sponsor
Qianfoshan Hospital · Academic / Other
Sex
All
Age
18 Years – 100 Years
Healthy volunteers
Not accepted

Summary

Recent evidence concerns acute kidney injury (AKI) following proton pump inhibitor (PPI) application. Few actual studies have compared the incidence, risk factors, and predictive models of AKI associated with PPI. The present study was a single-center retrospective study. The researchers retrospectively analyzed data from patients who received PPI medications between January 2018 and December 2020. PPI drugs included omeprazole, esomeprazole, rabeprazole, and pantoprazole. The primary outcome of the study was AKI, as defined by kidney disease: improving global outcomes (KDIGO). Secondary outcomes included length of hospital stay, hospital costs, and continuous renal replacement therapy. Independent risk factors associated with AKI were identified by univariate analysis and multifactorial logistic regression analysis (P \< 0.05). Logistic regression models were constructed based on the variables obtained from the analysis. Internal validation of the model was performed by the ten-fold cross-validation method. Model discriminatory power was assessed by the area under the curve (AUC) of the receiver operating characteristic curve (ROC). The study aims to develop a PPI-related AKI prediction model based on an electronic medical record system that can be used to predict AKI in hospitalized patients and contribute to the early prevention, diagnosis and treatment of AKI, ultimately reducing morbidity and improving prognosis.

Conditions

Interventions

TypeNameDescription
DRUGProton pump inhibitorInpatients using proton pump inhibitor

Timeline

Start date
2022-07-01
Primary completion
2023-10-31
Completion
2023-10-31
First posted
2022-09-09
Last updated
2023-11-18

Locations

1 site across 1 country: China

Source: ClinicalTrials.gov record NCT05533619. Inclusion in this directory is not an endorsement.