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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
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT05533619
Enrollment
30000
Registered
2022-09-09
Start date
2022-07-01
Completion date
2023-10-31
Last updated
2023-11-18

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Acute Kidney Injury, Proton Pump Inhibitor

Keywords

Proton pump inhibitor, Acute kidney injury, Pharmacoepidemiology, Miss diagnosis, Risk factors, Logic regression

Brief 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.

Interventions

DRUGProton pump inhibitor

Inpatients using proton pump inhibitor

Sponsors

Qianfoshan Hospital
Lead SponsorOTHER

Study design

Observational model
OTHER
Time perspective
RETROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
18 Years to 100 Years
Healthy volunteers
No

Inclusion criteria

* All inpatients who used proton pump inhibitor during hospitalization * Hospital stay ≥ 48h * Age ≥18 years * There are two or more blood creatinine tests during hospitalization

Exclusion criteria

* Hospital stay \< 48h * Age \<18 years * Glomerular filtration rate (GFR)\< 30ml/min/1.73m2 within 48 hours after admission * AKI was diagnosed on admission * Less than two Scr test results during hospitalization * The Scr values were always lower than 40 μmol/L during hospitalization * Cases with incomplete medical history information

Design outcomes

Primary

MeasureTime frameDescription
The incidence of acute kidney injury in hospitalized patients treated with proton pump inhibitorsThrough study completion,up to half a year.To analyze the incidence of acute kidney injury in hospitalized patients after using proton pump inhibitors, and to build a prediction model. To assess the risk factors before using proton pump inhibitors is helpful to the early prevention, diagnosis and treatment of AKI.

Countries

China

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026