Analysis of Risk Factors of Beta-Lactam Drugs Related Acute Kidney Injury in Hospitalized Patients and Developments of Machine Learning Model
Acute kidney injury (AKI), also known as acute kidney failure (ARF), is a common and complex kidney disease in clinic and an important factor related to poor prognosis of patients in clinic. In the present study, a single-center retrospective study was conducted in our center. The clinical data of hospitalized patients received β-Lactam drugs from January 2018 to December 2020 was retrospectively analyzed. The multiple logistic regression analysis suggested that complicated with hypertension, anemia, pneumonia, shock, sepsis, heart failure, combined use of proton pump inhibitors (PPI), angiotensin-converting enzyme inhibitor (ACEI), angiotensin Ⅱ receptor antagonist (ARB) were independent risk factors for AKI related to β-Lactam drugs. In clinical practice, patients with acute kidney injury risk factors should be closely monitored for changes in their blood creatinine and urine output to avoid acute kidney injury. For patients who have suffered from acute kidney injury, the cause should be removed in time and corresponding symptomatic treatment should be given.
Risk Factors and Machine Learning Model for Aminoglycines Related Acute Kidney Injury
Risk Factors and Machine Learning Model for Diuretics Related Acute Kidney Injury
Risk Factors and Machine Learning Model for Proton Pump Inhibitor Related Acute Kidney Injury
Machine Learning Models for Prediction of Acute Kidney Injury After Noncardiac Surgery
Machine Learning Predict Acute Kidney Injury in Patients Following Cardiac Surgery