[Risk factors of acute kidney injury in hospitalized patients with infective endocarditis and their predictive values].
摘要
OBJECTIVE: To analyze the risk factors of acute kidney injury (AKI) in hospitalized patients with infective endocarditis (IE), construct prediction model, and discuss its predictive value. METHODS: The clinical data of 402 adult inpatients diagnosed with IE admitted to the Affiliated Hospital of Qingdao University from January 2010 to January 2020 were retrospectively analyzed. The patients were divided into the AKI group and the non-AKI group. The clinical data, such as gender, age, presence of diabetes, basic estimated glomerular filtration rate (eGFR), laboratory indexes at admission, involvement of valves, presence of sepsis, medication during hospitalization, surgery and outcome of the two groups were compared. Multivariate Logistic regression analysis was used to screen the risk factors of AKI in IE inpatients. A predictive model was constructed, and receiver operating characteristic (ROC) curve was used to analyze the predictive value of the model. RESULTS: ) cocci infection rate and surgery rate (22.8% vs. 40.4%, 60.9% vs. 81.8 %), with significant differences (all P < 0.05). There were no significant differences in the gender, number and location of involved valves, and laboratory indexes at admission between the two groups. Compared with the non-AKI group, the inpatient mortality rate of the AKI group was higher (30.4% vs. 8.6%, P < 0.01), and the inpatient mortality rate of patients with AKI stage 2 and stage 3 was significantly higher than that of patients with AKI stage 1 (43.5% vs. 17.4%, P < 0.01). In multivariate Logistic regression analysis, the lower basic eGFR [hazard ratio (HR) = 0.136, 95% confidence interval (95%CI) was 0.066-0.280], sepsis (HR = 6.100, 95%CI was 2.394-15.543), demand for NSAIDs (HR = 2.990, 95%CI was 1.184-7.546) and radiocontrast agent (HR = 3.153, 95%CI was 1.207-8.238) were independent risk factors for AKI in hospitalized patients with IE (all P < 0.05). A prediction model was constructed based on the above risk factors, an