Background: Vancomycin (VAN), an antibiotic produced by microbial fermentation, is used to treat gram-positive infections. With extensive broad-spectrum antibiotics use, bacterial resistance to vancomycin continues to increase. In this study, we explored the factors affecting the blood concentration of vancomycin and established a prediction equation for VAN blood concentration, providing a reference for the individual application of vancomycin.
Methods: We used a single-center, retrospective, case-control study design based on real-world data from the Hospital Information System of the First Affiliated Hospital of the Teaching Hospital of Bengbu Medical School from January 1, 2017, to December 31, 2018. Inpatients whose VAN blood concentration (enzyme amplification immunoassay) was monitored were selected. Single-factor and multivariate logistic regression analyses were performed using SPSS 21.0 software to screen factors affecting VAN blood concentration compliance rate. VAN blood concentration was then determined. A receiver operator characteristic (ROC) curve of influencing factors was then used to establish a prediction model.
Results: In total, 168 patients (122 males and 46 females) were enrolled. Eighty-one had their VAN blood concentration monitored, and 87 had concentrations that did not reach the standard. Multivariate logistic model analyses showed that patient drug allergy history, alanine aminotransferase (ALT), aspartate aminotransferase (AST), patient infusion volume, and urine volume influenced VAN blood concentration compliance rate. According to logistic model analysis, a history of drug allergy (95% CI: 1.225-24.850, P<0.05), ALT (95% CI: 0.979-0.999, P<0.05), AST (95% CI: 1.003-1.027, P<0.05), patient infusion volume (95% CI: 0.996-0.998, P<0.05), patient urine volume (95% CI: 1.001-1.003, P<0.05), and combined predictors were used to construct ROC curves. For combined predictive factors, area under the ROC curve (0.829, 95% CI: 0.755-0.902, P<0.005) was greater than that of the five individual indicators and was predicted to be the preferred value.
Conclusions: In clinical practice, the patient’s daily average infusion and urine volumes can be substituted into the joint predictor calculation formula: P=1/[1+e-(0.940-0.004*Xinfusion+0.002*Xurine)]. By calculating the combined predictive factor to predict VAN blood concentration compliance rate, the dosing regimen can be adjusted.
Keywords: Real-world research; Vancomycin; Blood concentration monitoring; Influencing factor; Logistic regression analysis