Machine Learning-Based Model for Estimating Vancomycin Maintenance Dose to Target the Area under the Concentration Curve of 400-600 mg·h/L in Japanese Patients.

In therapeutic drug monitoring of vancomycin (VCM), the area under the concentration-time curve (AUC) is related to clinical efficacy and toxicity. Determining the maintenance for patient is necessary since VCM concentrations are affected by factors such as renal function. We constructed a machine learning-based model to estimate the maintenance dose to target an AUC of 400-600 mg⋅h/L in each combination of patient's factors. This retrospective observational study was conducted at two hospitals. Patients who received VCM intravenously with measured trough and another point (e.g., peak) concentrations within the November 2011 to March 2019 period were enrolled. We extracted the factors that affect VCM concentration and constructed a decision tree model using a classification and regression tree algorithm. Of the 1380 patients, 822 were included. Training data were split up to four times and included 24 subgroups. The average corrected VCM daily doses ranged 17.6-59.4 mg/kg. Estimated glomerular filtration rate, age, and body mass index were selected as predictive variables that affected the recommended daily dose. In the validation data, our model had slightly higher proportions of AUC of 400-600 mg⋅h/L than other nomograms. However, our model was based only on limited patients. Thus, further clinical studies are needed to develop a general-purpose model in the future. We successfully constructed a model that recommends VCM maintenance daily doses with AUC of 400-600 mg⋅h/L for each combination of independent variables. Our model has the potential for application as a simple decision-making tool for medical staff.

Hepatic drug metabolism in older people with body composition changes.

AIM: Dosage adjustment is essential in older individuals because they are prone to experience a decline in liver function and changes in body composition. However, quantitative tests or equations for evaluating the activity of hepatic drug metabolism have not yet been clearly established. We examined hepatic drug metabolism activities in older individuals, focusing on changes in body composition parameters. METHODS: Lansoprazole and nifedipine, substrates of the metabolic enzymes cytochrome P450 (CYP) 2C19 and 3A4, respectively, were selected to study hepatic drug metabolism. Residual samples from blood test for older patients were evaluated to determine drug metabolism. The body composition of relevant patients was determined by analyzing characteristic parameters of skeletal muscle mass index (SMI), handgrip strength (HGS) and hepatic steatosis index (HSI). The differences in hepatic drug metabolism were studied statistically among categories in terms of the cut-off value of these parameters. RESULTS: Older male patients receiving lansoprazole and nifedipine in the low SMI (<7.0 kg/m2 ) category showed an 85-90% reduction in respective CYP2C19 and CYP3A4 metabolic activities compared with the normal SMI category. For the female patients, CYP2C19 and CYP3A4 metabolic activities showed no significant correlation with SMI and HGS. Fatty liver disease (HSI ≥36) was found to reduce CYP2C19 metabolic activity particularly in older female patients. CONCLUSIONS: Low CYP2C19 metabolic activity was statistically correlated with low SMI in male patients and high HSI in female patients, whereas low CYP3A4 metabolic activity was statistically correlated with low HGS in male patients. Geriatr Gerontol Int 2022; 22: 449-454.

A Risk Prediction Flowchart of Vancomycin-Induced Acute Kidney Injury to Use When Starting Vancomycin Administration: A Multicenter Retrospective Study.

We previously constructed a risk prediction model of vancomycin (VCM)-associated nephrotoxicity for use when performing initial therapeutic drug monitoring (TDM), using decision tree analysis. However, we could not build a model to be used at the time of initial administration due to insufficient sample size. Therefore, we performed a multicenter study at four hospitals in Japan. We investigated patients who received VCM intravenously at a standard dose from the first day until the initial TDM from November 2011 to March 2019. Acute kidney injury (AKI) was defined according to the criteria established by the "Kidney disease: Improving global outcomes" group. We extracted potential risk factors that could be evaluated on the day of initial administration and constructed a flowchart using a chi-squared automatic interaction detection algorithm. Among 843 patients, 115 (13.6%) developed AKI. The flowchart comprised three splitting variables (concomitant drugs (vasopressor drugs and tazobactam/piperacillin) and body mass index ≥ 30) and four subgroups. The incidence rates of AKI ranged from 9.34 to 36.8%, and they were classified as low-, intermediate-, and high-risk groups. The accuracy of flowchart was judged appropriate (86.4%). We successfully constructed a simple flowchart predicting VCM-induced AKI to be used when starting VCM administration.

Improvement of renal function estimation equations for elderly Japanese people.

BACKGROUND AND AIM: The Cockcroft-Gault (C-G) equation for estimation of creatinine clearance (CCr) is still used in a clinical setting for drug dosage adjustment. Because differences between measured and estimated CCr values have been reported, particularly for Japanese elderly people, the aim of this study was to improve the accuracy of CCr estimation equations, such as C-G and Orita-Horio, by fitting to newly obtained data. Also, glomerular filtration rate (GFR) estimation equations, such as the Modification of Diet in Renal Disease (MDRD), the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI), and the eGFR equation for Japanese people, were studied to compare with measured CCr. METHOD: Data from 313 subjects over the age of 40 years with laboratory data available were used for analysis in this study. Special attention was paid to elderly people, and approximately 70% of the subjects were over the age of 65 years. RESULTS: The accuracy of estimation by the two conventional (C-G, Orita-Horio) CCr estimation equations was greatly improved by introducing adjusted body weight for which the degree of obesity is over 30% instead of measured body weight. By fitting the coefficients of the estimation equations to the present population, the mean error was reduced by almost half, particularly for people over the age of 75. Although all the values calculated by the GFR estimation equations were underestimated compared with measured CCr due to secretion, a coefficient of determination of above 0.65 was obtained for all GFR estimation equations. CONCLUSIONS: Improvement of the fitted CCr estimation equations suggests that reconstruction of renal function estimation equations is required, especially for old people. Further work is required to find optimal renal function (CCr and/or GFR) estimation equations for drug dosage adjustment.