Improved Formula for Predicting Hemodialyzability of Intravenous and Oral Drugs.

BACKGROUND: The rate of drug removal by hemodialysis needs to be considered when designing drug dosage regimens for patients on hemodialysis. We previously developed a simplified equation to predict the removal rates of intravenously administered drugs by hemodialysis. Here, we addressed shortcomings of this equation and developed a more accurate equation that can also predict the removal rates of orally administered drugs. METHODS: A total of 70 drugs with known pharmacokinetic and physical parameters and drug removal rates that were measured during hemodialysis in clinical cases were randomly assigned at a 4:1 ratio to a training data group or a test data group. A prediction equation was developed by performing stepwise multiple regression analyses using the training data (i.e., the removal rate by hemodialysis) as the objective variable and pharmacokinetic parameters as the explanatory variables. The equation was validated using the test data. RESULTS: Multiple regression analyses revealed that molecular weight (MW), protein binding rate, and fraction excreted unchanged in urine relative to the volume of distribution (Vd) were independently correlated with the drug clearance rate (adjusted coefficient of determination, 0.83; p = 2.2e-16). The following equation was obtained: drug removal rate by hemodialysis (%) = -17.32 × [log (MW)] - 0.39 × [protein binding rate (%)] + 0.06 × [fraction excreted unchanged in urine (%)/Vd (L/kg)] + 83.34. Validation of the equation using the test data showed a very high correlation between predicted and measured reduction rate (R = 0.93, p = 1.87e-6). Mean error was -3.34 (95% confidence interval: -10.03, 3.35), mean absolute error was 9.59, and root mean square error was 16.48. CONCLUSION: The modified equation derived in this study using pharmacokinetic and physical parameters as variables precisely predicted the removal rates of both intravenous and oral drugs by hemodialysis.

Investigation of methods for more accurate estimation of kidney function in people with high muscle mass
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Serum creatinine (SCr) levels depend on muscle mass and are therefore elevated in people with high muscle mass, potentially leading to underestimation of kidney function in this population. Although recent therapeutic guidelines have shown measurement of serum cystatin C (ScysC) to be useful, this method has not been validated in people with high muscle mass. We conducted this study to investigate methods for more accurately estimating kidney function in people with high muscle mass. Linear regression analysis was used to assess the correlation of endogenous creatinine clearance (24-hour CLcr) and 24-hour CLcr × 0.715 (i.e., modified glomerular filtration rate (GFR)); with estimated kidney function from SCr and ScysC in 15 healthy young adult men with high muscle mass. A significant but weak positive correlation was observed between 24-hour CLcr and estimated CLcr by the Cockcroft and Gault formula (CG CLcr; R2 = 0.371, p = 0.016). The estimated GFR calculated from ScysC (eGFRcys) was significantly higher than CLcr × 0.715, but the two were not correlated (R2 = 0.125, p = 0.197). However, when CG CLcr and eGFRcr were adjusted by muscle mass parameters, the correlation between measured and estimated values improved. Further improvement was seen when participants with a fat mass greater than 25% were excluded (R2 = 0.623, p = 0.004; R2 = 0.510, p = 0.014; n = 11 for both). The results of our study suggest that currently used formulas for estimating kidney function, including eGFRcys, may not be appropriate for people with high muscle mass, but use of muscle mass parameters may improve predictivity.
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Coefficient of Determination between Estimated and Measured Renal Function in Japanese Patients with Sarcopenia May Be Improved by Adjusting for Muscle Mass and Sex: A Prospective Study.

Creatinine (Cr) levels are strongly affected by muscle mass, and the estimated glomerular filtration rate (eGFR), a measure based on serum creatinine (SCr), is often overestimated in patients with sarcopenia. To evaluate the coefficient of determination (R2) between eGFR and the actual measured value, we performed a linear regression analysis of a modified GFR (mGFR: measured Cr clearance × 0.715) and various renal function estimates adjusted for muscle mass in 19 patients with sarcopenia. The eGFR values based on SCr (eGFRcr) were higher than those based on mGFR, although a high R2 (0.704; p < 0.001) was found between these values. There was no deviation between eGFR based on serum cystatin C (eGFRcys) and mGFR, although the R2 value 0.691 was equivalent to that of eGFRcr. In the equation used to calculate eGFRcr not adjusted for body surface area (mL/min), muscle mass parameters obtained from bioelectrical impedance analysis were used instead of actual body weight to recalculate the eGFRcr. The R2 between this eGFRcr and mGFR did not improve, although there was less deviation. However, assuming that all patients were female by using female coefficients for all patients, the R2 between eGFRcr-fcc (eGFRcr with female coefficient correction) and mGFR improved and was the highest (0.808) on substitution of appendicular skeletal muscle mass. The correlation between eGFRcr-fcc and mGFR improved over eGFRcys when muscle mass was substituted for body weight in the equation used to estimate eGFR in patients with sarcopenia and sex differences were removed.