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Simple Formula for Predicting Drug Removal Rates During Hemodialysis.

Motoki UrataYuki NaritaMasaki FukunagaDaisuke KadowakiSumio Hirata
Published in: Therapeutic apheresis and dialysis : official peer-reviewed journal of the International Society for Apheresis, the Japanese Society for Apheresis, the Japanese Society for Dialysis Therapy (2018)
The present study sought to derive a simple formula for predicting the drug removal rates during hemodialysis. We examined the relationship between drug removal rates during hemodialysis and the molecular weights or pharmacokinetic parameters of injectable drugs (N = 90) obtained from pharmaceutical interview forms in Japan. Stepwise multiple regression analysis with the removal rate by hemodialysis as the objective variable adjusted for molecular weight or pharmacokinetic parameters as explanatory variables, showed that the logarithm of molecular weight (B = -18.87), the protein binding rate (B = -0.40), and the fraction of the unchanged drug excreted into the urine/volume of distribution (B = 0.05) were significantly and independently associated with drug removal rate by hemodialysis (α = 90.78, adjusted R2  = 0.64, P = 2.2e-16 ). Our data demonstrated that molecular weight, protein binding rate, and volume of distribution were important factors affecting drug removal during hemodialysis, and that our simple regression equation could be used to predict the drug removal rate during hemodialysis.
Keyphrases
  • end stage renal disease
  • peritoneal dialysis
  • chronic kidney disease
  • adverse drug
  • drug induced
  • emergency department
  • machine learning
  • human milk
  • deep learning
  • big data
  • dna binding
  • low birth weight