title: Computation of drug concentrations in endocardial vegetations in patients during antibiotic therapy.
abstract: The treatment of endocarditis often requires prolonged antibiotic therapy. Individualized drug dosage regimens have made such therapy possible even in patients with impaired renal function. However, the problem of efficacy remains. Especially for aminoglycosides, it would be a useful guide to have at least an approximate idea of the concentration of an antibiotic within an endocardial vegetation. This study was designed to develop software to model the drug concentrations at different layers within spherical vegetations to provide a guide during clinical therapy of patients with endocarditis. A general model describing the diffusion of antibiotics in spheres has now been developed and interfaced with the USC*PACK PC Clinical Programs in order to compute and plot concentrations, within the vegetation, based on the regimen given to the patient and the diffusitivity of the antibiotic into the vegetation. Some preliminary results of this research, which are still in progress, are presented. Diffusion into simulated spherical vegetations has been computed for different treatment regimens for endocarditis: amikacin or netilmicin and vancomycin were given to three elderly patients (3 women, 74, 75 and 92 years old, with initial estimated creatinine clearances of 51, 36, and 31 ml/min/1.73 m2, respectively). Although Amikacin has a low diffusivity, the concentrations, even in the center of the vegetation, appear to be effective. The effects of various regimens, including a 'once-a-day' aminoglycoside regimen, are presented.
authors.affiliation: ADCAPT, Hopital A. Charial, Hospices Civils de Lyon, Francheville, France.
authors.forename: P
authors.initials: P
authors.lastname: Maire
authors.forename: X
authors.initials: X
authors.lastname: Barbaut
authors.forename: J M
authors.initials: JM
authors.lastname: Vergnaud
authors.forename: M
authors.initials: M
authors.lastname: el Brouzi
authors.forename: M A
authors.initials: MA
authors.lastname: Confesson
authors.forename: C
authors.initials: C
authors.lastname: Pivot
authors.forename: M
authors.initials: M
authors.lastname: Chuzeville
authors.forename: N
authors.initials: N
authors.lastname: Ivanoff
authors.forename: J L
authors.initials: JL
authors.lastname: Brazier
authors.forename: R W
authors.initials: RW
authors.lastname: Jelliffe
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000583:Amikacin / Q000008:administration & dosage / Q000493:pharmacokinetics / Q000627:therapeutic use; D000900:Anti-Bacterial Agents / Q000008:administration & dosage / Q000493:pharmacokinetics* / Q000627:therapeutic use; D004058:Diffusion; D004334:Drug Administration Schedule; D016903:Drug Monitoring; D004360:Drug Therapy, Computer-Assisted; D004697:Endocarditis, Bacterial / Q000188:drug therapy / Q000378:metabolism* / Q000473:pathology; D005260:Female; D006801:Humans; D008954:Models, Biological; D008956:Models, Chemical; D009428:Netilmicin / Q000008:administration & dosage / Q000493:pharmacokinetics / Q000627:therapeutic use; D012984:Software; D014640:Vancomycin / Q000008:administration & dosage / Q000493:pharmacokinetics / Q000627:therapeutic use
chemical_list: D000900:Anti-Bacterial Agents; D009428:Netilmicin; D014640:Vancomycin; D000583:Amikacin