Search

Objectives: To assess whether using the Tree flowchart obviates unnecessary magnetic resonance imaging (MRI)-guided biopsies in breast lesions only visible on MRI.Methods: This retrospective IRB-approved study evaluated consecutive suspicious (BI-RADS 4) breast lesions only visible on MRI that were referred to our institution for MRI-guided biopsy. All lesions were evaluated according to the Tree flowchart for breast MRI by experienced readers. The Tree flowchart is a decision rule that assigns levels of suspicion to specific combinations of diagnostic criteria. Receiver operating characteristic (ROC) curve analysis was used to evaluate diagnostic accuracy. To assess reproducibility by kappa statistics, a second reader rated a subset of 82 patients.Results: There were 454 patients with 469 histopathologically verified lesions included (98 malignant, 371 benign lesions). The area under the curve (AUC) of the Tree flowchart was 0.873 (95% CI: 0.839-0.901). The inter-reader agreement was almost perfect (kappa: 0.944; 95% CI 0.889-0.998). ROC analysis revealed exclusively benign lesions if the Tree node was ≤2, potentially avoiding unnecessary biopsies in 103 cases (27.8%).Conclusions: Using the Tree flowchart in breast lesions only visible on MRI, more than 25% of biopsies could be avoided without missing any breast cancer.Key Points: • The Tree flowchart may obviate >25% of unnecessary MRI-guided breast biopsies. • This decrease in MRI-guided biopsies does not cause any false-negative cases. • The Tree flowchart predicts 30.6% of malignancies with >98% specificity. • The Tree's high specificity aids in decision-making after benign biopsy results. [ABSTRACT FROM AUTHOR]

Background: Amikacin is an aminoglycoside commonly used in intensive care units for the treatment of patients with life-threatening Gram-negative infections. Although aminoglycosides are extensively used, the accurate determination of their optimal dosage is complicated by marked intra- and interindividual variability in intensive care unit patients. Amikacin pharmacokinetics have been described in numerous studies over the past 25 years.Objective: This review presents a synthesis of the population pharmacokinetic models for amikacin described in critically ill patients. The objective was to determine whether there was a consensus on a structural model and which covariates had been identified.Methods: A literature search was conducted from the PubMed database, from its inception up until December 2015, using the following terms: 'amikacin', 'pharmacokinetic(s)', 'population', 'model(ling)' and 'nonlinear mixed effect'. Articles were excluded if they were not pertinent. The reference lists of all selected articles were also evaluated.Results: Ten articles were included in this review: pharmacokinetics of amikacin were described by a one-compartment or a two-compartment model. Various covariates were tested, but only two (creatinine clearance and total body weight) were included in almost all of the described models. After inclusion of these covariates, the interindividual variability (range) in clearance and the volume of distribution were 44.4 % (28.2-69.4 %) and 31.3 % (8.1-44.7 %), respectively. The residual variability (range) was around 21.0 % (9.0-31.0 %), using a proportional model, and for a combined model (proportional/additive), the median (range) values were 0.615 mg/L (0.2-1.03 mg/L) and 29.2 % (26.8-31.6 %).Conclusion: This review highlights the different population pharmacokinetic models for amikacin developed in critically ill patients over the past decades and proposes relevant information for clinicians and researchers. To optimize amikacin dosage, this review points out the relevant covariates according to the target population. In a population of critically ill patients, dose optimization mainly depends on creatinine clearance and total body weight. New pharmacokinetic population studies could be considered, with new covariates of interest to be tested in model building and to further explain variability. Another future perspective could be external evaluation of previously published models. [ABSTRACT FROM AUTHOR]

The study was undertaken to look for a correlation between the measured elimination rate constants (k) of aminoglycosides and creatinine during haemodialysis. The pharmacokinetics of aminoglycosides were studied during 44 courses of haemodialysis in 21 patients. The measured k of gentamicin and tobramycin from the start until 30 min after the end of haemodialysis (mean 0.18 h; t=3 h 51 min) was significantly correlated with the measured k of creatinine (mean 0.13 h; t=5 h, 20 min), and also with the gentamicin and tobramycin k during haemodialysis (mean 0.20 h, t=3 h, 28 min), as predicted by a computer program. Thus, serum concentrations of aminoglycosides 30 min after haemodialysis can be estimated by simple regression equations. However, because the measured and predicted values may diverge considerably in the individual patient, monitoring of aminoglycoside concentrations in serum after haemodialysis remains necessary. [ABSTRACT FROM AUTHOR]

Objective: The pharmacokinetics of amikacin were studied in patients undergoing slow hemodialysis (HD).Design: Slow HD was performed at the dialysate flow rate of 30 ml/min. After a single intravenous dose of amikacin 5 mg/kg, pharmacokinetic variables were calculated by fitting individual concentration-time curves to a two-compartment open model.Patients: 6 critically ill patients with renal failure were entered into the study.Results: The volume of distribution was 0.35 +/- 0.03 l/kg. Total body clearance was 35.1 +/- 2.3 ml/min with an elimination half-life of 10.5 h. During a 10.5 h session of slow HD, the serum amikacin concentration decreased from the peak level of 21.3 +/- 1.2 mg/l to 7.2 +/- 0.9 mg/l.Conclusion: Slow HD eliminate amikacin more efficiently than other types of slowly performed renal replacement therapy and had profound effects on the pharmacokinetics. Amikacin elimination by this approach should be taken into consideration for designing a dosage schedule during the treatment. [ABSTRACT FROM AUTHOR]