Population Pharmacokinetic Study of the Suitability of Standard Dosing Regimens of Amikacin in Critically Ill Patients with Open-Abdomen and Negative-Pressure Wound Therapy.

The aim was to assess the appropriateness of recommended regimens for empirical MIC coverage in critically ill patients with open-abdomen and negative-pressure therapy (OA/NPT). Over a 5-year period, every critically ill patient who received amikacin and who underwent therapeutic drug monitoring (TDM) while being treated by OA/NPT was retrospectively included. A population pharmacokinetic (PK) modeling was performed considering the effect of 10 covariates (age, sex, total body weight [TBW], adapted body weight [ABW], body surface area [BSA], modified sepsis-related organ failure assessment [SOFA] score, vasopressor use, creatinine clearance [CLCR], fluid balance, and amount of fluids collected by the NPT over the sampling day) in patients who underwent continuous renal replacement therapy (CRRT) or did not receive CRRT. Monte Carlo simulations were employed to determine the fractional target attainment (FTA) for the PK/pharmacodynamic [PD] targets (maximum concentration of drug [Cmax]/MIC ratio of ≥8 and a ratio of the area under the concentration-time curve from 0 to 24 h [AUC0-24]/MIC of ≥75). Seventy critically ill patients treated by OA/NPT (contributing 179 concentration values) were included. Amikacin PK concentrations were best described by a two-compartment model with linear elimination and proportional residual error, with CLCR and ABW as significant covariates for volume of distribution (V) and CLCR for CL. The reported V) in non-CRRT and CRRT patients was 35.8 and 40.2 liters, respectively. In Monte Carlo simulations, ABW-adjusted doses between 25 and 35 mg/kg were needed to reach an FTA of >85% for various renal functions. Despite an increased V and a wide interindividual variability, desirable PK/PD targets may be achieved using an ABW-based loading dose of 25 to 30 mg/kg. When less susceptible pathogens are targeted, higher dosing regimens are probably needed in patients with augmented renal clearance (ARC). Further studies are needed to assess the effect of OA/NPT on the PK parameters of antimicrobial agents.

HIV-1 resistance patterns to integrase inhibitors in antiretroviral-experienced patients with virological failure on raltegravir-containing regimens.

BACKGROUND: Our aim was to study the in vivo viral genetic pathways for resistance to raltegravir, in antiretroviral-experienced patients with virological failure (VF) on raltegravir-containing regimens. METHODS: We set up a prospective study including antiretroviral-experienced patients receiving raltegravir-based regimens. Integrase (IN) genotypic resistance analysis was performed at baseline. IN was also sequenced at follow-up points in the case of VF, i.e. plasma HIV-1 RNA>400 copies/mL at month 3 and/or >50 copies/mL at month 6. For phenotyping, the IN region was recombined with an IN-deleted HXB2-based HIV-1 backbone. A titrated amount of IN recombinant viruses was used for antiviral testing against raltegravir and elvitegravir. RESULTS: Among 51 patients, 11 (21.6%) had VF. Four different patterns of IN mutations were observed: (i) emergence of Q148H/R with secondary mutations (n=5 patients); (ii) emergence of N155H, then replaced by a pattern including Y143C/H/R (n=3); (iii) selection of S230N (n=1); and (iv) no evidence of selection of IN mutations (n=2). The median raltegravir and elvitegravir fold changes (FCs) were 244 (154-647) and 793 (339-892), respectively, for the Q148H/R pattern, while the median raltegravir and elvitegravir FCs were 21 (6-52) and 3 (2-3), respectively, with Y143C/H/R. The median plasma raltegravir Cmin was lower in patients with selection of the N155H mutation followed by Y143C/H/R compared with patients with Q148H/R and with patients without emerging mutations or without VF. CONCLUSIONS: Diverse genetic profiles can be associated with VF on raltegravir-containing regimens, including the dynamics of replacement of mutational profiles. Pharmacokinetic parameters could be involved in this genetic evolution.