Retrospective evaluation of the effect of valproate therapy on transaminase elevations in patients with hepatitis C.

STUDY OBJECTIVE: To evaluate whether a relationship exists between valproate treatment and transaminase elevations in patients who are positive for hepatitis C virus (HCV). DESIGN: Retrospective medical record review. SETTING: Veterans affairs medical center. PATIENTS: A total of 214 HCV-positive patients; 28 were treated with valproate (study group), 186 were not (control group). INTERVENTION: Demographic characteristics; valproate treatment histories; plasma concentrations of alanine aminotransferase (ALT) and aspartate aminotransferase (AST), albumin, and bilirubin; and exposure to other potentially hepatotoxic drugs, including probable alcohol abuse, were evaluated. MEASUREMENTS AND MAIN RESULTS: Hepatotoxicity was staged by comparing maximum ALT and AST values against upper limits of normal or patients' mean elevated baseline ALT and AST values. Data were analyzed using a logistic regression model. Control patients and those with longer durations of HCV were more likely (p<0.0171 and p<0.0142, respectively) to exhibit higher stages of hepatotoxicity. More valproate-treated patients were exposed to other potential hepatotoxins at the time of peak transaminase elevations (50% vs 39%, p<0.005), whereas more control patients received two or more potential hepatotoxins (13% vs 4%, p<0.00005). CONCLUSION: Valproate treatment, either alone or in the presence of other potential hepatotoxins, does not appear to be related to increased transaminase elevations in patients with HCV

In vitro characterization of fluoroquinolone concentration/MIC antimicrobial activity and resistance while simulating clinical pharmacokinetics of levofloxacin, ofloxacin, or ciprofloxacin against Streptococcus pneumoniae.

The relationship between antibacterial effect, resistance, and concentration/MIC parameters with S. pneumoniae was studied. Thirty duplicate bacterial concentration-time-kill curve (TKC) experiments were performed with an in vitro model. TKC with levofloxacin (LVX), Ofloxacin (OFX), and ciprofloxacin (CIP) were studied against six S. pneumoniae isolates. Experiments simulated variable peak serum concentrations, but clinically relevant half-lives and dosing intervals. TKC were performed in Mueller-Hinton Broth supplemented with horse blood (SMHB) at 10(7) CFU/ml. Susceptibility was assessed on colonies recovered post TKC. Multiple regression tested association of pharmacodynamic variables with antimicrobial effect, and logistic regression with resistance post TKC. Only drug (r(2) = 0.27; p < 0.0001) and AUC/MIC(24) (r(2) = 0.15; p < 0.001) were significant variables predictive of antibacterial effect. LVX AUC/MIC(24) of

Increased therapeutic failure for cephalexin versus comparator antibiotics in the treatment of uncomplicated outpatient cellulitis.

We reviewed records of outpatients to determine the therapeutic failure rate of cephalexin in treating uncomplicated cellulitis. Therapeutic failure was defined as an increase in antibiotic dosage, prescription renewal, or addition or substitution of another antibiotic. Demographics, physical characteristics, risk factors, intervention, and outcome data were collected. Twenty-seven percent of patients failed therapy with an oral antibiotic. The failure rate for cephalexin was 40% versus 20% for comparator antibiotics (p=0.02, odds ratio [OR] 2.62, 95% confidence interval [CI] 1.18-5.75). We identified no statistically significant variables related to cephalexin failure. Concomitant acid suppressive therapy was administered with cephalexin in 42% of failures and 20% of nonfailures (p=0.11, OR 2.78, 95% CI 0.77-9.87). These data suggest that cephalexin's efficacy was less than that of other antimicrobials in treating cellulitis, possibly related to concurrent acid suppression.

Mycobacterium fortuitum meningitis associated with an epidural catheter: case report and a review of the literature.

Mycobacterium fortuitum is a rapidly growing organism that has rarely been associated with meningitis. A patient developed M. fortuitum meningitis as the result of a permanent indwelling, contaminated, epidural catheter. Diagnosis and treatment of the disease are difficult in that clinical features may be indolent, and many antimicrobials with activity against M. fortuitum have minimal cerebrospinal fluid penetration. This patient was cured with an antibiotic regimen that consisted of doxycycline, ciprofloxacin, imipenem, and clarithromycin, and removal of the epidural catheter.

In vitro antimicrobial effects of various combinations of penicillin and clindamycin against four strains of Streptococcus pyogenes.

Previous studies using mouse models of Streptococcus pyogenes necrotizing fasciitis demonstrated that clindamycin had greater efficacy than penicillin. Frequently both agents are used concurrently in the treatment of severe S. pyogenes infections. This study investigated interactions between penicillin and clindamycin. E-test and broth microdilution assays suggested additivity or indifference, while timed-killing assays demonstrated concentration-dependent variable effects. Timed-kill studies utilizing clinical concentrations suggest that there is no antagonism with the combination of drugs but that the combination does not have a bactericidal advantage over either penicillin or clindamycin alone.

Characterization of synergy between ofloxacin, ceftazidime, and tobramycin against Pseudomonas aeruginosa.

The purposes of this study were to investigate the potential for synergy between ceftazidime, tobramycin, and ofloxacin against two clinical isolates (PSA 9258, and PSA 9263) of Pseudomonas aeruginosa utilizing time-concentration-kill curves. A pharmacodynamic model was used to simulate one-compartment pharmacokinetics for single-, double-, or triple-drug combinations utilizing two different elimination half-lives (T1/2). Each duplicate experiment was conducted for 24 h in cation-supplemented Mueller-Hinton broth. Synergy, indifference, and antagonism were defined as reductions of > or = 2.0, > or = 0 to < or = 2, or < or = 0 in mean log10 CFU/ml (CFU = colony-forming units) in bacterial counts at any time point during the 24-hour experiment, respectively. Time-concentration-kill curve studies simulating a peak concentration (CP) = 6 micrograms/ml and T1/2 = 5.5 h for ofloxacin combined with ceftazidime (CP = 80 micrograms/ml; T1/2 = 2 h) resulted in 2.18 and 1.81 log CFU/ml mean decreases in bacterial counts for PSA 9258 and 9263, respectively. Simulated ofloxacin pharmacokinetic parameters (CP = 6 micrograms/ml); T1/2 = 5.5 h) combined with tobramycin (CP = 8 micrograms/ml; T1/2 = 2 h) produced 2.26 and 0.6 log CFU/ml mean reductions in bacterial counts for PSA 9258 and 9263, respectively. Time-concentration-kill curve results were inconsistent with checkerboard synergy experiments which indicated antagonism for ofloxacin/tobramycin combinations (fractional inhibitory concentrations = 2.0/2.5) and indifference for ofloxacin/ceftazidime combinations (fractional inhibitory concentrations = 1.0/1.0). In secondary experiments, tobramycin (T1/2 = 2 h) and ceftazidime (T1/2 = 2 h) at concentrations of one fourth and equal to the minimum inhibitory concentration were combined with ofloxacin (CP = 6 micrograms/ml; T1/2 = 5.5 h). When ofloxacin was combined with tobramycin equivalent to the minimum inhibitory concentration, mean reductions in bacterial counts were 3.74 and 5.59 CFU/ml. These results suggest that an enhanced antipseudomonal activity may result by the combination of clinically achievable concentrations of ofloxacin with minimum inhibitory concentration equivalent concentrations of tobramycin.

A pharmacodynamic evaluation of ciprofloxacin and ofloxacin against two strains of Pseudomonas aeruginosa.

The greater potency of ciprofloxacin in vitro to that of ofloxacin against Pseudomonas aeruginosa may be potentially offset by the more favorable pharmacokinetic profile of the latter drug. In order to test this hypothesis, we generated time concentration kill curves for P. aeruginosa ATCC 27853 and a clinical isolate P. aeruginosa PSA 9258 using an in-vitro model to simulate the pharmacokinetic characteristics found in vivo for ciprofloxacin at a peak concentration (CPmax) of 5 mg/L and an elimination T1/2 of 4.5 h, and ofloxacin at a CPmax of 5 mg/L and a T1/2 of both 4.5 h and 6 h, and at a CPmax of 8.0 mg/L and a T1/2 of 6 h. A 3 log10 kill (T3 kill) of P. aeruginosa ATCC 27853 was achieved in 0.15 h by ciprofloxacin and of P. aeruginosa PSA 9258 in 0.09 h. Ofloxacin at a CPmax of 8 mg/L and T1/2 of 6 h achieved a T3 kill of P. aeruginosa ATCC 27853 in 0.74 h and of P. aeruginosa PSA 9258 in 0.16 h. The area under the kill curve (AUKC) was 1.10 x 10(4)and 1.96 x 10(3) mL-h/cfu for ciprofloxacin against P. aeruginosa ATCC 27853 and P. aeruginosa PSA 9258, respectively and that of ofloxacin at CPmax 8 mg/L and a T1/2 of 6 h was 9.78 x 10(4)and 2.20 x 10(4) mL-h/cfu respectively. Significant differences (P > or = 0.05) were evident between ciprofloxacin and all ofloxacin regimens against P. aeruginosa ATCC 27853 but not against P. aeruginosa PSA 9258. There was a poor correlation (r = 0.22) between the AUKC and area under the time concentration curve (AUC) for P. aeruginosa ATCC 27853 but a strong correlation (r = 0.96) between the AUKC and area under the inhibitory curve (AUIC). Similar results were obtained for P. aeruginosa PSA 9258 for which the correlation between AUKC and AUC was weak (r = 0.10) whereas that between the AUKC and AUIC was strong (r = 0.93). When the data for both P. aeruginosa were combined, a correlation coefficient of r = 0.04 for AUC and r = 0.80 for AUIC was found. These limited data suggest that fluoroquinolones can be compared using the AUIC for specific bacterial isolates. In addition, the larger AUC, higher CP, and longer T1/2 of ofloxacin in vivo did not fully compensate for the intrinsic differences in the antibiotic susceptibility against P. aeruginosa.

Twenty-four-hour area under the concentration-time curve/MIC ratio as a generic predictor of fluoroquinolone antimicrobial effect by using three strains of Pseudomonas aeruginosa and an in vitro pharmacodynamic model.

Several investigators have suggested that the 24-h area under the concentration-time curve (AUC)/MIC ratio (AUC/MIC24 or AUIC24) can be used to make comparisons of antimicrobial activity between fluoroquinolone antibiotics. Limited data exist regarding the generic predictive ability of AUC/MIC24 for the antimicrobial effects of fluoroquinolones. The purposes of the present investigation were to determine if the AUC/MIC24 can be used as a generic outcome predictor of fluoroquinolone antibacterial activity and to determine if a similar AUC/MIC24 breakpoint can be established for different fluoroquinolones. Using an in vitro pharmacodynamic model, 29 duplicate concentration time-kill curve experiments simulated AUC/MIC24s ranging from 52 to 508 SIT-1.h (inverse serum inhibitory titer integrated over time) with ciprofloxacin or ofloxacin against three strains of Pseudomonas aeruginosa. Each 24-h experiment was performed in cation-supplemented Mueller-Hinton broth with a starting inoculum of 10(6) CFU/ml. At timed intervals cation-supplemented Mueller-Hinton broth samples were collected for CFU and fluoroquinolone concentration determinations. Transformation of bacterial counts into the cumulative bacterial effect parameter of the 24-h area under the effect curve (AUEC24) was performed for each concentration time-kill curve. Multivariate regression analysis was used to compare pharmacodynamic predictors (AUC/MIC24, 24-h AUC, peak concentration [Cmax] to MIC ratios [Cmax:MIC], etc.) with ln AUEC24. To identify threshold breakpoint AUC/MIC24s, AUEC24s were stratified by the magnitude of AUC/MIC24 into subgroups, which were analyzed for differences in antibacterial effect. The Kruskal-Wallis test and subsequent Tukey's multiple comparison test were used to determine which AUC/MIC subgroups were significantly different. Multiple regression analysis revealed that only AUC/MIC24 (r2 = 0.65) and MIC (r2 = 0.03) were significantly correlated with antibacterial effect. At similar AUC/MIC24s, yet different MICs, Cmaxs, or elimination half-lives, the AUEC24s were similar for both fluoroquinolones. The relationship between AUC/MIC24 and ln AUEC24 was best described by a sigmoidal maximal antimicrobial effect (Emax) model (r2 = 0.72; Emax = 9.1; AUC/MIC50 = 119 SIT-1.h; S = 2.01 [S is an exponent that reflects the degree of sigmoidicity]). Ciprofloxacin-bacteria AUC/MIC24 values of < 100 SIT-1.h were significantly different (P < 0.05) from the AUC/MIC24 values of > 100 SIT-1.h. An ofloxacin AUC/MIC24 of > 100 SIT-1.h and an AUC/MIC24 of < 100 SIT-1.h exhibited a trend toward a significant difference (P > 0.05 but < 0.1). The inverse relationship between drug exposure and MIC increase postexposure was described by a sigmoidal fixed Emax model (AUC/MIC24, r2 = 0.40; AUC/MIC50 = 95 SIT-1.h; S = 1.97; Cmax:MIC, r2 = 0.41; Cmax:MIC50 = 7.3; S = 2.01). These data suggest that AUC/MIC24 may be the most descriptive measurement of fluoroquinolone antimicrobial activity against P. aeruginosa, that ofloxacin and ciprofloxacin have similar AUC/MIC24 threshold breakpoints at approximately 100 SIT-1.h, that the concentration-dependent selection of resistant organisms may parallel the threshold breakpoint of the antimicrobial effect, and that AUC/MIC24 generically describes the antibacterial effects of different fluoroquinolones.

Comparison of gentamicin pharmacokinetic parameters determined by fluorescence polarization immunoassay and latex agglutination methods.

Fluorescence polarization immunoassay (FPIA) (TDx, Abbott Laboratories Diagnostics, Irvin, TX, U.S.A.) is commonly utilized for quantitative determination of gentamicin serum concentrations. Recently, automated homogeneous latex agglutination (LA) (Technicon Immuno-1, Miles Diagnostics Division, Tarrytown, NY, U.S.A.) for the quantitative determination of gentamicin serum concentrations has been approved for commercial use. The purpose of this study was to determine whether gentamicin serum concentration-time data from the same patients assayed by FPIA and LA would produce the same estimates for half-life, elimination rate constant, distribution volume, drug clearance, dosage interval, and dose. A total of 70 pre- and postinfusion serum samples were obtained from 19 patients. Each sample was divided into two aliquots; one was assayed by FPIA and the other by LA. The correlation coefficient between the two assay methods was 0.99 (y = 1.03x - 0.05). The mean differences for half-life, volume of distribution, elimination rate constant, total body clearance, and gentamicin dosage were 0.13, 0.32, 0.66, -0.99, and 0.03%, respectively. No statistically significant differences were seen in calculated gentamicin pharmacokinetic parameters (p < 0.05). Pharmacokinetic parameters and dosage recommendations derived from FPIA and the LA assay using pre- and postinfusion serum concentration-time data appear interchangeable and do not result in differences between gentamicin dosing regimens.