Seventy-four acutely ill patients were treated with intravenous ciprofloxacin at dosages ranging between 200 mg every 12 h and 400 mg every 8 h. A population pharmacokinetic-pharmacodynamic analysis relating drug exposure (and other factors) to infectious outcome was performed. Plasma samples were obtained and assayed for ciprofloxacin by high-performance liquid chromatography. Samples from patients were frequently cultured so that the day of bacterial eradication could be determined. The pharmacokinetic data were fitted by iterative two-stage analysis, assuming a linear two-compartment model. Logistic regression was used to model ciprofloxacin exposure (and other potential covariates) versus the probabilities of achieving clinical and microbiologic cures. The same variables were also modelled versus the time to bacterial eradication by proportional hazards regression. The independent variables considered were dose, site of infection, infecting organism and the MIC for it, percent time above the MIC, peak, peak/MIC ratio, trough, trough/MIC ratio, 24-h area under the concentration-time curve (AUC), AUC/MIC ratio (AUIC), presence of other active antibacterial agents, and patient characteristics. The most important predictor for all three measures of ciprofloxacin pharmacodynamics was the AUIC. A 24-h AUIC of 125 SIT-' h (inverse serum inhibitory titer integrated over time) was found to be a significant breakpoint for probabilities of both clinical and microbiologic cures. At an AUIC below 125 (19 patients), the percent probabilities of clinical and microbiologic cures were 42 and 26%, respectively. At an AUIC above 125 (45 patients), the probabilities were 80%o (P < 0.005) and 82% (P < 0.001), respectively. There were two significant breakpoints in the time-to-bacterialeradication data. At an AUIC below 125 (21 patients), the median time to eradication exceeded 32 days; at an AUIC of 125 to 250 (15 patients), time to eradication was 6.6 days; and at AUIC above 250 (28 patients), the median time to eradication was 1.9 days (groups differed; P < 0.005). These findings, when combined with pharmacokinetic data reported in the companion article, provide the rationale and tools needed for targeting the dosage of intravenous ciprofloxacin to individual patients' pharmacokinetics and their bacterial pathogens' susceptibilities. An a priori dosing algorithm (based on MIC, patient creatinine clearance and weight, and the clinician-specified AUIC target) was developed. This approach was shown, retrospectively, to be more precise than current guidelines, and it can be used to achieve more rapid bacteriologic and clinical responses to ciprofloxacin, as a consequence of targeting the AUIC.

Summary Infections in critically ill patients are associated with persistently poor clinical outcomes. These patients have severely altered and variable antibiotic pharmacokinetics and are infected by less susceptible pathogens. Antibiotic dosing that does not account for these features is likely to result in sub-optimal outcomes. In this paper, we review the patient- and pathogen-related challenges that contribute to inadequate antibiotic dosing and discuss how a process for individualised antibiotic therapy, that increases the accuracy of dosing, can be implemented to further optimise care for the critically ill patient. The process for optimised antibiotic dosing firstly requires determination of the physiological derangements in the patient that can alter antibiotic concentrations including altered fluid status, microvascular failure, serum albumin concentrations as well as altered renal and hepatic function. Secondly, knowledge of the susceptibility of the infecting pathogen should be determined through liaison with the microbiology laboratory. The patient and pathogen challenges can then be solved by combining susceptibility data with measured antibiotic concentration data (where possible) into a clinical dosing software. Such software uses pharmacokinetic-pharmacodynamic (PK/PD) models from critically ill patients to accurately predict the dosing requirements for the individual patient with the aim of optimising antibiotic exposure and maximising effectiveness.

We attempted to find a relationship between the microbiological properties of bloodstream isolates of methicillin-resistant Staphylococcus aureus (MRSA) and the efficacy of vancomycin in the treatment of bacteremia. Vancomycin susceptibility testing was performed, and bactericidal activity was determined for 30 isolates from 30 different patients with MRSA bacteremia for whom clinical and microbiological outcome data were available. The majority of these patients had been previously enrolled in multicenter prospective studies of MRSA bacteremia refractory to conventional vancomycin therapy. Logistic regression found a statistically significant relationship between treatment success with vancomycin and decreases in both vancomycin MICs (<0.5 g/ml versus 1.0 to 2.0 g/ml; P ‫؍‬ 0.02) and degree of killing (reduction in 1og 10 CFU/milliliter) by vancomycin over 72 h of incubation in vitro (P ‫؍‬ 0.03). For MRSA isolates with vancomycin MICs < 0.5 g/ml, vancomycin was 55.6% successful in the treatment of bacteremia whereas vancomycin was only 9.5% effective in cases in which vancomycin MICs for MRSA were 1 to 2 g/ml.

Vancomycin AUC24/MIC values predict time-related clinical and bacteriological outcomes for patients with lower respiratory tract infections caused by methicillin-resistant S. aureus.

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Intravenously administered ciprofloxacin was compared with imipenem for the treatment of severe pneumonia. In this prospective, randomized, double-blind, multicenter trial, which included an intent-to-treat analysis, a total of 405 patients with severe pneumonia were enrolled. The mean APACHE II score was 17.6, 79%o of the patients required mechanical ventilation, and 78% had nosocomial pneumonia. A subgroup of 205 patients (98 ciprofloxacin-treated patients and 107 imipenem-treated patients) were evaluable for the major efficacy endpoints. Patients were randomized to receive intravenous treatment with either ciprofloxacin (400 mg every 8 h) or imipenem (1,000 mg every 8 h), and doses were adjusted for renal function. The primary and secondary efficacy endpoints were bacteriological and clinical responses at 3 to 7 days after completion of therapy. Ciprofloxacin-treated patients had a higher bacteriological eradication rate than did imipenem-treated patients (69 versus 59%o; 95% confidence interval of -0.6%, 26.2%; P = 0.069) and also a significantly higher clinical response rate (69 versus 56%; 95% confidence interval of 3.5%, 28.5%; P = 0.021). The greatest difference between ciprofloxacin and imipenem was in eradication of members of the family Enterobateriaceae (93 versus 65%; P = 0.009). Stepwise logistic regression analysis demonstrated the following factors to be associated with bacteriological eradication: absence of Pseudomonas aeruginosa (P < 0.01), higher weight (P < 0.01), a low APACHE IH score (P = 0.03), and treatment with ciprofloxacin (P = 0.04). When P. aeruginosa was recovered from initial respiratory tract cultures, failure to achieve bacteriological eradication and development of resistance during therapy were common in both treatment groups (67 and 33% for ciprofloxacin and 59 and 53% for imipenem, respectively). Seizures were observed more frequently with imipenem than with ciprofloxacin (6 versus 1%; P = 0.028). These results demonstrate that in patients with severe pneumonia, monotherapy with ciprofloxacin is at least equivalent to monotherapy with imipenem in terms of bacteriological eradication and clinical response. For both treatment groups, the presence of P. aeruginosa had a negative impact on treatment success. Seizures were more common with imipenem than with ciprofloxacin. Monotherapy for severe pneumonia is a safe and elfective initial strategy but may need to be modified if P. aeruginosa is suspected or recovered from patients.Despite improvements in antimicrobial chemotherapy and supportive care, bacterial pneumonia, whether nosocomial or community acquired, remains an infection with substantial mortality. Nosocomial pneumonia accounts for about 15% of

The selection of bacterial resistance was examined in relationship to antibiotic pharmacokinetics (PK) and organism MICs in the patients from four nosocomial lower respiratory tract infection clinical trials. The evaluable database included 107 acutely ill patients, 128 pathogens, and five antimicrobial regimens. Antimicrobial pharmacokinetics were characterized by using serum concentrations, and culture and sensitivity tests were performed daily on tracheal aspirates to examine resistance. Pharmacodynamic (PD) models were developed to identify factors associated with the probability of developing bacterial resistance. Overall, in 32 of 128 (25%) initially susceptible cases resistance developed during therapy. An initial univariate screen and a classification and regression tree analysis identified the ratio of the area under the concentration-time curve from 0 to 24 h to the MIC (AUC0–24/MIC) as a significant predictor of the development of resistance (P < 0.001). The final PK/PD model, a variant of the Hill equation, demonstrated that the probability of developing resistance during therapy increased significantly when antimicrobial exposure was at an AUC0–24/MIC ratio of less than 100. This relationship was observed across all treatments and within all organism groupings, with the exception of β-lactamase-producing gram-negative organisms (consistent with type I β-lactamase producers) treated with β-lactam monotherapy. Combination therapy resulted in much lower rates of resistance than monotherapy, probably because all of the combination regimens examined had an AUC0–24/MIC ratio in excess of 100. In summary, the selection of antimicrobial resistance appears to be strongly associated with suboptimal antimicrobial exposure, defined as an AUC0–24/MIC ratio of less than 100.