Antibiotic therapy for severe bacterial infections: correlation between the inhibitory quotient and outcome

International Journal of Antimicrobial Agents 23 (2004) 120–128

Antibiotic therapy for severe bacterial infections: correlation between the inhibitory quotient and outcome Teresa Spanu a,∗ , Rosaria Santangelo a , Felicita Andreotti b , Giuliana Lo Cascio a , Giuseppe Velardi a , Giovanni Fadda a a

Department of Microbiology, Catholic University of the Sacred Heart, Largo F. Vito 1, 00168 Rome, Italy Department of Cardiology, Catholic University of the Sacred Heart, Largo F. Vito 1, 00168 Rome, Italy

b

Received 7 February 2003; accepted 17 June 2003

Abstract In severe bacterial infections, treatment failure can occur even when the infecting organism has displayed in vitro susceptibility to the antibiotics used. Several pharmacokinetic–pharmacodynamic parameters show better correlation with therapeutic outcome than susceptibility results. This study was devised to assess the relation between the inhibitory quotient (IQ), i.e., the ratio of achievable antibiotic concentration at the infection site to the minimum inhibitory concentration for the infecting organism, and both clinical and bacteriological outcomes in 290 severe bacterial infections. Multivariate analysis showed that the IQ was a strong predictor of therapeutic outcome (P < 0.001–0.002): values <4 predicted failure, and those ≥6 cure. This simple parameter could be routinely used to guide effective antibiotic therapy. © 2003 Elsevier B.V. and the International Society of Chemotherapy. All rights reserved. Keywords: Inhibitory quotient; Antimicrobial therapy; Therapeutic outcome

1. Introduction In vitro antimicrobial susceptibility testing plays a pivotal role in the treatment of bacterial infections [1–3]. These tests provide a profile of the infecting organism in terms of its susceptibility or resistance to a number of possible therapeutic agents, based on the minimum inhibitory concentration (MIC), i.e., the lowest concentration of the drug which will prevent the growth of the offending bacterial strain. The classification of MICs as indicative of susceptibility or resistance has become far more reliable since the introduction of validated breakpoints for interpreting test results, such as those recommended by the National Committee for Clinical Laboratory Standards (NCCLS) [2,3]. However, while use of an antibiotic to which the infecting organism has displayed in vitro resistance is significantly associated with treatment failure, positive outcomes are less closely related to use of agents to which the organism has displayed sensitivity, especially in cases of serious infection [4].

∗ Corresponding author. Tel.: +39-06-3015-4218; fax: +39-06-305-1152. E-mail address: [email protected] (T. Spanu).

Failure may occur for a variety of reasons. In some cases it can be attributed to the use of a drug whose MIC is in the borderline zone of susceptibility for the infecting organism, particularly if low doses are used Forrest et al. [5]. In addition, however, the success of antibiotic treatment is influenced by a host of in vitro factors that cannot be addressed by in vitro susceptibility testing [6–8]. The site of infection, for instance, is a critical factor in the selection of an appropriate antibacterial agent and the effective dosage [8]. The drug used must be able to reach adequate concentrations at the specific site of the infection. A local concentration that is equal to or only slightly higher than the MIC will almost certainly prove to be insufficient to inhibit fully bacterial growth without major contributions from host defences which are often compromised in patients with serious bacterial infections [9,10]. Optimal therapy thus requires more than the knowledge of whether the infecting organism was sensitive to a given antibiotic in vitro: the physician must be able to determine whether that drug will be able to reach effective levels at the site of the infection and, if so, after what doses. In 1981, Ellner and Neu devised what they considered a more effective means for interpreting MIC data, the inhibitory quotient (IQ), a simple-to-calculate index that

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T. Spanu et al. / International Journal of Antimicrobial Agents 23 (2004) 120–128

reflects not only the in vitro activity of the drug and but also its pharmacokinetics [11,12]. The IQ represents the ratio of the concentration that can be achieved at the specific site of infection to the MIC of the drug with respect to the infecting organism. Although its use was proposed almost 20 years ago, the clinical value of the IQ in the selection of treatment has never been systematically evaluated. The purpose of this study was to examine the outcome of serious bacterial infections in patients who were treated with antimicrobial agents to which the organism was susceptible in vitro and to evaluate whether use of the IQ might be capable of improving the efficacy of treatment.

2. Materials and method

121

(2) Multiple infecting organisms, i.e., more than one organism isolated from the same infection site. (3) Use of combination therapy, i.e., the patient’s infection had been treated simultaneously with two or more antimicrobial drugs. (4) Premature interruption of therapy, i.e., the antibiotic had been discontinued after fewer than 5 days of treatment. (5) Death prior to completion of treatment, i.e., within 72 h of the initiation of antimicrobial therapy. (6) Lack of pharmacokinetic data, i.e., published figures were not available for peak concentrations of the drug used at the given site of infection. (7) Impaired renal function and/or granulocytopenia reflected respectively by serum creatinine >300 ␮mol/l and/or granulocyte counts of <1 × 109 l−1 .

2.1.2. Inclusion criteria and definitions Patients receiving antimicrobial agents to which their infecting pathogens had tested susceptible using NCCLS definitions [3] within the first 3 days after the onset of infections as therapy, were included in this analysis. Cases with one or more of the following characteristics were excluded:

Application of the above exclusions yielded 201 patients in whom bacterial infection had been documented at one site only (biliary tract, bloodstream, cerebrospinal fluid, lungs, pancreas and urinary tract) and was thus classified as primary. Eight-nine others met all of inclusion criteria listed above with the exception of the first. In these patients, blood cultures were positive for the same organism that had been isolated from another clinical specimen (e.g. urine, sputum, etc). For the purposes of our primary analysis, each of these 89 cases was considered a single infection defined as secondary bacteraemia and the infection documented at the other site was not considered at all. Our initial analysis thus centred on a total of 290 infections, 201 of which were primary and the remaining 89 secondary (bacteraemias). For this analysis, we evaluated the possible relations between the outcome (clinical and bacteriological as described below) of therapy and the following aspects of each of the 290 infections considered: drug used, MIC, IQ (method of calculation described below); patient age; infecting organism; site of infection; in addition, the type of infection was also evaluated for bloodstream infections (i.e., primary versus secondary bacteraemia) and those of the lower respiratory tract (community-acquired pneumonia vs. ventilator-associated pneumonia). Later, the subgroup with secondary bacteraemia (89 patients) was subjected to separate analysis, in which IQs were calculated with respect to both the primary and secondary infection sites to determine which correlated best with the outcome of treatment.

(1) Infections at more than one site (e.g., lungs and urinary tract), regardless of whether or not they were caused by the same organisms. This type of exclusion was necessary to avoid confounding factors in our primary analysis, i.e., evaluation of the possible correlation between the IQ of the prescribed treatment (which reflects the site of infection) and clinical outcome of therapy. The exception to this rule regarded patients with secondary bacteraemia, which are described in greater detail below.

2.1.3. Clinical and bacteriological outcomes Clinical and bacteriological outcomes were defined based on findings on the last day of treatment. For analysis of the subgroup with secondary bacteraemia, separate bacteriological outcomes were recorded for the primary and secondary sites of infection. The clinical outcome was considered favourable if all of the following were documented: remission of symptoms, normal body temperature (<37.5 ◦ C), normalisation or a

2.1. Study design 2.1.1. Patients and infections Between January 1998 and June 2001, we conducted a prospective observational study of bacterial infections consecutively diagnosed among adult inpatients at the Catholic University Medical Centre in Rome. Infections were identified by the recovery of bacteria from clinical specimens (biliary tract, bloodstream, cerebrospinal fluid, lower respiratory tract, pancreas, urinary tract), together with clinical abnormalities, white blood cell counts and radiological investigations when appropriate [13–15]. Standard methods were used to process the clinical specimens and identify the isolated organisms [16]. The MICs of antimicrobial drugs were determined using a standardised broth microdilution method and classified as indicative of susceptibility, intermediate susceptibility, or resistance according to NCCLS guidelines [2,3]. The study was observational in that administration of antimicrobial therapy was selected by the patient’s physician not the investigators. Clinical data and information on drug regimens were collected from the medical records by two investigators, who were not involved in the patients’ management.

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≥15% decrease in the white blood cell count and when applicable, improvement of radiological abnormalities. All other responses were classified as unfavourable. Deaths were classified as infection-related or non-related. Bacteriological outcomes were defined as favourable if the post-treatment cultures were negative or if no more material could be obtained for culture (e.g. sputum in pneumonia). The response was considered unfavourable when post-treatment cultures were still positive for the same organism, regardless of whether or not the latter had acquired resistance to antibiotic used. 2.2. Inhibitory quotient The IQ was calculated as follows: level of antimicrobial agent achievable at the infection site with the dose used IQ = MIC for the infecting organism The local levels of the drug antimicrobial agent achievable at various infection sites with the doses administered for treatments were collected from the data published by Mandell et al. [13], Lorian [17], and Bassi et al. [18]. When discordant data emerged from these sources, the average was used. 2.3. Statistical analyses Univariate and multivariate models of logistic regression were used to evaluate the association between different variables (continuous and categorical) and clinical and bacteriological outcomes. In the univariate analyses, the independent variables were IQ, infecting organism, MIC for the latter, antimicrobial agent used and patient age. Univariate analyses were performed for all infections, as well as for each site of infection; for pneumonias and bacteraemias, analysis was also performed for each type of infection. In the latter case the

infection site was included in the model as an additional independent parameter. The multivariate analyses were performed for site of infection only; for bacteraemias and pneumonias, type of infection was also included in the model. Correlations between IQs and clinical and bacteriological outcomes were also evaluated. Relative risks (RRs) for treatment failure with 95% confidence intervals (CIs) were computed for the IQ categories, <4 and ≥6. We referred to Neu for breakpoint values to categorise IQs ([12]). The association between categorised IQs and death was also assessed with Fisher’s exact test. A two-tailed P < 0.05 was considered statistically significant. Plus or minus values are mean ± S.D. Analyses were performed using the SAS package [19].

3. Results 3.1. Patients, infections, and antimicrobial agents The 290 patients considered in this study included 166 men and 124 women ranging in age from 18 to 94 years (mean 56 ± 18.2 years). At the beginning of treatment their Acute Physiology and Chronic Health Evaluation (APACHE III) scores ranged from 14.5 to 51.8 (mean: 25.9 ± 6.2) [20]. Table 1 shows the sites and types of the 290 infections (201 primary, 89 secondary) considered in our initial analysis, as well as the clinical outcomes of antimicrobial therapy. Table 2 shows the organisms responsible for the 290 infections, 241 (83.1%) of which were caused by Gram-negative rods. The types of antimicrobial drugs used to treat these infections are listed in Appendix A, which shows the peak concentrations that can be reached at various infection sites with the actual doses used. Over half (55%) of the infections were treated with ␤-lactams; the remaining infections were treated with aminoglycosides (23%), fluoroquinolones (14%) or glycopeptides (8%).

Table 1 Favourable and unfavourable clinical outcomes of 201 primary infections and 89 secondary bacteraemias Types of infection

No. of infections

No. (%) of clinical outocome Favourable

Unfavourable

No. of deaths

69 19 10 24 6 10 28

19 (9.4)

Primary infection Cholangitis Community-acquired pneumonia Ventilator-associated pneumonia Bacteraemia Other infectionsa Secondary bacteraemiab

201 54 35 34 51 27 89

132 35 25 10 45 17 61

Total

290

193 (66.5)

a

(65.7) (64.8) (71.4) (29.4) (88.2) (63) (68.5)

(34.3) (35.2) (28.6) (70.6) (11.8) (37) (31.5)

97 (33.5)

1 (2.9) 13 (38.2) 3 (5.9) (7.4) 2 (2.2) 21 (7.2)

12 meningitis, 5 pancreatitis, 10 pyelitis. The source of infection in 89 secondary bacteraemias was: biliary tract (n = 57.64%), urinary tract (n = 24.27%) and lower respiratory tract (n = 8.9%). b

T. Spanu et al. / International Journal of Antimicrobial Agents 23 (2004) 120–128 Table 2 Favourable and unfavourable bacteriological outcomes of 290 strains isolated from 290 infections Species

No. of isolates

3.3. Variables related to outcome Univariate analysis revealed a significant association (P < 0.001) between IQ and both the clinical and bacteriological outcomes (Fig. 1), which were concordant in all but one case. Fig. 2 and Table 4 show the relations between the IQ of the treatment used and clinical outcomes stratified by site and type of infection. To a lesser extent, clinical outcome was also significantly related to the infecting organism (P = 0.003), MIC (P = 0.002), antimicrobial agent (P < 0.001), type (P = 0.002) and site of infection (P = 0.004), but not to patient’s age. In multivariate analysis, the IQ remained the most significant variable associated with clinical outcome (P from <0.001 to 0.003, depending on the site of infection). As shown in Fig. 2, unfavourable outcomes were almost exclusively associated with an IQ < 4: only one infection with an IQ of 3.5 (a case of primary bacteraemia) was cured. An IQ < 4 was associated with a relative risk of unfavourable outcome of 94 (95% CI = 13.0–663.0, P < 0.001). Overall, IQs of 4–5.9 or greater were significantly associated with favourable therapeutic responses (P < 0.001), and the relative odds of a favourable outcome for treatments with an IQs ≥ 6 was 32 (95% CI = 8.0–124.0, P < 0.001). More specifically, all cases of cholangitis with IQ ≥ 4 were cured, except one case in which an infected biliary tract drainage catheter was left in place (Fig. 2). This patient met the criteria for a favourable clinical outcome at the termination of therapy, but the bacteriological outcome was unfavourable (i.e., biliary drainage cultures were persistently positive), and clinical recurrence of the infection occurred 3 months later. Favourable outcomes were also recorded for all the infections in which the IQ ≥ 6 grouped together under the heading Other (Fig. 2). As for the 69 lower respiratory tract infections (Fig. 2), all 22 cases with IQs ≥ 6 were cured. In the remaining 47, the clinical outcome was related to the type of the infection: 77.8% of the community-acquired pneumonias with IQs of 4–5.9 were successfully treated as opposed to only 28.6% of those associated with assisted ventilation. Of the 34 patients with ventilator-associated pneumonia, death occurred in 8/10 (80%) of those with IQs < 4 and only in 5/18 (27.8%) with IQs of 4–5.9. The IQ in these patients was significantly related to death (P = 0.006). Among the 51 patients with

No. (%) of bacteriological outcome Favourable

Unfavourable 90 50 12 1 8 6 4 4 2 2 0 1 0 8 7 1

Gram-negative Pseudomonas aeruginosa Acinetobacter baumannii Escherichia coli Enterobacter aerogenes Enterobacter cloacae Klebsiella pneumoniae Stenotrophomonas maltophilia Serratia marcescens Proteus mirabilis Citrobacter freundii Klebsiella oxytoca Haemophilus influenzae Gram-positive Staphylococcus aureus Streptococcus pneumoniae

241 108 28 25 24 15 12 10 6 5 3 3 2 49 33 16

151 58 16 24 16 9 8 6 4 3 3 2 2 41 26 15

(62.7) (53.7) (57.1) (96) (66.7) (60) (66.7) (60) (66.7) (60) (100) (66.7) (100) (83.7) (78.8) (93.7)

Total

290

192 (66.2)

123

(37.3) (46.3) (42.9) (4) (33.3) (40) (33.3) (40) (33.3) (40) (0) (33.3) (0) (16.3) (21.2) (6.3)

98 (33.8)

3.2. Outcomes As shown in Table 1, favourable outcomes were recorded for 193/290 (66.5%) infections. Clinical and bacteriological outcomes were concordant in all cases with the exception of one patient with cholangitis, who is described in greater detail below (Tables 1 and 2). They were most common in cases of primary bacteraemia (45/51 cases; 88.2%) and least frequent in ventilator-associated pneumonia (10/34 cases; 29.4%). Within the secondary bacteraemia subgroup, favourable clinical outcomes were recorded in 61/89 (68.5%) cases. The distribution of these outcomes according to the site primary infection is shown in Table 3. Death occurred in 21/290 patients (7.2%), 13 of whom (61.9%) had ventilator-associated pneumonia. The overall mortality rate of patients with the latter type of infection was 38.2%. All but one of the 21 deaths were associated with infections caused by Gram-negative organisms, chiefly Pseudomonas aeruginosa, Acinetobacter baumannii and Enterobacter aerogenes.

Table 3 Distribution of clinical outcomes of 89 cases of secondary bacteraemia according to the IQ for the primary infection site Primary infection site (no.)

IQ range 0.5–3.9 (n = 26 infections)

4–5.9 (n = 10 infections)

>6 (n = 53 infections)

No. of clinical outcomes Favourable

Unfavourable

Favourable

Unfavourable

Favourable

Unfavourable

Biliary tract (57) Respiratory tract (8) Urinary tract (24)

0 0 0

23 3 0

7 1 0

0 2 0

27 2 24

0 0 0

Total (89)

0

26

8

2

53

0

124

T. Spanu et al. / International Journal of Antimicrobial Agents 23 (2004) 120–128 Clinical outcomes 56

129

56

100 percentage of favourable and unfavourable outcomes

percentage of favourable and unfavourable outcomes

100 80

26

60 21

42

40 20

9

6

1 0 0.5-3.9

4 -5.9

6.0-10

P <0.001

Bacteriological outcomes

P <0.001

129 42

80 27

60 20 40

9

20

6

1 0 0.5-3.9

>10

4 -5.9

6.0-10

>10

inhibitory quotient

inhibitory quotient

Fig. 1. Frequency distribution of favourable (䊐) and unfavourable (䊏) clinical and bacteriological outcomes vs. IQ. The number above each bar indicates the number of infections and the number of infecting organisms. P-values are derived from the univariate analysis.

primary bacteraemia, one of the two cases with IQs of 4–5.9 and all those (43/43) with IQs ≥ 6 responded favourably to therapy (Fig. 2). In contrast, clinical cures were less common (61/89; 68.5%) among patients with secondary bacteraemia. Analysis of outcome according to the IQ calculated for the bloodstream infections showed that positive outcomes occurred in 30% (3/10) of patients with IQs of 4–5.9, in 57.1% (12/21) of those with IQs of 6–10, and in 88.5% (46/52) with IQs ≥ 10 (Fig. 2). As explained in Section 2, the primary sites of infections and their IQs in the secondary bacteraemia subgroup were considered in a separate analysis. As shown in Table 4, the vast majority of these patients had biliary (n = 57) or urinary (n = 24) infections. Almost all of the favourable outcomes in this subgroup were associated with IQs of ≥6 for the primary site of infection, and multivariate analysis showed that outcome was significantly related to the IQ for the primary infection site (P = 0.002) but not to that of the secondary site (P = 0.736).

4. Discussion In in vitro testing, all of the infecting pathogens considered in this study were fully susceptible to the drug(s) used to combat them, but many displayed in vivo resistance. In fact, there was no significant relation between clinical outcome and in vitro susceptibility results, and similar findings have been reported by others [4]. Treatment failures were associated with both high and low MICs, but they were most frequent when low doses of antimicrobial agents were administered. Organisms near the MIC breakpoint (indicating borderline susceptibility) were the first to express resistance. When the MIC of the drug used is close to the marginal point of susceptibility, or when low doses of antimicrobial agents are administered, concentrations below the MIC are obtained, thus increasing the risk of selection of resistant organisms. The MIC is considered a fundamental factor for calculating effective antibiotic doses, and in mild or moderate

Table 4 Range, mean, median values of inhibitory quotients in 290 bacterial infections according to clinical outcomes Infection

P-valuea

Clinical outcome (no.) Favourable (193)

Unfavourable (97)

IQ range

Mean (±S.D.)

Median

IQ range

Mean (±S.D.)

Median

Cholangitis Community-acquired pneumonia Ventilator-associated pneumonia Primary bacteraemia Other infections Secondary bacteraemia

4–300 4–65 5–14 3.5–400 6.5–190 4–300

34 (±64.0) 13.0 (±14.0) 7.6 (±2.8) 78.9 (±90.5) 34.0 (±45.0) 34.0 (±32.3)

15.0 8.0 6.5 42 14.3 73

0.5–3.9 0.5–4.5 0.5–6 1.2–4 0.7–4 2–80

2.0 2.1 3.0 2.3 2.7 20.0

(±1.5) (±1.2) (±1.7) (±0.9) (±1.1) (±34.0)

1.8 2.0 4.0 2.0 3.0 6.0

0.002 0.063 0.013 <0.001 NTb 0.002

Total

3.5–400

72.4 (±195.0)

19

0.5–80

7.5 (±19.0)

3.0

<0.001

a

P-values are derived from univariate analysis. NT: not tested. No analyses was performed for the 27 infections grouped as Other since the clinical outcomes were always negative for IQ < 6 and always positive for IQ ≥ 6. b

T. Spanu et al. / International Journal of Antimicrobial Agents 23 (2004) 120–128

P =0.002 6

9

20

100

percentage of favourable and

percentage of favourable and unfavourable outcomes

19

80 60 40 20 0 0.5-3.9

4 -5.9

6.0-10

8

2

0.5-3.9

4 -5.9

60 40 20 0

percentage of favourable and unfavourable outcomes

>10

Ventilator-associated pneumonia P=0.013

8

4

10

2

percentage of favourable and unfavourable outcomes

100 7

80 60 40 20

2

0

14

80 60 40

4 20 0

0.5-3.9

4 -5.9

6.0-10

>10

0.5-3.9

inhibitory quotient

Primary bacteraemia

6.0-10

Secondary bacteraemia

P<0.001 3

4 -5.9

40

P=0.002

6

100

100

5 80 60

1 1

40

1

0 0.5-3.9

4 -5.9

6.0-10

>10

inhibitory quotient

percentage of favourable and unfavourable outcomes

percentage of favourable and unfavourable outcomes

6.0-10

inhibitory quotient

100

20

13

80

>10

Community-acquired pneumonia P=0.063 10

4

100

inhibitory quotient

8

P =NT

Other

unfavourable outcomes

Cholangitis

125

>10

46

80

7 12

60

9 40

3

20

6

0 0.5-3.9

4 -5.9

6.0-10

>10

inhibitory quotient inhibitory quotient

Fig. 2. Frequency distribution of favourable (䊐) and unfavourable (䊏) clinical outcomes vs. IQ in 54 cases of cholangitis, 27 infections grouped as others, 35 community acquired pneumonias, 34 ventilator-associated pneumonias, 51 primary bacteraemias and 89 secondary bacteraemias. The number above each bar indicates the number of infections. P-values are derived from the univariate analysis.

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T. Spanu et al. / International Journal of Antimicrobial Agents 23 (2004) 120–128

infections it is usually an adequate guide to therapy [7]. For severe infections, however, it is generally unreliable unless it is integrated with other data. Prediction of outcome may be improved when the drug’s pharmacokinetics are also considered [6,8,21–27]. For the fluoroquinolones and aminoglycosides, which exert concentration-dependent killing, the results of in vitro studies and animal testing indicate that the bactericidal activity of these drugs is optimal when their peak concentration (Cmax ) is 8–10 times greater than the MIC [6,28–33]. Ratios of this magnitude are necessary to prevent the development of resistant organisms and have been associated with improved therapeutic outcomes in clinical studies [22,28,34]. With antimicrobials, such as ␤-lactams or vancomycin, whose antibacterial effects are time-dependent, outcome is related to the amount of time the serum level exceeds the MIC of the infecting organism, and when such levels are achieved for 40–50% of a dosing interval, a favourable therapeutic outcome can usually be expected [35]. However, for these drugs as well, higher killing rates have been documented with peak concentrations up to four times higher than the MICs, although further increases do not improve bactericidal rates [36–39]. One of the newest measures based on the principles of pharmacokinetics and pharmacodynamics is area under the inhibitory curve (AUIC) [24]. The AUIC represents the ratio of the antibiotic area under the concentration-time curve (AUC24 ) to the organism’s MIC, or AUC24 /MIC. Although AUIC, time > MIC, and peak levels > MIC are seemingly diverse parameters, there are few examples in the literature that demonstrate the differences between these pharmacodynamic measures, and most examples are in animals receiving antibiotics with short half-lives [40,41]. For drugs with extended half-lives, the importance of differentiating between these parameters diminishes. We assessed the relation between IQ values and outcome of antimicrobial therapy in 290 severe bacterial infections treated with antimicrobial agents to which the infecting organism had displayed in vitro susceptibility. The IQ of an antimicrobial agent, with respect to a given pathogen, represents the multiple of the minimum inhibitory concentration that can be achieved with a given dose at the specific site of infection. In both univariate and multivariate analyses, this parameter proved to be a much stronger predictor of therapeutic outcome in patients with severe bacterial infections than either the MIC of the antimicrobial agent used or its qualitative interpretation (i.e., susceptible). On the whole, IQs below 4 were rarely associated with favourable therapeutic outcomes (P < 0.001) (Fig. 2), and this observation is consistent with that of Neu, who first suggested the clinical importance of this IQ cut-off [11,12]. Within the group of treatment regimens with IQs ≥ 4, we also found that those with IQs of 4–5.9 had a significantly greater probability of success and almost all primary infections and the vast majority of secondary bacteraemias with IQs ≥ 6 were associated with favourable outcomes.

Over two-thirds of the deaths recorded occurred in patients with ventilator-associated pneumonia. The overall mortality rate for this type of infection (38.2%) is consistent with previously published findings [42]. The risk depends primarily on the type of pathogen and the type of antibiotic therapy [42–44]. In our patients, both of these variables and IQ values were significantly related to mortality. On multivariate analysis, the IQ remained the variable most significantly associated with death (P = 0.003). There were no deaths among ventilator-associated pneumonia cases in which the IQ was 6 or more. Patients with secondary bacteraemia are a particular challenge since therapy must be adequate to eliminate the infection at both the primary and secondary sites. In our initial analysis, univariate analysis revealed that of the secondary bacteraemia subgroup, the bloodstream IQ was indeed a significant predictor of therapeutic outcome (P = 0.002). Nonetheless, in multivariate analysis of our subgroup of patients with secondary bacteraemia, the clinical outcome was significantly related to the IQ for the primary site of infection but not that for the bloodstream infection. As Table 4 shows, this difference was particularly important in secondary bacteraemia patients with biliary-tract infections, 40.4% of whom experienced therapeutic failure (all associated with primary-site IQs of <4), and in the subgroup with pneumonia, where unfavourable outcomes were recorded in half of all cases (all associated with primary-site IQs of <6). At these sites, the concentration of an antibiotic (depending on the agent, of course) is often lower than that reached in the bloodstream (Appendix A). In contrast, for the patients whose primary focus of infection was the urinary tract, where many drugs reach levels that are higher than those in the blood, high primary-site IQs (≥6) and favourable outcomes were recorded in all cases. In conclusion, our findings indicate that routine use of the IQ, which integrates the predicted in vivo concentration of the antibiotic at the infection site and the organism’s MIC, might be a cost-effective means of improving the efficacy of antimicrobial therapy in cases of severe bacterial infections.

Acknowledgements The authors thank Antonella Bacchieri, biostatistician, for performing the statistical analyses and Marian Kent for editorial assistance.

Appendix A Concentrations of various antimicrobial agents at different sites used to calculate inhibitory quotients

T. Spanu et al. / International Journal of Antimicrobial Agents 23 (2004) 120–128

Antimicrobial agent

Amikacin Ampicillin Ampicillin Aztreonam Aztreonam Cefoperazone Cefoperazone Cefotetan Cefotetan Ceftazidime Ceftazidime Ceftizoxime Ceftizoxime Ceftriaxone Ceftriaxone Ciprofloxacin Ciprofloxacin Gentamicin Imipenem Imipenem Pefloxacin Penicillin G Piperacillin Piperacillin Piperacillin/tazobactam Piperacillin/tazobactam Teicoplanin Teicoplanin Tobramycin Vancomycin Vancomycin a b

127

Concentrationa (␮g/ml) Doseb

Blood

Bile

Cerebrospinal fluid

Pancreas

Sputum

Urine

7.5 mg/kg 1.5 g 2.0 g 1.0 g 2.0 g 1.0 g 2.0 g 1.0 g 2.0 g 1.0 g 2.0 g 1.0 g 2.0 g 1.0 g 2.0 g 0.1 g 0.2 g 1.0 mg/kg 0.5 g 1.0 g 0.4 g 2 mU 2.0 g 4.0 g 3.375 g 4.5 g 0.2 g 0.4 g 1.0 mg/kg 0.5 g 1.0 g

38.0 40.0 47.6 90.0 205.0 153.0 253.0 161.0 237.0 69.0 179.0 84.4 131.0 136.0 270.0 2.1 3.8 7.0 43.0 73.0 5.8 20.0 199.0 451.0 209.0 224.0 53.0 112.0 4.0 8.0 25.0

7.0 60.0 86.4 – – 465.0 1825.0 940.0 – 19.0 35.5 23.4 – – 153.4 3.0 7.8 – 3.0 15.2 – – 385.7 1792.0 385.7 1792.0 – 1.9 0.5 3.1 –

– – 2.0 7.2 – – – – – 15.0 35.0 – – 5.4 11.0 0.1 – – 7.7 13.1 – 0.6 – – – – – – – 1.6 4.0

– – – – – – – – – – – – – – – – – – 3.3 – – – – – – – – – – – –

– – – 1.0 7.0 – 1.5 1.0 – – – 3.2 4.3 – 4.5 1.0 3.9 – 2.0 3.2 – 0.2 3.8 12.2 – 12.2 – 0.6 0.2 – 3.0

– – – 3000.0 – – – 1700.0 – 5.0 9999.0 – – 995.0 – – – – 100.0 – – – – 5.0 – – – 43.3 – – –

Data on site’s concentrations were collected from Bassi et al. [18], Lorian [17], and Mandell et al. [13]. By intravenous administration.

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