A Combination Antibiogram to Guide Empiric Therapy for Pseudomonas aeruginosa Infections . Year-to-Year Variation and Influence of Day of Hospitalization Isolation

Copyright: © 2016 Alnamnakani B, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. *Corresponding author: John A Bosso, PharmD, South Carolina College of Pharmacy, Charleston, USA, Tel: 843-792-8501; Fax: 843-792-1712; E-mail: bossoja@musc.edu


Introduction
Pseudomonas aeruginosa is responsible for a variety of serious nosocomial infections including ventilator-associated pneumonia and catheter-associated urinary tract infections [1].As this pathogen is capable of expressing numerous resistance mechanisms including beta-lactamase production, decreased permeability of the outer bacterial membrane and active efflux, [2] selection of appropriate treatment is challenging and related infections are associated with significant morbidity and mortality [3].A number of rationales have been described for the empirical institution of combination therapy in treating Pseudomonas aeruginosa or other gram-negative infections including expansion of the spectrum of activity, potential synergy, avoidance of adverse drug reactions (presuming smaller doses of each antibiotic), and prevention of resistance [4].While there is a paucity of data to support most of these rationales, there is no question that a properly selected combination of agents, based upon local susceptibility data, will indeed broaden the spectrum of activity and increase the odds that one of the agents will possess in vitro activity against the pathogen.This practice has, in fact, been incorporated into the current national guidelines for the treatment of hospital-acquired pneumonia [5].Thus, selection of the two antimicrobials is critical and an institutionspecific combination antibiogram should inform these decisions in cases of suspected or proven Pseudomonas aeruginosa infections.Combination antibiograms, which consider the activity of two antibiotic combinations

Methods
Pseudomonas aeruginosa susceptibility data for the antibiotics of interest for the years 2009 through 2012 represented results from tests performed by our institution's Clinical Microbiology Laboratory.These data were de-identified prior to any analysis.Our academic medical center is a 709 bed, tertiary care facility providing care for both adult and pediatric patients although only isolates from adult patients were considered in this analysis.Each year's data were assessed separately and duplicate isolates (same organism from same patient, regardless of body site, from same year) were not included.Isolates from patients with cystic fibrosis were not included in this analysis as these often exhibit higher levels of resistance and have been shown to skew the average numbers generated for antibiograms [6].Susceptibility was determined using disk diffusion as per CLSI guidance [7] and interpretive criteria were not changed by our laboratory during the study period.For purposes of our analysis, organisms were considered either susceptible or non-susceptible.The antibiotics of interest were the formulary anti-pseudomonal beta-lactams, Open Access 2 yielded similar results.As little variation in the most active combinations was seen from year-to-year, it was determined that inferential statistical testing was not necessary to interpret the data.

Discussion
Infections with multidrug resistant Gram-negative pathogens, including Pseudomonas aeruginosa, are not only associated with considerable morbidity and mortality but present an economic burden as well, as they are associated with greater hospital/treatment costs and longer lengths of stay when compared to those associated with their drug-susceptible counterparts [8].As rapid institution of an effective combination appears related to improved patient outcomes and shortens hospital stays, it is critical that information is readily available to the clinician making these therapeutic decisions [4].Empiric or definitive antibiotic selection for an infection with a suspected or known pathogen is based upon such considerations as in vitro activity and favorable pharmacokinetics/pharmacodynamics, given the nature of the infection and patient characteristics.As in vitro activity is a prime consideration, construction of a combination antibiogram, based upon institutionspecific susceptibility data as done here, can provide that guidance.Further, such information would serve to ensure that choices recommended on an institution's clinical pathways or order forms for Pseudomonas aeruginosaassociated infections are appropriate based on local data.
The creation and use of combination antibiograms to inform empiric combination antibiotic therapy decisions for suspected or proven Pseudomonas aeruginosa infections has been described and advocated by others.Similar to our findings, Mizuta et al. [9] reported an anti-pseudomonal combination antibiogram in which the most active combinations included a β-lactam and an aminoglycoside.Combinations with the widest coverage over a four year span included ceftzidime, piperacillin/tazobactam or cefepime with either tobramycin or amikacin.As with our study, little year-to-year variation was noted.Others have constructed and used intensive care unit-specific antibiograms for aminoglycosides and fluoroquinolones.These specific medications included cefepime, meropenem, aztreonam, pipericillin/tazobactam, amikacin, tobramycin, gentamicin and ciprofloxacin.To determine the combined in vitro activity or coverage for a given combination in a given year, the number of total isolates susceptible to a given β-lactam was first determined.Subsequently, the number of non-susceptible isolates to each β-lactam that were susceptible to each of the other antibiotics was enumerated.In this way the total number/percent of isolates in a given year susceptible to any given combination was determined and the most active or best combinations identified.Once this exercise was complete the rank order of possible combinations, based upon combined activity, was determined.Additionally, variability between years was assessed.In addition to performing this analysis for all isolates in the database, we repeated the exercise for those isolates cultured from patients within the first two days of hospitalization and those from day three onward for comparison for the years 2011 and 2012, as those in the latter group might be more reflective of hospital-acquired strains.
As not all isolates were tested to both drugs in a given combination, calculations for percent susceptible to a combination were based on the number tested to both drugs.

Results
The total number of isolates (n=249, 244, 304 and 297 for years 2009, 2010, 2011 and 2012, respectively) considered and the three most active combinations for each year are presented in table 1 while the same results for isolates cultured within the first two days of hospitalization versus those collected on day three and onward are presented in table 2. The combinations with the greatest combined activity each year, in most cases, included an anti-pseudomonal β-lactam and an aminoglycoside.In only one instance each did a second or third ranked combination include ciprofloxacin or two β-lactams.Most combinations provided combined coverage in excess of 90% except those with aztreonam (data not shown).The comparison for best combinations for isolates collected within the first two days of hospitalization vs those collected on day three or beyond Open Access
While our creation of a combination antibiogram for Pseudomonas aeruginosa is not unique, its replication on a year-by-year basis over a four-year time span is important as it illustrates, at least for our institution that the best combinations may not vary appreciably over time.Whether this would hold true over longer time periods or at other institutions remains to be determined.However, our results suggest that a combination antibiogram based on susceptibility results from a given year would provide suitable guidance for the ensuing year.Further, the observation that results for isolates collected on day three or later of hospitalization, more likely representing nosocomial pathogens, did not vary dramatically from those in isolates collected earlier is also of interest and potential importance even though it only compares two years.It should noted, however, that definition of "hospital-acquired" is a loose one.Although frequently used as a discriminator, one would in fact need sequential cultures starting on hospital admission and then continued daily until a pathogen is first detected to confidently label it as "hospital-acquired".Our observation in this regard should be viewed in that light.
These results should be viewed with some caution.It must be appreciated that this was a single center study considering only Pseudomonas aeruginosa and that our results may not apply elsewhere or for other gram-negative, multidrug resistant pathogens.A combination antibiogram considering multiple pathogens might have yielded different results and conclusions.It is also reasonable to speculate that custom combination antibiograms for individual patient care units might well yield different results from those generated with the institution's combined susceptibility database [12,13].However, a sufficient number of isolates must be available to make such a sub-analysis reliable.As in our case, these numbers are often lacking at the individual unit level for any specific organism.As already mentioned above, whether our 4-year time frame for analysis adequately reflects or predicts more long-term changes is unknown.Also, our exclusion of isolates from cystic fibrosis patients might have affected results and subsequent conclusions.
The process of creating a combination antibiogram is neither complex nor unreasonably time consuming.Despite the theoretical limitations of our study, we are comfortable recommending that production of combination antibiograms should be considered by other institutions dealing with infections associated with multidrug-resistant pathogens and requiring combination therapy as a means to inform empiric prescribing decisions.
n H U B f o r S c i e n t i f i c R e s e a r c h Citation: Alnamnakani B, Bosso JA (2016) A Combination Antibiogram to Guide Empiric Therapy for Pseudomonas aeruginosa Infections.Year-to-Year Variation and Influence of Day of Hospitalization Isolation.J Clin Lab Med 1(1): doi http://dx.doi.org/10.16966/2572-9578.105

Table 1 :
Best Coverage Combinations by Year (all isolates) a Number of isolates tested to both drugs in the combination