Influence of antipseudomonal agents on Pseudomonas aeruginosa colonization and acquisition of resistance in critically ill medical patients

Risk stratification for multidrug-resistant Gram-negative infections in ICU patients

PURPOSE OF REVIEW

Antimicrobial resistance among Gram-negative microorganisms has alarmingly increased in the past 10 years worldwide. Infections caused by these microorganisms are difficult to treat, especially in critically ill patients.The present review examines how to accurately predict which patients carry a greater risk of colonization or infection on which to base the timely choice of an effective empirical antibiotic treatment regimen and avoid antibiotic overuse.

RECENT FINDINGS

There are many risk factors for acquiring one of many multidrug-resistant Gram-negative microorganisms (MDR-GN); however, scores anticipating colonization, infection among those colonized, or mortality among those infected have a variable accuracy. Accuracy of scores anticipating colonization is low. Scores predicting infections among colonized patients are, in general, better, and ICU patients infected with MDR-GN have a worse prognosis than those infected by non-resistant microorganisms. Scores are, in general, better at excluding patients.

SUMMARY

Despite these limitations, scores continue to gain popularity including those by Giannella, Tumbarello, Johnson, or the scores INCREMENT carbapenem-producing Enterobacteriaceae score, Cano, Tartof, or CarbaSCORE.

Risk stratification and treatment of ICU-acquired pneumonia caused by multidrug- resistant/extensively drug-resistant/pandrug-resistant bacteria

PURPOSE OF REVIEW

Describe the risk factors and discuss the management of multidrug-resistant (MDR) bacteria responsible for pneumonia among critically ill patients, including methicillin-resistant Staphylococcus aureus, extended spectrum beta-lactamase-producing Enterobactericeae, carbapenem-resistant Enterobactericeae, multidrug resistant Pseudomonas aeruginosa, and Acinetobacter baumannii.

RECENT FINDINGS

Multiple factors have been associated with infections because of MDR bacteria, including prolonged hospital stay, presence of invasive devices, mechanical ventilation, colonization with resistant pathogens, and use of broad-spectrum antibiotics. Management of these infections includes the prompt use of appropriate antimicrobial therapy, implementation of antimicrobial stewardship protocols, and targeted active microbiology surveillance. Combination therapy and novel molecules have been used for the treatment of severe infections caused by resistant bacteria.

SUMMARY

The exponential increase of antimicrobial resistance among virulent pathogens currently represents one of the main challenges for clinicians in the intensive care unit. Knowledge of the local epidemiology, patient risk stratification, and infection-control policies remain key elements for the management of MDR infections. Results from clinical trials on new molecules are largely awaited.

Risk factors and the resistance mechanisms involved in Pseudomonas aeruginosa mutation in critically ill patients

Background

The objective of this study was to determine the main risk factors of Pseudomonas aeruginosa mutation as well as the mechanisms of acquired resistance.

Methods

We conducted a 2-year prospective study in patients who were carriers of a Pseudomonas aeruginosa strain and who had been admitted to a medical/surgical ICU.

Results

Of the 153 patients who were included, 34 had a mutation in their strain. In a multivariate analysis, a duration of ventilation > 24 days was a risk factor for mutation (risk ratio 4.29; CI 95% 1.94-9.49) while initial resistance was a protective factor (RR 0.36; CI 95% 0.18-0.71). In a univariate analysis, exposure of P. aeruginosa to ceftazidime was associated with an over-production of AmpC cephalosporinase and exposure to meropenem was associated with impermeability. A segmentation method based on the duration of ventilation (> 24 days), initial resistance, and exposure of strains to ceftazidime made it possible to predict at 83% the occurrence of mutation.

Conclusion

The duration of ventilation and the presence of resistance as soon as P. aeruginosa is identified are predictive factors of mutation in ICU patients.

Predictors of Outcomes in Patients with Prolonged Weaning with Focus on Respiratory Tract Pathogens and Infection

BACKGROUND

The impact of respiratory tract pathogens and infection on outcomes in patients with prolonged weaning is largely unknown.

OBJECTIVE

We studied predictors of weaning outcomes (death and failure to achieve spontaneous ventilation) in a population treated during a 3.5-year period in a specialized and certified weaning centre.

METHODS

Patient data were retrieved retrospectively from the clinical charts. Complete datasets were available in 173 patients. The following parameters were investigated as potential predictors of both endpoints: age; comorbidities; tracheobronchial pathogens; bacteraemia, pneumonia and number of pneumonias; and number of inhouse treatment cycles (none vs. ≥1).

RESULTS

Tracheobronchial pathogens, pneumonia, bacteraemia and the number of antibiotic cycles all significantly increased weaning duration and hospitalisation times. Independent predictors of death were atrial fibrillation (OR 2.6, 95% CI 1.2-5.8, p = 0.02) and tracheobronchial multiresistant Pseudomonas aeruginosa (OR 3.9, 95% CI 1.4-11.0, p = 0.01). Independent predictors of failure to achieve spontaneous ventilation included chronic obstructive pulmonary disease (OR 2.8, 95% CI 1.0-7.8, p = 0.045); neuromuscular disease (OR 8.3, 95% CI 1.2-27.2, p = 0.02); tracheobronchial P. aeruginosa (OR 3.3, 95% CI 1.3-9.3, p = 0.01); Stenotrophomonas maltophilia (OR 7.9, 95% CI 1.4-51.6, p = 0.02); and pneumonia (OR 4.4, 95% CI 1.5-10.9, p = 0.003).

CONCLUSIONS

The impact of respiratory tract pathogens and infection on weaning outcomes was remarkable. Predictors of death and failure to achieve spontaneous ventilation differed considerably. A priority may be to investigate preventive strategies against colonisation and infection with respiratory pathogens, particularly P. aeruginosa.

Risk factors for colonization and infection by Pseudomonas aeruginosa in patients hospitalized in intensive care units in France

Pseudomonas aeruginosa (P.aeruginosa) remains a prominent nosocomial pathogen responsible for high morbi-mortality in intensive care units (ICUs). P.aeruginosa transmission is known to be partly endogenous and exogenous. Main factors have been highlighted but the precise role of environment in regard to antibiotics use remained unclear.

Pseudomonas aeruginosa blood stream infection isolates from patients with recurrent blood stream infection: Is it the same genotype?

The type identity of strains of Pseudomonas aeruginosa from primary and recurrent blood stream infection (BSI) has not been widely studied. Twenty-eight patients were identified retrospectively from 2008 to 2013 from five different laboratories; available epidemiological, clinical and microbiological data were obtained for each patient. Isolates were genotyped by iPLEX MassARRAY MALDI-TOF MS and rep-PCR. This showed that recurrent P. aeruginosa BSI was more commonly due to the same genotypically related strain as that from the primary episode. Relapse due to a genotypically related strain occurred earlier in time than a relapsing infection from an unrelated strain (median time: 26 vs. 91 days, respectively). Line related infections were the most common source of suspected BSI and almost half of all BSI episodes were associated with neutropenia, possibly indicating translocation of the organism from the patient's gut in this setting. Development of meropenem resistance occurred in two relapse isolates, which may suggest that prior antibiotic therapy for the primary BSI was a driver for the subsequent development of resistance in the recurrent isolate.

Emergence of antimicrobial resistance to Pseudomonas aeruginosa in the intensive care unit: association with the duration of antibiotic exposure and mode of administration

Background

Antibiotics are frequently used in intensive care units (ICUs), and their use is associated with the emergence of bacterial resistance to antibiotics. The aim of this study was to investigate the association between the emergence of Pseudomonas aeruginosa resistance and the duration of antibiotic exposure or mode of administration in an ICU unit.

Methods

A 4-year cohort study of intensive care unit was performed in patients with P. aeruginosa isolates from clinical specimens, initially susceptible to the investigated antibiotics (piperacillin/tazobactam, ceftazidime, ciprofloxacin, meropenem and amikacin). Odds ratios (ORs) with 95% confidence interval (95% CI) of emergence of resistance were calculated using logistic regression analysis for various exposure periods to antibiotics (1–3, 4–7, 8–15 and >15 days) relative to no exposure with adjustment for age, sex, Simplified Acute Physiology Score 3 (SAPS 3) and length of stay. ORs on the emergence of P. aeruginosa resistance were also calculated for the various modes of administration.

Results

Included were 187 patients [mean age 61 years, 69% male, mean SAPS 3 score (SD): 59 (12.3)]. None of the antibiotics investigated showed the emergence of resistance within 1–3 days. Significant meropenem resistance emerged within 8–15 days [OR 79.1 (14.9–421.0)] after antibiotic exposure unlike other antibiotics (>15 days). No difference was observed between intermittent and extended administration of meropenem and between beta-lactam mono- or combined therapy.

Conclusions

Use of meropenem was associated with the emergence of resistance as soon as 8 days after exposure to the antibiotic.

Multidrug-resistant Pseudomonas aeruginosa lower respiratory tract infections in the intensive care unit: Prevalence and risk factors

Intensive care unit (ICU) admission is a risk for multidrug-resistant (MDR) Pseudomonas aeruginosa, but factors specific to critically ill pneumonia patients are not fully characterized. Objective was to determine risk factors associated with MDR P. aeruginosa pneumonia among ICU patients. This was a retrospective case-control study of P. aeruginosa pneumonia in the ICU; cystic fibrosis and colonizers were excluded. Risk factors included comorbid conditions and prior healthcare exposure (anti-pseudomonal antibiotics, hospitalizations, nursing home, P. aeruginosa colonization/infection, mechanical ventilation). Of 200 patients, 47 (23.5%) had MDR P. aeruginosa pneumonia. Independent predictors for MDR were ≥24h antibiotics in the preceding 90days (carbapenems, fluoroquinolones, and piperacillin-tazobactam) (odds ratio, 3.6 [95% CI, 1.6-8.1]) and nursing home residence (2.3 [1.1-4.9]). MDR P. aeruginosa remains prevalent among ICU patients with pneumonia. Given poor outcomes with delayed therapy, patients should be thoroughly assessed for prior anti-pseudomonal antibiotic exposure and nursing home residency.

Strategies to enhance rational use of antibiotics in hospital: a guideline by the German Society for Infectious Diseases

Introduction

In the time of increasing resistance and paucity of new drug development there is a growing need for strategies to enhance rational use of antibiotics in German and Austrian hospitals. An evidence-based guideline on recommendations for implementation of antibiotic stewardship (ABS) programmes was developed by the German Society for Infectious Diseases in association with the following societies, associations and institutions: German Society of Hospital Pharmacists, German Society for Hygiene and Microbiology, Paul Ehrlich Society for Chemotherapy, The Austrian Association of Hospital Pharmacists, Austrian Society for Infectious Diseases and Tropical Medicine, Austrian Society for Antimicrobial Chemotherapy, Robert Koch Institute.

Materials and methods

A structured literature research was performed in the databases EMBASE, BIOSIS, MEDLINE and The Cochrane Library from January 2006 to November 2010 with an update to April 2012 (MEDLINE and The Cochrane Library). The grading of recommendations in relation to their evidence is according to the AWMF Guidance Manual and Rules for Guideline Development.

Conclusion

The guideline provides the grounds for rational use of antibiotics in hospital to counteract antimicrobial resistance and to improve the quality of care of patients with infections by maximising clinical outcomes while minimising toxicity. Requirements for a successful implementation of ABS programmes as well as core and supplemental ABS strategies are outlined. The German version of the guideline was published by the German Association of the Scientific Medical Societies (AWMF) in December 2013.

Acquisition of Pseudomonas aeruginosa and its resistance phenotypes in critically ill medical patients: role of colonization pressure and antibiotic exposure

INTRODUCTION

The objective of this work was to investigate the risk factors for the acquisition of Pseudomonas aeruginosa and its resistance phenotypes in critically ill patients, taking into account colonization pressure.

METHODS

We conducted a prospective cohort study in an 8-bed medical intensive care unit during a 35-month period. Nasopharyngeal and rectal swabs and respiratory secretions were obtained within 48 hours of admission and thrice weekly thereafter. During the study, a policy of consecutive mixing and cycling periods of three classes of antipseudomonal antibiotics was followed in the unit.

RESULTS

Of 850 patients admitted for ≥ 3 days, 751 (88.3%) received an antibiotic, 562 of which (66.1%) were antipseudomonal antibiotics. A total of 68 patients (8%) carried P. aeruginosa upon admission, and among the remaining 782, 104 (13%) acquired at least one strain of P. aeruginosa during their stay. Multivariate analysis selected shock (odds ratio (OR) = 2.1; 95% confidence interval (CI), 1.2 to 3.7), intubation (OR = 3.6; 95% CI, 1.7 to 7.5), enteral nutrition (OR = 3.6; 95% CI, 1.8 to 7.6), parenteral nutrition (OR = 3.9; 95% CI, 1.6 to 9.6), tracheostomy (OR = 4.4; 95% CI, 2.3 to 8.3) and colonization pressure >0.43 (OR = 4; 95% CI, 1.2 to 5) as independently associated with the acquisition of P. aeruginosa, whereas exposure to fluoroquinolones for >3 days (OR = 0.4; 95% CI, 0.2 to 0.8) was protective. In the whole series, prior exposure to carbapenems was independently associated with carbapenem resistance, and prior amikacin use predicted piperacillin-tazobactam, fluoroquinolone and multiple-drug resistance.

CONCLUSIONS

In critical care settings with a high rate of antibiotic use, colonization pressure and non-antibiotic exposures may be the crucial factors for P. aeruginosa acquisition, whereas fluoroquinolones may actually decrease its likelihood. For the acquisition of strains resistant to piperacillin-tazobactam, fluoroquinolones and multiple drugs, exposure to amikacin may be more relevant than previously recognized.

Trends and correlation of antibacterial usage and bacterial resistance: time series analysis for antibacterial stewardship in a Chinese teaching hospital (2009-2013)

The purpose of this investigation was to describe the effect of antibacterial stewardship and evaluate the trends and correlation of antibacterial resistance and usage from 2009 to 2013 in a tertiary-care teaching hospital in northwest China. Antibacterial usage was expressed as defined daily doses per 100 patients per day (DDDs/100 PDs). Hospital-wide population-level data and time series analysis were used to evaluate the trends and determine associations between antibacterial exposure and acquisition of resistance. Yearly consumption of overall antibacterials significantly decreased from 66.54 to 28.08 DDDs/100 PDs (β = -10.504, p < 0.01). The resistant rates of the five most frequently isolated species (including Escherichia coli, Acinetobacter baumannii, Staphylococcus aureus, Pseudomonas aeruginosa, and Klebsiella pneumoniae) significantly decreased or remained stable, and none of them showed a statistically significant upward trend. The medical quality indicators got better or remained stable. Autoregressive integrated moving average (ARIMA) models demonstrated that the monthly resistance rate of P. aeruginosa to imipenem was strongly correlated with antipseudomonal carbapenems usage (β = 34.94, p < 0.001), as did the correlation of P. aeruginosa to meropenem with antipseudomonal third-generation cephalosporins usage (β = 32.76, p < 0.01) and K. pneumoniae to amikacin with aminoglycosides usage (β = 22.01, p < 0.001). The decreased antibacterial use paralleled the improved bacterial resistance without deteriorating medical quality indicators during antimicrobial stewardship. It also suggests that optimum antibiotic use is necessary to alleviate the threat posed by resistant microorganisms at the hospital level.

Risk factors for Pseudomonas aeruginosa acquisition in intensive care units: a prospective multicentre study

BACKGROUND

Pseudomonas aeruginosa is a major nosocomial pathogen in intensive care units (ICUs); however, endogenous versus exogenous origin of contamination remains unclear.

AIM

To identify individual and environmental ICU risk factors for P. aeruginosa acquisition.

METHODS

A five-month prospective multicentric study was performed in ten French ICUs. Adult patients hospitalized in ICU for ≥ 24 h were included and screened for P. aeruginosa colonization on admission, weekly and before discharge. P. aeruginosa acquisition was defined by a subsequent colonization or infection if screening swabs on admission were negative. Water samples were obtained weekly on water taps of the ICUs. Data on patient characteristics, invasive devices exposure, antimicrobial therapy, P. aeruginosa water and patient colonization pressures, and ICU characteristics were collected. Hazard ratios (HRs) were estimated using multivariate Cox model.

FINDINGS

Among the 1314 patients without P. aeruginosa on admission, 201 (15%) acquired P. aeruginosa during their ICU stay. Individual characteristics significantly associated with P. aeruginosa acquisition were history of previous P. aeruginosa infection or colonization, cumulative duration of mechanical ventilation and cumulative days of antibiotics not active against P. aeruginosa. Environmental risk factors for P. aeruginosa acquisition were cumulative daily ward 'nine equivalents of nursing manpower use score' (NEMS) [hazard ratio (HR): 1.47 for ≥ 30 points; 95% confidence interval (CI): 1.06-2.03] and contaminated tap water in patient's room (HR: 1.76; CI: 1.09-2.84).

CONCLUSION

Individual risk factors and environmental factors for which intervention is possible were identified for P. aeruginosa acquisition.

Antibiotic pressure is a major risk factor for rectal colonization by multidrug-resistant Pseudomonas aeruginosa in critically ill patients

The intestinal reservoir is central to the epidemiology of Pseudomonas aeruginosa, but the dynamics of intestinal colonization by different phenotypes have been poorly described. To determine the impact of antimicrobial exposure on intestinal colonization by multidrug-resistant (MDR) and extensively drug-resistant (XDR) P. aeruginosa, we screened intensive care unit (ICU) patients for rectal colonization on admission and at weekly intervals. During an 18-month study period, 414 ICU patients were enrolled, of whom 179 (43%) were colonized; 112 (63%) of these were identified at ICU admission and 67 (37%) during their ICU stay. At 10 days after ICU admission, the probabilities of carriage were 44%, 24%, and 24% for non-MDR, MDR-non-XDR, and XDR P. aeruginosa strains, respectively (log rank, 0.02). Pulsed-field gel electrophoresis showed 10 pairs of non-MDR P. aeruginosa and subsequent MDR-non-XDR strains isolated from the same patients to be clonally identical and another 13 pairs (8 MDR-non-XDR and 5 XDR) to be unrelated. There was one specific clone between the 8 MDR-non-XDR strains and an identical genotype in the 5 XDR isolates. The Cox regression analysis identified MDR P. aeruginosa acquisition as associated with the underlying disease severity (adjusted hazard ratio [aHR], 1.97; 95% confidence interval [CI], 1.22 to 3.18; P = 0.006) and prior use of fluoroquinolones (aHR, 1.02; 95% CI, 1.00 to 1.04; P = 0.039), group 2 carbapenems (aHR, 1.03; 95% CI, 1.00 to 1.07; P = 0.041), and ertapenem (aHR, 1.08; 95% CI, 1.02 to 1.14; P = 0.004). The epidemiology of MDR P. aeruginosa is complex, and different clusters may coexist. Interestingly, ertapenem was found to be associated with the emergence of MDR isolates.

Cycling empirical antibiotic therapy in hospitals: meta-analysis and models

The rise of resistance together with the shortage of new broad-spectrum antibiotics underlines the urgency of optimizing the use of available drugs to minimize disease burden. Theoretical studies suggest that coordinating empirical usage of antibiotics in a hospital ward can contain the spread of resistance. However, theoretical and clinical studies came to different conclusions regarding the usefulness of rotating first-line therapy (cycling). Here, we performed a quantitative pathogen-specific meta-analysis of clinical studies comparing cycling to standard practice. We searched PubMed and Google Scholar and identified 46 clinical studies addressing the effect of cycling on nosocomial infections, of which 11 met our selection criteria. We employed a method for multivariate meta-analysis using incidence rates as endpoints and find that cycling reduced the incidence rate/1000 patient days of both total infections by 4.95 [9.43–0.48] and resistant infections by 7.2 [14.00–0.44]. This positive effect was observed in most pathogens despite a large variance between individual species. Our findings remain robust in uni- and multivariate metaregressions. We used theoretical models that reflect various infections and hospital settings to compare cycling to random assignment to different drugs (mixing). We make the realistic assumption that therapy is changed when first line treatment is ineffective, which we call “adjustable cycling/mixing”. In concordance with earlier theoretical studies, we find that in strict regimens, cycling is detrimental. However, in adjustable regimens single resistance is suppressed and cycling is successful in most settings. Both a meta-regression and our theoretical model indicate that “adjustable cycling” is especially useful to suppress emergence of multiple resistance. While our model predicts that cycling periods of one month perform well, we expect that too long cycling periods are detrimental. Our results suggest that “adjustable cycling” suppresses multiple resistance and warrants further investigations that allow comparing various diseases and hospital settings.

The rise of antibiotic resistance is a major concern for public health. In hospitals, frequent usage of antibiotics leads to high resistance levels; at the same time the patients are especially vulnerable. We therefore urgently need treatment strategies that limit resistance without compromising patient care. Here, we investigate two strategies that coordinate the usage of different antibiotics in a hospital ward: “cycling”, i.e. scheduled changes in antibiotic treatment for all patients, and “mixing”, i.e. random assignment of patients to antibiotics. Previously, theoretical and clinical studies came to different conclusions regarding the usefulness of these strategies. We combine meta-analyses of clinical studies and epidemiological modeling to address this question. Our meta-analyses suggest that cycling is beneficial in reducing the total incidence rate of hospital-acquired infections as well as the incidence rate of resistant infections, and that this is most pronounced at low baseline levels of resistance. We corroborate our findings with theoretical epidemiological models. When incorporating treatment adjustment upon deterioration of a patient's condition (“adjustable cycling”), we find that our theoretical model is in excellent accordance with the clinical data. With this combined approach we present substantial evidence that adjustable cycling can be beneficial for suppressing the emergence of multiple resistance.

Acquisition of resistant microorganisms and infections in HIV-infected patients admitted to the ICU

Whether critically ill human immunodeficiency virus (HIV)-infected patients are at risk of acquiring nosocomial infections and resistant or potentially resistant microorganisms (RPRMs) remains to be clarified. The aim was to compare the acquisition of RPRMs, infections and mortality in critically ill HIV-infected and non-infected patients. An observational, prospective cohort study of patients admitted to a medical intensive care unit (ICU) was undertaken. Swabbing of nares, pharynx and rectum, and culture of respiratory secretions were obtained within 48 h of admission and thrice weekly thereafter. Clinical samples were obtained as deemed necessary by the attending physician. Clinical variables, severity scores on admission and exposures during ICU stay were collected. Logistic regression was used to evaluate ICU mortality. Out of the 969 included patients, 64 (6.6%) were HIV-infected. These patients had a higher Acute Physiology and Chronic Health Evaluation (APACHE) II score on admission (19.5 ± 6.6 vs. 21.1 ± 5.4, p = 0.02), stayed longer in the care unit and were more exposed to several invasive devices and antibiotics. There were no differences in the rate of acquisition of RPRMs and the only difference in ICU-acquired infections was a significantly higher incidence of catheter-related bacteraemia (3% vs. 9%, p = 0.03). The ICU-related mortality was similar in both groups (14% vs. 16%, p = 0.70) and in HIV-infected patients, it tended to be associated with a lower CD4 cell count (p = 0.06). Despite a longer ICU stay, critically ill HIV-infected patients did not show a higher rate of RPRMs acquisition. The rate of ICU-acquired infection was similar between HIV-infected and non-infected patients, except for catheter-related bacteraemia, which was higher in the HIV-infected population. Mortality was similar in both groups.

A systematic review and meta-analyses show that carbapenem use and medical devices are the leading risk factors for carbapenem-resistant Pseudomonas aeruginosa

A systematic review and meta-analyses were performed to identify the risk factors associated with carbapenem-resistant Pseudomonas aeruginosa and to identify sources and reservoirs for the pathogen. A systematic search of PubMed and Embase databases from 1 January 1987 until 27 January 2012 identified 1,662 articles, 53 of which were included in a systematic review and 38 in a random-effects meta-analysis study. The use of carbapenem, use of fluoroquinolones, use of vancomycin, use of other antibiotics, having medical devices, intensive care unit (ICU) admission, having underlying diseases, patient characteristics, and length of hospital stay were significant risk factors in multivariate analyses. The meta-analyses showed that carbapenem use (odds ratio [OR] = 7.09; 95% confidence interval [CI] = 5.43 to 9.25) and medical devices (OR = 5.11; 95% CI = 3.55 to 7.37) generated the highest pooled estimates. Cumulative meta-analyses showed that the pooled estimate of carbapenem use was stable and that the pooled estimate of the risk factor "having medical devices" increased with time. We conclude that our results highlight the importance of antibiotic stewardship and the thoughtful use of medical devices in helping prevent outbreaks of carbapenem-resistant P. aeruginosa.

Surveillance and correlation of antimicrobial usage and resistance of Pseudomonas aeruginosa: a hospital population-based study

This retrospective study evaluated trends and association between resistance of Pseudomonas aeruginosa isolated from patients with hospital-acquired infections (HAIs) and hospital antimicrobial usage from 2003 through 2011 in a tertiary care hospital in northeast China. HAI was defined as occurrence of infection after hospital admission, without evidence that infection was present or incubating (≦48 h) on admission. In vitro susceptibilities were determined by disk diffusion test and susceptibility profiles were determined using zone diameter interpretive criteria, as recommended by Clinical and Laboratory Standards Institute (CLSI). Data on usage of various antimicrobial agents, expressed as defined daily dose (DDD) per 1,000 patients-days developed by WHO Anatomical Therapeutical Chemical (ATC)/DDD index 2011, were collected from hospital pharmacy computer database. Most of 747 strains of P. aeruginosa were collected from respiratory samples (201 isolates, 26.9%), blood (179, 24.0%), secretions and pus (145, 19.4%) over the years. Time series analysis demonstrated a significant increase in resistance rates of P. aeruginosa to ticarcillin/clavulanic acid, piperacillin/tazobactam, cefoperazone/sulbactam, piperacillin, imipenem, meropenem, ceftazidime, cefepime, ciprofloxacin, and levofloxacin except aminoglycosides over time in the hospital (P<0.001). The rates of carbapenem-resistant P. aeruginosa (CRPA) isolated from patients with HAIs were 14.3%, 17.1%, 21.1%, 24.6%, 37.0%, 48.8%, 56.4%, 51.2%, and 54.1% over time. A significant increase in usage of anti-pseudomonal carbapenems (P<0.001) was seen. ARIMA models demonstrated that anti-pseudomonal carbapenems usage was strongly correlated with the prevalence of imipenem and meropenem-resistant P. aeruginosa (P<0.001). Increasing of quarterly CRPA was strongly correlated at one time lag with quarterly use of anti-pseudomonal carbapenems (P<0.001). Our data demonstrated positive correlation between anti-pseudomonal antimicrobial usage and P. aeruginosa resistance to several classes of antibiotics, but not all antimicrobial agents in the hospital.

Multilevel modelling of the prevalence of hospitalized patients infected with Pseudomonas aeruginosa

Pseudomonas aeruginosa is one of the leading nosocomial pathogens. The question of the respective contribution of endogenous and exogenous sources remains controversial. In this study, we shed new light on this issue by means of a multilevel logistic regression analysis which allowed a simultaneous investigation of factors associated with prevalence of patients infected with P. aeruginosa at two levels: patient and healthcare facility (HCF) in the eastern regions of France. A total of 25 533 in-patients from 51 HCFs were included in the analysis. The overall prevalence was 0·37% (range 0-1·65%). Multilevel modelling estimated that <14% of total variability of the outcome variable was explained by differences between HCFs and that after adjusting for patient-level variables, which explained 52% of HCF-level variance, the latter became non-significantly different from zero. A compositional effect (patient factors), rather than a contextual effect (ecological factors), explains heterogeneity of the prevalence of patients infected with P. aeruginosa in the eastern HCFs of France.