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Control of Gram-negative multi-drug resistant microorganisms in an Italian ICU: Rapid decline as a result of a multifaceted intervention, including conservative use of antibiotics

      Highlights

      • A multifaceted intervention to control selection and transmission of MDROs in the ICU.
      • An in-ward leader revised antibiotic prescription and involved all staff members.
      • ASP intervention included introduction of round-the-clock microbiological support.
      • Rapid and steep fall of Gram-negative resistant isolates after bundle implementation.

      Abstract

      Background

      Gram-negative Multi-Drug-Resistant Organisms (GNMDROs) cause an increasing burden of disease in Intensive Care Units (ICUs). We deployed a multifaceted intervention to control selection and transmission of GNMDROs and to estimate at which rate GNMDROs would decline with our interventional bundle.

      Methods

      Interventions implemented in 2015: in-ward Antimicrobial-Stewardship-Program for appropriate management of antimicrobial prescription; infection monitoring with nasal/rectal swabs and repeated procalcitonin assays; 24 h microbiological support (since 2016); prevention of catheter-related infections, VAPs and in-ward GNMDROs transmission; education of ICU personnel. In May 2017, epidemiological, clinical and microbiological data were collected and retrospectively analyzed. Rates of resistance in Klebsiella pneumoniae, Pseudomonas aeruginosa and Acinetobacter baumannii, as well as percentages of resistance among all Gram-negative bacteria were compared during the study period.

      Results

      Of 668 patients, at least one isolate was obtained from 399 patients. The proportions of patients with infection and with Gram-negative isolates were even across the 5 semesters (p = 0.8). For Klebsiella pneumoniae, the number of strains resistant to carbapenems fell from 94% to 6% (p < 0.001). Significant drops were also observed for Pseudomonas aeruginosa and Acinetobacter baumannii. Percentages of resistance for all Gram-negative isolates fell from 91% to 13% (p < 0.0001). The reduction in antibiotic prescription translated in a considerable reduction of pharmacy costs. Multivariate models confirmed that the hospitalization semester was the most relevant independent predictor of resistance among Gram-negative bacteria.

      Conclusions

      Our experience provides further evidence that a multi-faceted intervention, aimed to reduce selection and transmission of GNMDROs with efficient microbiological support, may yield remarkable results in a short time interval.

      Keywords

      Introduction

      Acutely ill patients assisted in the Intensive Care Unit (ICU) are at high risk of both colonization and infection with Multidrug Resistant Organisms (MDROs) (
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      Availability of next generation antibiotics in the industrial pipeline would not be sufficient to overcome this worrying scenario unless effective strategies to control GNMDROs selection are defined (
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      • Coulthard K.
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      • et al.
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      ). Several strategies for the prevention and control of GNMDROs have been elaborated and are currently under evaluation in intensive care units (
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      Infection control measures to decrease the burden of antimicrobial resistance in the critical care setting.
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      ). Nearly all of them include programs of antimicrobial stewardship (ASP), whereby appropriate use of antibiotics is pursued in terms of restricted prescription, right dosing, rapid de-escalation and shortening of treatment (
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      Aggressive versus conservative antibiotic use to prevent and treat ventilator-associated pneumonia in patients with severe traumatic brain injury: comparison of two case series.
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      • Dimopoulos G.
      • Garnacho-Montero J.
      • et al.
      The intensive care medicine research agenda on multidrug-resistant bacteria, antibiotics, and stewardship.
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      The antibiotic course has had its day.
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      • Povoa P.
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      Duration of antibiotic therapy in the intensive care unit.
      ). Some of these strategies include increase in the efficiency of microbiological support, to ease early targeted prescription (
      • Kollef M.H.
      • Bassetti M.
      • Francois B.
      • Burnham J.
      • Dimopoulos G.
      • Garnacho-Montero J.
      • et al.
      The intensive care medicine research agenda on multidrug-resistant bacteria, antibiotics, and stewardship.
      ,
      • Llewelyn M.J.
      • Fitzpatrick J.M.
      • Darwin E.
      • SarahTonkin C.
      • Gorton C.
      • Paul J.
      • et al.
      The antibiotic course has had its day.
      ,
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      Non-antibiotic treatments for bacterial diseases in an era of progressive antibiotic resistance.
      ,
      • Taccone F.S.
      • Bond O.
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      Individualized antibiotic strategies.
      ,
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      • Povoa P.
      • Martin-Loeches I.
      Duration of antibiotic therapy in the intensive care unit.
      ).
      At our site, the recent rise in the prevalence of GNMDROs was in line with other Italian reports (
      • Orsi G.B.
      • Giuliano S.
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      • Ciorba V.
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      • Giordano A.
      • et al.
      Changed epidemiology of ICU acquired bloodstream infections over 12 years in an Italian teaching hospital.
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      Analysis of peripheral blood lymphocyte subsets in critical patients at ICU admission: a preliminary investigation of their role in the prediction of sepsis during ICU stay.
      ). We therefore defined and deployed our local strategy to control GNMDROs, and set up a complex network of informatics to measure the efficacy of our strategy and the time frame necessary to reduce GNMDRO prevalence.

      Methods

      Study design and study population

      We conducted a quasi-experimental pre-post study, with retrospective evaluation of results of our interventional bundle, using data extracted from the Abruzzo’s hospital discharge database and our central laboratory database.
      The study population included all patients hospitalized for >24 h in the Intensive Care Unit at Pescara General Hospital, Italy, and discharged with any ICD-9-CM code in primary up to tenth diagnoses, between January 1, 2015 and May 31, 2017. ICU patients were tracked whatever the caring ward(s) before or after the ICU. Microbiological data for all inpatients are accessible in digital format at a single database (Werfen, Italy). For statistical analyses, the hospital discharge and laboratory databases were linked through encrypted identification codes. Results of cultural assays, either positive or negative, were retrieved. For all positive microbiological samples, information included isolate speciation and results of antibiotic sensitivity tests performed. Because data managed by the automated system of collection were encrypted and anonymous, neither Ethical Committee approval nor informed consent was required for this study.
      Patients were distributed in accordance with the date of ICU entrance into one of the 5 semesters of the study period: first semester 2015, pre-intervention phase; second semester 2015 and first semester 2016, whereby interventions were sequentially put in place (Figure 1); second semester 2016 and first semester 2017: outcome evaluation phase, with the whole bundle at work.
      Figure 1
      Figure 1The Bundle of interventions deployed in the Intensive Care Unit at Pescara General Hospital and the time frame of each bundle element.
      The major outcome of our investigation was measuring the variation in the percentages of carbapenem-resistant Klebsiella pneumoniae, Pseudomonas aeruginosa and Acinetobacter baumannii strains, as well as percentages of bacterial resistance (as described below) in patients across the 5 semesters. Secondary outcomes of our investigation were variation in frequency of infection, length of stay and overall mortality among hospitalized patients. Data on antibiotic consumption for ICU patients in the first 4 semesters of the study were collected, in order to measure possible variations in expenditure for antibiotics as a consequence of our interventional bundle.

      Description of the interventions for GNMDROs control

      During 2015 and early in 2016 (Figure 1) we sequentially implemented a bundle of interventions to prevent and control GNMDROs colonizations and infections, including the following:
      Close monitoring of ensuing infections in febrile neuro-critical patients out of empirical antibiotic prescription, by daily determinations of leukocytes, Procalcitonin (PCT) and C-Reactive Protein (since April, 2015).
      Reinforcement of existing procedures for the prevention of catheter-related infections, through education of ICU personnel and quarterly staff meetings (since April 2015).
      MDRO Screening at ICU entrance, using nasal swabs for MRSA and rectal swabs for GNMDROs; rectal swabs were repeated weekly (since March, 2015). Blood cultures, tracheal aspirates, broncho-alveolar lavages, urine, CSF or other samples were collected whenever infection was suspected, as in the past.
      Reinforcement of existing procedures for Infection Control, including: hand glove change after any contact with patients, irrespective of MDRO carriage; frequent hand washing; immediate notification of both colonizations and infections by GNMDROs to the local Epidemiological Surveillance Office (ESO); within-day visit by ESO personnel to aid implementation of in-ward contact isolation; additional environmental and touch surface cleaning procedures after any cluster of ≥2 patients with the same GNMDRO (since March, 2015).
      Implementation of an Antimicrobial-Stewardship-Program based on: identification of a single ICU clinician in charge of supervising in-ward antibiotic prescriptions; waiting for microbiological data to prescribe antibiotics whenever possible; choice of monotherapy rather than combination therapy whenever appropriate; use of the loading dose and extended/continuous infusions whenever indicated; shortening of treatments aided by biomarkers and clinical/microbiological data; de-escalation to monotherapy or narrow-spectrum antibiotics in patients with adequate microbiology; multidisciplinary discussions of relapsing infections or infections in immunocompromised patients (since April, 2015).
      Update of local protocols for antimicrobial prophylaxis in: trauma, neuro-critical and neurosurgical patients, open fractures and deep wounds, based on evidence in the literature. Choice of antibiotics and duration of prophylaxis were narrowed, whenever timely surgical treatment was provided (since January, 2016).
      Since February 2016, the local Microbiological Unit was upgraded to round-the clock laboratory activity, allowing microscope evaluation of positive blood samples after or without Gram staining (in order to appreciate lack of motility suggesting Klebsiella spp. or Acinetobacter spp.), quick identification of bacterial species via fluorescent in situ hybridization, detection of genome elements encoding ‘Alert’ resistance traits (mecA/C, van A/B genes, genes related to KPC, VIM, NDM, OXA 48/181 carbapenemases) by PCR technologies; phenotype-based (biochemical and proteomic) microbial characterization as soon as positive cultures were available. Phone notification of ongoing microbiological results to the on-duty ICU clinician was introduced.
      Medical education of ICU personnel on the above protocols was performed, using Continuing Medical Education programs (since February, 2016).

      Additional data source

      For each patient, the following variables were considered: age, gender, length of stay, patient’s provenience (direct ICU hospitalization or transfer from other wards), diagnosis at ICU entrance (traumatic brain injury, polytrauma, acute respiratory or cardiac insufficiency, septic shock or multi-organ-failure, acute neurological illness (ischemic/hemorrhagic stroke, subarachnoid hemorrhage), gastrointestinal/liver, endocrine/metabolic disease; poisoning) and comorbidities (CMs), by Charlson Comorbility Index (CCI), using diagnostic information in individual hospital discharge records. According to CCI score, patients were classified as: no CMs (CCI = 0), one CM (CCI = 1), ≥2 CMs (CCI ≥ 2).

      Outcomes

      GNMDROs

      The primary microbiological outcome of our investigation was measuring the number of the most clinically relevant GNMDROs across the 5 semesters. Our data collection system tracked the number of the following 3 Gram Negative isolates per semester: meropenem/ imipenem resistant Klebsiella pneumoniae; meropenem/imipenem resistant Pseudomonas aeruginosa; meropenem/imipenem Acinetobacter baumannii. Among Gram-positive Bacteria, the number of MRSA and MRCoNS isolates was evaluated in parallel.

      Percentage of antibiotic resistance

      To retrieve additional information about subtle variations in microbial resistance across the 5 semesters, for all Gram-negative microbial isolates collected, including those above mentioned, we evaluated the percentage of resistance as the ratio = antibiotics for which the isolate was resistant over the total of antibiotics tested. Type and numbers of antibiotics tested for each isolate did not vary across the study period. For each study semester, the percentages of resistance among Gram-negative Bacteria were expressed as medians and interquartile ranges (IQR).

      Secondary outcomes

      Additional outcomes were length of stay, number of patients with infection and overall mortality during the study period. Use of and expenditure for antibiotics were also monitored in the first 4 study semesters.

      Microbiology

      Sensitivity assays were performed at the central Microbiology Unit, Pescara General Hospital, using the Vitek2 system (bioMérieux, France), Accelerate PhenoTest (Accelerate Diagnostics, US), GeneXpert (Cepheid, US), as well as disc diffusion methods and agar MIC determination (antibiotic discs and MIC test strips by Liofilchem, Italy) according to the EUCAST 2017 guidelines. Results of sensitivity assays were categorized as positive/negative in accordance with the EUCAST 2017 breakpoints (
      • EUCAST (European Committee on Antimicrobial Susceptibility Testing)
      ). All methods were not modified across the study period.

      Statistical analysis

      Data were reported as medians and IQR for continuous variables, and frequencies and percentages for categorical variables. Microbiological and patients’ characteristics, reported overall, for each semester and positive/negative results were compared with the Kruskal-Wallis test (or Mann-Whitney test as appropriate) for continuous variables and the Chi-square test for categorical variables. Length-of-stay and overall mortality were evaluated for all included patients. Outcomes across semesters were compared with the Kruskal-Wallis for trend test (
      • Jonckheere A.R.
      A distribution-free k-sample test against ordered alternatives.
      ) for continuous variables and the Mantel-Haenszel Chi-square test for categorical variables. As percentages of resistance and length-of-stay were not normally distributed, we evaluated the best model (lower value better fit) according to Akaike information criterion and to parsimony and clinical interpretability of data. To address this issue, normal, Poisson and negative binomial distributions were run with fixed and random effect by patients (only for percentages of resistance). Negative binomial distribution with random effect by patient from generalized linear mixed model (
      • Willett J.B.
      • Singer J.D.
      Applied longitudinal data analysis: modeling change and event occurrence.
      ) represented the best fit and results were expressed as adjusted Incidence rate ratios (IRRs) with their 95% confidence intervals (CIs). Logistic regression analyses were performed to assess independent predictors of percentages of resistance, length-of-stay and overall mortality and results were expressed as adjusted Odds ratios (ORs) with 95% CIs. Covariates considered in multivariate analyses were: semester (1st 2015–1st 2017), age (years in quartiles), sex (male/female), CCI (0,1 or >1), diagnosis on admission (brain injury, polytrauma, cardiac or respiratory insufficiency, SEPSIS/Septic SHOCK/Multi Organ Failure (MOF), ischemic/hemorrhagic stroke, aneurysmal subaracnoid hemorrhage), ward at hospital admission (ICU vs other) and presence of any resistance (for length-of-stay and overall mortality). A P-value <0.05 was considered for statistical significance. All statistical analyses were performed using SAS 9.4 (SAS Institute, Cary, NC, USA).

      Results

      Six hundred and sixty-eight patients were hospitalized in the ICU between January, 2015, and May, 2017, and were assisted for longer than 24 h. At least one microbiological isolate was obtained from 412 patients (64%), whereas negative culture results were obtained for the remaining 235 patients (Figure 2). Type of cultural isolate and/or results of sensitivity tests were unavailable for 13 (3.1%) of the 412 patients with least one microbiological isolate. In the 399 remaining patients considered for further analyses, 5119 cultures were performed, 1734 (33.9%) yielding isolates with evaluable resistance tests (Figure 2). Twenty-eight patients (7.0%) were linked with contaminants only, such as a single isolate of Coagulase-Negative Staphylococcus. All other patients were linked with single or multiple isolates of potential Gram-negative or Gram-positive pathogens.
      Figure 2
      Figure 2Flow chart of the process for the identification of patients for the retrospective analysis of bacterial resistance in our quasi-experimental model of pre-post intervention.
      Table 1 compares the main clinical and demographic features of patients with negative and positive microbiological results. Length-of-stay was significantly longer (15.0 vs 13.0d, p < 0.001) and mortality was higher (35.7% vs 26.0%, p = 0.01) for patients with positive microbiological results (Table 1). Microbial isolates obtained from any of the assessed sources are described in Table 2. Interestingly, numbers and percentages of Gram-negative bacteria under investigation were unchanged across the five semesters (p = 0.8). Similarly, antibiotic resistance tests performed for each positive isolate did not show any relevant variation across the study period (Table 2). Shown in Table 3 are the proportions of patients with and without infection(s) across the study semesters, as well the type and site of infection. Interestingly, these proportions were once more unchanged and nearly identical over time, indicating that neither the characteristics of patients nor those of their incident infections were different during the study (p = 0.8).
      Table 1Main clinical and demographic features of patients with negative and positive microbiological results.
      VariablesNegative (N = 235)At least one Positive (N = 412)p
      χ-square test for categorical variables and the Kruskal-Wallis test for continuous variables.
      AGE, median (IQR)69.6 (50.9–78.5)66.8 (52.2–77.0)0.50
      Male gender, n (%)148 (63.0)242 (58.7)0.29
      CCI = 0, n (%)127 (54.0)201 (48.8)0.01
      CCI = 1, n (%)76 (32.3)176 (42.7)
      CCI > 1, n (%)32 (13.6)35 (8.5)
      Diagnosis at admission
       Traumatic brain injury, n (%)26 (11.1)53 (12.9)0.02
       Polytrauma, n (%)22 (9.4)35 (8.5)
       Heart or respiratory failure, n (%)63 (26.8)102 (24.8)
       Sepsis/Septic shock/Multi Organ Failure (MOF), n (%)21 (8.9)61 (14.8)
       Ischemic or hemorrhagic stroke; aneurysmal subarachnoid hemorrhage, n (%)76 (32.3)140 (34.1)
       Other, n (%)27 (11.5)20 (4.9)
      ICU admission, n (%)115 (48.9)306 (74.3)<0.0001
      Lenght of stay, days, median (IQR)13.0 (5.0–20.0)15.0 (8.0–25.5)0.0003
      Overall mortality, n (%)61 (26.0)147 (35.7)0.01
      * χ-square test for categorical variables and the Kruskal-Wallis test for continuous variables.
      Table 2Trend of median of percentages (IQR) of microbial isolates and specimens from positive patients across semesters.
      Months
      Overall n = 17342015 Jan–June n = 3572015 July–Dec n = 3562016 Jan–June n = 4512016 July–Dec n = 2582017 Jan–May n = 312p
      χ-square test.
      Microorganism
      Acinetobacter baumannii, n (%)203 (11.7)83 (23.2)23 (6.5)38 (8.4)37 (14.3)22 (7.1)0.81
      Enterococcus faecium, n (%)15 (0.9)5 (1.4)0 (0.0)8 (1.8)0 (0.0)2 (0.6)
      Escherichia coli, n (%)150 (8.7)18 (5.0)35 (9.8)48 (10.6)9 (3.5)40 (12.8)
      Klebsiella pneumoniae, n (%)143 (8.2)11 (3.1)42 (11.8)59 (13.1)15 (5.8)16 (5.1)
      Proteus mirabilis, n (%)29 (1.7)4 (1.1)5 (1.4)4 (0.9)3 (1.2)13 (4.2)
      Pseudomonas aeruginosa, n (%)204 (11.8)37 (10.4)40 (11.2)38 (8.4)51 (19.8)38 (12.2)
      Staphylococcus aureus, n (%)196 (11.3)22 (6.2)59 (16.6)59 (13.1)30 (11.6)26 (8.3)
       Others794 (45.8)177 (49.6)152 (42.7)197 (43.7)113 (43.8)155 (49.7)
      Specimen
       Blood culture, n (%)702 (40.5)152 (42.6)141 (39.6)196 (43.5)99 (38.4)114 (36.7)0.05
       Rectal swab, n (%)149 (8.6)13 (3.6)29 (8.1)29 (6.4)30 (11.6)48 (15.4)
       Nasal swab, n (%)31 (1.8)7 (2.0)5 (1.4)6 (1.3)9 (3.5)4 (1.3)
       Tracheal aspirate, n (%)365 (21.1)68 (19.0)100 (28.1)89 (19.7)49 (19.0)59 (19.0)
       Broncho-alveolar lavage, n (%)69 (4.0)10 (2.8)5 (1.4)13 (2.9)24 (9.3)17 (5.5)
       Cerebro-spinal fluid (CSF), n (%)31 (1.8)11 (3.1)4 (1.1)2 (0.4)1 (0.4)13 (4.2)
       Culture of the intracranial device, n (%)12 (0.7)8 (2.2)3 (0.8)0 (0.0)0 (0.0)1 (0.3)
       Central catheter tip cultures, n (%)39 (2.3)8 (2.2)9 (2.5)11 (2.4)3 (1.2)8 (2.6)
       Urinary catheter tip cultures, n (%)100 (5.8)26 (7.3)25 (7.0)22 (4.9)12 (4.7)15 (4.8)
       Any intra cavity fluid (as pleural or peritoneal), n (%)55 (3.2)15 (4.2)7 (1.9)17 (3.7)6 (2.4)10 (3.2)
       Wound swab, n (%)114 (6.6)30 (8.4)11 (3.1)51 (11.3)11 (4.3)11 (3.5)
       Urine culture, n (%)64 (3.7)9 (2.5)17 (4.8)13 (2.9)14 (5.4)11 (3.5)
      * χ-square test.
      Table 3Numbers and percentages of patients with or without infection(s) across the study semesters.
      Months
      2015 Jan–June n = 762015 July–Dec n = 882016 Jan–June n = 852016 July–Dec n = 712017 Jan–May n = 79
      Patients without infection, n (%)48 (63.2)57 (64.8)52 (61.2)46 (64.8)49 (62.0)
      Septic shock/sepsis, n (%)7 (9.2)11 (12.5)5 (5.9)6 (8.5)4 (5.1)
      Pneumoniae, n (%)8 (10.5)7 (8.0)12 (14.1)5 (7.0)10 (12.7)
      Peritonitis, n (%)2 (2.6)1 (1.1)3 (3.5)1 (1.4)2 (2.5)
      Other infection, n (%)11 (14.5)12 (13.6)13 (15.3)13 (18.3)14 (17.7)
      Mortality rate, n (%)26 (34.2)32 (36.4)28 (32.9)31 (43.7)26 (32.9)
      To measure the microbiological impact of our bundle of interventions, we first focused on the variation of GNMDROs with high clinical impact, measuring the prevalence of resistant strains of Klebsiella pneumoniae, Pseudomonas aeruginosa, and Acinetobacter baumannii observed. As our collection methodology could not retrieve genotypic data on antimicrobial resistance, such strains were identified as those resistant to meropenem and imipenem at sensitivity tests. Resistance to meropenem, imipenem and piperacillin/tazobactam was analyzed separately, showing overlapping results. The major outcome of our investigation is reported in Table 4. The most striking results were obtained with Klebsiella pneumoniae, for which the incidence of carbapenem-resistant strains fell from 94% in the first semester in 2015 to 6% in 2017 (p < 0.001).
      Table 4Trend of median percentage (IQR) of resistance of microbial isolates across the 5 study semesters.
      Months
      2015 Jan–June2015 July–Dec2016 Jan–June2016 July-Dec2017 Jan–Mayp
      Kruskal-Wallis for trend test.
      Rate of resistantmicrorganismOverall
       Gram negative, %72991.0 (36.0–91.0)46.0 (12.0–91.0)46.0 (17.0–91.0)43.0 (17.0–83.0)13.0 (0.0–76.0)<0.0001
      K. pneumoniae, %14394.0 (12.0–94.0)93.5 (29.0–94.0)87.0 (12.0–94.0)56.0 (6.0–93.0)6.0 (6.0–6.0)<0.0001
      A. baumannii, %20391.0 (91.0–91.0)91.0 (90.0k92.0)91.0 (90.0–91.0)83.0 (83.0–91.0)83.0 (83.0–3.0)<0.0001
      P. aeruginosa, %20438.0 (36.0–54.0)46.0(36.0–58.0)46.0 (36.0–50.0)25.0 (6.0–36.0)27.5 (0.0–89.0)<0.0001
       Gram Positive, %60423.5 (7.0–43.0)19.0 (7.0–33.0)13.0 (6.0–31.0)20.0 (13.0–31.0)17.0 (6.0–36.0)0.05
      S. aureus, %1967.0 (6.0–19.0)7.0 (7.0–7.0)13.0 (6.0–20.0)6.0 (6.0–13.0)19.0 (6.0–19.0)0.54
       MRSA, %10938.0 (11.0–63.0)25.0 (11.0–50.0)11.0 (10.0–40.0)30.0 (11.0–50.0)30.0 (11.0–50.0)0.01
      Rate of antibioticresistance
       Meropenem, %86089.0 (27.0–89.0)32.0 (17.0–89.0)27.0 (17.0–89.0)27.0 (13.0–80.0)21.0 (7.0–31.0)<0.0001
       Imipenem, %91175.0 (30.0–88.0)40.0 (18.0–88.0)30.0 (23.0–88.0)31.0 (14.0–75.0)17.0 (0.0–50.0)<0.0001
       Piperacillina/tazobactam %86673.0 (25.0–90.0)33.0 (15.0–90.0)27.0 (20.0–89.0)25.0 (7.0–40.0)14.0 (0.0–27.0)<0.0001
      * Kruskal-Wallis for trend test.
      Significant drops were observed also for Pseudomonas aeruginosa and Acinetobacter baumannii (Table 4). The results of our additional analyses on percentages of resistance among all Gram-negative isolates (729 of 1734, 42%) confirmed the same trend, dropping from 91% of the first semester, 2015, to 13% in 2017 (p < 0.0001, Table 4). Our bundle of interventions was aimed to control selection and transmission of GNMDROs in the ICU. To assess whether the observed variations might be due to factors other than our interventions, we measured the variation of resistance in parallel Gram-positive isolates. The incidence of MRSA, MSSA and MRCoNS isolates was not significantly different across the study period (Table 4).
      The prescriptions of antibiotics, as well as the expenditure for each class of antibiotics could be tracked in detail for the first 4 semesters in the study period; they are shown in Table 5. Interestingly, prescriptions of carbapenems, quinolones and colistin, measured in DDD/patient, sharply dropped across the 4 semesters. On the other hand, the average global per patient expenditure for antibiotics in the second semester, 2016, was reduced to approximately one third of that in the first semester, 2015 (€367.54 vs €1041.40, respectively).
      Table 5Variations in antibiotic prescription and related costs, split for the antibiotic classes in use, across the two years (four semesters) traceable in the study period. Antibiotic prescriptions are reported in DDD (Defined Daily Dose) per patient; costs are reported for Euros per patient.
      Anatomical Therapeutic Chemical Classification System (ATC)DDD/patient€/patient
      2015 Jan–June n = 762015 July–Dec n = 882016 Jan–June n = 852016 July–Dec n = 712015 Jan–June n = 762015 July–Dec n = 882016 Jan–June n = 852016 July–Dec n = 71
      J01AA Tetracyclines2.471.253.441.13267.32135.13371.40121.80
      J01CA Penicillins, Extended-Spectrum0.000.000.000.040.000.000.060.36
      J01CE Beta-lactamase sensitive penicillins7.205.550.000.0160.6050.610.000.27
      J01CR Combinations of penicillins, including beta-lactamase inhibitors0.000.007.4415.170.000.0056.8442.40
      J01DB First generation cephalosporins list2.111.400.821.485.473.632.124.42
      J01DD Third-generation cephalosporins0.140.201.141.020.470.573.701.77
      J01DE Fourth-generation cephalosporins0.000.000.000.700.000.000.0010.85
      J01DH Carbapenems6.214.952.542.18133.59101.0848.0231.75
      J01EE Combinations of sulfonamides and trimethoprim, including derivatives0.260.150.710.002.261.175.750.00
      J01FA Macrolide antibiotics2.010.321.060.0021.284.789.840.00
      J01GB Other aminoglycosides0.620.291.350.380.950.281.310.37
      J01MA Fluoroquinolones8.993.881.590.2321.6311.813.344.41
      J01XA Glycopeptide antibacterials4.734.802.182.25166.14189.6686.1278.90
      J01XB Polymyxins6.363.381.790.7071.8339.0120.838.14
      J01XD Imidazole derivatives0.820.571.240.820.770.561.161.13
      J01XX Other antibacterials2.952.391.580.49288.27252.61179.5460.08
      Overall45.3729.1226.8826.941041.40790.91790.04367.54
      All multivariate models confirmed that the semester of hospitalization was the most relevant and significant independent predictor of resistance in Gram-negative isolates, whatever the measure of resistance chosen, among age, CCI, length-of-stay, diagnosis at entrance, and provenience. To increase the robustness of the final multivariate models, we chose percentages of resistance in all Gram-negative isolates. The relative risk for antibiotic resistance in Gram-negative isolates dropped more than three-fold in the 1st semester, 2017, relative to the first (3.18, CI 1.87–5.40) and second semester (3.01, CI 1.80–5.05) in 2015 (Figure 3). Patients hospitalized in the ICU due to polytrauma were at higher risk of resistance and females were protected relative to males (Figure 3).
      Figure 3
      Figure 3Forrest Plot for prediction of Antibiotic Resistance among Gram Negative bacteria.
      Finally, we explored the possibility that the variations measured in the incidence of GNMDROs might significantly impact both on length of stay in the ICU and on all-cause mortality. Subgroup analyses failed to reveal a clear-cut association for both variants, mainly because of lack of statistical power due to small sample sizes (data not shown). For this reason, we had to limit our investigation to evaluate the hypothesis that the isolation of bacterial strains with any level of resistance might predict longer ICU stays and a higher mortality burden. Among multivariate models for independent predictors of length-of-stay, the model including all patients revealed a 30% increase in the length-of-stay among patients with isolates with any resistance in comparison with patients with isolates without resistance or no isolate (1.30, CI 1.05–1.61, Figure 4A). On the other hand, multivariate models including all patients with Gram-negative isolates revealed a near-significant association between reporting an isolate with any percentage of resistance and increased mortality (2.28, CI 0.82–6.89, Figure 4B).
      Figure 4
      Figure 4Forrest plot for predictors of length of stay (a) and overall mortality among patients with gram negative bacterial isolates (b).
      To highlight the impact of our intervention in reducing resistant strains and the entity of resistance in bacterial isolates, we depicted the frequency of the isolates as they spread across predefined resistance percentage intervals, comparing the first (upper row) and last (bottom row) semester in Figure 5. The drop in highly resistant strains and the parallel rise in isolates without any resistance is obvious under this kind of graphic representation.
      Figure 5
      Figure 5Proportion of microbial isolates into the 10 decimal, consecutive classes of percentage of antimicrobial resistance in antibiograms, as distributed in:
      (a) The first semester in 2015 (beginning of the intervention).
      (b) The first semester in 2017 (last semester in the intervention period).
      Note the sharp fall in high (80–90%) percentages of resistance in the final semester, as well as the relevant rise in the proportion of isolates with low (0–10%) percentages of resistance.

      Discussion

      Prevalence of GNMDROs is on the rise in industrialized countries (
      • Bassetti M.
      • Poulakou G.
      • Timsit J.F.
      Focus on antimicrobial use in the era of increasing antimicrobial resistance in ICU.
      ,
      • Martin-Loeches I.
      • Torres A.
      • Rinaudo M.
      • Terraneo S.
      • de Rosa F.
      • Ramirez P.
      • et al.
      Resistance patterns and outcomes in intensive care unit (ICU)—acquired pneumonia. Validation of European Centre for Disease Prevention and Control (ECDC) and the Centers for Disease Control and Prevention (CDC) classification of multidrug resistant organisms.
      ,
      • Orsi G.B.
      • Giuliano S.
      • Franchi C.
      • Ciorba V.
      • Protano C.
      • Giordano A.
      • et al.
      Changed epidemiology of ICU acquired bloodstream infections over 12 years in an Italian teaching hospital.
      ). This phenomenon is a major concern for clinicians and other health care stakeholders due to the increasing burden of disease and mortality associated with GNMDROs (
      • Ho J.
      • Tambyah P.A.
      • Paterson D.L.
      Multiresistant Gram-negative infections: a global perspective.
      ,
      • Lambert M.L.
      • Suetens C.
      • Savey A.
      • Palomar M.
      • Hiesmayr M.
      • Morales I.
      • et al.
      Clinical outcomes of health-care-associated infections and antimicrobial resistance in patients admitted to European intensive-care units: a cohort study.
      ). As reported in a recent review, antimicrobial resistance in the next 30 years might cause more than 10 million deaths worldwide, unless effective strategies of control are defined (
      • Meyer E.
      • Schwab F.
      • Schroeren-Boersch B.
      • Gastmeier P.
      Dramatic increase of third-generation cephalosporin-resistant E. coli in German intensive care units: secular trends in antibiotic drug use and bacterial resistance, 2001 to 2008.
      ). Reducing the prevalence of GNMDROs is nowadays a mandatory task in ICUs, as well as in most clinical settings (
      • Lambert M.L.
      • Suetens C.
      • Savey A.
      • Palomar M.
      • Hiesmayr M.
      • Morales I.
      • et al.
      Clinical outcomes of health-care-associated infections and antimicrobial resistance in patients admitted to European intensive-care units: a cohort study.
      ). A recent meta-analysis provided interesting evidence that this may be an accomplishable task, provided that a bundle of interventions, including antimicrobial stewardship, is applied (
      • Teerawattanapong N.
      • Kengkla K.
      • Dilokthornsakul P.
      • Saokaew S.
      • Apisarnthanarak A.
      • Chaiyakunapruk N.
      Prevention and control of multidrug-resistant Gram-negative bacteria in adult intensive care units: a systematic review and network meta-analysis.
      ). Bundles including 4 interventions performed better than those including 2 or 3 interventions (
      • Teerawattanapong N.
      • Kengkla K.
      • Dilokthornsakul P.
      • Saokaew S.
      • Apisarnthanarak A.
      • Chaiyakunapruk N.
      Prevention and control of multidrug-resistant Gram-negative bacteria in adult intensive care units: a systematic review and network meta-analysis.
      ). This suggests that control of GNMDROs is possible, but clinicians have to combine multiple efforts. First is reduction of collateral selection of resistance induced by antibiotic prescription (
      • Zilahi G.
      • McMahon M.A.
      • Povoa P.
      • Martin-Loeches I.
      Duration of antibiotic therapy in the intensive care unit.
      ). Even the concept of antibiotic treatment course has been recently challenged in this view (
      • Kollef M.H.
      • Bassetti M.
      • Francois B.
      • Burnham J.
      • Dimopoulos G.
      • Garnacho-Montero J.
      • et al.
      The intensive care medicine research agenda on multidrug-resistant bacteria, antibiotics, and stewardship.
      ), in favor of individualized, shorter and targeted antibiotic treatments associated with proper control of the infection source (
      • Taccone F.S.
      • Bond O.
      • Cavicchi F.Z.
      • Hites M.
      Individualized antibiotic strategies.
      ). In this view, strict control of preventable sources of infection (i.e. catheter-related bloodstream infections and Ventilator-associated Pneumonias) is a mandatory adjunct (
      • O’Grady N.P.
      • Alexander M.
      • Dellinger E.P.
      • Gerberding J.L.
      • Heard S.O.
      • Maki D.G.
      • et al.
      Guidelines for the prevention of intravascular catheter-related infections.
      ), together with prevention of in-ward horizontal transmission of GNMDROs (
      • Bassetti M.
      • Giacobbe D.R.
      • Giamarellou H.
      • Viscoli C.
      • Daikos G.L.
      • Dimopoulos G.
      • et al.
      Management of KPC-producing Klebsiella pneumoniae infections.
      ).
      Crucial to the reduction of undue selective antibiotic pressure, however, is the need of proper microbiological support (
      • Garnacho-Montero J.
      • Dimopoulos G.
      • Poulakou G.
      • Akova M.
      • Cisneros J.M.
      • De Waele J.
      • et al.
      Task force on management and prevention of Acinetobacter baumannii infections in the ICU.
      ,
      • Khan R.
      • Al-Dorzi H.M.
      • Al-Attas K.
      • Ahmed F.W.
      • Marini A.M.
      • Mundekkadan S.
      • et al.
      The impact of implementing multifaceted interventions on the prevention of ventilator-associated pneumonia.
      ). Ideally, even in critically ill patients, targeted antibiotic treatments would reduce undue antibiotic exposure (
      • Luyt C.E.
      • Brechot N.
      • Trouillet J.L.
      • Chastre J.
      Antibiotic stewardship in the intensive care unit.
      ). In line with this approach, it has been recently demonstrated that treating critically ill patients without hemodynamic instability after microbiological documentation of infection does not reduce the efficacy of antibiotics (
      • Hranjec T.
      • Rosenberger L.H.
      • Swenson B.
      • Metzger R.
      • Flohr T.R.
      • Politano A.D.
      • et al.
      Aggressive versus conservative initiation of antimicrobial treatment in critically ill surgical patients with suspected intensive-care-unit-acquired infection: a quasi-experimental, before and after observational cohort study.
      ). In this ideal scenario, empirical treatment of infections could be reduced to a minimum (
      • Luyt C.E.
      • Brechot N.
      • Trouillet J.L.
      • Chastre J.
      Antibiotic stewardship in the intensive care unit.
      ), with an expected parallel reduction in mortality attributable to GNMDROs (
      • Terpenning M.S.
      • Bradley S.F.
      • Wan J.Y.
      • Chenoweth C.E.
      • Jorgensen K.A.
      • Kauffman C.A.
      Colonization and infection with antibiotic-resistant bacteria in a long-term care facility.
      ).
      With all this in mind, early in 2015 we started a complex ICU Antimicrobial Stewardship project, putting a single ICU clinician in charge of supervising prescription of antibiotics and protocols of antimicrobial prophylaxis, in collaboration with a single reference infectivologist. This move substantially impacted on antibiotic prescription in our ICU early in 2015, and was likely related to the first drop in GNMRDOs observed. Late in the same year, financial support allowed upgrading our Microbiology Unit to 24 h activity. This started early in 2016, allowing microbiological information as early as 24–36 h after sampling, with immediate communication to ICU clinicians.
      Our complex interventional program yielded significant results in terms of resistance reduction within a relatively short period of time, which is one of the major open questions in the field of infection control programs in ICU, as a remarkable decrease in resistance in GNMDROs was measured after a few months. Interestingly, this reduction in isolation of GNMDROs was neither related to a casual trend in reduction of infections in patients enrolled in the 5 semesters, nor to a reduction of incidence of bacterial isolates from species at higher risk of multi-drug resistance, as both infections and isolates remained even and stable across the study period. Our experience lands support to the idea that similar programs, centered on empowerment of in-ward based antimicrobial stewardship and round-the-clock microbiological support, may be reproducible, both in ICU and in other settings devoted to septic patients.
      The number of MRSA isolates was unchanged, as was the number of other staphylococcal strains. Little was done for tracking MRSA and MRCoNS in patients and personnel. Nasal swabs were introduced in 2015 upon admission in the ICU and the Hematology Department, but no other procedure for systematic search, isolation and treatment of Staphylococci was undertaken (
      • Kohlenberg A.
      • Schwab F.
      • Behnke M.
      • Gastmeier P.
      Screening and control of methicillin-resistant Staphylococcus aureus in 186 intensive care units: different situations and individual solutions.
      ).
      Our interventional bundle, based on increased microbiological efficiency, obviously increased our yearly expenditures for the enlarged microbiology team. This was partly compensated, however, by the well documented parallel reduction in ICU antibiotic expenditure, as shown by our analyses. In particular, the most relevant reductions in prescription and expenses were demonstrated for those classes of antibiotics most blamed for the rapid and persistent selection of GNMDROs in patients’ microbiotas, that is quinolones and carbapenems, providing further evidence to the idea that systemic curbing of undue prescription of such antibiotic classes may represent a major path to quickly reduce emergence of GNMDROs in ICU patients, without any negative impact on in-ward mortality (
      • Bassetti M.
      • Poulakou G.
      • Timsit J.F.
      Focus on antimicrobial use in the era of increasing antimicrobial resistance in ICU.
      ,
      • Khan R.
      • Al-Dorzi H.M.
      • Al-Attas K.
      • Ahmed F.W.
      • Marini A.M.
      • Mundekkadan S.
      • et al.
      The impact of implementing multifaceted interventions on the prevention of ventilator-associated pneumonia.
      ). Further estimates of cost effectiveness, including the reduction in direct and indirect costs due to GNMDRO infections, are warranted in the near future (
      • Zilberberg M.D.
      • Shorr A.F.
      Economic aspects of preventing health care-associated infections in the intensive care unit.
      ).
      Our experimental design has several limitations. We concentrated our efforts in a single 9-bed ICU in a single Italian Institution, with high prevalence of GNMDROs in recent years (
      • Orsi G.B.
      • Giuliano S.
      • Franchi C.
      • Ciorba V.
      • Protano C.
      • Giordano A.
      • et al.
      Changed epidemiology of ICU acquired bloodstream infections over 12 years in an Italian teaching hospital.
      ,
      • Frattari A.
      • Polilli E.
      • Primiterra V.
      • Savini V.
      • Ursini T.
      • Di Iorio G.
      • Parruti G.
      Analysis of peripheral blood lymphocyte subsets in critical patients at ICU admission: a preliminary investigation of their role in the prediction of sepsis during ICU stay.
      ); our intervention was prospective, but measurements of the impact of our approach were retrospective, on a relatively short time span and on a relatively small number of patients. The methodology used to quantify the prevalence of resistance, although very sensitive to subtle variations in the incidence of antibiotic resistance, may well have its limitations. Our retrospective data collection system allowed us to monitor resistance in bacterial isolates, as well as rates of patients with and without infection across the study period, but we could not directly quantify infections caused by GNMDROs. This might partly explain why the significant reduction in GNMDROs did not translate into a significant decrease in the overall mortality in our sample (
      • Terpenning M.S.
      • Bradley S.F.
      • Wan J.Y.
      • Chenoweth C.E.
      • Jorgensen K.A.
      • Kauffman C.A.
      Colonization and infection with antibiotic-resistant bacteria in a long-term care facility.
      ), in spite of a suggestive trend in multivariate models for mortality. Our experimental design will be transformed into a prospective methodology for ongoing, real-time control of GNMDROs and infections in the ICU, to overcome this present limitation.
      Nonetheless, the relatively close environment of our multifaceted intervention might have represented an ideal setting for a proof-of-concept study, aimed to demonstrate that changing both the control and the organization of antibiotic prescription, curbing undue prescription of quinolones and carbapenems, as well as intensifying microbiological support to antibiotic prescription may yield encouraging and remarkable results in ICU patients.

      Conflict of interest

      All authors report no conflicts of interest relevant to this article.

      Funding source

      The present investigation was an independent, Institutional endeavor, performed without any financial or operative additional support. None of the authors, apart from GL (statistician), received any bursary or financial compensation for the present work from any commercial or Institutional source.

      Ethical approval

      Because data managed by the automated system of collection were encrypted and anonymous, neither Ethical Committee approval nor informed consent was required for this study.

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