DÄ internationalArchive50/2017Surveillance of Antibiotic Use and Resistance in Intensive Care Units (SARI)

Original article

Surveillance of Antibiotic Use and Resistance in Intensive Care Units (SARI)

A 15-Year Cohort Study

Dtsch Arztebl Int 2017; 114: 858-65. DOI: 10.3238/arztebl.2017.0858

Remschmidt, C; Schneider, S; Meyer, E; Schroeren-Boersch, B; Gastmeier, P; Schwab, F

Background: The project entitled Surveillance of Antibiotic Use and Resistance in Intensive Care Units (SARI) was initiated in Germany in 2000. In this article, we describe developments in antibiotic use and resistance rates in the participating intensive care units over the years 2001–2015.

Methods: The intensive care units supplied monthly figures on patient days, antibiotic use (in defined daily doses, DDD), and resistance data for 13 pathogens. The density of antibiotic use per 1000 patient days was calculated on the basis of antibiotic use, DDD, and patient days, and the resistance density per 1000 patient days was calculated from the number of resistant pathogens.

Results: In the years 2001–2015, data on 2 920 068 patient days were collected in 77 intensive care units. The average overall antibiotic use rose by 19% over this period, with a marked increase in the density of carbapenem use (from 76 to 250 DDD per 1000 patient days, +230%) and piperacillin-tazobactam use (from 42 to 146 DDD per 1000 patient days, +247%). The proportion of Escherichia coli and Klebsiella pneumoniae isolates that were resistant to third-generation cephalosporins increased markedly initially, then remained stable over the remainder of the observation period. The proportion of methicillin-resistant Staphylococcus aureus was stable over the entire period. The rates of vancomycin resistance among Enterococcus faecium isolates and imipenem resistance among gram-negative pathogens increased from 2.3% to 13.3% and from 0.1% to 0.3%, respectively.

Conclusion: The resistance density of gram-negative multiresistant pathogens in the participating intensive care units increased markedly. The rise in imipenem-resistant pathogens arouses particular concern. The increased use of broad-spectrum/reserve antibiotics may well have contributed to this development. Efforts to use antibiotics rationally, e.g., with the support of multidisciplinary “antibiotic stewardship” teams, are therefore vitally important. As participation in SARI is voluntary, these surveillance data cannot be considered representative of Germany as a whole.

LNSLNS

Worldwide, the consumption of antibiotics has increased substantially in the past decades (1). Increased use of antibiotics promotes—in addition to other factors (2)—the selection and spread of antibiotic-resistant or multiresistant pathogens, with the result that the treatment of infections caused by these pathogens becomes more difficult (3). The problem is concentrated in intensive care units (ICUs) (4), where often multimorbid patients generally present with a higher risk for nosocomial infections (5) and infections with multiresistant pathogens can lead to additional complications, prolonged hospital stays, and higher healthcare costs (69).

In February 2000 the project for the surveillance of antibiotic use and resistance in intensive care units (SARI) in Germany was initiated for the purpose of benchmarking (10, 11). After a one-year pilot phase, SARI has continuously captured antibiotic use densities and resistance data for selected pathogens on ICUs in Germany.

This article aims to describe the development of antibiotic resistance and changes in resistance rates in the past 15 years in this cohort of ICUs in Germany.

Methods

Participation in SARI is voluntary. The methods are explained in greater detail in the eMethods section and have already been described elsewhere (1012) (http://sari.eu-burden.info/down/protokoll.pdf). In sum, participating ICUs report on a monthly basis the number of patient days, use (in g) of all orally or parenterally administered antibiotics, and resistance rates of the following pathogens:

  • Staphylococcus (S.) aureus
  • Streptococcus pneumoniae
  • Coagulase-negative staphylococci (CNS)
  • Enterococcus faecalis
  • Enterococcus faecium
  • Escherichia (E.) coli
  • Klebsiella (K.) pneumoniae
  • Enterobacter cloacae
  • Serratia marcescens
  • Citrobacter spp.
  • Pseudomonas aeruginosa
  • Stenotrophomonas maltophilia
  • Acinetobacter (A.) baumannii.

Resistance testing can be performed according to German industry standard (DIN) 58940, the CLSI (Clinical & Laboratory Standards Institute), or EUCAST (European Committee on Antimicrobial Susceptibility Testing). Copy strains—that is, isolates detected within 30 days from a patient with an identical antibiogram—were not included in the analysis. The frequency of taking specimens from patients is the prerogative of the clinician in the respective ICU; tests performed exclusively for the purpose of screening were not considered. We did not collect data on the total number specimens sampled, the location of the specimen sampling, nor on whether an infection or colonization was present or whether the pathogen was acquired in an outpatient or inpatient setting.

From the antibiotics use, the defined daily doses (DDD), and the patient days, the antibiotic use density was calculated as follows: (antibiotic use in g/DDD in g) × 1000 patient days. The resistance rate of a pathogen is calculated from the number of resistant isolates of a species against a specific antibiotic, divided by the number of all pathogens tested against this antibiotic × 100. The antibiotic resistance density results from the number of resistant pathogens/1000 patient days.

Statistical analysis

Pooled mean values, medians, and interquartile ranges (25th and 75th percentile) of antibiotic use density, resistance rates, and antibiotic resistance density were calculated from the reported data for the period 2001–2015. Since not all ICUs participated in SARI for the entire duration of the study, a sensitivity analysis was used to calculate the antibiotic use density, resistance rates, and resistance density for only those ICUs that had reported data continuously from 2001 to 2015 (core cohort). At the time points 2001 and 2015, the results of the core cohort were compared with those of the total cohort, in order to identify possible differences in trends in antibiotic use and resistance rates. We used the Wilcoxon test to calculate for both cohorts on the basis of the inpatient ward whether the use of antibiotics and the resistance rates of the analyzed pathogens changed between 2001 and 2015. We used SAS 9.4 (SAS Institute, Cary, NC, USA) to evaluate the data.

Results

In 2001–2015 data were collected in 44 hospitals in 13 federal states on 77 ICUs with a total of 2 920 068 patient days (eTable 1). The median size of the hospitals was 572 (interquartile range 411–1008) beds, and the median size of the ICUs was 12 (1016) beds. 45% of ICUs were managed in an interdisciplinary way, 25% specalized in internal medicine, and 30% were surgical.

eTable 1

Antibiotic use

The total consumption of antibiotics over the study period increased by 19%, from 1180 DDD/1000 patient days to 1407 DDD/1000 patient days in 2015 (Figure 1, Table 1). The antibiotic use density, however, varied between ICUs: for example, the median in 2015 was 1330 DDD/1000 patient days and the interquartile range 1145–1605 DDD/1000 patient days. The five groups of antibiotics used most often in 2015 were penicillins with β-lactamase inhibitors (262 DDD/1000 patient days), carbapenems (250 DDD/1000 patient days), fluoroquinolones (157 DDD/1000 patient days), macrolides (104 DDD/1000 patient days), and third-generation cephalosporins (91 DDD/1000 patient days), which accounted for 61% of the total use.

Figure 1

Among the classes of antibiotics, the use of carbapenems increased most, from 76 DDD/1000 patient days in 2001 to 250 DDD/1000 patient days in 2015 +230%) (Table 1 and eTable 2). This increase is mainly accounted for by the use of meropenem (+638%). Increases were also noted in the use of penicillins with β-lactamase inhibitors (+28%), glycopeptides (+48%), macrolides (+36%), and other antibiotics (+928%). The notable increase in the use of other antibiotics is mainly due to linezolid, tigecycline, and daptomycin—substances that were not, or had only just become, available in 2001. In the group of penicillins with β-lactamase inhibitors, the greatest increase was seen for piperacillin/tazobactam (+247%). Over the observation period, the use of first and second generation cephalosporins decreased (−29%), as did that of aminoglycosides (−75%) and imidazoles (−40%) (Figure 1, Table 1, and eTable 2).

eTable 2

Antibiotic resistance

In the period from 2001 through 2015, a total of 263 639 isolates were tested (138 686 gram-positive and 124 953 gram-negative), which corresponds to a copy-strain adjusted isolation rate of 90 isolates per 1000 patient days for the 13 pathogens. From 2001 through 2010, almost 60% of laboratories used the DIN 58940 and 40% the CSLI standard (eTable 3) every year. From 2010 onwards, the first laboratories switched to the EUCAST standard. In 2013, 40% used DIN 58940, 39% used the CLSI standard, and 21% the EUCAST standard.

eTable 3

Since 2001 the number of isolates increased by 22%, with the greatest increase observed in E. coli (+87%), Enterococcus species (+65%), and K. pneumoniae (+63%), whereas the greatest decrease was observed among A. baumannii isolates (–72%). The decrease in A. baumannii isolates was constant over the entire study period, but this effect may have been affected by additional species differentiation that was introduced by some laboratories from 2012 onwards (see eMethods section).

The most commonly identified gram-positive pathogens were S. aureus (n = 54 320), Enterococcus faecalis (n = 26 578), and Enterococcus faecium (n = 17 813); the most common gram-negative pathogens were E. coli (n = 44 809), Pseudomonas aeruginosa (n = 27 216), and K. pneumoniae (n = 17 529). Trends in selected resistance patterns for four gram-positive and five gram-negative pathogens are shown in Table 2 and eTable 4.

eTable 4

Gram-positive pathogens

According to SARI, the proportion of methicillin-resistant S. aureus (MRSA) has stabilized in recent years (eTable 4). However, in 2015, almost 23% of all S. aureus strains were still resistant to oxacillin (Table 2). Of note is the increase in vancomycin-resistant E. faecium (VRE) isolates. In 2001, only individual VRE-isolates were confirmed, whereas in 2015 more than 75% of all ICUs participating in SARI were affected; the resistance rate was 13.3%, which translates into a resistance density of 1.1 VRE/1000 patient days (Table 2 and eTable 4, Figure 2). A new observation among this pathogen was an increase in linezolid-resistant isolates, to 1.6% (n = 28/1776 isolates) in 2015 (eTable 4).

Figure 2

Gram-negative pathogens

Between 2001 and 2011, the proportion of E. coli and K. pneumoniae isolates with resistance to third-generation cephalosporins increased notably (eFigure). Since then the resistance rate has stabilized, and in 2015 it was 16.3% and 15.7%, respectively (Table 2). Resistance rates to ciprofloxacin in these two pathogens increased over the entire study period from 8.3% to 26% (E. coli) and from 5.1% to 15.9% (K. pneumoniae) (eTable 4). In recent years, the proportion of imipenem-resistant K. pneumoniae isolates has also risen. At the start of the study period, such isolates were seen only in individual cases. In 2015, by contrast, they were confirmed in more than 25% of all participating ICUs. The resistance rate was 1.6% (eFigure, Table 2).

The increase in A. baumannii isolates with resistance to imipenem was particularly pronounced. The resistance rate has more than doubled over recent years and was 43% in 2015 (eFigure, Table 2).

Resistance density

Even though the resistance density is considered a measure for the actual resistance burden, the resistance density for MRSA was stable from 2001 to 2015, whereas it notably increased in VRE (from 0.1/1000 patient days to 1.1/1000 patient days) and imipenem-resistant A. baumannii (from 0.03/1000 patient days to 0.3/1000 patient days) (Table 2, Figure 3). Since 2001 the resistance density of multiresistant gram-negative pathogens has altogether increased substantially and accounted for 54% of the resistance burden in the ICUs participating in SARI by 2015.

Figure 3

Discussion

Since the start of the SARI project more than 15 years ago, the use of antibiotics in intensive care units participating in SARI has risen by 19%. This rise is mainly due to the increased use since 2009 of piperacillin/tazobactam, carbapenems, and glycopeptides. Studies from France, Norway, and Switzerland similarly observed an increase in antibiotic use in intensive care units, especially of reserve antibiotics or broad-spectrum antibiotics (1315). Because of different study periods and possible differences in the study populations, a direct comparison of the results is feasible only to a limited degree.

Regarding the development of resistance in gram-positive pathogens, the increase of VRE in SARI ICUs is notable, and the incipient confirmations of linezolid-resistant E. faecium isolates further restrict therapeutic options (16). The development and selection of VRE can be explained primarily by the use of different antibiotics and the resultant selection pressure on the Enterococcus species that naturally occurs in the gastrointestinal tract (1719). In addition to vancomycin (19), ceftriaxone (20) and antibiotics with anaerobic activity—for example, metronidazole or piperacillin/tazobactam—seem to have an important role in the selection process (18, 21, 22). According to SARI, the rise in VRE started in 2007. Simultaneously, the use of glycopeptide antibiotics and piperacillin/tazobactam increased. By contrast, we did not identify an increase in the use of third-generation cephalosporins and imidazole derivatives in the study period. In terms of the spread of VRE in hospitals, however, other factors also have an important role. Because of their high environmental tenacity, VRE can survive for long periods on inanimate surfaces, which facilitates transmission between patients, especially if hygiene measures are not strictly adhered to (19, 23).

In addition to VRE, according to the European Centre for Disease Prevention and Control (ECDC), another cause for concern is the increase of multiresistant gram-negative pathogens in invasive infections (24). Europe-wide between 2011 and 2014, the mean proportion of VRE increased from 6.2% to 7.9%, whereas the proportion of E. coli and K. pneumoniae isolates with resistance to third-generation cephalosporins increased from 9.6% to 12% and from 23.6% to 28%, respectively. Furthermore, the proportion of imipenem-resistant K. pneumoniae isolates increased from 6% to 7.3% (24). Systematic reviews and meta-analyses indicate that the case fatality rate in infections with VRE (25), E. coli and K. pneumoniae with resistance to third-generation cephalosporins (26), and K. pneumoniae with resistance to imipenem (27) is significantly raised compared with infections with susceptible pathogens.

In SARI ICUs, resistant gram-negative pathogens have gained in importance. Except for P. aeruginosa, they were identified in individual cases only at the start of the study period. In the meantime, resistant gram-negative pathogens have become responsible for half of the resistance burden in SARI ICUs. The proportion of E. coli and K. pneumoniae isolates with resistance to third-generation cephalosporins in SARI ICUs has not risen further in the past 3–4 years after a notable increase between 2001 and 2011, but the resistance rate in both pathogens in 2015 was still high, above 15%. One explanation of this stagnation may be the fact that because of increasing resistance against third-generation cephalosporins, carbapenems had to be used increasingly in empiric and definitive antibiotic therapy (12). This facilitated the selection of imipenem-resistant K. pneumoniae and A. baumannii isolates that are difficult to treat and, in the worst case scenario, are associated with hospital outbreaks (2831). On SARI ICUs, imipenem-resistant A. baumannii isolates have been identified regularly since 2005, whereas imipenem-resistant E. coli isolates have hardly been identified at all, and K. pneumoniae isolates only since 2014. A look back, however, shows that the development of resistance of the same pathogens against third-generation cephalosporins started in a similar way 15 years ago, and in the meantime this has become an ongoing problem in Germany’s ICUs. The fact that the proportion of resistant Enterobactericeae seems to increase even in the general population (32) makes it clear that it is not enough to study resistance patterns only in hospitals.

Intervention options

The rising prevalence of multiresistant pathogens presents an enormous challenge to medical professionals. For this reason, the use of classes of antibiotics that can still be used to treat the relevant pathogens—for example, in empiric antibiotic therapy—is increasingly necessary. This is especially the case for the increasingly older and comorbid patients in ICUs (4, 33). In order to slow down the rise and spread of multiresistant pathogens in intensive care units, strict adherence to hygiene measures is required, as is rational use of antibiotics, for example, with the support of multidisciplinary “antibiotic stewardship” teams (3, 34, 35). Furthermore, surveillance of antibiotic consumption and antibiotic resistance according to § 23 paragraph 4 of the German Protection Against Infection Act (Infektionsschutzgesetz, IfSG) can contribute to optimizing the use of antibiotics and observing the further spread of multiresistant pathogens (36). Ultimately, a multidisciplinary and cross-sectoral approach (One Health concept) is needed to stop the spread of multiresistant pathogens in general; in additional to human and veterinary medicine, animal husbandry, agriculture, and the environment will have to be included in this concept (37).

Limitations

Because of the ecological study design, the results should be interpreted with caution, and the following limitations should be borne in mind:

  • Participation in SARI is voluntary. For this reason, it is not clear to which extent the results are generalizable to all of Germany’s ICUs. Because ICUs are largely heterogeneous in terms of patient populations, size, and hospitals’ different levels of medical care, we cannot assume that the results are representative for the whole of Germany. As the proportion of university hospitals and maximum care hospitals is very high in our sample, antibiotic use and resistance rates may have been overestimated.
  • Only 20 of the 77 ICUs provided data continuously over the entire study period. However, the sensitivity analysis (eTable 5) does not give any indication that antibiotic use and resistance rates in the total cohort and the core cohort developed materially differently.
  • Resistance testing was done by different laboratories and followed different standards (DIN 58940, CLSI, and EUCAST). These standards partly differ in terms of their threshold values for the categories “susceptible,” “intermediate,” or “resistant” (to a particular antibiotic). If laboratories swap CLSI for EUCAST, the resistance rate of some pathogens to certain antibiotics may rise (38). Furthermore, threshold values also changed over the study period within certain testing methods—for example, CLSI 2009–2011. This poses an additional obstacle to the interpretation of the resistance rate (3840). Even though in our data, the effect of such changes cannot be identified, an (additional) rise in resistance rates from 2011 onwards seems to be plausible.
  • As SARI did not collect data on the collection sites where pathogens were isolated, the proportions of infections and colonization cannot be calculated.
  • The DDD used to describe antibiotic use does not necessarily reflect the recommended daily dose (RDD) or the prescribed daily dose (PDD) in Germany. For this reason, antibiotic use may have been overestimated—for example, when the prescribed dose was higher than the defined daily dose in some β-lactam antibiotics—or underestimated—for example, when a reduced dose was given to patients with kidney failure.
eTable 5

In spite of these limitations, the present data can help to better assess trends in antibiotic consumption and resistance patterns in Germany’s ICUs and to develop measures to combat the development of resistance.

Acknowledgment

We thank all participants in the SARI project for their support.

Funding

The SARI project received funding from the German Federal Ministry of Education and Research (BMBF) until the end of 2006.

Conflict of interest statement

The authors declare that no conflict of interest exists.

Manuscript received on 20 January 2017, revised version accepted on
18 September 2017.

Translated from the original German by Birte Twisselmann, PhD.

Corresponding author
Dr. med. Cornelius Remschmidt

Institut für Hygiene und Umweltmedizin

Charité Universitätsmedizin Berlin

Hindenburgdamm 27

12203 Berlin, Germany

cornelius.remschmidt@charite.de

Supplementary material
For eReferences please refer to:
www.aerzteblatt-international.de/ref5017

eMethods, eFigure, eTables:
www.aerzteblatt-international.de/17m0858

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Institute of Hygiene and Environmental Medicine, Charité—Universitätsmedizin Berlin:
Dr. med. Remschmidt, Dr. med. Schneider, PD Dr. med. Meyer, Prof. Dr. med. Gastmeier,
Dr. rer. medic. Schwab
Institute for Environmental Health Sciences and Hospital Infection Control, Medical Center—University of Freiburg: Barbara Schroeren-Boersch
1. Van Boeckel TP, Gandra S, Ashok A, et al.: Global antibiotic consumption 2000 to 2010: an analysis of national pharmaceutical sales data. Lancet Infect Dis 2014; 14: 742–50 CrossRef
2. Holmes AH, Moore LS, Sundsfjord A, et al.: Understanding the mechanisms and drivers of antimicrobial resistance. Lancet 2016; 387: 176–87 CrossRef
3. Laxminarayan R, Duse A, Wattal C, et al.: Antibiotic resistance-the need for global solutions. Lancet Infect Dis 2013; 13: 1057–98 CrossRef
4. Sader HS, Farrell DJ, Flamm RK, Jones RN: Antimicrobial susceptibility of Gram-negative organisms isolated from patients hospitalized in intensive care units in United States and European hospitals (2009–2011). Diagn Microbiol Infect Dis 2014; 78: 443–8 CrossRef MEDLINE
5. Vincent JL, Rello J, Marshall J, et al.: International study of the prevalence and outcomes of infection in intensive care units. JAMA 2009; 302: 2323–9 CrossRef MEDLINE
6. Neidell MJ, Cohen B, Furuya Y, et al.: Costs of healthcare- and community-associated infections with antimicrobial-resistant versus antimicrobial-susceptible organisms. Clin Infect Dis 2012; 55: 807–15 CrossRef MEDLINE PubMed Central
7. Cheah AL, Spelman T, Liew D, et al.: Enterococcal bacteraemia: factors influencing mortality, length of stay and costs of hospitalization. Clin Microbiol Infect 2013; 19: E181–9 CrossRef MEDLINE
8. Shorr AF: Review of studies of the impact on Gram-negative bacterial resistance on outcomes in the intensive care unit. Crit Care Med 2009; 37: 1463–9 CrossRef MEDLINE
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