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The Dynamics of Enterococcus Transmission from Bacterial Reservoirs Commonly Encountered by Anesthesia Providers

Loftus, Randy W. MD*; Koff, Matthew D. MS, MD*; Brown, Jeremiah R. MS, PhD; Patel, Hetal M. BS*; Jensen, Jens T. MS*; Reddy, Sundara MD; Ruoff, Kathryn L. PhD§; Heard, Stephen O. MD; Yeager, Mark P. MD*; Dodds, Thomas M. MD*

doi: 10.1213/ANE.0000000000000123
Patient Safety: Research Report

BACKGROUND: Enterococci, the second leading cause of health care-associated infections, have evolved from commensal and harmless organisms to multidrug-resistant bacteria associated with a significant increase in patient morbidity and mortality. Prevention of ongoing spread of this organism within and between hospitals is important. In this study, we characterized Enterococcus transmission dynamics for bacterial reservoirs commonly encountered by anesthesia providers during the routine administration of general anesthesia.

METHODS: Enterococcus isolates previously obtained from bacterial reservoirs frequently encountered by anesthesiologists (patient nasopharynx and axilla, anesthesia provider hands, and the adjustable pressure-limiting valve and agent dial of the anesthesia machine) at 3 major academic medical centers were identified as possible intraoperative bacterial transmission events by class of pathogen, temporal association, and phenotypic analysis (analytical profile indexing). They were then subjected to antibiotic disk diffusion sensitivity for transmission event confirmation. Isolates involved in confirmed transmission events were further analyzed to characterize the frequency, mode, origin, location of transmission events, and antibiotic susceptibility of transmitted pathogens.

RESULTS: Three hundred eighty-nine anesthesia reservoir isolates were previously identified by gross morphology and simple rapid tests as Enterococcus. The combination of further analytical profile indexing analysis and temporal association implicated 43% (166/389) of those isolates in possible intraoperative bacterial transmission events. Approximately, 30% (49/166) of possible transmission events were confirmed by additional antibiotic disk diffusion analysis. Two phenotypes, E5 and E7, explained 80% (39/49) of confirmed transmission events. For both phenotypes, provider hands were a common reservoir of origin proximal to the transmission event (96% [72/75] hand origin for E7 and 89% [50/56] hand origin for E5) and site of transmission (94% [16/17] hand transmission location for E7 and 86% [19/22] hand transmission location for E5).

CONCLUSIONS: Anesthesia provider hand contamination is a common proximal source and transmission location for Enterococcus transmission events in the anesthesia work area. Future work should evaluate the impact of intraoperative hand hygiene improvement strategies on the dynamics of intraoperative Enterococcus transmission.

Published ahead of print June 17, 2014

From the *Department of Anesthesiology, Dartmouth-Hitchcock Medical Center; The Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire; Department of Anesthesiology, The University of Iowa Hospitals and Clinics, Iowa City, Iowa; §Department of Pathology, Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire; and Department of Anesthesiology, UMass Memorial Medical Center, Worcester, Massachusetts.

Accepted for publication December 20, 2013.

Published ahead of print June 17, 2014

Funding: Anesthesia Patient Safety Foundation.

The authors declare no conflicts of interest.

Reprints will not be available from the authors.

Address correspondence to Randy W. Loftus, MD, Department of Anesthesiology, Dartmouth-Hitchcock Medical Center, 1 Medical Center Dr., Lebanon, NH 03756. Address e-mail to randy.w.loftus@hitchcock.org.

Health care-associated infections (HCAIs) have remained persistent despite advances in surgical technique, disinfection and sterilization procedures, and a multitude of infection control measures.1–5 The persistent nature of HCAIs is connected to the evolution of bacterial resistance and to community health, because HCAIs, due to invasive, multidrug-resistant bacterial pathogens, are no longer confined to acute health care settings.2 It is therefore important to understand the epidemiology of bacterial transmission across all health care settings to generate sustained reductions in HCAIs.6–9 Staphylococci, Enterococci, and members of the family Enterobacteriaceae are classes of bacterial pathogens most commonly associated with HCAI development. In this study, we sought to characterize the potential role of the anesthesiologist in intraoperative spread of Enterococci by characterizing the dynamics of Enterococcus transmission involving bacterial reservoirs frequently encountered by anesthesiologists. Our primary aims were to examine the mode, frequency, probable sources, the location of bacterial transmission events, and antibiotic resistance patterns for the most prevalent Enterococcus phenotypes isolated from reservoirs routinely contacted by anesthesia providers. These reservoirs included patient skin sites strongly associated with surgical site infections (SSIs),10,11 anesthesia provider hands (transiently colonized by bacterial contaminants of other potential reservoirs and as such, a reasonable alternative to rectal swabs),12,13 and proven representatives of the anesthesia environment (adjustable pressure-limiting valve and agent dial).6,7,9 Our secondary aims were to examine whether Enterococcus isolates transmitted from these reservoirs could be linked by pulsed-field gel electrophoresis (PFGE) to 30-day postoperative patient cultures and to determine the incubation periods (growth rates) for these same Enterococcus phenotypes.

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METHODS

General Approach

We previously conducted a prospective, randomized, observational study at 3 major academic medical centers, Dartmouth-Hitchcock Medical Center in New Hampshire, the University of Iowa Hospitals and Clinics in Iowa, and the UMass Memorial Medical Center in Massachusetts to characterize the frequency and implications of bacterial transmission events to intravascular devices in the intraoperative arena.9 The study took place over 12 consecutive months (from March 2009 to February 2010). Approval was obtained at each study site from the respective IRB for the protection of human subjects with a waiver for informed patient consent. For the current study, additional approval was obtained from the Committee for Protection of Human Subjects at Dartmouth-Hitchcock Medical Center.

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Experimental Model for Study of Bacterial Cross Contamination

We examined 2170 environmental bacterial culture sites, 2640 health care provider hand cultures, and 1087 patient skin cultures in 274 case-pairs representing 548 operating rooms across the 3 major academic medical centers. The unit of randomization was the operating room environment accomplished via use of a computer-generated list. The first and second patients of the day in each operating room environment were selected for analysis (the study unit a case-pair), with the above reservoirs sampled in parallel (according to the sequence described in Fig. 1) during the routine administration of general anesthesia. Operating rooms were randomized in order that the study results reflect the usual process of general anesthesia across a wide variety of environments, providers, and operative procedures. The patient, provider, and procedural demographics for operating rooms observed have been reported.9 From these reservoirs, >6000 potential and 2184 true bacterial pathogens were isolated and archived for later analysis. Each pathogen received a unique identification number linked to a specific date, operating room, reservoir, patient, and provider.

Figure 1

Figure 1

The potential association of each pathogen with patient, provider and environmental characteristics, and patient bacterial cultures in those patients with 30-day postoperative infections was assessed. Basic demographic information collected and linked to each frozen pathogen included the hospital site, age, sex, case 1 or case 2, ASA physical status classification, Study on the Efficacy of Nosocomial Infection control (SENIC)14 score (an index predicting the probability of postoperative HCAI development for a given patient), case duration, patient comorbidities, patient origin, patient discharge location, and procedure type.9

We used a validated model for study of intraoperative bacterial cross contamination (Fig. 1) in this previous study. Bacterial reservoirs including anesthesia provider hands, patient skin sites strongly associated with SSIs10,11 and increased risk of Enterococcus transmission events,12,13 the adjustable pressure-limiting valve and agent dial of the anesthesia machine, and proven representatives of the anesthesia environment6,7,9 were selected for evaluation in order that the results represent reservoirs within the purview of anesthesia providers. We prospectively evaluated the relative contribution of these bacterial reservoirs to intraoperative bacterial transmission events to high-risk intravascular devices (stopcocks) and to the subsequent development of 30-day postoperative patient cultures, and in some cases, HCAIs. Our focus in the initial study was on bacterial organisms transmitted to intravascular devices, and we used the combination of class of organism, phenotype defined by a series of biochemical reactions (Analytical Profile Index [API]), and temporal association given the timed sequence of bacterial culture acquisition during the process of patient care in each operating room (Fig. 1) to identify epidemiologically related transmission events. PFGE was used to examine potential links between intraoperative transmission events and subsequent infection development.

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Systematic Evaluation of the Epidemiology of Transmission for Major Bacterial Pathogens

We have since conducted a systematic analysis of bacterial pathogens that are most likely to cause SSIs, including Staphylococcus aureus (methicillin-sensitive and methicillin-resistant), Enterococcus (vancomycin-resistant [VRE] and vancomycin-susceptible [VSE]), and gram negative pathogens to characterize the potential role of the anesthesiologist pertaining to intraoperative transmission of these important disease-causing organisms. Consistent with the framework established by the Centers for Disease Control and Prevention,15 we sought to characterize the overall mode, frequency, probable sources and the location of transmission events, and antibiotic resistance patterns for frequently transmitted Enterococci phenotypes as they pertain to bacterial reservoirs engaged by the anesthesia provider during routine practice. We also sought to examine the potential association with 30-day postoperative patient cultures and potential phenotypic differences in incubation period (growth rate) for these same organisms to ascertain whether anesthesiologists participate significantly in the intraoperative spread of Enterococcus pathogens later causing infection, and so that we could begin to understand the mechanisms for evasion of current disinfection practices, respectively. The sequence of this systematic analysis focused on Enterococci is shown in Figure 2.

Figure 2

Figure 2

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Microbiological Analysis

As the first step in this analysis, we had previously classified all major bacterial pathogens isolated from these reservoirs according to colony morphology, gram stain, and simple rapid tests. As such, we were able to identify and archive all Enterococcus isolates obtained from anesthesia reservoirs during the study period. In this study, we reviewed 274 case-pairs (548 cases) for evidence of possible Enterococcus transmission defined by the presence of an Enterococcus isolate in 2 or more reservoir sites across the case-pair. We then used a commercially available bioMerieux API identification system (Marcy 1’ Etoile, France) to identify phenotype. Each API-derived phenotype represents observable characteristics of bacterial organisms in uptake and use of elemental nutrients required for cell survival. Each API test comprised at least 20 different biochemical assays. The response of the organism tested to each assay yields a unique 7 digit number (biotype, API phenotype) that can be used for species identification via input into a large database and/or to compare bacterial strains. Isolates of the same class with an identical biotype are thought to be epidemiologically related. With identification of the class of organism and API phenotype, we then used temporal association (the same class of pathogen isolated in >1 site surveyed in the same operating room on the same day at the same time with the same biotype, Fig. 1) to identify possible transmission events occurring within and between operative cases. This initial methodology was previously validated.9 We added disk diffusion antibiotic susceptibility testing analysis (antibiotic susceptibility profiling-same response to methicillin and 15 commonly used prophylactic antibiotics, Appendix) to this model to provide further support for the identification of transmission events and the most proximal reservoir origin (provider, environment or patient) for these events. Because susceptibility to antibiotics is another observable characteristic intimately related to the bacterial genome, a similar API phenotype combined with diffusion antibiotic susceptibility analysis and an appropriate temporal exposure allowed us to identify with reasonable certainty intraoperative bacterial transmission events involving Enterococci between and within operative cases (mode of transmission) and to examine the most proximal origin and location of these transmission events. Bacterial sensitivity was recorded and subsequently analyzed as sensitive or resistant (intermediate resistance was considered resistant due to clinical relevance).16

This experimental model serves to examine reservoirs proximal to anesthesia providers during routine administration of general anesthesia, reservoirs that could be potentially addressed by improvements in aseptic practice, while also addressing more distal reservoirs, such as the patient rectum, when organisms from distal reservoirs are transmitted to proximal reservoirs contacted by the anesthesia provider. A positive rectal site for Enterococcus commonly occurs in conjunction with skin colonization (in patients with VRE bacteremia, 100% of study patients had rectal colonization and 86% skin colonization),12 and the antecubital fossa and blood pressure cuff, often in contact with the axilla, have been shown to be the best predictors of VRE transmission.13 Further, most patients with positive rectal swabs for VRE will test positive at other skin sites with the same organism.13 Thus, the patient skin sites cultured in this model not only serve to assess the dynamics of Enterococcus transmission in reservoirs pertinent to anesthesia providers but also effectively assess distal reservoirs for this organism.

Provider hand contamination was assumed to be the most proximal reservoir if the transmitted isolate was identical to an isolate from the hands of 1 or more anesthesia providers but not found in the examined patient skin sites or environmental reservoirs earlier in the sampling sequence. Environmental contamination was assumed to be the most proximal reservoir if the transmitted isolate was identical to an isolate from the environment sampled at baseline or at case end but not isolated either from the hands of providers or from the patient reservoirs earlier in the sampling sequence. The hands of all providers who would potentially interact with the anesthesia environment were sampled at baseline (Fig. 1). Patient skin contamination was assumed to be the most proximal reservoir if the transmitted isolate was identical to an isolate from the patient nasopharynx or axilla sampled at case start but was not isolated from provider hands or environmental reservoirs earlier in the sampling sequence.

Transmission events were then compared, by temporal association, biotype, and disk diffusion antibiotic susceptibility testing analysis, with all patient cultures obtained in the 30-day postoperative period. Probable patient bacterial culture links, defined by the same class of pathogen, the same biotype, the same response to commonly used prophylactic antibiotics, and an appropriate temporal exposure, were then confirmed with PFGE.17

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Evaluation of Bacterial Growth Rates

In addition, the 2 most prevalent Enterococci phenotypes encountered in the intraoperative anesthesia work area (E5 and E7, [Table 1]) were subjected to growth rate analysis under ideal growth conditions by using a previously reported technique (time to positivity).8

Table 1

Table 1

In order that the growth rates accounted for vancomycin resistance (each phenotype comprised vancomycin-sensitive and resistant isolates) and reservoir of origin, 10 VSE and 10 VRE isolates were randomly selected from the available pool of isolates for both E5 and E7 phenotypes. In addition, a negative control was prepared for each phenotype group. Thus, each experimental phenotype group comprised 11 samples for a total of 22 samples. Selected organisms were grown on blood agar plates for 24 hours at 36.5°C. A 0.5 McFarland standard dilution was then prepared for each organism and serially diluted to a final concentration of 50,000 colony forming units/mL. A BacT/Alert bottle containing aerobic culture media (BacT/Alert, Biomerieux Inc., Durham, NC) was then disinfected with an alcohol prep for 30 seconds and allowed to air dry. One mL 50,000 colony forming units/1.0 mL test concentration for each sample was then drawn up by using aseptic technique and injected into the aerobic culture media contained within the BacT/Alert bottle. All inoculated bottles were then placed into the BacT/Alert machine and incubated at 36.5°C for 5 days or until positive. The BacT/Alert incubator identified a positive bottle based on colorimetry; a color change in the media secondary to CO2 production from the growing bacteria was detected via spectroscopy occurring every 10 minutes. If the color change did not occur within 5 days, the bottle was determined to be negative. For positive samples, the time to positivity was recorded. For negative samples, the BacT/Alert bottle was removed from the incubator, and sterility was confirmed by aspirating 1 mL fluid by using standard, aseptic technique, spreading the solution onto standard blood agar plates and incubating for 72 hours at 36.5°C. Time to positivity in hours was then compared for each VSE phenotype.

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Statistical Analysis

In this study, we sought to examine transmission dynamics for Enterococcus isolates frequently encountered in reservoirs relevant to the routine administration of general anesthesia. Our primary aims were to examine the mode, frequency, probable sources, and the location of intraoperative bacterial transmission events and to examine antibiotic resistance patterns for the most prevalent Enterococci phenotypes isolated from patient skin sites (the nasopharynx and axilla), anesthesia provider hands (transiently colonized and a reasonable alternative to rectal swabs), and proven representatives of the anesthesia environment (the adjustable pressure-limiting valve and agent dial). Our secondary aims were to examine the phenotypic association of frequently transmitted pathogens with subsequent 30-day postoperative patient cultures and to examine the incubation periods for these same Enterococci phenotypes.

The relative contributions of the patient, environmental, and provider hand bacterial reservoirs to Enterococci transmission events (reservoir source and/or transmission location between and within operative cases) involving the 2 most prevalent Enterococci phenotypes were compared by using the χ2 or Fisher exact test where appropriate. For cell counts <5, Fisher exact test was used. As transmission dynamics were the primary outcome, fixed effects logistic regression analysis was used to adjust all transmission dynamic comparisons for ASA physical status and SENIC as ordinal variables and for hospital site, as these factors were previously associated with increased risk of 30-day postoperative infection.9 An α level of P < 0.05 was defined as statistically significant.

Differences in antibiotic resistance profiles for Enterococci phenotypes were compared by using the χ2 or Fisher exact test for categorical data. For cell counts <5, Fisher exact test was used. Phenotypic comparisons were reported as relative risk unless cell size was zero, in which case odds ratios were reported. We addressed multiple comparisons by defining P values of <0.003 as statistically significant (0.05/15). Fixed effects logistic regression analysis was then used to adjust significant differences for ASA physical status and SENIC as ordinal variables and for hospital site: factors previously associated with increased risk of 30-day postoperative infection.9 An α level of P < 0.05 after adjustment was defined as statistically significant.

Phenotypic contributions to 30-day postoperative patient cultures were compared by using Fisher exact test. To assess phenotypic differences in growth rates, Kaplan-Meier time to event analysis was conducted to evaluate the difference between phenotypes in time to critical growth threshold (that required for detection) after injection. We used the log-rank test for equality of time to critical threshold of contamination differences across the 2 phenotypes. An α level of P <0.05 was defined as statistically significant.

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RESULTS

A total of 389 bacterial isolates obtained from anesthesia reservoirs were previously identified as Enterococcus by gross morphology and simple rapid tests. In this study, API biotype analysis and temporal association implicated 43% (166/389) of these isolates in possible intraoperative bacterial transmission events.

As shown in Table 1, possible Enterococcus transmission events involved 13 different API biotypes. E faecalis (Biotype E5, N = 56) and E faecalis (Biotype E7, N = 75) explained 79% (131/166) of these events. Only 4% (7/161) of possibly transmitted Enterococci isolates were resistant to vancomycin and were all E faecium (VRE). As shown in Figure 3, 89% (149/166) of Enterococcus organisms implicated in probable transmission events were isolated from anesthesia provider hand reservoirs.

Figure 3

Figure 3

Thirty-six (60/166) percent, 20% (34/166), and 43% (72/166) isolates were obtained from sites 0, 1 and 2, respectively. There were no significant differences in the rates of Enterococcus transmission among sites (data not shown).

Approximately, 30% (49/166) of probable transmission events were further supported via the same class of pathogen, temporal association, identical biotypes, and additional antimicrobial susceptibility testing. As shown in Figure 4, residual contamination of provider hands was the reservoir of isolation for 86% (42/49) of organisms implicated in confirmed transmission events.

Figure 4

Figure 4

E faecalis phenotypes E5 and E7 explained 80% (39/49) of transmission events (Table 2) supported by antimicrobial susceptibility. Both phenotypes were transmitted similarly of the overall rate and mode (between or within case transmission) (Table 3). For both phenotypes, provider hands were a frequent proximal reservoir of origin (96% [72/75] for E7 and 89% [50/56] for E5). Similarly, provider hands were a frequent site of transmission for both phenotypes (94% [16/17] for E7 and 86% [19/22] for E5) (Table 3).

Table 2

Table 2

Table 3

Table 3

Phenotype E5 was more likely than phenotype E7 to be resistant to penicillin (relative risk 2.15, 1.54–3.00, P = 0.001), (Table 4).

Table 4

Table 4

Six of 548 patients (1%) had cultures positive for Enterococci in the 30-day postoperative period. There was no difference between those E7 and E5 phenotypes implicated in transmission events of the overall incidence of positive postoperative patient cultures. We were unable to demonstrate any PFGE links of patient cultures to intraoperative bacterial transmission events. There was no difference between phenotypes in inadequate prophylactic antibiotic coverage (Table 5). One patient was diagnosed with a confirmed HCAI due to E faecalis.

Table 5

Table 5

Finally, as shown in Figure 5, there was no difference in incubation periods for each of the frequently transmitted E. faecalis phenotypes under ideal, aerobic conditions.

Figure 5

Figure 5

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DISCUSSION

We have previously systematically evaluated the relative contributions of known intraoperative bacterial reservoirs to high-risk bacterial transmission events involving IV stopcock sets.9 We have extended this analysis by examining the dynamics of Enterococcus transmission from bacterial reservoirs frequently encountered by anesthesia providers.

Enterococci, bacterial organisms once thought to be of low virulence, harmless, and commensal, have evolved to the extent that they are now the second leading cause of hospital-acquired infections. In fact, they now explain up to 14% of hospital-acquired urinary tract infections, 11% of SSIs, and 7% of bloodstream infections.18 They are especially problematic for immunocompromised patients such as those undergoing renal, hepatic, and bone marrow transplantation accounting for up to 50% of cases of sepsis that ultimately lead to patient death.19–22

The evolution of this organism to its current state is thought to be derived from several mechanisms, including the development of multidrug resistance. While there are up to 14 different species of Enterococcus, only 2 are considered to be of significant clinical relevance, E faecalis and E faecium.23 E faecalis causes approximately 80% of hospital-acquired infections attributed to Enterococci, while E faecium explains most of the remainder. While the importance of E faecalis is highlighted due to its ability to cause infection, E faecium is also very important because it has expanded greatly in antibiotic resistance; the incidence of vancomycin-resistant E faecium isolates increased 20-fold from 1987 to 1993.24 Therefore, it is important that we gain a better understanding of E faecalis and E faecium transmission in all health care environments to attenuate the spread of this evolving pathogen.

Previous studies evaluating Enterococcus transmission have focused mainly on VRE in the intensive care unit setting and have shown that VRE commonly colonizes the skin (axilla, upper arm in the area of the blood pressure cuff, hands, and groin) of patients infected with the organism, that contamination of the axilla frequently correlates with positive rectal swabs in patients colonized with VRE, and that health care provider contact with patients infected or colonized with VRE leads to contamination of provider hands and/or the surrounding patient environment in up to 40% of cases after a single contact.12,13 In addition, previous work has described a case of intraoperative VRE transmission that ultimately led to postoperative bacteremia as confirmed by PFGE.6

In this study, we used a previously validated experimental model to examine the dynamics of VRE and VSE transmission from intraoperative bacterial reservoirs relevant to anesthesia providers in the anesthesia work area environment. Reservoirs including anesthesia provider hands, patient skin sites strongly correlated with SSIs, and the surrounding patient environment were assessed in parallel during the routine administration of general anesthesia under a wide variety of conditions consistent with the overall practice of general anesthesia.9 We found that most Enterococcus isolates obtained from these reservoirs were E faecalis, consistent with the epidemiology of hospital-wide enterococci isolates.24

We identified anesthesia provider hand contamination as a frequent proximal reservoir of origin and transmission location for possible and confirmed transmission events involving E faecalis phenotypes (E5 and E7) commonly isolated from anesthesia work area reservoirs. We found that between and within case modes of transmission for these phenotypes occurred at similar rates ranging from 11% to 23%. This rate of transmission is alarming, given issues pertaining to spread of major bacterial pathogens within and between operative cases, potentially to compromised hosts, and potential residual contamination of environmental surfaces in the surrounding patient environment given previous reports of bacterial resilience.13 While initial univariate analysis suggested that phenotype E5 was more likely to be transmitted than E7, adjustment for ASA physical status, site, and SENIC, factors previously associated with postoperative infection,9 revealed that hospital site was a major confounder. The reason for impact of hospital site on Enterococcus transmission remains unknown and warrants further study, but we hypothesize that it is related to variability in aseptic practice among institutions. The findings of this study showing that hand contamination of anesthesia providers is an important proximal reservoir and transmission location for Enterococcus in the anesthesia work area, combined with evidence as reported previously that intraoperative hand hygiene is in need of improvement,9 suggest that future work should evaluate the impact of hand hygiene improvement strategies on Enterococcus transmission in the intraoperative setting.

We were unable to show that patient skin contamination significantly increased the risk of Enterococcus transmission as compared with provider hands with or without adjustment for potentially confounding variables, and we were unable to identify a single case of between or within case Enterococcus transmission via the contaminated environment. These are different findings than that derived for the epidemiology of S aureus transmission, where patient and environmental reservoirs played a much larger role in transmission within and between cases.9,25

Phenotype E5 was more likely than phenotype E7 to be resistant to penicillin. As the acquisition of drug resistant traits has been shown to offer a survival advantage,18 we hypothesized that E5 might also have a growth advantage potentially facilitating its colonization and survival in the anesthesia work area environment. We tested this hypothesis by evaluating the growth rates (incubation periods) of randomly selected E5 and E7 phenotype isolates, with the random selection intended to normalize isolates across vancomycin resistance and isolation site. We found that there was no difference in growth rates between phenotypes under the experimental conditions that we tested. Thus, this finding supports the results of the logistic regression analysis demonstrating no difference between transmission rates between the frequently encountered E5 and E7 Enterococcus isolates.

We were unable to establish a link between intraoperative Enterococci transmission events and postoperative patient cultures. Given the limitations of the methodology used, these findings do not eliminate the possibility that transmission of Enterococcus from reservoirs encountered by anesthesiologists can lead to infection development. In fact, this has been shown before.6 However, the overall frequency at which this occurs is probably less than that of S aureus.25 Furthermore, frequent intraoperative transmission events involving Enterococcus, as demonstrated in this study, could, in theory, lead to patient colonization and ultimately result in infection early or late in the patient’s hospital course, especially if the transmission events involve a compromised host.

A limitation of this study is that it addresses the dynamics of Enterococcus transmission pertaining to the practice of anesthesiology but does not address overall intraoperative Enterococcus transmission. However, the focus of this study was to examine the dynamics of Enterococcus transmission from reservoirs frequently encountered by anesthesiologists to ascertain the “finger print” of the anesthesia provider in the spread of this organism. Our model not only accounted for these more proximal, relevant reservoirs to the practice of anesthesiology but also accounted for spread of Enterococcus to these sites from more distal reservoirs such as the rectum by including a reasonable surrogate for positive rectal samples, the axilla, a skin site commonly contaminated in conjunction with the rectum and a potent transmission site for Enterococcus.12,13 Finally, as we have discussed previously,9 transmission links in this study were identified by using a previously validated model combining standard microbiological techniques, temporal resolution, bacterial typing, and in this study, antibiotic sensitivity patterns. PFGE was used in cases for evaluation of potential links to patient cultures but not for transmission: the major outcome of the study. While PFGE has been shown to be more discriminating than biotype analysis alone, the benefit of this technique has not been proven superior to the combination of biotype analysis and temporal resolution as used in this study, and PFGE has its own limitations.9

In conclusion, we have shown that anesthesia provider hand contamination is an important proximal source and transmission location for within and between case Enterococcus transmission events in the intraoperative setting. Future work should examine the impact of improved intraoperative hand hygiene compliance on the dynamics of Enterococcus transmission in the anesthesia work area.

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Appendix

Table

Table

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DISCLOSURES

Name: Randy W. Loftus, MD.

Contribution: This author helped design and conduct the study, analyze the data, and write the manuscript.

Attestation: Randy W. Loftus has seen the original study data, reviewed the analysis of the data, approved the final manuscript, and is the author responsible for archiving the study files.

Name: Matthew D. Koff, MS, MD.

Contribution: This author helped design and conduct the study, analyze the data, and write the manuscript.

Attestation: Matthew D. Koff has seen the original study data, reviewed the analysis of the data, and approved the final manuscript.

Name: Jeremiah R. Brown, MS, PhD.

Contribution: This author helped analyze the data and write the manuscript.

Attestation: Jeremiah R. Brown has seen the original study data, reviewed the analysis of the data, and approved the final manuscript.

Name: Hetal M. Patel, BS.

Contribution: This author helped conduct the study.

Attestation: Hetal M. Patel has seen the original study data and approved the final manuscript.

Name: Jens T. Jensen, MS.

Contribution: This author helped conduct the study, analyze the data, and write the manuscript.

Attestation: Jens T. Jensen has seen the original study data, reviewed the analysis of the data, and approved the final manuscript.

Name: Sundara Reddy, MD.

Contribution: This author helped design and conduct the study and write the manuscript.

Attestation: Sundara Reddy has seen the original study data and approved the final manuscript.

Name: Kathryn L. Ruoff, PhD.

Contribution: This author helped design and conduct the study, analyze the data, and write the manuscript.

Attestation: Kathryn L. Ruoff has seen the original study data and approved the final manuscript.

Name: Stephen O. Heard, MD.

Contribution: This author helped design and conduct the study, analyze the data, and write the manuscript.

Attestation: Stephen O. Heard has seen the original study data and approved the final manuscript.

Name: Mark P. Yeager, MD.

Contribution: This author helped design the study, analyze the data, and write the manuscript.

Attestation: Mark P. Yeager has seen the original study data and approved the final manuscript.

Name: Thomas M. Dodds, MD.

Contribution: This author helped design and conduct the study, analyze the data, and write the manuscript.

Attestation: Thomas M. Dodds has seen the original study data, reviewed the analysis of the data, and approved the final manuscript.

This manuscript was handled by: Sorin J. Brull, MD, FCARCSI (Hon).

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ACKNOWLEDGMENTS

We would like to thank Leonard Mermel, DO, ScM, AM (Hon), Professor of Medicine, Warren Alpert Medical School of Brown University, Medical Director, Epidemiology and Infection Control Department, Rhode Island Hospital, for his careful review of this manuscript.

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