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Transmission Dynamics of Gram-Negative Bacterial Pathogens in the Anesthesia Work Area

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

doi: 10.1213/ANE.0000000000000626
Patient Safety: Research Report

BACKGROUND: Gram-negative organisms are a major health care concern with increasing prevalence of infection and community spread. Our primary aim was to characterize the transmission dynamics of frequently encountered gram-negative bacteria in the anesthesia work area environment (AWE). Our secondary aim was to examine links between these transmission events and 30-day postoperative health care-associated infections (HCAIs).

METHODS: Gram-negative isolates obtained from the AWE (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). The top 5 frequently encountered genera were subjected to antibiotic disk diffusion sensitivity to identify epidemiologically related transmission events. Complete multivariable logistic regression analysis and binomial tests of proportion were then used to examine the relative contributions of reservoirs of origin and within- and between-case modes of transmission, respectively, to epidemiologically related transmission events. Analyses were conducted with and without the inclusion of duplicate transmission events of the same genera occurring in a given study unit (first and second case of the day in each operating room observed) to examine the potential effect of statistical dependency. Transmitted isolates were compared by pulsed-field gel electrophoresis to disease-causing bacteria for 30-day postoperative HCAIs.

RESULTS: The top 5 frequently encountered gram-negative genera included Acinetobacter, Pseudomonas, Brevundimonas, Enterobacter, and Moraxella that together accounted for 81% (767/945) of possible transmission events. For all isolates, 22% (167/767) of possible transmission events were identified by antibiotic susceptibility patterns as epidemiologically related and underwent further study of transmission dynamics. There were 20 duplicates involving within- and between-case transmission events. Thus, approximately 19% (147/767) of isolates excluding duplicates were considered epidemiologically related. Contaminated provider hand reservoirs were less likely (all isolates, odds ratio 0.12, 95% confidence interval 0.03–0.50, P = 0.004; without duplicate events, odds ratio 0.05, 95% confidence interval 0.01–0.49, P = 0.010) than contaminated patient or environmental sites to serve as the reservoir of origin for epidemiologically related transmission events. Within- and between-case modes of gram-negative bacilli transmission occurred at similar rates (all isolates, 7% between-case, 5.2% within-case, binomial P value 0.176; without duplicates, 6.3% between-case, 3.7% within-case, binomial P value 0.036). Overall, 4.0% (23/548) of patients suffered from HCAIs and had an intraoperative exposure to gram-negative isolates. In 8.0% (2/23) of those patients, gram-negative bacteria were linked by pulsed-field gel electrophoresis to the causative organism of infection. Patient and provider hands were identified as the reservoirs of origin and the environment confirmed as a vehicle for between-case transmission events linked to HCAIs.

CONCLUSIONS: Between- and within-case AWE gram-negative bacterial transmission occurs frequently and is linked by pulsed-field gel electrophoresis to 30-day postoperative infections. Provider hands are less likely than contaminated environmental or patient skin surfaces to serve as the reservoir of origin for transmission events.

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

Accepted for publication December 27, 2014.

Funding: APSF and departmental.

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.

Gram-negative pathogens contribute to the hospital-wide problems of health care-associated infections (HCAIs) and bacterial resistance.1–3 They are associated with surgical site,1 central line–associated,4,5 and primary blood stream infections (BSIs)6; postoperative meningitis and epidural abscesses7; and a multitude of infections occurring in complex health care settings such as the intensive care unit.8,9 These organisms have evolved to develop new and important mechanisms of antibiotic resistance and have extended beyond the acute health care settings to healthy members of the community.10,11 In fact, the family Enterobacteriaceae (e.g., Citrobacter, Enterobacter, Serratia, E coli, Klebsiella, Proteus, Shigella, and others) has become a worldwide public health concern associated with increased morbidity, mortality, and health care costs.11 Because bacterial transmission is a root cause of HCAI development, it is important that we understand and attenuate the spread of these important pathogens across all health care arenas, including the operating room environment. The primary aim of this study was to identify and examine transmission dynamics (reservoirs of origin and modes of transmission) involving frequently encountered gram-negative bacterial organisms in the anesthesia work area environment (AWE). The secondary aim was to examine links between these transmission events and subsequent 30-day postoperative HCAIs.

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METHODS

General Approach

A prospective, randomized, observational study was previously conducted over 12 consecutive months (from March 2009 to February 2010) at Dartmouth-Hitchcock Medical Center (DHMC) in New Hampshire, the University of Iowa Hospitals and Clinics in Iowa, and the UMass Memorial Medical Center in Massachusetts. The primary aim of this prior study was to characterize the frequency and implications of overall bacterial transmission events to intravascular devices in the intraoperative arena.12 A model for study of intraoperative bacterial cross-contamination was used to identify bacterial isolates and transmission events involving AWE reservoirs across 274 operating rooms.12 The distribution of number of study units and provider encounters across the 3 study sites is shown in Figure 1. The study unit was a case pair, with the first and second case of the day in each room observed to evaluate bacterial transmission occurring within and between operative cases (Fig. 2). Measured bacterial reservoirs included provider hands throughout care (before, during, and after), patient sites (nasopharynx and axilla) after induction of anesthesia, and baseline and case end environmental cultures. These sites were assessed in parallel during the process of patient care.12 Health care provider hand hygiene, patient decolonization, and environmental cleaning processes were not altered during the study period, and aseptic practice procedures at each site were tracked and recorded.12 A waiver for informed consent was obtained after approval at each study site from the respective IRBs for the protection of human subjects.12 Additional approval was obtained from the Committee for Protection of Human Subjects at DHMC for the current study.

Figure 1

Figure 1

Figure 2

Figure 2

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Evaluation of Gram-Negative Transmission Dynamics (Primary Aim)

In the prior study, >6000 bacterial pathogens were isolated and archived for later analysis including Staphylococcal, Enterococcal, and gram-negative organisms.12 The primary focus of the current analysis is gram-negative bacilli. The experimental model used to obtain gram-negative isolates included reservoirs that could be potentially addressed by improvements in aseptic/disinfection practice conducted or facilitated by anesthesia providers, while also addressing the potential role of other more distal reservoirs, such as the patient’s rectum, when organisms from distal reservoirs are transmitted to more proximal reservoirs contacted by the anesthesia provider. Rectal colonization with bacterial organisms commonly occurs in conjunction with skin colonization,13 and the antecubital fossa and blood pressure cuff, often in contact with the axilla, have been shown to be significant predictors of bacterial transmission in colonized patients.14 Thus, the patient sites measured in the model served to effectively measure the patient’s contribution to transmission/infection involving gram-negative pathogens.12–14

A systematic analysis of gram-negative isolates (Fig. 3) was used to examine intraoperative gram-negative transmission dynamics. All previously archived major bacterial pathogens were classified according to colony morphology, gram stain, and simple rapid tests. Next, 274 case pairs (548 cases) were reviewed for evidence of possible gram-negative transmission defined by the presence of a gram-negative isolate in 2 or more reservoir sites across the case pair. Bacterial phenotype was then identified via use of a commercially available bioMerieux Analytical Profile Index (API) identification system (Marcy 1’Etoile, France) that generates a 7-digit profile number based on positive or negative reactions in a minimum of 20 phenotypic tests.15 Temporal associations (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 API phenotype) were then used to identify possible transmission events occurring within and between operative cases. Possible transmission events were further evaluated by disk diffusion antibiotic susceptibility testing analysis (antibiotic susceptibility profiling-same response to 12 commonly used prophylactic antibiotics potentially effective against gram-negatives, Appendix) to identify epidemiologically related transmission events. Reservoir(s) of origin and modes (within- and/or between-case transmission) of transmission were then characterized for the top 5 frequently encountered genera.

Figure 3

Figure 3

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Definitions

Transmission event: The presence of a bacterial pathogen in a reservoir during the process of patient care that was not present in baseline cultures at case start. Reservoir of origin: Provider origin of a transmission event was assumed if the transmitted isolate was identical to an isolate from the hands of 1 or more anesthesia providers but not found in the patient or environmental reservoirs earlier in the sampling sequence. Environmental origin of contamination was assumed 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. Patient origin of contamination was assumed if the transmitted isolate was identical to an isolate from the patient sampled at case start but was not isolated from provider hands or environmental reservoirs earlier in the sampling sequence. Epidemiologically related transmission events: Two or more major bacterial pathogens present in >1 intraoperative site in a case series that were identical according to class of pathogen, standard microbiological tests, API, antibiotic susceptibility, and temporal association (appropriate reservoir of exposure and timing of the event occurring in the same operating room case pair, on the same operating day, during procedures whereby patients were undergoing care in the same environment, and with the same set of health care providers measured). Mode of transmission: Transmission occurring within or between operative cases. Statistically dependent transmission events: In study units where >1 within- and/or between-case transmission event involving the same bacterial genera for a study unit occurred, statistical dependence was assumed. As described further in the statistical methods, the primary analysis included all transmission events, statistically dependent or independent. For the exploratory analysis, duplicate within- and between-case transmission events were deleted to examine the sensitivity of the analyses to statistical dependence.

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Evaluation for Microbiological Links Between Gram-Negative Transmission Events and 30-Day Postoperative Infections (Secondary Aim)

Epidemiologically related transmission events were compared to the causative organism of 30-day postoperative infections via temporal association, biotype, disk diffusion antibiotic susceptibility testing, and pulsed-field gel electrophoresis (PFGE) analysis.16 HCAIs were defined according to National Healthcare Safety Network definitions.17

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Demographic Information

Information pertaining to hospital site, age, sex, case 1 or case 2, ASA physical status classification, Study on the Efficacy of Nosocomial Infection Control (SENIC)18 score (an index characterizing patient morbidity and associated with probability of postoperative HCAI development for a given patient), patient comorbidities, patient origin, patient discharge location, procedure type, and case duration of >2 hours was collected.

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Statistical Analysis

The primary aim was to examine the primary reservoir of origin and mode of transmission for all epidemiologically related transmission events involving frequently encountered gram-negative pathogens in the AWE. An analysis involving deletion of duplicate transmission events (>1 within- and/or between-case transmission event involving the same bacterial genera for a study unit, the first and second case of the day) was also conducted to examine the potential effect of statistical dependence (Table 1).

Table 1

Table 1

For both analyses, reservoirs of origin were compared via forward and reverse stepwise multivariable logistic regression analysis models that included adjustment for potentially confounding site and exposure variables. For the analysis involving all isolates, significant variables from forward stepwise included discharge location to same day, case duration >2 hours (a component of SENIC score),18 and case (first or second case of the day), while significant variables from reverse stepwise included discharge location to same day, case, orthopedic procedure, and SENIC >2. The final model for all isolates included all variables from forward and reverse regression at an α of ≤0.10, which were discharge location and case duration >2 hours, as well as hospital site. All first-order interactions were assessed, with only an interaction for discharge location and site 2 significant. Table 2a shows the results of the multivariable analysis for all isolates with and without the interaction term. An α level of P < 0.05 was defined as statistically significant. Table 2b shows the results of the analysis involving deletion of duplicate transmission events. Forward and backward stepwise logistic regression showed that case, duration >2 hours, and discharge location were significant, and they remained in the final model. There were no significant interaction terms. An α level of P < 0.05 was defined as statistically significant.

Table 2

Table 2

Intergenera differences in modes of transmission for the top 5 most frequently encountered genera were compared via Fisher exact test. To test whether transmission was equally likely by within- and between-case modes of transmission, a 2-sided binomial was used to test whether the proportion of total within-case events was 50% as a fraction of all transmissions, in which the transmission was defined as either within-case or between-case but not both. Analyses involved all isolates and deletion of duplicates, and the results were adjusted for multiple comparisons by multiplying the P value by 2. An α level of P < 0.05 was defined as statistically significant (Table 3).

Table 3

Table 3

The secondary aim was to examine links between transmission events and 30-day postoperative HCAIs. Gram-negative bacterial links to 30-day postoperative HCAIs were identified and reported qualitatively (Table 4).

Table 4

Table 4

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Sample Size

All gram-negative isolates obtained during the prospective, randomized, observational study previously conducted over 12 consecutive months (from March 2009 to February 2010) at DHMC in New Hampshire, the University of Iowa Hospitals and Clinics in Iowa, and the UMass Memorial Medical Center in Massachusetts were used in this analysis.

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RESULTS

Gram-negative isolates (N = 2682) were obtained from 1448 AWE reservoirs and a subset (N = 945) identified as possible transmission events. Acinetobacter, Pseudomonas, Brevundimonas, Enterobacter, and Moraxella genera accounted for 81% (767/945) of possible transmission events. Twenty-two percent (167/767) of all isolates were considered epidemiologically related after antibiotic susceptibility testing (Table 1). There were 20 duplicates involving within- and between-case transmission events. Thus, approximately 19% (147/767) of isolates excluding duplicates were considered epidemiologically related.

Contaminated provider hands were less likely to serve as the reservoir of origin for transmission events (all isolates, odds ratio 0.12, 95% confidence interval 0.03–0.50, P = 0.004; without duplicates, odds ratio 0.05, 95% confidence interval 0.01–0.49, P = 0.010) than contaminated patient or environmental surfaces (Table 2). This difference remained significant with or without inclusion of the significant interaction term for the analysis including all isolates (Table 2a).

There were intergenera differences in modes of transmission for the analysis involving all isolates (P = 0.004), but this difference did not remain statistically significant in the analysis excluding duplicate transmission events (P = 0.096) (Table 3). Approximately 7% (54/767) and 5% (41/767) of all isolates implicated in an epidemiologically related intraoperative bacterial transmission sequence were involved in between- and within-case modes of transmission, respectively (binomial test of between- and within-case transmission event proportions, P = 0.178). After exclusion of duplicates, approximately 6% (47/748) and 4% (28/748) of isolates were involved in between- and within-case modes of transmission, respectively (binomial test of between- and within-case transmission event proportions, P = 0.036) (Table 3).

Overall, 4% (23/548) of patients suffered from HCAI development and had some intraoperative gram-negative exposure. In 8% (2/23) of those patients, gram-negative bacteria were linked by PFGE to the causative organism of infection. The organisms confirmed as causative for infection by PFGE were Enterobacter aerogenes and S liquefaciens. In the case of E aerogenes transmission, the infection was pneumonia, with the identified source as provider hands and the transmission location the patient. For S liquefaciens, the infection was pneumonia, with the identified source and transmission location as the patient. In addition, we were able to show how a patient infected and colonized with Proteus mirabilis in case 1 led to transmission of the organism to the nasopharynx of the second patient of the day (Table 4).

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DISCUSSION

We have examined the transmission dynamics and associated morbidity of gram-negative bacteria frequently isolated from the AWE. This work may aide the development of improved intraoperative infection control measures targeting a reduction in the intraoperative spread of gram-negative pathogens.

We found that Acinetobacter, Pseudomonas, Brevundimonas, Enterobacter, and Moraxella genera are frequently encountered in and transmitted from anesthesia reservoirs. Acinetobacter spp. are considered a major problem for multidrug-resistant organisms in orthopedic military wounds19,20 and have been identified as important pathogens in intensive care unit infections,21 and environmental cleaning has been shown to be an important preventive measure for these organisms.22Pseudomonas spp. are major bacterial pathogens involved in ventilator-associated pneumonias,23 BSIs,24 and surgical site infections25 and are associated with increased patient mortality.23 Similarly, Enterobacter spp. are common pathogens involved in BSIs and respiratory and wound infections and are associated with increased morbidity and mortality.6,11,26 In fact, Enterobacter spp. are an important cause of mediastinitis and sternal wound infections.27 Though less pathogenic, Moraxella spp. and Brevundimonas have been implicated as the disease-causing pathogen for infectious complications.28,29 Thus, all identified, frequently encountered genera in the surgical operating room have clinical relevance.

Our study of intraoperative gram-negative transmission dynamics shows that contaminated provider hands are a less potent transmission vehicle than contaminated patient or environmental sites. Thus, this work suggests that improvement measures targeting a reduction in intraoperative gram-negative transmission should consider not only the frequency of reservoir pathogen isolation but also the likelihood of transmission given reservoir contamination (potency of transmission). These results suggest that in addition to provider hands, patient and environmental reservoirs should be addressed.

This study shows that transmission of gram-negative pathogens within and between cases occurs at alarmingly high rates. Additionally, there may be significant overall and intergenera differences in the frequency of between- and within-case modes of transmission. Because there are differences in the analysis of all isolates as compared to the analysis excluding duplicates, and it is unclear which approach yields the correct answer, the finding of a significantly higher proportion of between-case transmission in the analysis excluding duplicates should be interpreted with caution. We have concluded that until further evaluation, the proportions are similar. This finding is however consistent with prior work highlighting the importance of intraoperative environmental reservoirs in transmission of bacterial pathogens,12 and it supports the finding in this study that contaminated hands are a less potent transmission vehicle for intraoperative gram-negative pathogens. At the very least, these findings suggest that there is room for improvement in the environmental cleaning practices used during the study period which have been previously reported.12

Patients were followed prospectively to ascertain whether we could link transmitted organisms to infection. Using PFGE, we were able to link E aerogenes and S marcescens transmission to cases of postoperative pneumonia, and we were able to show how infected patients can bring organisms to the operating room (e.g., P mirabilis) that are subsequently transmitted to patients undergoing care in the same arena. In the case of E aerogenes, the transmission was provider hand-derived. In the case of S marcescens and P mirabilis, the transmission originated with the patient, endogenous in the case of S marcescens with transmission from a nonsterile site to a sterile site during instrumentation, and exogenous in the case of P mirabilis transmission, likely via provider hands or the environment. Thus, prevention of all of these infections (between-case transmission in the case of P mirabilis) would have required addressing patient, environmental (between-case transmission), and provider reservoirs, that is, a multimodal program.

This study is limited by the insensitivity of the culture methods used, with the results likely underestimating the overall magnitude of transmission events and the subsequent development of infection. In addition, we recognize that a traditional approach to gram-negative transmission involves rectal swabs and as such, may not have identified all cases of patient colonization with gram-negative organisms. However, the intent of this study was to examine bacterial reservoirs relevant to the anesthesiologist, not to examine overall intraoperative bacterial transmission. We also recognize that a clonal relationship is not confirmed for transmission events, but our model is strengthened with an approach combining temporal association with a systematic analysis involving a series of phenotypic tests. PFGE was used to confirm clonal relationships in cases where transmission events were compared to the causative organism of infection, because this period lacked temporal association.

In conclusion, epidemiologically related gram-negative transmission events occur frequently within and between operative cases. Health care provider hands are less likely to serve as a reservoir of origin for transmission events than contaminated patient or environmental surfaces. Intraoperative gram-negative transmission events are linked to 30-day postoperative infections by PFGE. Improvement measures targeting gram-negative pathogens are indicated and should include the relative potency of reservoir transmission.

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Appendix

Table

Table

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DISCLOSURES

Name: Randy W. Loftus, MD.

Contribution: This author helped design the study, 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: 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: Matthew D. Koff, MD, MS.

Contribution: This author helped design the study, conduct the study, 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: Jens T. Jensen, MS.

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

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 the study, 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 the study, 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 the study, 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: Thomas M. Dodds, MD.

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

Attestation: Thomas M. Dodds approved the final manuscript.

Name: Michael L. Beach, MD.

Contribution: This author helped analyze the results.

Attestation: Michael L. Beach approved the final manuscript.

Name: Mark P. Yeager, MD.

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

Attestation: Mark P. Yeager 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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