A threshold of 100 or more colony-forming units on the anesthesia machine predicts bacterial pathogen detection: a retrospective laboratory-based analysis.

PURPOSE: Preventing the spread of pathogens in the anesthesia work area reduces surgical site infections. Improved cleaning reduces the percentage of anesthesia machine samples with ≥ 100 colony-forming units (CFU) per surface area sampled. Targeting a threshold of < 100 CFU when cleaning anesthesia machines may be associated with a lower prevalence of bacterial pathogens. We hypothesized that anesthesia work area reservoir samples returning < 100 CFU would have a low (< 5%) prevalence of pathogens. METHODS: In this retrospective cohort study of bacterial count data from nine hospitals, obtained between 2017 and 2022, anesthesia attending and assistants' hands, patient skin sites (nares, axilla, and groin), and anesthesia machine (adjustable pressure-limiting valve and agent dials) reservoirs were sampled at case start and at case end. The patient intravenous stopcock set was sampled at case end. The isolation of ≥ 1 CFU of Staphylococcus aureus, methicillin-resistant Staphylococcus aureus, Enterococcus, vancomycin-resistant Enterococcus, gram-negative (i.e., Klebsiella, Acinetobacter, Pseudomonas, and Enterobacter spp.) or coagulase-negative Staphylococcus was compared for reservoir samples returning ≥ 100 CFU vs those returning < 100 CFU. RESULTS: Bacterial pathogens were isolated from 24% (7,601/31,783) of reservoir samples, 93% (98/105) of operating rooms, and 83% (2,170/2,616) of cases. The ratio of total pathogen isolates to total CFU was < 0.0003%. Anesthesia machine reservoirs returned ≥ 100 CFU for 44% (2,262/5,150) of cases. Twenty-three percent of samples returning ≥ 100 CFU were positive for ≥ 1 bacterial pathogen (521/2,262; 99% lower confidence limit, 22%) vs 3% of samples returning < 100 CFU (96/2,888; 99% upper limit, 4%). CONCLUSIONS: Anesthesia machine reservoir samples returning < 100 CFU were associated with negligible pathogen detection. This threshold can be used for assessment of terminal, routine, and between-case cleaning of the anesthesia machine and equipment. Such feedback may be useful because the 44% prevalence of ≥ 100 CFU was comparable to the 46% (25/54) reported earlier from an unrelated hospital.

RéSUMé: OBJECTIF: La prévention de la propagation des agents pathogènes dans la zone de travail de l'anesthésie réduit les infections du site opératoire. L'amélioration du nettoyage réduit le pourcentage d'échantillons de l'appareil d'anesthésie présentant ≥ 100 unités de formation de colonie (UFC) par surface échantillonnée. Le fait de cibler un seuil < 100 UFC lors du nettoyage des appareils d'anesthésie pourrait être associé à une prévalence plus faible d'agents pathogènes bactériens. Nous avons émis l'hypothèse que les échantillons des réservoirs de la zone de travail d'anesthésie < 100 UFC résulteraient en une faible prévalence (< 5 %) d'agents pathogènes. MéTHODE: Dans cette étude de cohorte rétrospective des données de décompte bactérien de neuf hôpitaux, obtenues entre 2017 et 2022, les mains des anesthésiologistes et des assistant·es en anesthésie, les sites cutanés des patient·es (narines, aisselles et aines) et les réservoirs de l'appareil d'anesthésie (soupape de réglage de limitation de pression et cadrans d'agent) ont été échantillonnés au début et à la fin de chaque cas. Les échantillons sur l'ensemble de robinets d'arrêt intraveineux des patient·es ont été prélevés à la fin de chaque cas. L'isolement de ≥ 1 UFC de staphylocoque doré, de staphylocoque doré résistant à la méthicilline, d'entérocoque, d'entérocoque résistant à la vancomycine, de staphylocoque à Gram négatif (c.-à-d. Klebsiella, Acinetobacter, Pseudomonas et Enterobacter spp.) ou à coagulase négative a été comparé pour les échantillons de réservoir retournant ≥ 100 UFC vs ceux qui comportaient < 100 UFC. RéSULTATS: Des bactéries pathogènes ont été isolées dans 24 % (7601/31 783) des échantillons de réservoir, 93 % (98/105) des salles d'opération et 83 % (2170/2616) des cas. Le rapport entre le nombre total d'isolats d'agents pathogènes et le nombre total d'UFC était de < 0,0003 %. Les échantillons pris sur les réservoirs d'appareils d'anesthésie ont retourné ≥ 100 UFC dans 44 % (2262/5150) des cas. Vingt-trois pour cent des échantillons retournés ≥ 100 UFC étaient positifs pour ≥ 1 agent pathogène bactérien (521/2262; limite de confiance inférieure à 99 %, 22 %) vs 3 % des échantillons retournant < 100 UFC (96/2888 ; 99 % de la limite supérieure, 4 %). CONCLUSION: Les échantillons pris sur les réservoirs de l'appareil d'anesthésie comportant < 100 UFC étaient associés à une détection négligeable d'agents pathogènes. Ce seuil peut être utilisé pour l'évaluation du nettoyage final, de routine et entre les cas de l'appareil et de l'équipement d'anesthésie. Une telle rétroaction peut être utile parce que la prévalence de 44 % de ≥ 100 UFC était comparable aux 46 % (25/54) rapportés précédemment dans un autre hôpital.

Most hospital patients at risk for bacterial infection undergo an anesthetic: implications for infection control practices related to the anesthesia workspace.

PURPOSE: Even with nearly 100% compliance with prophylactic antibiotic protocols, many surgical patients (> 5%) develop surgical site infections, some caused by pathogens transmitted from the anesthesia workspace (e.g., anesthesia machine), including multidrug-resistant Staphylococcus aureus. Reducing contamination of the anesthesia workspace substantively reduces the risk of surgical site infections. We estimated the percentage of hospital patients at risk for health care-associated infections who may benefit from the application of basic preventive measures under the control of anesthesia practitioners (e.g., their hand hygiene). METHODS: We conducted a retrospective cohort study which included every patient admitted to the University of Miami Health System from April 2021 through March 2022 for hospitalization, surgery, emergency department visits, or outpatient visits. Lists were created for the start date and times of every parenteral antibiotic administered and every anesthetic. RESULTS: Among 28,213 patient encounters including parenteral antibiotic(s), more than half (64.3%) also included an anesthetic (99% confidence interval, 62.2 to 66.6). The hypothesis that most antibiotics were administered during encounters when a patient underwent an anesthetic was accepted (P < 0.001). This observation may seem counterintuitive because parenteral antibiotics were administered for fewer than half of the 53,235 anesthetics (34.2%). The result was a consequence of most anesthetics (63.5%) at the health system being conducted in nonoperating room locations, and only 7.2% of such patients received a parenteral antibiotic. CONCLUSIONS: Because approximately two-thirds of patients who receive an intravenous antibiotic also undergo an anesthetic, greater use of effective infection control measures in the anesthesia operating room workspace has the potential to substantively reduce overall rates of hospital infections.

RéSUMé: OBJECTIF: Même avec un respect de près de 100 % des protocoles antibiotiques prophylactiques, bon nombre de patients et patientes en chirurgie (> 5 %) développent des infections du site opératoire, dont certaines sont causées par des agents pathogènes transmis par l'espace de travail anesthésique (p. ex. appareil d'anesthésie), y compris un staphylocoque doré multirésistant. La réduction de la contamination de l'espace de travail anesthésique réduit considérablement le risque d'infections du site opératoire. Nous avons estimé le pourcentage de patientes et patients hospitalisé·es à risque d'infections associées aux soins de santé qui pourraient bénéficier de l'application de mesures préventives de base sous le contrôle de praticiens et praticiennes d'anesthésie (par exemple, leur hygiène des mains). MéTHODE: Nous avons mené une étude de cohorte rétrospective qui comprenait toutes les personnes admises au Système de santé de l'Université de Miami d'avril 2021 à mars 2022 pour une hospitalisation, une intervention chirurgicale, des visites aux urgences ou des consultations externes. Des listes ont été créées pour la date et l'heure de début de chaque antibiotique parentéral administré et de chaque anesthésique. RéSULTATS: Parmi les 28 213 consultations avec les patient·es comprenant des antibiotiques parentéraux, plus de la moitié (64,3 %) comportaient également un anesthésique (intervalle de confiance à 99 %, 62,2 à 66,6). L'hypothèse selon laquelle la plupart des antibiotiques étaient administrés lors de rencontres lorsqu'une personne bénéficiait d'une anesthésie a été acceptée (P < 0,001). Cette observation peut sembler contre-intuitive, car des antibiotiques parentéraux ont été administrés pour moins de la moitié des 53 235 anesthésiques (34,2 %). En effet, la plupart des anesthésies (63,5 %) ont été administrées en dehors de la salle d'opération, et seulement 7,2 % de cette patientèle a reçu un antibiotique parentéral. CONCLUSION: Étant donné qu'environ les deux tiers des patientes et patients qui reçoivent un antibiotique par voie intraveineuse bénéficient également d'une anesthésie, une plus grande utilisation de mesures efficaces de contrôle des infections dans l'espace de travail anesthésique de la salle d'opération pourrait réduire considérablement les taux globaux d'infections hospitalières.

Epidemiology of Enterococcus , Staphylococcus aureus , Klebsiella , Acinetobacter , Pseudomonas , and Enterobacter Species Transmission in the Pediatric Anesthesia Work Area Environment With and Without Practitioner Use of a Personalized Body-Worn Alcohol Dispenser.

BACKGROUND: Personalized body-worn alcohol dispensers may serve as an important tool for perioperative infection control, but the impact of these devices on the epidemiology of transmission of high-risk Enterococcus , Staphylococcus aureus , Klebsiella, Acinetobacter , Pseudomonas , and Enterobacter (ESKAPE) pathogens is unknown. We aimed to characterize the epidemiology of ESKAPE transmission in the pediatric anesthesia work area environment with and without a personalized body-worn alcohol dispenser. METHODS: This controlled before and after study included 40 pediatric patients enrolled over a 1-year study period. Two groups of operating room cases were compared: (1) operating room cases caring for patients with usual care (December 17, 2019, to August 25, 2020), and (2) operating room cases caring for patients with usual care plus the addition of a personalized, body-worn alcohol hand rub dispenser (September 30, 2020, to December 16, 2020). Operating rooms were randomly selected for observation of ESKAPE transmission in both groups. Device use was tracked via wireless technology and recorded in hourly hand decontamination events. RESULTS: Anesthesia providers used the alcohol dispenser 3.3 ± 2.1 times per hour. A total of 57 ESKAPE transmission events (29 treatment and 28 control) were identified. The personalized body-worn alcohol dispenser impacted ESKAPE transmission by increasing the contribution of provider hand contamination at case start (21/29 device versus 10/28 usual care; relative risk, [RR] 2.03; 99.17% confidence interval [CI], 1.025-5.27; P = .0066) and decreasing the contribution of environmental contamination at case end (3/29 device versus 12/28 usual care; RR, 0.24; 99.17% CI, 0.022-0.947; P = .0059). ESKAPE pathogen contamination involved 20% (8/40) of patient intravascular devices. There were 85% (34/40) of preoperative patient skin surfaces contaminated with ≥1 (1.78 ± 0.19 [standard deviation {SD}]) ESKAPE pathogens. CONCLUSIONS: A personalized body-worn alcohol dispenser can impact the epidemiology of ESKAPE transmission in the pediatric anesthesia work area environment. Improved preoperative patient decolonization and vascular care are indicated to address ESKAPE pathogens among pediatric anesthesia work area reservoirs.

Quantifying and interpreting inequality of surgical site infections among operating rooms.

PURPOSE: The incidence of surgical site infection differs among operating rooms (ORs). However, cost effectiveness of interventions targeting ORs depends on infection counts. The purpose of this study was to quantify the inequality of infection counts among ORs. METHODS: We performed a single-centre historical cohort study of elective surgical cases spanning a 160-week period from May 2017 to May 2020, identifying cases of infection within 90 days using International Classification of Diseases, Tenth Revision, Clinical Modification diagnosis codes. We used the Gini index to measure inequality of infections among ORs. As a reference, the Gini index for inequality of household disposable income in the US in 2017 was 0.39, and 0.31 for Canada. RESULTS: There were 3,148 (3.67%) infections among the 85,744 cases studied. The 20% of 57 ORs with the most and least infections accounted for 44% (99% confidence interval [CI], 36 to 52) and 5% (99% CI, 2 to 8), respectively. The Gini index was 0.40 (99% CI, 0.31 to 0.50), which is comparable to income inequality in the US. There were more infections in ORs with more minutes of cases (Spearman correlation ρ = 0.68; P < 0.001), but generally not in ORs with more total cases (ρ = 0.11; P = 0.43). Moderately long (3.3 to 4.8 hr) cases had a large effect, having greater incidences of infection, while not being so long as to have just one case per day per OR. There was substantially greater inequality in infection counts among the 557 observed combinations of OR specialty (Gini index 0.85; 99% CI, 0.81 to 0.88). CONCLUSIONS: Inequality of infections among ORs is substantial and caused by both inequality in the incidence of infections and inequality in the total minutes of cases. Inequality in infections among OR and specialty combinations is due principally to inequality in total minutes of cases.

RéSUMé: OBJECTIF: L'incidence d'infections opératoires diffère d'une salle d'opération (SOP) à une autre. Toutefois, le rapport coût-efficacité des interventions ciblant les SOP dépend de l'incidence des infections. Le but de cette étude était de quantifier l'inégalité du nombre d'infections entre les SOP. MéTHODE: Nous avons effectué une étude de cohorte historique et monocentrique des cas chirurgicaux non urgents couvrant une période de 160 semaines allant de mai 2017 à mai 2020. Nous avons identifié les cas d'infection dans les 90 jours suivant l'opération à l'aide des codes de diagnostic de la Classification internationale des maladies, dixième révision, modification clinique. Nous avons utilisé l'indice de Gini pour mesurer l'inégalité des infections entre les SOP. À titre de référence, en 2017, l'indice de Gini pour l'inégalité du revenu disponible des ménages était de 0,39 aux États-Unis et de 0,31 pour le Canada. RéSULTATS: Il y a eu 3148 (3,67 %) infections parmi les 85 744 cas étudiés. Les quintiles des 57 SOP ayant le plus et le moins d'infections représentaient 44 % (intervalle de confiance [IC] 99 %, 36 à 52) et 5 % (IC 99 %, 2 à 8) des infections, respectivement. L'indice de Gini était de 0,40 (IC 99 %, 0,31 à 0,50), ce qui est comparable à l'inégalité des revenus aux États-Unis. Il y avait plus d'infections dans les SOP comptant plus de minutes de cas (corrélation de Spearman ρ = 0,68; P < 0,001), mais généralement pas dans les SOP avec un nombre plus élevé de cas totaux (ρ = 0,11; P = 0,43). Les cas modérément longs (3,3 à 4,8 heures) ont eu un effet important, ayant des incidences plus importantes d'infection, tout en n'étant pas suffisamment longs pour n'avoir qu'un seul cas par jour et par SOP. Une inégalité sensiblement plus prononcée a été remarquée dans le nombre d'infections parmi les 557 combinaisons observées de spécialité de SOP (indice de Gini 0,85; IC 99 %, 0,81 à 0,88). CONCLUSION: L'inégalité des infections entre les SOP est importante et causée à la fois par l'inégalité dans l'incidence des infections et par l'inégalité dans la durée totale (en minutes) des cas. L'inégalité dans les infections entre les SOP et les combinaisons de spécialités est principalement due à l'inégalité dans le nombre total de minutes des cas.

Perioperative COVID-19 Defense: An Evidence-Based Approach for Optimization of Infection Control and Operating Room Management.

We describe an evidence-based approach for optimization of infection control and operating room management during the coronavirus disease 2019 (COVID-19) pandemic. Confirmed modes of viral transmission are primarily, but not exclusively, contact with contaminated environmental surfaces and aerosolization. Evidence-based improvement strategies for attenuation of residual environmental contamination involve a combination of deep cleaning with surface disinfectants and ultraviolet light (UV-C). (1) Place alcohol-based hand rubs on the intravenous (IV) pole to the left of the provider. Double glove during induction. (2) Place a wire basket lined with a zip closure plastic bag on the IV pole to the right of the provider. Place all contaminated instruments in the bag (eg, laryngoscope blades and handles) and close. Designate and maintain clean and dirty areas. After induction of anesthesia, wipe down all equipment and surfaces with disinfection wipes that contain a quaternary ammonium compound and alcohol. Use a top-down cleaning sequence adequate to reduce bioburden. Treat operating rooms using UV-C. (3) Decolonize patients using preprocedural chlorhexidine wipes, 2 doses of nasal povidone-iodine within 1 hour of incision, and chlorhexidine mouth rinse. (4) Create a closed lumen IV system and use hub disinfection. (5) Provide data feedback by surveillance of Enterococcus, Staphylococcus aureus, Klebsiella, Acinetobacter, Pseudomonas, and Enterobacter spp. (ESKAPE) transmission. (6) To reduce the use of surgical masks and to reduce potential COVID-19 exposure, use relatively long (eg, 12 hours) staff shifts. If there are 8 essential cases to be done (each lasting 1-2 hours), the ideal solution is to have 2 teams complete the 8 cases, not 8 first case starts. (7) Do 1 case in each operating room daily, with terminal cleaning after each case including UV-C or equivalent. (8) Do not have patients go into a large, pooled phase I postanesthesia care unit because of the risk of contaminating facility at large along with many staff. Instead, have most patients recover in the room where they had surgery as is done routinely in Japan. These 8 programmatic recommendations stand on a substantial body of empirical evidence characterizing the epidemiology of perioperative transmission and infection development made possible by support from the Anesthesia Patient Safety Foundation (APSF).

Futility of Cluster Designs at Individual Hospitals to Study Surgical Site Infections and Interventions Involving the Installation of Capital Equipment in Operating Rooms.

Anesthesia workspaces are integral components in the chains of many intraoperative bacterial transmission events resulting in surgical site infections (SSI). Matched cohort designs can be used to compare SSI rates among operating rooms (ORs) with or without capital equipment purchases (e.g., new anesthesia machines). Patients receiving care in intervention ORs (i.e., with installed capital equipment) are matched with similar patients receiving care in ORs lacking the intervention. We evaluate statistical power of an alternative design for clinical trials in which, instead, SSI incidences are compared directly among ORs (i.e., the ORs form the clusters) at single hospitals (e.g., the 5 ORs with bactericidal lights vs. the 5 other ORs). Data used for parameter estimates were SSI for 24 categories of procedures among 338 hospitals in the State of California, 2015. Estimated statistical power was ≅8.4% for detecting a reduction in the incidence of SSI from 3.6% to 2.4% over 1 year with 5 intervention ORs and 5 control ORs. For ≅80% statistical power, >20 such hospitals would be needed to complete a study in 1 year. Matched paired cluster designs pair similar ORs (e.g., 2 cardiac ORs, 1 to intervention and 1 to control). With 5 pairs, statistical power would be even less than the estimated 8.4%. Cluster designs (i.e., analyses by OR) are not suitable for comparing SSI among ORs at single hospitals. Even though matched cohort designs are non-randomized and thus have lesser validity, matching patients by their risk factors for SSI is more practical.

Infection control in the operating room: is it more than a clean dish?

PURPOSE OF REVIEW: Healthcare-associated infections (HCAIs) are driven by a complex interplay between host defenses, pathogen traits, and pathogen transmission. A better understanding of each of these factors is required to extend infection control beyond antibiotic therapy to improvements in basic preventive measures that can achieve sustained HCAI reductions. The purpose of this article is to review recent advancements in our understanding of these issues for the operating room environment. RECENT FINDINGS: The importance and implications of intraoperative bacterial transmission have been solidified, and hyper transmissible, virulent, and antibiotic resistant bacterial strains have been characterized. As a result, a best practice for improved intraoperative infection control has been delineated. Little advancement has been made in our understanding of the efficacy of higher inspired oxygen concentrations, improved postoperative glucose control, perioperative normothermia, and prophylactic antibiotic selection, timing, and dose for HCAI prevention. SUMMARY: Recent work has led to the development of evidence-based hand hygiene, environmental cleaning, patient decolonization, and intravascular catheter design and handling improvement strategies. Evidence suggests that a best practice for postoperative infection control is a multimodal program that utilizes these interventions to target patient, provider, and environmental reservoirs in parallel. The development of novel diagnostic tools for targeted attenuation of hyper virulent, transmissible and resistant strains/strain characteristics is indicated to improve patient decolonization efforts.

The dynamics and implications of bacterial transmission events arising from the anesthesia work area.

Health care-associated infections are a hospital-wide concern associated with a significant increase in patient morbidity, mortality, and health care costs. Bacterial transmission in the anesthesia work area of the operating room environment is a root cause of 30-day postoperative infections affecting as many as 16% of patients undergoing surgery. A better understanding of anesthesia-related bacterial transmission dynamics may help to generate improvements in intraoperative infection control and improve patient safety.

Hand hygiene knowledge and perceptions among anesthesia providers.

BACKGROUND: Health care worker compliance with hand hygiene guidelines is an important measure for health care-associated infection prevention, yet overall compliance across all health care arenas remains low. A correct answer to 4 of 4 structured questions pertaining to indications for hand decontamination (according to types of contact) has been associated with improved health care provider hand hygiene compliance when compared to those health care providers answering incorrectly for 1 or more questions. A better understanding of knowledge deficits among anesthesia providers may lead to hand hygiene improvement strategies. In this study, our primary aims were to characterize and identify predictors for hand hygiene knowledge deficits among anesthesia providers. METHODS: We modified this previously tested survey instrument to measure anesthesia provider hand hygiene knowledge regarding the 5 moments of hand hygiene across national and multicenter groups. Complete knowledge was defined by correct answers to 5 questions addressing the 5 moments for hand hygiene and received a score of 1. Incomplete knowledge was defined by an incorrect answer to 1 or more of the 5 questions and received a score of 0. We used a multilevel random-effects XTMELOGIT logistic model clustering at the respondent and geographic location for insufficient knowledge and forward/backward stepwise logistic regression analysis to identify predictors for incomplete knowledge. RESULTS: The survey response rates were 55.8% and 18.2% for the multicenter and national survey study groups, respectively. One or more knowledge deficits occurred with 81.6% of survey respondents, with the mean number of correct answers 2.89 (95% confidence interval, 2.78- 2.99). Failure of providers to recognize prior contact with the environment and prior contact with the patient as hand hygiene opportunities contributed to the low mean. Several cognitive factors were associated with a reduced risk of incomplete knowledge including providers responding positively to washing their hands after contact with the environment (odds ratio [OR] 0.23, 0.14-0.37, P < 0.001), disinfecting their environment during patient care (OR 0.54, 0.35-0.82, P = 0.004), believing that they can influence their colleagues (OR 0.43, 0.27-0.68, P < 0.001), and intending to adhere to guidelines (OR 0.56, 0.36-0.86, P = 0.008). These covariates were associated with an area under receiver operator characteristics curve of 0.79 (95% confidence interval, 0.74-0.83). CONCLUSIONS: Anesthesia provider knowledge deficits around to hand hygiene guidelines occur frequently and are often due to failure to recognize opportunities for hand hygiene after prior contact with contaminated patient and environmental reservoirs. Intraoperative hand hygiene improvement programs should address these knowledge deficits. Predictors for incomplete knowledge as identified in this study should be validated in future studies.

Transmission dynamics of gram-negative bacterial pathogens in the anesthesia work area.

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.

The epidemiology of Staphylococcus aureus transmission in the anesthesia work area.

BACKGROUND: Little is known regarding the epidemiology of intraoperative Staphylococcus aureus transmission. The primary aim of this study was to examine the mode of transmission, reservoir of origin, transmission locations, and antibiotic susceptibility for frequently encountered S aureus strains (phenotypes) in the anesthesia work area. Our secondary aims were to examine phenotypic associations with 30-day postoperative patient cultures, phenotypic growth rates, and risk factors for phenotypic isolation. METHODS: S aureus isolates previously identified as possible intraoperative bacterial transmission events by class of pathogen, temporal association, and analytical profile indexing were subjected to antibiotic disk diffusion sensitivity. The combination of these techniques was then used to confirm S aureus transmission events and to classify them as occurring within or between operative cases (mode). The origin of S aureus transmission events was determined via use of a previously validated experimental model and links to 30-day postoperative patient cultures confirmed via pulsed-field gel electrophoresis. Growth rates were assessed via time-to-positivity analysis, and risk factors for isolation were characterized via logistic regression. RESULTS: One hundred seventy S aureus isolates previously implicated as possible intraoperative transmission events were further subdivided by analytical profile indexing phenotype. Two phenotypes, phenotype P (patients) and phenotype H (hands), accounted for 65% of isolates. Phenotype P and phenotype H contributed to at least 1 confirmed transmission event in 39% and 28% of cases, respectively. Patient skin surfaces (odds ratio [OR], 8.40; 95% confidence interval [CI], 2.30-30.73) and environmental (OR, 10.89; 95% CI, 1.29-92.13) samples were more likely than provider hands (referent) to have phenotype P positivity. Phenotype P was more likely than phenotype H to be resistant to methicillin (OR, 4.38; 95% CI, 1.59-12.06; P = 0.004) and to be linked to 30-day postoperative patient cultures (risk ratio, 36.63 [risk difference, 0.174; 95% CI, 0.019-0.328]; P < 0.001). Phenotype P exhibited a faster growth rate for methicillin resistant and for methicillin susceptible than phenotype H (phenotype P: median, 10.32H; interquartile range, 10.08-10.56; phenotype H: median, 10.56H; interquartile range, 10.32-10.8; P = 0.012). Risk factors for isolation of phenotype P included age (OR, 14.11; 95% CI, 3.12-63.5; P = 0.001) and patient exposure to the hospital ward (OR, 41.11; 95% CI, 5.30-318.78; P < 0.001). CONCLUSIONS: Two S aureus phenotypes are frequently transmitted in the anesthesia work area. A patient and environmentally derived phenotype is associated with increased risk of antibiotic resistance and links to 30-day postoperative patient cultures as compared with a provider hand-derived phenotype. Future work should be directed toward improved screening and decolonization of patients entering the perioperative arena and improved intraoperative environmental cleaning to attenuate postoperative health care-associated infections.

The dynamics of Enterococcus transmission from bacterial reservoirs commonly encountered by anesthesia providers.

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.

Estimation of the contribution to intraoperative pathogen transmission from bacterial contamination of patient nose, patient groin and axilla, anesthesia practitioners' hands, anesthesia machine, and intravenous lumen.

BACKGROUND: Earlier studies showed net cost saving from anesthesia practitioners' use of a bundle of infection prevention products, with feedback on monitored Staphylococcus aureus intraoperative transmission. ESKAPE pathogens also include Enterococcus and gram-negative pathogens: Klebsiella, Acinetobacter, Pseudomonas, and Enterobacter. We evaluated whether bacterial contamination of patient nose, patient groin and axilla, anesthesia practitioners' hands, anesthesia machine, and intravenous lumen all contribute meaningfully to ESKAPE pathogen transmission within anesthesia work areas. METHODS: The retrospective cohort study used bacterial count data from nine hospitals, 43 months, and 448 ESKAPE pathogen transmission events within anesthesia areas of 86 operating rooms. Transmission was measured within and between pairs of successive surgical cases performed in the same operating room on the same day. RESULTS: There were 203 transmission events with S. aureus, 72 with Enterococcus, and 173 with gram negatives. ESKAPE pathogens in the nose contributed to transmission for 50% (99% confidence limit ≥45%) of case pairs, on the groin or axilla for 54% (≥49%), on the hands for 53% (≥47%), on the anesthesia machine for 21% (≥17%), and in the intravenous lumen for 24% (≥20%). ESKAPE pathogens in the nose started a transmission pathway for 27% (≥22%) of case pairs, on the groin or axilla for 24% (≥19%), on the hands for 38% (≥33%), on the anesthesia machine for 11% (≥7.6%), and in the intravenous lumen for 8.0% (≥5.3%). All P ≤ 0.0022 compared with 5%. CONCLUSIONS: To prevent intraoperative ESKAPE pathogen transmission, anesthesia practitioners would need to address all five categories of infection control approaches: nasal antisepsis (e.g., povidone-iodine applied the morning of surgery), skin antisepsis (e.g., chlorhexidine wipes), hand antisepsis with dispensers next to the patient, decontamination of the anesthesia machine before and during anesthetics, and disinfecting caps for needleless connectors, disinfecting port protectors, and disinfecting caps for open female Luer type connectors.

The importance of targeting intraoperative transmission of bacteria with antibiotic resistance and strain characteristics.

BACKGROUND: Evidence-based intraoperative infection control measures can reduce Staphylococcus aureus transmission and infections. We aimed to determine whether transmitted S. aureus isolates were associated with increased risk of multidrug resistance and associated traits. METHODS: S. aureus isolates obtained from intraoperative environmental, patient skin, and provider hand reservoirs among 274 operating room case pairs (1st and 2nd case of the day) across 3 major academic medical centers from March 2009 to February 2010 underwent systematic-phenotypic-genomic analysis to identify clonal transmission events. The association of clonal S. aureus transmission with multidrug resistance and resistance traits was investigated. Transmission dynamics were characterized. RESULTS: Transmitted isolates (N=58) were associated with increased risk of multi-drug antibiotic resistance [33% (19/58) transmitted vs. 10% (12/115) other isolates, risk ratio 3.14, 99% CI 1.34-7.38, P=0.0006]. Transmission was associated with a significant increase in resistance traits including mecA [40% transmitted isolates vs. 17% other isolates, risk ratio 2.28, P=0.0026] and ant (6)-Ia [26% transmitted isolates vs. 9% other isolates, risk ratio 2.97, P=0.0050]. Provider hands were a frequent reservoir of origin, between-case a common mode of transmission, and patient skin and provider hands frequent transmission locations for multidrug resistant pathogens. CONCLUSIONS: Intraoperative S. aureus transmission was associated with multidrug resistance and resistance traits. Proven infection control measures should be leveraged to target intraoperative transmission of multidrug resistant pathogens.