Wanta, Brendan T.

Background/Objectives: Retained airway secretions are a common complication of mechanical ventilation and a major contributor to ventilator-associated pneumonia. Airway Pressure Release Ventilation following a Time-Controlled Adaptive Ventilation protocol (APRV-TCAV) has been anecdotally observed to improve secretion clearance, but the mechanism is not well established. Because TCAV sets the release time (TLow) from each patient’s own expiratory flow decay, we hypothesized that the resulting expiratory-dominant flow profile would generate a net antegrade force on secretions. This bench study compared secretion movement between APRV-TCAV and conventional Volume-Control Continuous Mandatory Ventilation (VC-CMV), with and without an in-line oscillatory device. Methods: A critical care ventilator was connected to a 3 L test lung via a 7 mm endotracheal tube (ETT). Simulated mucus (1% guar gum) was instilled into the ETT, and secretion movement was measured under VC-CMV (positive end-expiratory pressure (PEEP) 5, 10, 15 cmH2O) and APRV-TCAV (PHigh 20, 25, 30 cmH2O; PLow 0 cmH2O). Each condition was repeated with an in-line oscillatory device. Results: All VC-CMV settings produced retrograde secretion movement toward the test lung; all APRV-TCAV settings produced antegrade movement. The largest antegrade movement was observed at the widest PHigh-to-PLow differential. Adding the oscillatory device raised peak expiratory flow above peak inspiratory flow in every condition, yet abolished antegrade movement under APRV-TCAV. Conclusions: In this bench study, APRV-TCAV reversed the direction of secretion movement within the ETT, with larger antegrade movement at wider PHigh-to-PLow differentials. This suggests a potential mechanism by which the ventilator flow profile itself may influence secretion movement. The directional effect depended on the intact release-phase waveform and was abolished by in-line oscillatory therapy despite preserved peak flow asymmetry.

BACKGROUND: Improved cleaning in the anesthesia workspace is important for surgical site infection prevention. We sought to identify high-priority cleaning targets to guide post-induction surface disinfection and use of a triangular ultraviolet-C (UV-C) configuration involving placement of one emitter at the head and one on each side of the surgical bed. METHODS: The 20 sites most frequently touched by anesthesia practitioners, previously identified via video-based workflow analysis, were filtered to remove disposable (eg, stopcocks) and transient (eg, the patient bed) sites, leaving durable cleaning targets amenable to repeated surface disinfection and UV-C irradiation within and/or between cases. Inequality in the distribution of cleaning target touches was quantified using the Gini coefficient, and uncertainty was estimated using bootstrap resampling (10,000 iterations). We then assessed residual contamination after standard terminal cleaning across three operating rooms and 171 sites to evaluate the difficulty of cleaning high-touch surfaces and the efficacy of UV-C disinfection. Simulations using medical devices composed of materials representative of cleaning targets contaminated with high-level Clostridium difficile were conducted to evaluate generalizability to more resistant pathogens. RESULTS: There were 13 of 20 frequently touched sites that were considered durable cleaning targets. Touches were relatively equal among the 13 cleaning targets (Gini coefficient 0.16, 95% confidence interval [CI], 0.12–0.20). Cleaning targets included components of the anesthesia cart (first and second drawer handles); anesthesia machine (reservoir bag, circuit ventilator control, oxygen dial, vaporizer dial, adjustable pressure-limiting valve), monitoring equipment (screen buttons/knob, electrocardiogram leads); and room infrastructure (intravenous pole, operating room table and chair). Residual contamination after cleaning was identified at 4% (7/171) of sites, mostly (6/7) within the anesthesia workspace, involving the anesthesia cart (N = 2), machine (N = 3), and monitor (N = 1). Only one site outside of the anesthesia workspace, the circulating nurse’s mouse, had residual contamination. Triangular UV-C reduced mean (standard deviation [SD]) colony-forming units (CFU) from 60.47 (542.22) to 0.12 (1.08), achieving a 2.7-log reduction. Simulation with high-level C. difficile contamination demonstrated ≥3-log reductions on surfaces representative of high-touch sites, confirming applicability to resistant pathogens. CONCLUSIONS: Thirteen durable cleaning targets in the anesthesia workspace are largely equivalent in terms of risk of touch. They are amenable to UV-C augmentation of surface disinfection in the real-world clinical environment. These findings can guide targeted post-induction cleaning and use of triangular UV-C, particularly for surfaces with substantial contamination or resistant pathogens.

Background. The assessment of perioperative risk factors for the development of acute respiratory distress syndrome (ARDS) has been described in various surgical populations. However, there are only limited data among patients undergoing liver transplantation (LT), particularly regarding the influence of intraoperative ventilation parameters. We sought to identify the perioperative risk factors associated with the development of ARDS in LT recipients. Methods. This is a single-center, retrospective cohort study of adult patients who underwent LT at a tertiary academic medical center between January 1, 2006, and January 31, 2016. Postoperative ARDS was identified using the Berlin definition. Multivariable logistic regression analysis was used to identify perioperative risk factors for ARDS. Results. Of 817 eligible patients who underwent an LT during the study period, 20 (2.45%) developed postoperative ARDS. In the preoperative model, ongoing dialysis (odds ratio, 6.41; P < 0.01) was identified as an independent risk factor of ARDS post-LT. A higher mean peak inspiratory pressure per increase of 1 cm H2O (odds ratio, 1.31; P < 0.01) was the only independent risk factor in the intraoperative model. Patients who developed ARDS postoperatively had significantly greater intensive care unit and hospital stay compared to non-ARDS patients (P < 0.001). There were no significant differences in the 30-day (P = 0.16) and 1-year (P = 0.51) mortality between the groups. Conclusions. Dialysis at the time of transplant and elevated intraoperative mean peak inspiratory pressure were associated with the development of ARDS. ARDS post LT was associated with increased intensive care unit and hospital length of stay, but not increased mortality.

Purpose: Data regarding best practices for ventilator management strategies that improve outcomes in acute respiratory distress syndrome (ARDS) are readily available. However, little is known regarding processes to ensure compliance with these strategies. We developed a goal-directed mechanical ventilation order set that included physician-specified lung-protective ventilation and oxygenation goals to be implemented by respiratory therapists (RTs). We sought as a primary outcome to determine whether an RT-driven order set with predefined oxygenation and ventilation goals could be implemented and associated with improved adherence with best practice. Methods: We evaluated 1302 patients undergoing invasive mechanical ventilation (1693 separate episodes of invasive mechanical ventilation) prior to and after institution of a standardized, goal-directed mechanical ventilation order set using a controlled before-and-after study design. Patient-specific goals for oxygenation partial pressure of oxygen in arterial blood (Pao 2 ), ARDS Network [Net] positive end-expiratory pressure [PEEP]/fraction of inspired oxygen [Fio 2 ] table use) and ventilation (pH, partial pressure of carbon dioxide) were selected by prescribers and implemented by RTs. Results: Compliance with the new mechanical ventilation order set was high: 88.2% compliance versus 3.8% before implementation of the order set ( P < .001). Adherence to the PEEP/Fio 2 table after implementation of the order set was significantly greater (86.0% after vs 82.9% before, P = .02). There was no difference in duration of mechanical ventilation, intensive care unit (ICU) length of stay, and in-hospital or ICU mortality. Conclusions: A standardized best practice mechanical ventilation order set can be implemented by a multidisciplinary team and is associated with improved compliance to written orders and adherence to the ARDSNet PEEP/Fio 2 table.

Abstract Background: Surgical site infections (SSI) contribute to surgical patients' morbidity and costs. Operating room traffic may be a modifiable risk factor for SSI. We investigated the impact of additional operating room personnel on the risk of superficial SSI (sSSI). Patients and Methods: In this matched case-control study, cases included patients in whom sSSI developed in clean surgical incisions after elective, daytime operations. Control subjects were matched by age, gender, and procedure. Operating room personnel were classified as (1) surgical scrubbed, (2) surgical non-scrubbed, or (3) anesthesia. We used conditional logistic regression to test the extent to which additional personnel overall and from each work group were associated with infection. Results: In total, 474 patients and 803 control subjects were identified. Each additional person among total personnel and personnel from each work group was significantly associated with greater odds of infection (all personnel, odds ratio [OR] = 1.082, 95% confidence interval [CI] 1.031–1.134, p = 0.0013; surgical scrubbed OR = 1.132, 95% CI 1.029–1.245, p = 0.0105; surgical non-scrubbed OR = 1.123, 95% CI 1.008–1.251, p = 0.0357; anesthesia OR = 1.153, 95% CI 1.031–1.290, p = 0.0127). After adjusting for operative duration, body mass index, diabetes mellitus, and vascular disease, additional personnel and sSSI were no longer associated overall or for any work groups (total personnel OR = 1.033, 95% CI 0.974–1.095, p = 0.2746; surgical scrubbed OR = 1.060, 95% CI 0.952-1.179, p = 0.2893; surgical non-scrubbed OR = 1.023 95% CI 0.907–1.154, p = 0.7129; anesthesia OR = 1.051, 95% CI 0.926–1.193, p = 0.4442). Conclusion: The presence of additional operating room personnel was not independently associated with increased odds of sSSI. Efforts dedicated to sSSI reduction should focus on other modifiable risk factors.