Infectious Disease

Pham, V., Nguyen, L., Hedin, R.J., Shaver, C., Hammonds, K.A.P. and Culp, W.C., Jr. (2021). “Coronavirus Disease 2019: Anesthesia Machine Circuit Pressure During Use as an Improvised Intensive Care Unit Ventilator.” Anesth Analg 132(5): 1191-1198.

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BACKGROUND: Use of anesthesia machines as improvised intensive care unit (ICU) ventilators may occur in locations where waste anesthesia gas suction (WAGS) is unavailable. Anecdotal reports suggest as much as 18 cm H2O positive end-expiratory pressure (PEEP) being inadvertently applied under these circumstances, accompanied by inaccurate pressure readings by the anesthesia machine. We hypothesized that resistance within closed anesthesia gas scavenging systems (AGSS) disconnected from WAGS may inadvertently increase circuit pressures. METHODS: An anesthesia machine was connected to an anesthesia breathing circuit, a reference manometer, and a standard bag reservoir to simulate a lung. Ventilation was initiated as follows: volume control, tidal volume (TV) 500 mL, respiratory rate 12, ratio of inspiration to expiration times (I:E) 1:1.9, fraction of inspired oxygen (Fio2) 1.0, fresh gas flow (FGF) rate 2.0 liters per minute (LPM), and PEEP 0 cm H2O. After engaging the ventilator, PEEP and peak inspiratory pressure (PIP) were measured by the reference manometer and the anesthesia machine display simultaneously. The process was repeated using prescribed PEEP levels of 5, 10, 15, and 20 cm H2O. Measurements were repeated with the WAGS disconnected and then were performed again at FGF of 4, 6, 8, 10, and 15 LPM. This process was completed on 3 anesthesia machines: Dräger Perseus A500, Dräger Apollo, and the GE Avance CS2. Simple linear regression was used to assess differences. RESULTS: Utilizing nonparametric Bland-Altman analysis, the reference and machine manometer measurements of PIP demonstrated median differences of -0.40 cm H2O (95% limits of agreement [LOA], -1.00 to 0.55) for the Dräger Apollo, -0.40 cm H2O (95% LOA, -1.10 to 0.41) for the Dräger Perseus, and 1.70 cm H2O (95% LOA, 0.80-3.00) for the GE Avance CS2. At FGF 2 LPM and PEEP 0 cm H2O with the WAGS disconnected, the Dräger Apollo had a difference in PEEP of 0.02 cm H2O (95% confidence interval [CI], -0.04 to 0.08; P = .53); the Dräger Perseus A500, <0.0001 cm H2O (95% CI, -0.11 to 0.11; P = 1.00); and the GE Avance CS2, 8.62 cm H2O (95% CI, 8.55-8.69; P < .0001). After removing the hose connected to the AGSS and the visual indicator bag on the GE Avance CS2, the PEEP difference was 0.12 cm H2O (95% CI, 0.059-0.181; P = .0002). CONCLUSIONS: Displayed airway pressure measurements are clinically accurate in the setting of disconnected WAGS. The Dräger Perseus A500 and Apollo with open scavenging systems do not deliver inadvertent continuous positive airway pressure (CPAP) with WAGS disconnected, but the GE Avance CS2 with a closed AGSS does. This increase in airway pressure can be mitigated by the manufacturer's recommended alterations. Anesthesiologists should be aware of the potential clinically important increases in pressure that may be inadvertently delivered on some anesthesia machines, should the WAGS not be properly connected.

Wu, M.J., Chung, J.R., Kim, S.S., Jackson, M.L., Jackson, L.A., Belongia, E.A., McLean, H.Q., Gaglani, M., Reis, M., Beeram, M., Martin, E.T., Monto, A.S., Nowalk, M.P., Zimmerman, R., Santibanez, T.A., Singleton, J.A., Patel, M. and Flannery, B. (2021). “Influenza vaccination coverage among persons seeking outpatient medical care for acute respiratory illness in five states in the United States, 2011-2012 through 2018-2019.” Vaccine 39(12): 1788-1796.

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BACKGROUND: In the United States (U.S.), annual influenza vaccination has been recommended for all persons aged ≥6 months with the Healthy People 2020 coverage target of 70%. However, vaccination coverage has remained around 42-49% during the past eight influenza seasons. We sought to quantify influenza vaccination coverage and factors associated with vaccination in persons seeking outpatient medical care for an acute respiratory illness (ARI). METHODS: We enrolled outpatients aged ≥6 months with ARI from >50 U.S. clinics from 2011 to 2012 through 2018-2019 influenza seasons and tested for influenza with molecular assays. Vaccination status was based on documented receipt of the current season’s influenza vaccine. We estimated vaccination coverage among influenza-negative study participants by study site, age, and season, and compared to state-level influenza coverage estimates in the general population based on annual immunization surveys. We used multivariable logistic regression to examine factors independently associated with receipt of influenza vaccines. RESULTS: We enrolled 45,424 study participants with ARI who tested negative for influenza during the study period. Annual vaccination coverage among influenza-negative ARI patients and the general population in the participating states averaged 55% (range: 47-62%), and 52% (range: 46-54%), respectively. Among enrollees, coverage was highest among adults aged ≥65 years (82%; range, 80-85%) and lowest among adolescents aged 13-17 years (38%; range, 35-41%). Factors significantly associated with non-vaccination included non-White race, no college degree, exposure to cigarette smoke, absence of high-risk conditions, and not receiving prior season influenza vaccine. CONCLUSIONS: Influenza vaccination coverage over eight seasons among outpatients with non-influenza respiratory illness was slightly higher than coverage in the general population but 15% lower than national targets. Increased efforts to promote vaccination especially in groups with lower coverage are warranted to attain optimal health benefits of influenza vaccine.

McCullough, P.A. and Vijay, K. (2021). “SARS-CoV-2 infection and the COVID-19 pandemic: a call to action for therapy and interventions to resolve the crisis of hospitalization, death, and handle the aftermath.” Rev Cardiovasc Med 22(1): 9-10.

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In this bold issue of Reviews in Cardiovascular Medicine, we present the most comprehensive and scalable early ambulatory treatment program for high-risk patients who have contracted SARS-CoV-2. No such published regimen has received so much acclaim and the concepts embodied in this paper have been responsible for saving hundreds of thousands of lives and sparing millions of hospitalization. Since it took months for the large body of information to congeal on the pathophysiology and rationale for treatment, we cannot go back in time and estimate avoidable losses [6]. Going forward, available sources of data from Zelenko and Procter, suggest available drugs used in combination can reduce hospitalizations and death by 85% and that no high-risk patient with COVID-19 should go untreated at home. Lack of home treatment can only lead to long durations of illness, more intense symptoms, and increases the risk of hospitalization, death, and potentially post-COVID-19 syndromes. At this point in time, there is no justification in any part of the world for denial of available, appropriately prescribed off label intracellular anti-infectives, corticosteroids/colchicine, and antithrombotics. [No abstract; excerpt from article].

Jackson, M.L., Ferdinands, J., Nowalk, M.P., Zimmerman, R.K., Kieke, B., Gaglani, M., Murthy, K., Petrie, J.G., Martin, E.T., Chung, J.R., Flannery, B. and Jackson, L.A. (2021). “Differences between Frequentist and Bayesian inference in routine surveillance for influenza vaccine effectiveness: a test-negative case-control study.” BMC Public Health 21(1): 516.

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BACKGROUND: Routine influenza vaccine effectiveness (VE) surveillance networks use frequentist methods to estimate VE. With data from more than a decade of VE surveillance from diverse global populations now available, using Bayesian methods to explicitly account for this knowledge may be beneficial. This study explores differences between Bayesian vs. frequentist inference in multiple seasons with varying VE. METHODS: We used data from the United States Influenza Vaccine Effectiveness (US Flu VE) Network. Ambulatory care patients with acute respiratory illness were enrolled during seasons of varying observed VE based on traditional frequentist methods. We estimated VE against A(H1N1)pdm in 2015/16, dominated by A(H1N1)pdm; against A(H3N2) in 2017/18, dominated by A(H3N2); and compared VE for live attenuated influenza vaccine (LAIV) vs. inactivated influenza vaccine (IIV) among children aged 2-17 years in 2013/14, also dominated by A(H1N1)pdm. VE was estimated using both frequentist and Bayesian methods using the test-negative design. For the Bayesian estimates, prior VE distributions were based on data from all published test-negative studies of the same influenza type/subtype available prior to the season of interest. RESULTS: Across the three seasons, 16,342 subjects were included in the analyses. For 2015/16, frequentist and Bayesian VE estimates were essentially identical (41% each). For 2017/18, frequentist and Bayesian estimates of VE against A(H3N2) viruses were also nearly identical (26% vs. 23%, respectively), even though the presence of apparent antigenic match could potentially have pulled Bayesian estimates upward. Precision of estimates was similar between methods in both seasons. Frequentist and Bayesian estimates diverged for children in 2013/14. Under the frequentist approach, LAIV effectiveness was 62 percentage points lower than IIV, while LAIV was only 27 percentage points lower than IIV under the Bayesian approach. CONCLUSION: Bayesian estimates of influenza VE can differ from frequentist estimates to a clinically meaningful degree when VE diverges substantially from previous seasons.

Doyle, J.D., Beacham, L., Martin, E.T., Talbot, H.K., Monto, A., Gaglani, M., Middleton, D.B., Silveira, F.P., Zimmerman, R.K., Alyanak, E., Smith, E.R., Flannery, B.L., Rolfes, M. and Ferdinands, J.M. (2021). “Relative and Absolute Effectiveness of High-Dose and Standard-Dose Influenza Vaccine Against Influenza-Related Hospitalization Among Older Adults-United States, 2015-2017.” Clin Infect Dis 72(6): 995-1003.

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BACKGROUND: Seasonal influenza causes substantial morbidity and mortality in older adults. High-dose inactivated influenza vaccine (HD-IIV), with increased antigen content compared to standard-dose influenza vaccines (SD-IIV), is licensed for use in people aged ≥65 years. We sought to evaluate the effectiveness of HD-IIV and SD-IIV for prevention of influenza-associated hospitalizations. METHODS: Hospitalized patients with acute respiratory illness were enrolled in an observational vaccine effectiveness study at 8 hospitals in the United States Hospitalized Adult Influenza Vaccine Effectiveness Network during the 2015-2016 and 2016-2017 influenza seasons. Enrolled patients were tested for influenza, and receipt of influenza vaccine by type was recorded. Effectiveness of SD-IIV and HD-IIV was estimated using a test-negative design (comparing odds of influenza among vaccinated and unvaccinated patients). Relative effectiveness of SD-IIV and HD-IIV was estimated using logistic regression. RESULTS: Among 1487 enrolled patients aged ≥65 years, 1107 (74%) were vaccinated; 622 (56%) received HD-IIV, and 485 (44%) received SD-IIV. Overall, 277 (19%) tested positive for influenza, including 98 (16%) who received HD-IIV, 87 (18%) who received SD-IIV, and 92 (24%) who were unvaccinated. After adjusting for confounding variables, effectiveness of SD-IIV was 6% (95% confidence interval [CI] -42%, 38%) and that of HD-IIV was 32% (95% CI -3%, 54%), for a relative effectiveness of HD-IIV versus SD-IIV of 27% (95% CI -1%, 48%). CONCLUSIONS: During 2 US influenza seasons, vaccine effectiveness was low to moderate for prevention of influenza hospitalization among adults aged ≥65 years. High-dose vaccine offered greater effectiveness. None of these findings were statistically significant.