Guntupalli, Siva Kamal

Purpose Survivors of critical illness often acquire significant physical, cognitive, and psychological burdens following their intensive care unit (ICU) stay, termed “post-intensive care syndrome” (PICS). Screening for PICS is generally not performed outside of research settings largely due to lack of a simple assessment tool and time constraints. Methods This was a prospective cohort study at a single academic medical center in the USA. We included adults (18 years or older) who spent greater than 48 h in any ICU within the medical center. Following transfer out of the ICU and at 3 months, psychological, cognitive, and physical functioning were assessed using the Hospital Anxiety and Depression Scale, Impact of Event Scale-Revised, Montreal Cognitive Assessment-blind, and Barthel Index. We compared these validated questionnaires to a brief, 15-item PICS screening tool (5 questions/domain) that was developed by our multidisciplinary study team and administered to study participants after ICU discharge to general care. The primary objectives of this study were to assess the ability of validated screening tools administered at ICU discharge to predict PICS at 3 months and develop a novel screening tool for identifying patients at risk of PICS. Major Findings 191 participants completed the initial questionnaire, and 109 (56%) completed the 3-month follow-up. PICS tool scores were compared to 3-month follow-up data from validated questionnaires to evaluate predictive performance. Overall, the screening tool weakly-to-moderately correlated with continuous outcomes of the validated measures at 3-month follow-up. When evaluating sensitivity and specificity for individual domains, the screening tool had an area under curve of >0.7 for all three domains, indicating moderate-to-good sensitivity and specificity. Conclusions We developed a brief PICS screening tool that is feasible to use without prior training that modestly predicted the development of PICS following ICU stay.

BACKGROUND: Methacholine bronchoprovocation or challenge testing (MCT) is commonly performed to assess airway hyper-responsiveness in the setting of suspected asthma. Nebulization is an aerosol-generating procedure, but little is known about the risks of MCT in the context of the ongoing coronavirus disease 2019 (COVID-19) pandemic. We aimed to quantify and characterize aerosol generation during MCT by using different delivery methods and to assess the impact of adding a viral filter. METHODS: Seven healthy subjects performed simulated MCT in a near particle-free laboratory space with 4 different nebulizers and with a dosimeter. Two devices continuously sampled the ambient air during the procedure, which detected ultrafine particles, from 0.02–1 μm, and particles of sizes 0.3, 0.5, 1.0, 2.0, 5.0, and 10 µm, respectively. Particle generation was compared among all the devices, with and without viral filter placement. RESULTS: Ultrafine-particle generation during simulated MCT was significant across all the devices. Ultrafine-particle (0.02–1 μm) concentrations decreased 77%–91% with the addition of a viral filter and varied significantly between unfiltered (P < .001) and filtered devices (P < .001). Ultrafine-particle generation was lowest when using the dosimeter with filtered Hudson nebulizer (1,258 ± 1,644 particle/mL). Ultrafine-particle concentrations with the filtered nebulizer devices using a compressor were higher than particle concentrations detected when using the dosimeter: Monaghan (3,472 ± 1,794 particles/mL), PARI (4,403 ± 2,948), Hudson (6,320 ± 1,787) and AirLife (9,523 ± 5,098). CONCLUSIONS: The high particle concentrations generated during MCT pose significant infection control concerns during the COVID-19 pandemic. Particle generation during MCT was significantly reduced by using breath-actuated delivery and a viral filter, which offers an effective mitigation strategy.

BACKGROUND: Peak flow testing is a common procedure performed in ambulatory care. There are currently no data regarding aerosol generation during this procedure. Given the ongoing debate regarding the potential for aerosol transmission of SARS-CoV-2, we aimed to quantify and characterize aerosol generation during peak flow testing. METHODS: Five healthy volunteers performed peak flow maneuvers in a particle-free laboratory space. Two devices continuously sampled the ambient air during the procedure. One device can detect ultrafine particles 0.02–1 μ m in diameter, while the second device can detect particles 0.3, 0.5, 1.0, 2.0, 5.0, and 10 μ m in diameter. Five different peak flow meters were compared to ambient baseline during masked and unmasked tidal breathing. RESULTS: Ultrafine particles (0.02–1 μ m) were generated during peak flow measurement. There was no significant difference in ultrafine particle mean concentration between peak flow meters ( P = .23): Respironics (1.25 ± 0.47 particles/mL), Philips (3.06 ± 1.22), Clement Clarke (3.55 ± 1.22 particles/mL), Respironics Low Range (3.50 ± 1.52 particles/mL), and Monaghan (3.78 ± 1.31 particles/mL). Ultrafine particle mean concentration with peak flow testing was significantly higher than masked (0.22 ± 0.29 particles/mL) and unmasked tidal breathing (0.15 ± 0.18 particles/mL, P = .01), but the ultrafine particle concentrations were small compared to ambient particle concentrations in a pulmonary function testing room (89.9 ± 8.95 particles/mL). CONCLUSIONS: In this study, aerosol generation was present during peak flow testing, but concentrations were small compared to the background particle concentration in the ambient clinical environment. Surgical masks and eye protection are likely sufficient infection control measures during peak expiratory flow testing in asymptomatic patients with well controlled respiratory symptoms, but COVID-19 testing remains prudent in patients with acute respiratory symptoms prior to evaluation and peak expiratory flow assessment while the community prevalence of SARS-CoV-2 cases remains high.