The role of lung ultrasonography in COVID-19 disease management.

Coronavirus disease 2019 (COVID-19) has created unprecedented disruption for global healthcare systems. Offices and emergency departments (EDs) were the first responders to the pandemic, followed by medical wards and intensive care unit (ICUs). Worldwide efforts sprouted to coordinate proper response by increasing surge capacity and optimizing diagnosis and containment. Within the complex scenario of the outbreak, the medical community shared scientific research and implemented best-guess imaging strategies in order to save time and additional staff exposures. Early publications showed agreement between chest computed tomography (CT) and lung sonography: widespread ground-glass findings resembling acute respiratory distress syndrome (ARDS) on CT of COVID-19 patients matched lung ultrasound signs and patterns. Well-established accuracy of bedside sonography for lung conditions and its advantages (such as no ionizing radiation; low-cost, real-time bedside imaging; and easier disinfection steps) prompted a wider adoption of lung ultrasound for daily assessment and monitoring of COVID-19 patients. Growing literature, webinars, online materials, and international networks are promoting lung ultrasound for the same purpose. We propose 11 lung ultrasound roles for different medical settings during the pandemic, starting from the out-of-hospital setting, where lung ultrasound has ergonomic and infection control advantages. Then we describe how medical wards and ICUs can safely integrate lung ultrasound into COVID-19 care pathways. Finally, we present outpatient use of lung ultrasound to aid follow-up of positive case contacts and of those discharged from the hospital.

The COVID-19 Worsening Score (COWS)-a predictive bedside tool for critical illness.

OBJECTIVES: To evaluate the accuracy of a new COVID-19 prognostic score based on lung ultrasound (LUS) and previously validated variables in predicting critical illness. METHODS: We conducted a single-center retrospective cohort development and internal validation study of the COVID-19 Worsening Score (COWS), based on a combination of the previously validated COVID-GRAM score (GRAM) variables and LUS. Adult COVID-19 patients admitted to the emergency department (ED) were enrolled. Ten variables previously identified by GRAM, days from symptom onset, LUS findings, and peripheral oxygen saturation/fraction of inspired oxygen (P/F) ratio were analyzed. LUS score as a single predictor was assessed. We evaluated GRAM model's performance, the impact of adding LUS, and then developed a new model based on the most predictive variables. RESULTS: Among 274 COVID-19 patients enrolled, 174 developed critical illness. The GRAM score identified 51 patients at high risk of developing critical illness and 132 at low risk. LUS score over 15 (range 0 to 36) was associated with a higher risk ratio of critical illness (RR, 2.05; 95% confidence interval [CI], 1.52-2.77; area under the curve [AUC], 0.63; 95% CI 0.676-0.634). The newly developed COVID-19 Worsening Score relies on five variables to classify high- and low-risk patients with an overall accuracy of 80% and negative predictive value of 93% (95% CI, 87%-98%). Patients scoring more than 0.183 on COWS showed a RR of developing critical illness of 8.07 (95% CI, 4.97-11.1). CONCLUSIONS: COWS accurately identify patients who are unlikely to need intensive care unit (ICU) admission, preserving resources for the remaining high-risk patients.

Diaphragmatic thickening fraction as a potential predictor of response to continuous positive airway pressure ventilation in Covid-19 pneumonia: A single-center pilot study.

BACKGROUND: In a variable number of Covid-19 patients with acute respiratory failure, non-invasive breathing support strategies cannot provide adequate oxygenation, thus making invasive mechanical ventilation necessary. Factors predicting this unfavorable outcome are unknown, but we hypothesized that diaphragmatic weakness may contribute. METHODS: We prospectively analyzed the data of 27 consecutive patients admitted to the general Intensive Care Unit (ICU) from March 19, 2020, to April 20, 2020 and submitted to continuous positive airway pressure (CPAP) before considering invasive ventilation. Diaphragmatic thickening fraction (DTF) inferred by ultrasound was determined before applying CPAP. RESULTS: Eighteen patients recovered with CPAP, whereas nine required invasive mechanical ventilation with longer stay in ICU (p < 0.001) and hospital (p = 0.003). At univariate logistic regression analysis, CPAP failure was significantly associated with low DTF [ß: -0.396; OR: 0.673; p < 0.001] and high respiratory rate [ß: 0.452; OR: 1.572; p < 0.001] but only DTF reached statistical significance at multivariate analysis [ß: -0.384; OR: 0.681; p < 0.001]. The DTF best threshold predicting CPAP failure was 21.4 % (AUC: 0.944; sensitivity: 94.4 %, specificity: 88.9 %). CONCLUSIONS: In critically ill patients with Covid-19 respiratory failure admitted to ICU, a reduced DTF could be a potential predictor of CPAP failure and requirement of invasive ventilation.

A Gas-Powered, Patient-Responsive Automatic Resuscitator for Use in Acute Respiratory Failure: A Bench and Experimental Study.

BACKGROUND: During the COVID-19 pandemic, a need for innovative, inexpensive, and simple ventilator devices for mass use has emerged. The Oxylator (CPR Medical Devices, Markham, Ontario, Canada) is an FDA-approved, fist-size, portable ventilation device developed for out-of-hospital emergency ventilation. It has not been tested in conditions of severe lung injury or with added PEEP. We aimed to assess the performance and reliability of the device in simulated and experimental conditions of severe lung injury, and to derive monitoring methods to allow the delivery of safe, individualized ventilation during situations of surge. METHODS: We bench-tested the functioning of the device with an added PEEP valve extensively, mimicking adult patients with various respiratory mechanics during controlled ventilation, spontaneous breathing, and prolonged unstable conditions where mechanics or breathing effort was changed at every breath. The device was further tested on a porcine model (4 animals) after inducing lung injury, and these results were compared with conventional ventilation modes. RESULTS: The device was stable and predictable, delivering a constant flow (30 L/min) and cycling automatically at the inspiratory pressure set (minimum of 20 cm H2O) above auto-PEEP. Changes in respiratory mechanics manifested as changes in respiratory timing, allowing prediction of tidal volumes from breathing frequency. Simulating lung injury resulted in relatively low tidal volumes (330 mL with compliance of 20 mL/cm H2O). In the porcine model, arterial oxygenation, CO2, and pH were comparable to conventional modes of ventilation. CONCLUSIONS: The Oxylator is a simple device that delivered stable ventilation with tidal volumes within a clinically acceptable range in bench and porcine lung models with low compliance. External monitoring of respiratory timing is advisable, allowing tidal volume estimation and recognition of changes in respiratory mechanics. The device can be an efficient, low-cost, and practical rescue solution for providing short-term ventilatory support as a temporary bridge, but it requires a caregiver at the bedside.