Standardized protocol for ultrasound diagnosis of the lungs with COVID-19

BACKGROUND. The era of coronavirus disease (COVID-19) set the such task for lung ultrasound (LUS): to identify presence COVID-pneumonia, its differential diagnosis with other conditions which characterized by interstitial edema, determining severity damage and location, dynamics pulmonary changes tissue, development complications, as well assess effectiveness personalized therapy.
 OBJECTIVE. To develop a national LUS protocol COVID-19 based on balance completeness information optimal minimum time effort medical staff, who often do not specialize in using, equipment basic middle classes.
 MATERIALS AND METHODS. A total 1576 patients were examined. There 810 women (51.4 %) 766 men (48.6 %). age examined was range 18-83 years, average 52.3±14.6 years. 4710 performed, 1572 repeated 3144 – dynamics. Polysystemic performed 275 patients. Ultrasound devices both domestic foreign production used: Soneus P7 (Ultrasine, Ukraine), HandyUsound (Ukraine), Xario, USAP-770A (Toshiba, Japan), GE Venue (General Electric, USA) TE7 COVID (Mindray, China) probes convex, linear microconvex formats.
 RESULTS. Summarizing our own experience 2020-2021, we have developed version LUS-protocol, has convenient form recording all stages maximum coverage entire volume lungs according clear algorithm, graphical form, semiotics diagnostic scoring criteria damage.
 CONCLUSIONS. 1. Clinical data indicate feasibility using dynamic monitoring pneumonia caused SARS-CoV-2, especially oxygen-dependent at their bedside (POCUS principle). 2. Optimization use radiological methods due makes it possible reduce radiation dose patient.3. allows more adequate decision-making need intensive interventional therapy, leads faster diagnosis, improved care, reduced length stay ICU, reducing cost treatment.4. Ability impact SARS-CoV-2 healthcare professionals limiting physical contact patient. 5. standardized Ukrainian provides availability, efficiency interpretation received different doctors institutions. integration machine optimization workflow process.