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Data on respiratory mechanics and gas exchange in acute respiratory failure in COVID-19 patients is limited. Knowledge of respiratory mechanics and gas exchange in COVID-19 can lead to different selection of mechanical ventilation strategy, reduce ventilator-associated lung injury and improve outcomes. The objective of the study is to evaluate the respiratory mechanics, lung recruitability and gas exchange in COVID-19 -associated acute respiratory failure during the whole course of mechanical ventilation - invasive or non-invasive.
In December 2019, an outbreak of a novel coronavirus (SARS-CoV-2) emerged in Wuhan, China and rapidly spread worldwide. The World Health Organization (WHO) declared the outbreak a pandemic on March 11th, 2020. The clinical disease (COVID-19) results in critical illness in about 5% of patients with predominant acute respiratory failure.
The goal of the study is the evaluation of the respiratory mechanics (peak inspiratory pressure (PIP), plateau pressure (Pplat), static compliance (Cstat), driving pressure (DP) at different positive end-expiratory pressure (PEEP) levels and different tidal volumes (Vt) (6-8 ml/kg ideal body weight), lung recruitability (by change of DP and oxygenation) and gas exchange (PaO2/FiO2 ratio and alveolar dead space) in COVID-19 -associated acute respiratory failure during the whole course of mechanical ventilation - invasive or non-invasive for selection of safe and effective PEEP level, Vt, respiratory rate (RR) and inspiratory oxygen fraction (FiO2) during the whole course of mechanical ventilation - invasive or non-invasive.
This study is multicentral observational trial in 3 University clinics.
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Respiratory mechanics measurement | Diagnostic Test | Measurement of peak inspiratory pressure, plateau pressure, calculation of static compliance and driving pressure | ||
| Gas exchange measurement | Diagnostic Test | Measurement of arterial oxygen and tension and arterial dioxide tension, calculation of arterial partial oxygen tension to inspiratory oxygen fraction (PaO2/FiO2) ratio and alveolar dead space |
| Measure | Description | Time Frame |
|---|---|---|
| Optimum positive end-expiratory pressure (PEEP) level | Positive end-expiratory pressure (PEEP) selection at minimum level with maximum static compliance and the highest peripheral capillary oxygen saturation over fraction of inspired oxygen (SpO2/FiO2) | On day 1 during mechanical ventilation |
| Optimum positive end-expiratory pressure (PEEP) level | Positive end-expiratory pressure (PEEP) selection at minimum level with maximum static compliance and the highest peripheral capillary oxygen saturation over fraction of inspired oxygen (SpO2/FiO2) | On day 7 during mechanical ventilation |
| Number of patients with recruitable lung | Peripheral capillary oxygen saturation (SpO2) change from 90% after recruitment maneuver (doubled tidal volume for 15 respiratory cycles) - if peripheral capillary oxygen saturation (SpO2) after recruitment maneuver more than 95%-recruitable | On day 1 during mechanical ventilation |
| Number of patients with recruitable lung | Peripheral capillary oxygen saturation (SpO2) change from 90% after recruitment maneuver (doubled tidal volume for 15 respiratory cycles) - if peripheral capillary oxygen saturation (SpO2) after recruitment maneuver more than 95%-recruitable | On day 7 during mechanical ventilation |
| Measure | Description | Time Frame |
|---|---|---|
| Change in alveolar dead space | Calculation of the alveolar dead space using end-tidal carbon dioxide measurement and arterial carbon dioxide tension measurement | On day 1, 3, 5, 7, 10, 14, 21 during mechanical ventilation |
| Change in plethysmogram variability during recruitment maneuver |
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Inclusion Criteria:
Exclusion Criteria:
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All patients with COVID-19 requiring respiratory support
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| Name | Affiliation | Role |
|---|---|---|
| Andrey I Yaroshetskiy, Dr.Med.Sc. | Sechenov University | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Sechenov University Clinic #1 | Moscow | Russia | ||||
| Sechenov University Clinic #3 |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 25693014 | Background | Amato MB, Meade MO, Slutsky AS, Brochard L, Costa EL, Schoenfeld DA, Stewart TE, Briel M, Talmor D, Mercat A, Richard JC, Carvalho CR, Brower RG. Driving pressure and survival in the acute respiratory distress syndrome. N Engl J Med. 2015 Feb 19;372(8):747-55. doi: 10.1056/NEJMsa1410639. | |
| 32291463 | Result |
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| ID | Term |
|---|---|
| D000086382 | COVID-19 |
| D010349 | Patient Compliance |
| ID | Term |
|---|---|
| D011024 | Pneumonia, Viral |
| D011014 | Pneumonia |
| D012141 | Respiratory Tract Infections |
| D007239 | Infections |
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Measurement of plethysmogram variability before and during recruitment maneuver |
| On day 1, 3, 5, 7, 10, 14, 21 during mechanical ventilation |
| Change in arterial partial oxygen tension to inspiratory oxygen fraction (PaO2/FiO2) ratio | Calculation of the arterial partial oxygen tension to inspiratory oxygen fraction (PaO2/FiO2) ratio using arterial oxygen tension measurement | On day 1, 3, 5, 7, 10, 14, 21 during mechanical ventilation |
| Optimum positive end-expiratory pressure (PEEP) level | Positive end-expiratory pressure (PEEP) selection at minimum level with maximum static compliance and the highest peripheral capillary oxygen saturation over fraction of inspired oxygen (SpO2/FiO2) | On day 3, 5, 10, 14, 21 during mechanical ventilation |
| Change in driving pressure with different positive end-expiratory pressure (PEEP) levels | Driving pressure calculation at different positive end-expiratory pressure (PEEP) levels (8, 10, 12, 14) | On day 1, 3, 5, 7, 10, 14, 21 during mechanical ventilation |
| Moscow |
| Russia |
| Sechenov University Clinic #4 | Moscow | Russia |
| Gattinoni L, Chiumello D, Caironi P, Busana M, Romitti F, Brazzi L, Camporota L. COVID-19 pneumonia: different respiratory treatments for different phenotypes? Intensive Care Med. 2020 Jun;46(6):1099-1102. doi: 10.1007/s00134-020-06033-2. Epub 2020 Apr 14. No abstract available. |
| 32031570 | Result | Wang D, Hu B, Hu C, Zhu F, Liu X, Zhang J, Wang B, Xiang H, Cheng Z, Xiong Y, Zhao Y, Li Y, Wang X, Peng Z. Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China. JAMA. 2020 Mar 17;323(11):1061-1069. doi: 10.1001/jama.2020.1585. |
| 30535520 | Result | Toufen Junior C, De Santis Santiago RR, Hirota AS, Carvalho ARS, Gomes S, Amato MBP, Carvalho CRR. Driving pressure and long-term outcomes in moderate/severe acute respiratory distress syndrome. Ann Intensive Care. 2018 Dec 7;8(1):119. doi: 10.1186/s13613-018-0469-4. |
| 35246024 | Derived | Yaroshetskiy AI, Avdeev SN, Politov ME, Nogtev PV, Beresneva VG, Sorokin YD, Konanykhin VD, Krasnoshchekova AP, Merzhoeva ZM, Tsareva NA, Trushenko NV, Mandel IA, Yavorovskiy AG. Potential for the lung recruitment and the risk of lung overdistension during 21 days of mechanical ventilation in patients with COVID-19 after noninvasive ventilation failure: the COVID-VENT observational trial. BMC Anesthesiol. 2022 Mar 4;22(1):59. doi: 10.1186/s12871-022-01600-0. |
| D014777 |
| Virus Diseases |
| D018352 | Coronavirus Infections |
| D003333 | Coronaviridae Infections |
| D030341 | Nidovirales Infections |
| D012327 | RNA Virus Infections |
| D008171 | Lung Diseases |
| D012140 | Respiratory Tract Diseases |
| D010342 | Patient Acceptance of Health Care |
| D000074822 | Treatment Adherence and Compliance |
| D015438 | Health Behavior |
| D001519 | Behavior |