Dataset Information

Modeling lung perfusion abnormalities to explain early COVID-19 hypoxemia.

ABSTRACT: Early stages of the novel coronavirus disease (COVID-19) are associated with silent hypoxia and poor oxygenation despite relatively minor parenchymal involvement. Although speculated that such paradoxical findings may be explained by impaired hypoxic pulmonary vasoconstriction in infected lung regions, no studies have determined whether such extreme degrees of perfusion redistribution are physiologically plausible, and increasing attention is directed towards thrombotic microembolism as the underlying cause of hypoxemia. Herein, a mathematical model demonstrates that the large amount of pulmonary venous admixture observed in patients with early COVID-19 can be reasonably explained by a combination of pulmonary embolism, ventilation-perfusion mismatching in the noninjured lung, and normal perfusion of the relatively small fraction of injured lung. Although underlying perfusion heterogeneity exacerbates existing shunt and ventilation-perfusion mismatch in the model, the reported hypoxemia severity in early COVID-19 patients is not replicated without either extensive perfusion defects, severe ventilation-perfusion mismatch, or hyperperfusion of nonoxygenated regions.

SUBMITTER: Herrmann J

PROVIDER: S-EPMC7522238 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Modeling lung perfusion abnormalities to explain early COVID-19 hypoxemia.

Herrmann Jacob J Mori Vitor V Bates Jason H T JHT Suki Béla B

Nature communications 20200928 1

Early stages of the novel coronavirus disease (COVID-19) are associated with silent hypoxia and poor oxygenation despite relatively minor parenchymal involvement. Although speculated that such paradoxical findings may be explained by impaired hypoxic pulmonary vasoconstriction in infected lung regions, no studies have determined whether such extreme degrees of perfusion redistribution are physiologically plausible, and increasing attention is directed towards thrombotic microembolism as the unde ...[more]

PMID: 32985528

Similar Datasets

Project description:ObjectiveTo compare the efficacy and outcomes with inhaled nitric oxide (iNO) and inhaled epoprostenol (iEPO) in patients with refractory hypoxemia due to COVID-19.DesignRetrospective Cohort Study.SettingSingle health system multicenter academic teaching hospitals.Patients or subjectsAge group of 18-80 years admitted to the medical ICU.InterventionsMechanically ventilated patients with COVID-19 infection, who received either iNO or iEPO between March 1st, 2020, and June 30th, 2020.Measurements and main resultsThe primary outcome was the change in the PaO2/FiO2 (P/F) ratio 1 hour after initiation of pulmonary vasodilator therapy. Secondary outcomes include P/F ratios on days 1-3 after initiation, positive response in P/F ratio (increase of at least 20% in PaO2), total days of treatment, rebound hypoxemia (if there was a drop in oxygen saturation after treatment was stopped), ventilator free days (if any patient was extubated), days in ICU, days to extubation, days to tracheostomy, mortality days after intubation, 30-day survival and mortality. 183 patients were excluded, as they received both iNO and iEPO. Of the remaining 103 patients, 62 received iEPO and 41 received iNO. The severity of ARDS was similar in both groups. Change in P/F ratio at one hour was 116 (70.3) with iNO and 107 (57.6) with iEPO (Mean/SD). Twenty-two (53.7%) patients in the iNO group and 25 (40.3%) in the iEPO group were responders to pulmonary vasodilators n(%)(p = 0.152) (more than 20% increase in partial pressure of oxygen, Pao2), and 18 (43.9%) and 31 (50%) patients in the iNO and iEPO group (p = 0.685), respectively, had rebound hypoxemia. Only 7 patients in the cohort achieved ventilator free days (3 in the iEPO group and 4 in iNO group).ConclusionsWe found no significant difference between iNO and iEPO in terms of change in P/F ratio, duration of mechanical ventilation, ICU, in-hospital mortality in this cohort of mechanically ventilated patients with COVID-19. Larger, prospective studies are necessary to validate these results.

Dataset Information

Modeling lung perfusion abnormalities to explain early COVID-19 hypoxemia.

Publications

Modeling lung perfusion abnormalities to explain early COVID-19 hypoxemia.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets