Altered lung physiology in two cohorts after COVID-19 infection as assessed by computed cardiopulmonography.

The longer-term effects of COVID-19 on lung physiology remain poorly understood. Here, a new technique, computed cardiopulmonography (CCP), was used to study two COVID-19 cohorts (MCOVID and C-MORE-LP) at both ∼6 and ∼12 mo after infection. CCP is comprised of two components. The first is collection of highly precise, highly time-resolved measurements of gas exchange with a purpose-built molecular flow sensor based around laser absorption spectroscopy. The second component is estimation of physiological parameters by fitting a cardiopulmonary model to the data set. The measurement protocol involved 7 min of breathing air followed by 5 min of breathing pure O₂. One hundred seventy-eight participants were studied, with 97 returning for a repeat assessment. One hundred twenty-six arterial blood gas samples were drawn from MCOVID participants. For participants who had required intensive care and/or invasive mechanical ventilation, there was a significant increase in anatomical dead space of ∼30 mL and a significant increase in alveolar-to-arterial Po₂ gradient of ∼0.9 kPa relative to control participants. Those who had been hospitalized had reductions in functional residual capacity of ∼15%. Irrespectively of COVID-19 severity, participants who had had COVID-19 demonstrated a modest increase in ventilation inhomogeneity, broadly equivalent to that associated with 15 yr of aging. This study illustrates the capability of CCP to study aspects of lung function not so easily addressed through standard clinical lung function tests. However, without measurements before infection, it is not possible to conclude whether the findings relate to the effects of COVID-19 or whether they constitute risk factors for more serious disease.NEW & NOTEWORTHY This study used a novel technique, computed cardiopulmonography, to study the lungs of patients who have had COVID-19. Depending on severity of infection, there were increases in anatomical dead space, reductions in absolute lung volumes, and increases in ventilation inhomogeneity broadly equivalent to those associated with 15 yr of aging. However, without measurements taken before infection, it is unclear whether the changes result from COVID-19 infection or are risk factors for more severe disease.

Identifying putative ventilation-perfusion distributions in COVID-19 pneumonia.

Busana et al. (doi.org/10.1152/japplphysiol.00871.2020) published 5 patients with COVID-19 in whom the fraction of non-aerated lung tissue had been quantified by computed tomography. They assumed that shunt flow fraction was proportional to the non-aerated lung fraction, and, by randomly generating 106 different bimodal distributions for the ventilation-perfusion ([Formula: see text]) ratios in the lung, specified as sets of paired values {[Formula: see text]}, sought to identify as solutions those that generated the observed arterial partial pressures of CO2 and O2 (PaCO2 and PaO2). Our study sought to develop a direct method of calculation to replace the approach of randomly generating different distributions, and so provide more accurate solutions that were within the measurement error of the blood-gas data. For the one patient in whom Busana et al. did not find solutions, we demonstrated that the assumed shunt flow fraction led to a non-shunt blood flow that was too low to support the required gas exchange. For the other four patients, we found precise solutions (prediction error < 1x10-3 mmHg for both PaCO2 and PaO2), with distributions qualitatively similar to those of Busana et al. These distributions were extremely wide and unlikely to be physically realisable, because they predict the maintenance of very large concentration gradients in regions of the lung where convection is slow. We consider that these wide distributions arise because the assumed value for shunt flow is too low in these patients, and we discuss possible reasons why the assumption relating to shunt flow fraction may break down in COVID-19 pneumonia.

Clinical characteristics and survival analysis in critical and non-critical patients with COVID-19 in Wuhan, China: a single-center retrospective case control study.

Since the outbreak of COVID-19 in China at the end of 2019, the world has experienced a large-scale epidemic caused by the SARS-CoV-2. The epidemiological and clinical course of COVID-19 patients has been reported, but there have been few analyses about the characteristics, predictive risk factors, and outcomes of critical patients. In this single-center retrospective case-control study, 90 adult inpatients hospitalized at Tongji Hospital (Wuhan, China) were included. Demographic, clinical, laboratory tests, and treatment data were obtained and compared between critical and non-critical patients. We found that compared with non-critical patients, the critical patients had higher SOFA score and qSOFA scores. Critical patients had lower lymphocyte and platelet count, elevated D-dimer, decreased fibrinogen, and elevated high-sensitivity C-reactive protein (hsCRP), and interleukin-6(IL-6). More critical patients received treatment including antibiotics, anticoagulation, corticosteroid, and oxygen therapy than non-critical ones. Multivariable regression showed higher qSOFA score and elevation of IL-6 were related to critical patients. Antibiotic usage and anticoagulation were associated with decreased in-hospital mortality. And critical grouping contributed greatly to in-hospital death. Critical COVID-19 patients have a more severe clinical course. qSOFA score and elevation of IL-6 are risk factors for critical condition. Non-critical grouping, positive antibiotic application, and anticoagulation may be beneficial for patient survival.