Implications of microscale lung damage for COVID-19 pulmonary ventilation dynamics: A narrative review

Prevalence of mortality among mechanically ventilated patients in the intensive care units of Ethiopian hospitals and the associated factors: A systematic review and meta-analysis

BACKGROUND

In the intensive care unit (ICU), mechanical ventilation (MV) is a typical way of respiratory support. The severity of the illness raises the likelihood of death in patients who require MV. Several studies have been done in Ethiopia; however, the mortality rate differs among them. The objective of this systematic review and meta-analysis is to provide a pooled prevalence of mortality and associated factors among ICU-admitted patients receiving MV in Ethiopian hospitals.

METHODS

We used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 criteria to conduct a comprehensive systematic review and meta-analysis in this study. We searched PubMed/Medline, SCOPUS, Embase, Hinari, and Web of Science and found 22 articles that met our inclusion criteria. We used a random-effects model. To identify heterogeneity within the included studies, meta-regression and subgroup analysis were used. We employed Egger's regression test and funnel plots for assessing publication bias. STATA version 17.0 software was used for all statistical analyses.

RESULTS

In this systematic review and meta-analysis, the pooled prevalence of mortality among 7507 ICU-admitted patients from 22 articles, who received MV was estimated to be 54.74% [95% CI = 47.93, 61.55]. In the subgroup analysis by region, the Southern Nations, Nationalities, and Peoples (SNNP) subgroup (64.28%, 95% CI = 51.19, 77.37) had the highest prevalence. Patients with COVID-19 have the highest mortality rate (75.80%, 95% CI = 51.10, 100.00). Sepsis (OR = 6.85, 95%CI = 3.24, 14.46), Glasgow Coma Scale (GCS) score<8 (OR = 6.58, 95%CI = 1.96, 22.11), admission with medical cases (OR = 4.12, 95%CI = 2.00, 8.48), Multi Organ Dysfunction Syndrome (MODS) (OR = 2.70, 95%CI = 4.11, 12.62), and vasopressor treatment (OR = 19.06, 95%CI = 9.34, 38.88) were all statistically associated with mortality.

CONCLUSION

Our review found that the pooled prevalence of mortality among mechanically ventilated ICU-admitted patients in Ethiopia was considerably high compared to similar studies in the United States (US), China, and other countries. Sepsis, GCS<8, medical cases, MODS, and use of vasopressors were statistically associated with mortality. Clinicians should exercise caution while mechanically ventilating ICU-admitted patients with these factors. However, it should be noted that the exact cause and effect relationship could not be established with this meta-analysis, as the available evidence is not sufficient. Thus, more studies using prospective methods will be required.

Deep learning reveals lung shape differences on baseline chest CT between mild and severe COVID-19: A multi-site retrospective study

Severe COVID-19 can lead to extensive lung disease causing lung architectural distortion. In this study we employed machine learning and statistical atlas-based approaches to explore possible changes in lung shape among COVID-19 patients and evaluated whether the extent of these changes was associated with COVID-19 severity. On a large multi-institutional dataset (N = 3443), three different populations were defined; a) healthy (no COVID-19), b) mild COVID-19 (no ventilator required), c) severe COVID-19 (ventilator required), and the presence of lung shape differences between them were explored using baseline chest CT. Significant lung shape differences were observed along mediastinal surfaces of the lungs across all severity of COVID-19 disease. Additionally, differences were seen on basal surfaces of the lung when compared between healthy and severe COVID-19 patients. Finally, an AI model (a 3D residual convolutional network) characterizing these shape differences coupled with lung infiltrates (ground-glass opacities and consolidation regions) was found to be associated with COVID-19 severity.

Physics-based in silico modelling of microvascular pulmonary perfusion in COVID-19

Due to its ability to induce heterogenous, patient-specific damage in pulmonary alveoli and capillaries, COVID-19 poses challenges in defining a uniform profile to elucidate infection across all patients. Computational models that integrate changes in ventilation and perfusion with heterogeneous damage profiles offer valuable insights into the impact of COVID-19 on pulmonary health. This study aims to develop an in silico hypothesis-testing platform specifically focused on studying microvascular pulmonary perfusion in COVID-19-infected lungs. Through this platform, we explore the effects of various acinar-level pulmonary perfusion abnormalities on global lung function. Our modelling approach simulates changes in pulmonary perfusion and the resulting mismatch of ventilation and perfusion in COVID-19-afflicted lungs. Using this coupled modelling platform, we conducted multiple simulations to assess different scenarios of perfusion abnormalities in COVID-19-infected lungs. The simulation results showed an overall decrease in ventilation-perfusion (V/Q) ratio with inclusion of various types of perfusion abnormalities such as hypoperfusion with and without microangiopathy. This model serves as a foundation for comprehending and comparing the spectrum of findings associated with COVID-19 in the lung, paving the way for patient-specific modelling of microscale lung damage in emerging pulmonary pathologies like COVID-19.

Distinct lung cell signatures define the temporal evolution of diffuse alveolar damage in fatal COVID-19

BACKGROUND

Lung damage in severe COVID-19 is highly heterogeneous however studies with dedicated spatial distinction of discrete temporal phases of diffuse alveolar damage (DAD) and alternate lung injury patterns are lacking. Existing studies have also not accounted for progressive airspace obliteration in cellularity estimates. We used an imaging mass cytometry (IMC) analysis with an airspace correction step to more accurately identify the cellular immune response that underpins the heterogeneity of severe COVID-19 lung disease.

METHODS

Lung tissue was obtained at post-mortem from severe COVID-19 deaths. Pathologist-selected regions of interest (ROIs) were chosen by light microscopy representing the patho-evolutionary spectrum of DAD and alternate disease phenotypes were selected for comparison. Architecturally normal SARS-CoV-2-positive lung tissue and tissue from SARS-CoV-2-negative donors served as controls. ROIs were stained for 40 cellular protein markers and ablated using IMC before segmented cells were classified. Cell populations corrected by ROI airspace and their spatial relationships were compared across lung injury patterns.

FINDINGS

Forty patients (32M:8F, age: 22-98), 345 ROIs and >900k single cells were analysed. DAD progression was marked by airspace obliteration and significant increases in mononuclear phagocytes (MnPs), T and B lymphocytes and significant decreases in alveolar epithelial and endothelial cells. Neutrophil populations proved stable overall although several interferon-responding subsets demonstrated expansion. Spatial analysis revealed immune cell interactions occur prior to microscopically appreciable tissue injury.

INTERPRETATION

The immunopathogenesis of severe DAD in COVID-19 lung disease is characterised by sustained increases in MnPs and lymphocytes with key interactions occurring even prior to lung injury is established.

FUNDING

UK Research and Innovation/Medical Research Council through the UK Coronavirus Immunology Consortium, Barbour Foundation, General Sir John Monash Foundation, Newcastle University, JGW Patterson Foundation, Wellcome Trust.

Functional lung imaging using novel and emerging MRI techniques

Respiratory diseases are leading causes of death and disability in the world. While early diagnosis is key, this has proven difficult due to the lack of sensitive and non-invasive tools. Computed tomography is regarded as the gold standard for structural lung imaging but lacks functional information and involves significant radiation exposure. Lung magnetic resonance imaging (MRI) has historically been challenging due to its short T2 and low proton density. Hyperpolarised gas MRI is an emerging technique that is able to overcome these difficulties, permitting the functional and microstructural evaluation of the lung. Other novel imaging techniques such as fluorinated gas MRI, oxygen-enhanced MRI, Fourier decomposition MRI and phase-resolved functional lung imaging can also be used to interrogate lung function though they are currently at varying stages of development. This article provides a clinically focused review of these contrast and non-contrast MR imaging techniques and their current applications in lung disease.

Effects of tissue degradation by collagenase and elastase on the biaxial mechanics of porcine airways

BACKGROUND

Common respiratory illnesses, such as emphysema and chronic obstructive pulmonary disease, are characterized by connective tissue damage and remodeling. Two major fibers govern the mechanics of airway tissue: elastin enables stretch and permits airway recoil, while collagen prevents overextension with stiffer properties. Collagenase and elastase degradation treatments are common avenues for contrasting the role of collagen and elastin in healthy and diseased states; while previous lung studies of collagen and elastin have analyzed parenchymal strips in animal and human specimens, none have focused on the airways to date.

METHODS

Specimens were extracted from the proximal and distal airways, namely the trachea, large bronchi, and small bronchi to facilitate evaluations of material heterogeneity, and subjected to biaxial planar loading in the circumferential and axial directions to assess airway anisotropy. Next, samples were subjected to collagenase and elastase enzymatic treatment and tensile tests were repeated. Airway tissue mechanical properties pre- and post-treatment were comprehensively characterized via measures of initial and ultimate moduli, strain transitions, maximum stress, hysteresis, energy loss, and viscoelasticity to gain insights regarding the specialized role of individual connective tissue fibers and network interactions.

RESULTS

Enzymatic treatment demonstrated an increase in airway tissue compliance throughout loading and resulted in at least a 50% decrease in maximum stress overall. Strain transition values led to significant anisotropic manifestation post-treatment, where circumferential tissues transitioned at higher strains compared to axial counterparts. Hysteresis values and energy loss decreased after enzymatic treatment, where hysteresis reduced by almost half of the untreated value. Anisotropic ratios exhibited axially led stiffness at low strains which transitioned to circumferentially led stiffness when subjected to higher strains. Viscoelastic stress relaxation was found to be greater in the circumferential direction for bronchial airway regions compared to axial counterparts.

CONCLUSION

Targeted fiber treatment resulted in mechanical alterations across the loading range and interactions between elastin and collagen connective tissue networks was observed. Providing novel mechanical characterization of elastase and collagenase treated airways aids our understanding of individual and interconnected fiber roles, ultimately helping to establish a foundation for constructing constitutive models to represent various states and progressions of pulmonary disease.

Institutional Strategies to Maintain and Grow Imaging Research During the COVID-19 Pandemic

Understanding imaging research experiences, challenges, and strategies for academic radiology departments during and after COVID-19 is critical to prepare for future disruptive events. We summarize key insights and programmatic initiatives at major academic hospitals across the world, based on literature review and meetings of the Radiological Society of North America Vice Chairs of Research (RSNA VCR) group. Through expert discussion and case studies, we provide suggested guidelines to maintain and grow radiology research in the postpandemic era.

Effect of a Functional Phospholipid Metabolome-Protein Association Pathway on the Mechanism of COVID-19 Disease Progression

This study aimed to explore the clinical practice of phospholipid metabolic pathways in COVID-19. In this study, 48 COVID-19 patients and 17 healthy controls were included. Patients were divided into mild (n=40) and severe (n=8) according to their severity. Phospholipid metabolites, TCA circulating metabolites, eicosanoid metabolites, and closely associated enzymes and transfer proteins were detected in the plasma of all individuals using metabolomics and proteomics assays, respectively. 30 of the 33 metabolites found differed significantly (P<0.05) between patients and healthy controls (P<0.05), with D-dimmer significantly correlated with all of the lysophospholipid metabolites (LysoPE, LysoPC, LysoPI and LPA). In particular, we found that phosphatidylinositol (PI) and phosphatidylcholine (PC) could identify patients from healthy controls (AUC 0.771 and 0.745, respectively) and that the severity of the patients could be determined (AUC 0.663 and 0.809, respectively). The last measurement before discharge also revealed significant changes in both PI and PC. For the first time, our study explores the significance of the phospholipid metabolic system in COVID-19 patients. Based on molecular pathway mechanisms, three important phospholipid pathways related to Ceramide-Malate acid (Cer-SM), Lysophospholipid (LPs), and membrane function were established. Clinical values discovered included the role of Cer in maintaining the inflammatory internal environment, the modulation of procoagulant LPA by upstream fibrinolytic metabolites, and the role of PI and PC in predicting disease aggravation.

Towards a multi-scale computer modeling workflow for simulation of pulmonary ventilation in advanced COVID-19

Physics-based multi-scale in silico models offer an excellent opportunity to study the effects of heterogeneous tissue damage on airflow and pressure distributions in COVID-19-afflicted lungs. The main objective of this study is to develop a computational modeling workflow, coupling airflow and tissue mechanics as the first step towards a virtual hypothesis-testing platform for studying injury mechanics of COVID-19-afflicted lungs. We developed a CT-based modeling approach to simulate the regional changes in lung dynamics associated with heterogeneous subject-specific COVID-19-induced damage patterns in the parenchyma. Furthermore, we investigated the effect of various levels of inflammation in a meso-scale acinar mechanics model on global lung dynamics. Our simulation results showed that as the severity of damage in the patient's right lower, left lower, and to some extent in the right upper lobe increased, ventilation was redistributed to the least injured right middle and left upper lobes. Furthermore, our multi-scale model reasonably simulated a decrease in overall tidal volume as the level of tissue injury and surfactant loss in the meso-scale acinar mechanics model was increased. This study presents a major step towards multi-scale computational modeling workflows capable of simulating the effect of subject-specific heterogenous COVID-19-induced lung damage on ventilation dynamics.

Alveolar type II cells and pulmonary surfactant in COVID-19 era

In this review, we discuss the role of pulmonary surfactant in the host defense against respiratory pathogens, including novel coronavirus SARS-CoV-2. In the lower respiratory system, the virus uses angiotensin-converting enzyme 2 (ACE2) receptor in conjunction with serine protease TMPRSS2, expressed by alveolar type II (ATII) cells as one of the SARS-CoV-2 target cells, to enter. ATII cells are the main source of surfactant. After their infection and the resulting damage, the consequences may be severe and may include injury to the alveolar-capillary barrier, lung edema, inflammation, ineffective gas exchange, impaired lung mechanics and reduced oxygenation, which resembles acute respiratory distress syndrome (ARDS) of other etiology. The aim of this review is to highlight the key role of ATII cells and reduced surfactant in the pathogenesis of the respiratory form of COVID-19 and to emphasize the rational basis for exogenous surfactant therapy in COVID-19 ARDS patients.

Targeting phytoprotection in the COVID-19-induced lung damage and associated systemic effects-the evidence-based 3PM proposition to mitigate individual risks

The risks related to the COVID-19 are multi-faceted including but by far not restricted to the following: direct health risks by poorly understood effects of COVID-19 infection, overloaded capacities of healthcare units, restricted and slowed down care of patients with non-communicable disorders such as cancer, neurologic and cardiovascular pathologies, among others; social risks-restricted and broken social contacts, isolation, professional disruption, explosion of aggression in the society, violence in the familial environment; mental risks-loneliness, helplessness, defenceless, depressions; and economic risks-slowed down industrial productivity, broken delivery chains, unemployment, bankrupted SMEs, inflation, decreased capacity of the state to perform socially important programs and to support socio-economically weak subgroups in the population. Directly or indirectly, the above listed risks will get reflected in a healthcare occupation and workload which is a tremendous long-term challenge for the healthcare capacity and robustness. The article does not pretend to provide solutions for all kind of health risks. However, it aims to present the scientific evidence of great clinical utility for primary, secondary, and tertiary care to protect affected individuals in a cost-effective manner. To this end, due to pronounced antimicrobial, antioxidant, anti-inflammatory, and antiviral properties, naturally occurring plant substances are capable to protect affected individuals against COVID-19-associated life-threatening complications such as lung damage. Furthermore, they can be highly effective, if being applied to secondary and tertiary care of noncommunicable diseases under pandemic condition. Thus, the stratification of patients evaluating specific health conditions such as sleep quality, periodontitis, smoking, chronic inflammation and diseases, metabolic disorders and obesity, vascular dysfunction, and cancers would enable effective managemenet of COVID-19-associated complications in primary, secondary, and tertiary care in the context of predictive, preventive, and personalized medicine (3PM).

COVID-19 pneumonia: What APRNs should know

ABSTRACT

COVID-19-associated pneumonia is a complex acute care diagnosis that requires careful evaluation and management. This article includes pertinent recommendations for management of acutely ill patients with COVID-19 pneumonia.