Critical Pneumonia Research Articles

The effect of lopinavir - ritonavir on mortality in COVID-19 pneumonia

Aim: COVID-19 is a lethal disease for which there is still no specific treatment. The study aims to retrospectively investigate the effect of adding lopinavir/ritonavir to the treatment of patients using favipiravir (in the ward or intensive care unit) on mortality. Methods: This study was conducted in 181 Rt-PCR(+) adult patients with severe and critical COVID-19. Demographic and laboratory data, antiviral agents used in treatment (with or without lopinavir-ritonavir), presence of intubation, and clinical outcome were recorded. The patients were categorized into Group 1 (not receiving lopinavir-ritonavir), Group 2 (administered lopinavir-ritonavir in ward), and Group 3 (administered lopinavir-ritonavir in the intensive care unit). Results: The lowest mortality rate was found with Group 2 (21.4%) while this rate was 77.9% for Group 3 and 42.3% for Group 1 (p<0.001). There was no significant difference in length of hospital stay among groups (p>0.05). While 35.2% (25 patients) of Group 1 needed intubation, this rate was 21.4% (9 patients) in Group 2 (p<0.001). Conclusions: This study demonstrated that lopinavir / ritonavir treatment reduced mortality and the need for intubation when initiated before the critical pneumonia phase. Lopinavir/ritonavir may be useful in the treatment of COVID-19, especially as part of the combination regimen.

Association of gut microbiota with critical pneumonia: A two-sample Mendelian randomization study.

This study investigated the causal effect of gut microbiota on critical pneumonia. Data came from a large-scale gut microbiota data set (n = 18,340) and the critical pneumonia genome-wide genotyping array (cases n = 2758 and controls n = 42,8607). Inverse variance weighting was used as the primary Mendelian randomization (MR) analysis method. Weighted median, MR-Egger, simple model, weighted model, and MR-Egger, were used to evaluate robustness. Sensitivity analysis used Cochran Q test, MR-Egger intercept test, and MR-PRESSO. For critical pneumonia, inverse variance weighting estimates suggested that Class Verrucomicrobiae (OR = 0.415; 95% CI: 0.207, 0.833; P = .013), Family Verrucomicrobiaceae (OR = 0.415; 95% CI: 0.207, 0.833; P = .013), Genus Akkermansia (OR = 0.415; 95% CI: 0.207, 0.833; P = .013), Genus LachnospiraceaeFCS020group (OR = 0.449; 95% CI: 0.230, 0.890; P = .021), Genus Parasutterella (OR = 0.466; 95% CI: 0.233, 0.929; P = .030), Genus Prevotella7 (OR = 0.645; 95% CI: 0.432, 0.960; P = .031), Order Verrucomicrobiales (OR = 0.415; 95% CI: 0.207, 0.833; P = .013), and Phylum Cyanobacteria (OR = 0.510; 95% CI: 0.272, 0.956; P = .036) had a reduced risk, while Family Enterobacteriaceae (OR = 2.746; 95% CI: 1.008, 7.474; P = .048), Genus RuminococcaceaeUCG003 (OR = 2.811; 95% CI: 1.349, 5.851; P = .006) and Order Enterobacteriales (OR = 2.746; 95% CI: 1.008, 7.474; P = .048) were associated with an increased risk. Sensitivity analyses confirmed that the aforementioned correlations were robust.

Interferon-responsive neutrophils and macrophages extricate SARS-CoV-2 Omicron critical patients from the nasty fate of sepsis.

The SARS-CoV-2 Omicron variant is characterized by its high transmissibility, which has caused a worldwide epidemiological event. Yet, it turns ominous once the disease progression degenerates into severe pneumonia and sepsis, presenting a horrendous lethality. To elucidate the alveolar immune or inflammatory landscapes of Omicron critical-ill patients, we performed single-cell RNA-sequencing (scRNA-seq) of bronchoalveolar lavage fluid (BALF) from the patients with critical pneumonia caused by Omicron infection, and analyzed the correlation between the clinical severity scores and different immune cell subpopulations. In the BALF of Omicron critical patients, the alveolar violent myeloid inflammatory environment was determined. ISG15+ neutrophils and CXCL10+ macrophages, both expressed the interferon-stimulated genes (ISGs), were negatively correlated with clinical pulmonary infection score, while septic CST7+ neutrophils and inflammatory VCAN+ macrophages were positively correlated with sequential organ failure assessment. The percentages of ISG15+ neutrophils were associated with more protective alveolar epithelial cells, and may reshape CD4+ T cells to the exhaustive phenotype, thus preventing immune injuries. The CXCL10+ macrophages may promote plasmablast/plasma cell survival and activation as well as the production of specific antibodies. As compared to the previous BALF scRNA-seq data from SARS-CoV-2 wild-type/Alpha critical patients, the subsets of neutrophils and macrophages with pro-inflammatory and immunoregulatory features presented obvious distinctions, suggesting an immune disparity in Omicron variants. Overall, this study provides a BALF single-cell atlas of Omicron critical patients, and suggests that alveolar interferon-responsive neutrophils and macrophages may extricate SARS-CoV-2 Omicron critical patients from the nasty fate of sepsis.

Comparisons of APACHE II, CURB-65, Pneumonia severity index, and CHA2DS2-VAS score on new onset cardiovascular events, including atrial fibrillation, for critical illness with pneumonia

Abstract Background pneumonia patients afflicted with cardiac disease were frequented with higher rates of short-term mortality. Furthermore, the most common arrhythmia (25%) in critically ill patients is atrial fibrillation and its increased incidences in hospital mortality and extended length of hospital stays. The early detection of the occurrence of atrial fibrillation and other CV events is important among these severely pneumonia patients. Purpose The purpose of this article is to determine the appropriate risk assessments and to make a comparison of predictive performance among four common practice risk scores: APACHE II, CURB-65, pneumonia severity index and CHA2DS2-VASc. Methods This was a retrospective, observational study from consecutive critical pneumonia patients admitted to medical intensive care unit. Heart failure, acute coronary syndrome, atrial fibrillation, ventricular tachycardia or stroke are defined as a cardiovascular event. Those who had the missing data about APACHE II, CURB-65, PSI and CHA2DS2-VASc scores had already been excluded from this study. The baseline characteristics of patients between the disease groups (CV vs. non-CV; AF vs. non-AF) were compared by using the independent sample t-test for continuous variables and the chi-square test for categorical variables, respectively. The performance of discriminating in-hospital CV and AF events for the four risk scores was evaluated using the ROC curve analysis. The areas under the ROC curve (AUC) of the four risk scores were compared using the Delong’s non-parametric method. Results 252 (22.6%) of the 1,117 patients suffered from CV events during the hospitalization. Compared to patients averting CV events, those who experienced CV events during hospitalization were older, more likely to smoke, experiencing more altered mental states, of poor renal function, of higher prevalence of all comorbidities except liver disease, of a long duration of ICU and yielded higher values of the four risk scores. There were 99 patients who suffered from CV events other than an AF episode. After excluding the 99 patients, 153 (15%) of the remaining 1,018 patients had an AF event during hospitalization. The values of the four risk scores were also significantly greater in the AF group. The performance of discriminating CV events for the four risk scores was fair with the values of AUC ranging from 61.8% of APACHE II to 64.8% of CURB 65 (Fig 1). However, no significant difference of the AUC values between any two risk scores. In terms of discriminating AF episode (Fig 2) for the four risk scores, the performance was obviously poorer with the values of AUC less than 60%, except for the CURB 65. Conclusion CURB 65 is simple and effective tool for predicting new onset cardiovascular events, including atrial fibrillation, in ICU patients with pneumonia.new onset CV eventonw onset AF event

Another Face of the Post-COVID Syndrome in Elderly Patients: Increased Frailty Due to Systemic Inflammation

Aim: COVID-19 is known to be a condition that creates long-term morbidity and mortality in older adults. There is not enough information yet about the relationship between COVID-19 and frailty. In our study, we investigated whether COVID-19 increases frailty, a condition that can be counted among its long-term effects.
 
 Materials and Methods: The study included 73 patients over the age of 65 who were hospitalized in the Başkent University Medical Faculty Hospital COVID-19 Isolation Service, with positive COVID-19 PCR test. Patients were categorized as mild-moderate, severe, and critical pneumonia requiring intensive care unit admission. The FRAIL Frailty scale was applied to the patients on the first day of hospitalization. The FRAIL Frailty scale was applied again at the 3rd month follow-up after discharge. FRAIL index were compared on the first day of hospitalization and 3 months after discharge due to COVID-19.
 
 Results: 58.9% of the patients participating in our study were male and 41.1% were female. Their mean age was 77.48±7.68 years. The mean FRAIL score was 1.34±0.12 on the first day of hospitalization and 2.24±0.12 after discharge. The mean change in FRAIL score between the first day of hospitalization and after discharge was 60.3% and was statistically significant (p

To Study the Correlation of Clinical Severity and Cytokine Storm in COVID-19 Pulmonary Embolism Patients by Using Computed Tomography Pulmonary Angiography (CTPA) Qanadli Clot Burden Scoring System.

Pulmonary embolism (PE) is a fatal form of venous thromboembolism (VTE), with an overall untreated mortality of up to 30%. Greater than 50% of patients with lower extremity proximal DVT have concurrent PE at presentation. VTE has been seen in up to one-third of patients with COVID-19 infections requiring intensive care unit (ICU) admission.The objective of this study is to determine the correlation between CT pulmonary angiography, pulmonary embolism clot burden, and the Qanadli scoring system with clinically severe COVID-19 pneumonia and cytokine storm. 153 COVID-19 hospitalized patients who underwent CT pulmonary angiography (CTPA) for likelyPE on pretest probability modified Wells criteriawere enrolled. COVID-19 pneumonia was classified as URTI (upper respiratory tract infection), mild, severe, and critical COVID pneumonia. For data analysis, we categorized into two groups: (1) the non-severe group included URTI and mild pneumonia, and (2) the severe group included severe and critical pneumonia. We used the Qanadli scoring system to assess the PE percentages of pulmonary vascular obstruction using CTPA. Results: 41.8% (64) of COVID-19 patients were diagnosed with pulmonary embolism (PE) on CTPA. The majority of 51.6% of pulmonary vascular occlusions using the Qanadli scoring system for pulmonary embolism were at segmental arterial levels. Out of 104 COVID-19 cytokine storm patients, 45 (43%)were associated with pulmonary embolism. Overall, a 25% (16) mortality rate wasobserved in COVID-19 patients with pulmonary embolism. The pathogenesis of hypercoagulability in COVID-19 may include direct endothelial cell invasion by the virus, microvascular inflammation, endothelial exocytosis, and endotheliitis. A meta-analysis of 71 studies to investigate the occurrence of PE on CTPA in COVID-19 patients found 48.6% in ICU settingsand 65.3% of patients have clots in the peripheral pulmonary vasculature. There is a significant correlation between pulmonary embolism and high clot burdenQanadli CTPA scores, as well as between the severity of COVID-19 pneumonia and mortality. The association between critically ill COVID-19 pneumonia and pulmonary embolism may result in higher mortality and a poor prognostic marker.

COVID-19 musculoskeletal involvement in children.

Since the early phases of the COVID-19 pandemic, it has become clear that children are affected by mild respiratory symptoms rather than the critical pneumonia typical in adults. Nevertheless, it took longer to understand that pediatric patients with SARS-COV2 may develop a severe multisystem inflammatory response (a.k.a. multisystem inflammatory syndrome in children (MIS-C)), which can include musculoskeletal symptoms, and/or arthritis and myositis independently from MIS-C. Diagnostic imaging significantly contributed to the assessment of pulmonary disease due to COVID-19 but it has been rarely applied to evaluate musculoskeletal involvement in children with or without previous rheumatic diseases. Despite the paucity of radiological literature, muscle edema at magnetic resonance and synovitis at ultrasound have been described. Further use of diagnostic imaging for children with articular and muscular symptoms due to COVID-19 is strongly encouraged.

Human Genomics of COVID-19 Pneumonia: Contributions of Rare and Common Variants.

SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) infection is silent or benign in most infected individuals, but causes hypoxemic COVID-19 pneumonia in about 10% of cases. We review studies of the human genetics of life-threatening COVID-19 pneumonia, focusing on both rare and common variants. Large-scale genome-wide association studies have identified more than 20 common loci robustly associated with COVID-19 pneumonia with modest effect sizes, some implicating genes expressed in the lungs or leukocytes. The most robust association, on chromosome 3, concerns a haplotype inherited from Neanderthals. Sequencing studies focusing on rare variants with a strong effect have been particularly successful, identifying inborn errors of type I interferon (IFN) immunity in 1-5% of unvaccinated patients with critical pneumonia, and their autoimmune phenocopy, autoantibodies against type I IFN, in another 15-20% of cases. Our growing understanding of the impact of human genetic variation on immunity to SARS-CoV-2 is enabling health systems to improve protection for individuals and populations.

Artificial intelligence guided HRCT assessment predicts the severity of COVID-19 pneumonia based on clinical parameters

BackgroundThe purpose of the study was to compare the results of AI (artificial intelligence) analysis of the extent of pulmonary lesions on HRCT (high resolution computed tomography) images in COVID-19 pneumonia, with clinical data including laboratory markers of inflammation, to verify whether AI HRCT assessment can predict the clinical severity of COVID-19 pneumonia.MethodsThe analyzed group consisted of 388 patients with COVID-19 pneumonia, with automatically analyzed HRCT parameters of volume: AIV (absolute inflammation), AGV (absolute ground glass), ACV (absolute consolidation), PIV (percentage inflammation), PGV (percentage ground glass), PCV (percentage consolidation). Clinical data included: age, sex, admission parameters: respiratory rate, oxygen saturation, CRP (C-reactive protein), IL6 (interleukin 6), IG - immature granulocytes, WBC (white blood count), neutrophil count, lymphocyte count, serum ferritin, LDH (lactate dehydrogenase), NIH (National Institute of Health) severity score; parameters of clinical course: in-hospital death, transfer to the ICU (intensive care unit), length of hospital stay.ResultsThe highest correlation coefficients were found for PGV, PIV, with LDH (respectively 0.65, 0.64); PIV, PGV, with oxygen saturation (respectively − 0.53, -0.52); AIV, AGV, with CRP (respectively 0.48, 0.46); AGV, AIV, with ferritin (respectively 0.46, 0.45). Patients with critical pneumonia had significantly lower oxygen saturation, and higher levels of immune-inflammatory biomarkers on admission. The radiological parameters of lung involvement proved to be strong predictors of transfer to the ICU (in particular, PGV ≥ cut-off point 29% with Odds Ratio (OR): 7.53) and in-hospital death (in particular: AIV ≥ cut-off point 831 cm3 with OR: 4.31).ConclusionsAutomatic analysis of HRCT images by AI may be a valuable method for predicting the severity of COVID-19 pneumonia. The radiological parameters of lung involvement correlate with laboratory markers of inflammation, and are strong predictors of transfer to the ICU and in-hospital death from COVID-19.Trial registrationNational Center for Research and Development CRACoV-HHS project, contract number SZPITALE-JEDNOIMIENNE/18/2020.

Trends in care quality in China from 2011 to 2017: An analysis based on the National Specific (Single) Disease Monitoring System.

The Ministry of Health of China conducted a study targeting in single-disease quality control in 2009, aimed to strengthen quality management and improve health care services. This study retrospectively investigated the trends of quality indicators for six monitored diseases 2011-2017 to evaluate the improvement of care quality for the first batch of single-disease. We extracted data from the National Specific (Single) Disease Monitoring System for 2011-2017. We focused on six conditions: acute myocardial infarction, heart failure, community-acquired pneumonia, coronary artery bypass graft, hip / knee replacement, and acute ischemic stroke. A total of 56 quality indicators (QIs) were adopted to monitor the quality change and determine the trends in care quality. We also calculated the hospital process composite performance (HPCP) using a denominator-based weighting method for each hospital per year. The estimated annual percentage changes (EAPC) 2011-2017 were calculated at national and regional levels. The results showed that use of four QIs had significant downward trends, whereas 25 QIs (including reversed indicators) showed significant upward trends from 2011 to 2017. The greatest improvement was observed in CAP-4 (antibiotic treatment within four hours after admission to the hospital for critical pneumonia) in the central region (EAPC = 48.36, 95% CI = 15.92-89.87); while the largest decrease appeared in AIS-1 (thrombolytic therapy within 4.5 hours of symptom onset) in the western region (EAPC = -13.44, 95% CI = -24.98,-0.11). An increased HPCP was observed in four diseases nationwide, but not for acute myocardial infarction and heart failure. However, there were significant differences across regions in the process of care and outcomes, with the performance of Eastern and Western regions showing remarkable advantages compared with the Central region. We provide evidence for major advancement in care quality in China nationwide. However, the improvement of care in China was unbalanced geographically and should be carefully considered. Future challenges include expanding the coverage of quality monitoring, greater delivery efficiency, and region-balanced health care.

Interfering with Interferons: A Critical Mechanism for Critical COVID-19 Pneumonia.

Infection with SARS-CoV-2 results in clinical outcomes ranging from silent or benign infection in most individuals to critical pneumonia and death in a few. Genetic studies in patients have established that critical cases can result from inborn errors of TLR3- or TLR7-dependent type I interferon immunity, or from preexisting autoantibodies neutralizing primarily IFN-α and/or IFN-ω. These findings are consistent with virological studies showing that multiple SARS-CoV-2 proteins interfere with pathways of induction of, or response to, type I interferons. They are also congruent with cellular studies and mouse models that found that type I interferons can limit SARS-CoV-2 replication in vitro and in vivo, while their absence or diminution unleashes viral growth. Collectively, these findings point to insufficient type I interferon during the first days of infection as a general mechanism underlying critical COVID-19 pneumonia, with implications for treatment and directions for future research.

Humans with inherited MyD88 and IRAK-4 deficiencies are predisposed to hypoxemic COVID-19 pneumonia.

X-linked recessive deficiency of TLR7, a MyD88- and IRAK-4-dependent endosomal ssRNA sensor, impairs SARS-CoV-2 recognition and type I IFN production in plasmacytoid dendritic cells (pDCs), thereby underlying hypoxemic COVID-19 pneumonia with high penetrance. We report 22 unvaccinated patients with autosomal recessive MyD88 or IRAK-4 deficiency infected with SARS-CoV-2 (mean age: 10.9 yr; 2 mo to 24 yr), originating from 17 kindreds from eight countries on three continents. 16 patients were hospitalized: six with moderate, four with severe, and six with critical pneumonia, one of whom died. The risk of hypoxemic pneumonia increased with age. The risk of invasive mechanical ventilation was also much greater than in age-matched controls from the general population (OR: 74.7, 95% CI: 26.8-207.8, P < 0.001). The patients' susceptibility to SARS-CoV-2 can be attributed to impaired TLR7-dependent type I IFN production by pDCs, which do not sense SARS-CoV-2 correctly. Patients with inherited MyD88 or IRAK-4 deficiency were long thought to be selectively vulnerable to pyogenic bacteria, but also have a high risk of hypoxemic COVID-19 pneumonia.

A Prognostic Model for In-Hospital Mortality in Critically Ill Patients with Pneumonia.

To determine the utility of a novel serum biomarker for the outcome prediction of critically ill patients with pneumonia. A retrospective analysis of critically ill patients was performed at an emergency department. The expression and prediction value of parameters were assessed. Binary logistic regression analysis was utilized to determine the indicators associated with in-hospital mortality of pneumonia patients. The Last Absolute Shrinkage and Selection Operator was used to further determine the independent predictors, which were validated by multiple logistic regression. The receiver operator characteristic curve was performed to assess their prediction values. A prognostic nomogram model was finally established for the outcome prediction for critically ill patients with pneumonia. Retinol-binding protein (RBP) was significantly reduced in non-survived and pneumonia patients. CURB-65 score, levels of RBP, and blood urea nitrogen (BUN) were associated with in-hospital mortality of critically ill patients with pneumonia. Their combination was determined to be an ideal prognostic predictor (area under the curve of 0.762) and further developed into a nomogram prediction model (c-index 0.764). RBP is a novel in-hospital mortality predictor, which well supplements the CURB-65 score for critical pneumonia patients.

The role of artificial intelligence technology analysis of high-resolution computed tomography images in predicting the severity of COVID-19 pneumonia.

High-resolution computed tomography (HRCT) is usually used only for qualitative analysis of COVID-19 pneumonia. However, when coupled with artificial intelligence (AI) it can also automatically provide quantitative data. The purpose of the study was to analyze the role of automatic assessment of COVID‑19 pneumonia severity on HRCT images by AI technology. We retrospectively studied medical records of consecutive patients admitted to the Krakow University Hospital due to COVID‑19. Of the 1729 patients, 804 underwent HRCT with automatic analysis of such radiological parameters as absolute inflammation volume, absolute ground glass volume, absolute consolidation volume (ACV), percentage inflammation volume, percentage ground glass volume, percentage consolidation volume (PCV), and severity of pneumonia classified as none, mild, moderate, or critical. The automatically assessed radiological parameters correlated with the clinical parameters that reflected the severity of pneumonia (P <0.05). The patients with critical pneumonia, as compared with mild or moderate one, were more frequently men, had significantly lower oxygen saturation, higher respiratory rate, higher levels of inflammatory markers, as well as more common need for mechanical ventilation and admission to the intensive care unit. They were also more likely to die during hospitalization. Notably, as determined by the receiver operating characteristic curve analysis, radiological parameters above or equal to the cutoff points were independently associated with in‑hospital mortality (ACV odds ratio [OR], 4.08; 95% CI, 2.62-6.35; PCV OR, 4.05; 95% CI, 2.60-6.30). Using AI to analyze HRCT images is a simple and valuable approach to predict the severity of COVID‑19 pneumonia.

Neonatal outcomes related to maternal SARS-CoV-2 infection in French Guiana: A case-control study.

BackgroundThis study aims to assess the neonatal outcomes related to maternal SARS-COV-2 infection. MethodsIn this study, we identified newborns born between May 14 and August 31, 2020, to mothers who were PCR-SRAS-CoV-2 positive at the time of delivery. From the cohort of 974 infants, we performed a nested case-control study. ResultsDuring the study period, 133 (13.7%) mothers were positive for SARS‐CoV‐2. Among the 35 pregnant women with COVID-19 symptoms (26.3%), cough was the most common symptom, present in half of the cases. Four of them have progressed to critical pneumonia requiring transfer to intensive care unit. The neonates from mothers with positive SARS-CoV-2-RT-PCR, were routinely tested for COVID-19 within the first 24 h after labor, and 3 other newborns tested in the presence of symptoms. There was no significant difference between the two groups with respect to preterm birth, meconium-stained amniotic fluid distress, and neonatal asphyxia. Most infants were breastfed at birth, regardless of their mothers' COVID-19 status. In COVID-19-positive pregnant women admitted to intensive care unit, the proportion of preterm births (OR=12.5 [1.7–90.5]), fetal death in utero (OR=25.9 [2.2–305]) and admission in neonatal intensive care unit admission (OR=13.4 [3.0–60]), appeared higher than the controls. No maternal deaths were recorded. ConclusionsOur data suggest little neonatal morbidity associated with maternal COVID-19, except for those born to mothers admitted to intensive care unit. However, under breastfeeding conditions with rigorous hygiene precautions and parental education, the risk of transmission of SARS-COV-2 virus to the newborn was very low.

Lactate dehydrogenase and C-reactive protein as predictors of severity and prognosis in corona virus disease 2019 (COVID-19) in Iraqi patients

The Objective of the Study:-To estimate whether the initial C-reactive protein (CRP) and Lactate dehydrogenase (LDH) levels are able to act as markers of severity and prognosis in COVID-19 adult patients. Patients and Method: This cross sectional study was conducted in the Marjan medical teaching city during the period from January 2021 to augest2021. 100 Patients who complained from fever or chest symptoms were enrolled after laboratory confirmation of COVID19 via RT-PCR. Chest computed tomography scan(CT) was then performed to classify the patients into mild, moderate and severe, critical pneumonia groups according to world health organization(WHO)classification, initial plasma CRP level and LDH level were measured for all patients. Follow up and documentation were done for all patients. A thoracic radiologist interprets chest CT scan and produces a structured report. An informed written consent was obtained from each participant. Results: Cross sectional study of 100 cases with COVID 19 infection, mean age of patients (51.6 ± 15.5) years.51%are females and 49% are male, (79%) of patients admitted to hospital and then get well and discharged,16% died. CRP and LDH increase in complicated patients with COVID 19 infection. Critical cases have high LDH than other types of severity.

The Effects of Immunosuppressive Therapy on Mortality in Patients Followed in Intensive Care Units with the Diagnosis of Critical Coronavirus Disease-2019 Pneumonia

The Effects of Immunosuppressive Therapy on Mortality in Patients Followed in Intensive Care Units with the Diagnosis of Critical Coronavirus Disease-2019 Pneumonia

Clinical and Epidemiological Correlates of Low IFN-Gamma Responses in Mitogen Tube of QuantiFERON Assay in Tuberculosis Infection Screening During the COVID-19 Pandemic: A Population-Based Marker of COVID-19 Mortality?

BackgroundThe clinical and epidemiological implications of abnormal immune responses in COVID-19 for latent tuberculosis infection (LTBI) screening are unclear. MethodsWe reviewed QuantiFERON TB Gold Plus (QFT-Plus) results (36,709 patients) from July 2016 until October 2021 in Asturias (Spain). We also studied a cohort of ninety hospitalized patients with suspected/confirmed COVID-19 pneumonia and a group of elderly hospitalized patients with COVID-19 who underwent serial QFT-Plus and immune profiling testing. ResultsThe indeterminate QFT-Plus results rate went from 1.4% (July 2016 to November 2019) to 4.2% during the COVID-19 pandemic. The evolution of the number of cases with low/very low interferon-gamma (IFN-gamma) response in the mitogen tube paralleled the disease activity and number of deaths during the pandemic waves in our region (from March 2020 to October 2021). The percentages of positive QFT-plus patients did not significantly change before and during the pandemic (13.9% vs. 12.2%). Forty-nine patients from the suspected/confirmed COVID-19 pneumonia cohort (54.4%) had low/very low IFN-gamma response to mitogen, 22 of them (24.4%) had severe and critical pneumonia. None received immunosuppressants prior to testing. Abnormal radiological findings (P=0.01) but not COVID-19 severity was associated with low mitogen response. Immune profiling showed a reduction of CD8+T cells and a direct correlation between the number of EMRA CD8+T-cells and IFN-gamma response to mitogen (P=0.03). ConclusionLow IFN-gamma responses in mitogen tube of QFT-Plus often occur in COVID-19 pneumonia, which is associated with a low number of an effector CD8+T-cell subset and does not seem to affect LTBI screening; however, this abnormality seems to parallel the dynamics of COVID-19 at the population level and its mortality.

Human genetic and immunological determinants of critical COVID-19 pneumonia.

SARS-CoV-2 infection is benign in most individuals but, in around 10% of cases, it triggers hypoxaemic COVID-19 pneumonia, which leads to critical illness in around 3% of cases. The ensuing risk of death (approximately 1%across age and gender) doubles every five years from childhood onwards and is around 1.5 times greater in men than in women. Here we review the molecular and cellular determinants of critical COVID-19 pneumonia. Inborn errors of type I interferons(IFNs), including autosomal TLR3 and X-chromosome-linked TLR7 deficiencies, are found in around 1-5% of patients with critical pneumonia under 60 years old, and a lower proportion in older patients. Pre-existing auto-antibodies neutralizing IFNα, IFNβ and/or IFNω, which are more common in men than in women, are found in approximately 15-20% of patients with critical pneumonia over 70 years old, and a lower proportion in younger patients. Thus, at least 15% of cases of critical COVID-19 pneumonia can be explained. The TLR3- and TLR7-dependent production of type I IFNs by respiratory epithelial cells and plasmacytoid dendritic cells, respectively, is essential for host defence against SARS-CoV-2. In ways that can depend on age and sex, insufficient type I IFN immunity in the respiratory tract during the first few days of infection may account for the spread of the virus, leading to pulmonary and systemic inflammation.

Early Identification of COVID-19 Progression to Its Severe Form Using Artificial Intelligence

Background: Early prediction of disease progression in coronavirus disease 2019 (COVID-19) patients can be helpful for personalized therapy, as well as the optimal allocation of public health resources. Objectives: This study aimed to present predictive models for identifying potential high-risk COVID-19 patients upon hospital admission, based on the examination of clinical and radiological features by radiologists and artificial intelligence (AI). Patients and Methods: A total of 786 initially non-severe COVID-19 patients were retrospectively enrolled in this study between January 2 and May 28, 2020. The patients were randomly divided into training (n = 628, 80%) and test (n = 158, 20%) groups. Clinical factors, laboratory indicators, and radiologist- and AI-extracted radiological features of pneumonia lesions were determined using a convolution neural network. The features were selected based on the Boruta algorithm with five-fold cross-validation. Four models, including a model based on clinical findings (model C), a model based on the physician’s examination of radiological features (R-Doc model), a model based on AI-derived radiological features (R-AI model), and an AI-based model mimicking the physician’s examinations (AI-Mimic-Doc model), were constructed for predicting COVID-19 progression upon admission, using a logistic regression analysis. The predictive performance of the four models was evaluated by calculating the area under the receiver operating characteristic (AUC) curve with a 95% confidence interval (95% CI) and then compared using the DeLong test. Results: Overall, 238 out of 786 patients (30.3%) progressed into severe or critical pneumonia during the 14-day follow-up. Nine clinical findings, 17 laboratory indicators, 48 physician-extracted radiological features of pneumonia lesions, and 126 AI-driven radiological features were collected. The urea, albumin level, and lesion size in the basal segment of the right lower lobe of the lung or the proportion of CT values in the range of -200 - 60 in the left lung were the representative features for constructing the R-Doc and R-AI models, respectively. Comparison of the R-Doc model (AUC: 0.840, 95% CI: 0.747 - 0.933 for the training set and 0.731, 95% CI: 0.606 - 0.857 for the test set) with the R-AI model (AUC: 0.803, 95% CI: 0.701 - 0.906 for the training set and AUC: 0.731, 95% CI: 0.606 - 0.857 for the validation set) indicated a marginal difference in identifying patients at risk of progression to pneumonia upon admission (P &lt; 0.1). The R-AI model was superior to model C, with an AUC of 0.770 for the training set (95% CI: 0.657 - 0.882) and 0.666 for the validation set to identify high-risk non-severe cases upon admission. Conclusion: By using radiological features along with blood tests, early identification of COVID-19 patients, who are at risk of disease progression, can be achieved on admission (rapidly by using AI); therefore, the use of these features can contribute to the clinical management of COVID-19.