The importance of chest CT severity score and lung CT patterns in risk assessment in COVID-19-associated pneumonia: a comparative study.

Introduction: Chest computed tomography (CT) is suitable to assess morphological changes in the lungs. Chest CT scoring systems (CCTS) have been developed and use in order to quantify the severity of pulmonary involvement in COVID-19. CCTS has also been correlated with clinical outcomes. Here we wished to use a validated, relatively simple CTSS to assess chest CT patterns and to correlate CTSS with clinical outcomes in COVID-19. Patients and methods: Altogether 227 COVID-19 cases underwent chest CT scanning using a 128 multi-detector CT scanner (SOMATOM Go Top, Siemens Healthineers, Germany). Specific pathological features, such as ground-glass opacity (GGO), crazy-paving pattern, consolidation, fibrosis, subpleural lines, pleural effusion, lymphadenopathy and pulmonary embolism were evaluated. CTSS developed by Pan et al. (CTSS-Pan) was applied. CTSS and specific pathologies were correlated with demographic, clinical and laboratory data, A-DROP scores, as well as outcome measures. We compared CTSS-Pan to two other CT scoring systems. Results: The mean CTSS-Pan in the 227 COVID-19 patients was 14.6 ± 6.7. The need for ICU admission (p < 0.001) and death (p < 0.001) were significantly associated with higher CTSS. With respect to chest CT patterns, crazy-paving pattern was significantly associated with ICU admission. Subpleural lines exerted significant inverse associations with ICU admission and ventilation. Lymphadenopathy was associated with all three outcome parameters. Pulmonary embolism led to ICU admission. In the ROC analysis, CTSS>18.5 significantly predicted admission to ICU (p = 0.026) and CTSS>19.5 was the cutoff for increased mortality (p < 0.001). CTSS-Pan and the two other CTSS systems exerted similar performance. With respect to clinical outcomes, CTSS-Pan might have the best performance. Conclusion: CTSS may be suitable to assess severity and prognosis of COVID-19-associated pneumonia. CTSS and specific chest CT patterns may predict the need for ventilation, as well as mortality in COVID-19. This can help the physician to guide treatment strategies in COVID-19, as well as other pulmonary infections.

Corrigendum: Definition of the immune parameters related to COVID-19 severity.

[This corrects the article DOI: 10.3389/fimmu.2022.850846.].

Pulmonary embolism at CT pulmonary angiography in patients with COVID-19 at a tertiary care center in Nepal: a cross-sectional study.

Coronavirus disease 2019 (COVID-19) began to spread in December 2019 and was declared a pandemic by WHO on 11 March 2020. Pulmonary embolism (PE) is a known sequel to COVID-19 infection. Many patients showed worsened symptoms of thrombotic events of pulmonary arteries during the second week of the disease for which computed tomography pulmonary angiography (CTPA) is recommended. The most frequent complications in critically ill patients are prothrombotic coagulation abnormalities and thromboembolism. So, this study aimed to assess the prevalence of PE in patients with COVID-19 infection and to evaluate the relation to disease severity on CTPA findings. Methods: This cross-sectional study was performed to evaluate the patients who tested positive for COVID-19 and underwent CTPA. COVID-19 infection in participants was confirmed by a PCR of nasopharyngeal or oropharyngeal swab samples. Frequencies of computed tomography severity scores and CTPA were calculated and compared with clinical and laboratory findings. Results: The study included 92 patients with COVID-19 infection. Positive PE was found in 18.5% of the patients. The mean age of the patients was 59.83±13.58 years with an age range of 30-86 years. Among the total participants, 27.2% underwent ventilation, 19.6% died during treatment, and 80.4% of them got discharged. PE was developed in patients who did not receive prophylactic anticoagulation, which is statistically significant (P≤0.001). There was also a significant relationship between mechanical ventilation and CTPA findings. Conclusions: The authors conclude from their study that PE is one of the complications of COVID-19 infection. Rising D-dimer during the second week of disease alerts clinicians to do CTPA to exclude or confirm PE. This will help in the early diagnosis and treatment of PE.

CLINICO-RADIOLOGICAL EVALUATION AND CORRELATION OF HRCT CHEST IMAGING FINDINGS WITH DISEASE STATUS IN COVID-19 PATIENTS

Background: High-resolution computed tomography (HRCT) chest is rapid and has a strong sensitivity for diagnosing viral pneumonia including COVID 19 disease in its early stages in comparison to RT-PCR, thus being crucial in triaging patients for treatment and isolation, to prevent further transmission of the disease. In this study we are going to analyse the temporal changes in imaging findings of COVID-19 on HRCT chest. Methods: prospective study was conducted in the Department of Radiology of an exclusive 500 bedded COVID Hospital in Bhubaneswar, Odisha, India. Evaluation of hundred patients was done based on inclusion and exclusion criteria, after obtaining informed consent over a period of 2 years from September 2020 to September 2022. All pertinent epidemiological data was gathered from hospital records. All COVID 19 RT-PCR positive patients who underwent HRCT Chest on admission and repeat scan within 30 days, following the progression of the disease were included. Those who were clinically suspected COVID cases but were RT PCR negative on RT-PCR testing, were excluded. Results: HRCT chest demonstrated diffuse ground glass opacities to be the predominant finding (55%) with the associated findings of sub pleural atelectatic bands (31%) and septal thickening (23%). There was a positive correlation of blood parameters like CRP in COVID patients. A higher incidence was found in patients with Type-2 diabetes mellitus, followed by those with hypertension. In majority of the cases (80%) bilateral lungs and in about 81% cases, two or more lung lobes were involved. Mild and moderately ill patients were found to have a CTSS (CT severity score) in the score range of 15-25. Typical category was the most common type followed by atypical and indeterminate categories. Conclusions: 'Typical pattern' along with diffuse ground glass opacities of multiple lobes in the HRCT chest was the most common pattern of lung involvement. High Computer Tomography Severity Score (CTSS) corresponds to a higher disease severity, which helps in taking a timely decision for early treatment. HRCT Thorax has early and fast diagnostic capability as compared to RT-PCR in the detection of COVID-19. The elderly and those with comorbidities are at a higher risk of developing severe disease. Blood parameters like CRP can be used for disease monitoring and follow-up purposes. [ FROM AUTHOR] Copyright of Journal of Cardiovascular Disease Research (Journal of Cardiovascular Disease Research) is the property of Journal of Cardiovascular Disease Research and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

CT chest for COVID-19, a multicenter study—experience with 220 Egyptian patients

BackgroundCOVID-19 has become a national and an international pre-occupation to all doctors. Dealing with patients with clinical suspicion of COVID-19 is a daily markedly growing professional issue for radiologists. The number of COVID-19 cases we deal with is peaking since last March and so is our experience in recognizing the disease patterns and in assessing its severity. The purpose of this study is to assess the role of CT chest in the diagnosis of COVID-19 based on our experience with 220 Egyptian cases.ResultsA cross-sectional multicenter study involving 220 patients;68 (30.9%) females and 152 (69.1%) males, their age range was 10-92 years (average 49.198 years). Non-contrast MSCT chest was done to patients with clinically suspected COVID-19. Data assessment and analysis for lesions probability, pattern, localization, and severity were done.Bilateral affection was seen in 168/220 cases (76.36%). Multilobar affection was noted in 186/220 cases (84.54%). Lower lobes affection was noted in 179/220 cases (81.36%). Peripheral/subpleural affection was noted in 203/220 cases (92.27%). The common CT patterns (ground-glass opacities, consolidation, crazy paving, vascular thickening, traction bronchiectasis, vacuolar sign, architectural distortion signs, and reversed halo sign) and the uncommon CT patterns (halo sign, masses, nodules, lobar affection, tree in-bud-pattern and cysts) were discussed. Associated extra-pulmonary lesions described. Temporal changes, severity scoring, reporting, and possible pitfalls were all assessed.ConclusionIn our experience, CT plays a basic essential role in diagnosing COVID-19 in the current declared pandemic.

Typical and atypical chest computed tomography manifestations in COVID-19 patients

Background High-resolution computed tomography (CT) is the most reliable sensitive noninvasive imaging procedure recommended in the diagnosis, assessment, the severity, and follow-up of coronavirus disease 2019 (COVID-19).It has a qualitative and quantitative role. The COVID-19 Reporting and Data System evaluates the probability of COVID-19 pulmonary involvement, and the corresponding CT severity score, which evaluates the approximate percentage of each of the five lobes' involvement. Research question We aimed to illustrate chest CT typical and atypical manifestations in COVID-19 patients regarding their age, sex, patients' symptoms, and CT severity score. Study design and methods We conducted a cross-sectional study on 120 patients more than or equal to 18 years with confirmed COVID-19 infection (PCR positive) during the period from April 2021 to October 2021, who were admitted to Ain Shams University Isolation Hospitals, where all patients' clinical data and CT chest imaging for these patients will be collected.Copyright © 2023 Wolters Kluwer Medknow Publications. All rights reserved.

Correlation of clinical, laboratory, ventilation, and outcome parameters in hospitalized Coronavirus Disease 2019-infected patients with computed tomography severity score

Context Widespread prevalence of Coronavirus Disease 2019 (COVID-19) infection with high rates of morbidity and mortality necessitates early case definition and severity grading to predict prognosis and improve disease outcome parameters. Purpose To correlate computed tomography severity score (CTSS) in COVID-19-infected patients with their clinical, laboratory, method of ventilation, and disease outcome parameters. Patients and methods A retrospective analysis was performed on 139 COVID-19-infected patients with typical or indeterminate COVID radiological patterns with a correlation between CTSS and their clinical, laboratory, ventilation, hospital stay, and survival data. Results A total of 139 cases were included, with a mean age of 59.81 +/- 12.29 years, 63.3% males, 28.77% were noncomorbid, and oxygen saturation of 82.53 +/- 6.58 SD. They were subgrouped based on CTSS. A significant correlation was found between high CTSS and oxygen saturation, C-reactive protein, ferritin, D-dimer, lymphopenia, diabetes comorbid patients, need for high-flow oxygen therapy, need for noninvasive or invasive ventilation, mortality, and number of hospital stay in days. Conclusion Different parameters are correlated with high CTSS, especially low oxygen saturation, high C-reactive protein or ferritin values, diabetes, and long hospital stay.Copyright © 2023 Wolters Kluwer Medknow Publications. All rights reserved.

Predicting COVID-19 Severity Integrating RNA-Seq Data Using Machine Learning Techniques

A fundamental challenge in the fight against COVID-19 is the development of reliable and accurate tools to predict disease progression in a patient. This information can be extremely useful in distinguishing hospitalized patients at higher risk for needing UCI from patients with low severity. How SARS-CoV-2 infection will evolve is still unclear. Method(s): A novel pipeline was developed that can integrate RNA-Seq data from different databases to obtain a genetic biomarker COVID-19 severity index using an artificial intelligence algorithm. Our pipeline ensures robustness through multiple cross-validation processes in different steps. Result(s): CD93, RPS24, PSCA, and CD300E were identified as COVID-19 severity gene signatures. Furthermore, using the obtained gene signature, an effective multi-class classifier capable of discrimi-nating between control, outpatient, inpatient, and ICU COVID-19 patients was optimized, achieving an accuracy of 97.5%. Conclusion(s): In summary, during this research, a new intelligent pipeline was implemented to develop a specific gene signature that can detect the severity of patients suffering COVID-19. Our approach to clinical decision support systems achieved excellent results, even when processing unseen samples. Our system can be of great clinical utility for the strategy of planning, organizing and managing human and material resources, as well as for automatically classifying the severity of patients affected by COVID-19.Copyright © 2023 Bentham Science Publishers.

Medication regimen complexity (MRC-ICU) for in-hospital mortality prediction in COVID-19 patients

Purpose: The medication regimen complexity-intensive care unit (MRC-ICU) score was developed prior to the existence of COVID-19. The purpose of this study was to assess if MRC-ICU could predict in-hospital mortality in patients with COVID-19. Method(s): A single-center, observational study was conducted from August 2020 to January 2021. The primary outcome of this study was the area under the receiver operating characteristic (AUROC) for in-hospital mortality for the 48-hour MRC-ICU. Age, sequential organ failure assessment (SOFA), and World Health Organization (WHO) COVID-19 Severity Classification were assessed. Logistic regression was performed to predict in-hospital mortality as well as WHO Severity Classification at 7 days. Result(s): A total of 149 patients were included. The median SOFA score was 8 (IQR 5-11) and median MRC-ICU score at 48 hours was 15 (IQR 7-21). The in-hospital mortality rate was 36% (n = 54). The AUROC for MRC-ICU was 0.71 (95% Confidence Interval (CI), 0.62-0.78) compared to 0.66 for age, 0.81 SOFA, and 0.72 for the WHO Severity Classification. In univariate analysis, age, SOFA, MRC-ICU, and WHO Severity Classification all demonstrated significant association with in-hospital mortality, while SOFA, MRC-ICU, and WHO Severity Classification demonstrated significant association with WHO Severity Classification at 7 days. In univariate analysis, all 4 characteristics showed significant association with mortality;however, only age and SOFA remained significant following multivariate analysis. Conclusion(s): In the first analysis of medication-related variables as a predictor of severity and in-hospital mortality in COVID-19, MRC-ICU demonstrated acceptable predictive ability as represented by AUROC;however, SOFA was the strongest predictor in both AUROC and regression analysis.Copyright © The Author(s) 2023.

Association of Risk Factors among Nasal and Orbital Mucormycosis in Coronavirus Disease 2019 Infection: A Cross-Sectional Study.

Purpose: To study the risk factors of mucormycosis and analyze their association among nasal and orbital mucormycosis in Coronavirus disease 2019 (COVID-19) infection. Methods: All patients diagnosed of rhino-orbito-cerebral mucormycosis (ROCM) with previous COVID-19 infection were included in the study. The details such as age, sex, presence of co-morbidities, and serum ferritin levels were collected. ROCM patients were classified into two groups, nasal mucormycosis (stage 1 and 2 of ROCM) and orbital mucormycosis (stage 3 and 4 of ROCM), and data were collected. Duration of COVID-19 symptoms, the time interval between COVID-19 infection and onset of ROCM symptoms, computed tomography severity score (CTSS) and usage of steroids were collected accordingly. The collected data were compared between nasal group and orbital group. Results: Among 52 patients, 15 patients had nasal and 37 patients had orbital mucormycosis. Forty-one patients were more than 40 years, 43 patients were males. Seven out of ten risk factors were found to be significant on comparing nasal and orbital group. Patients of age more than 40 years (P = 0.034), elderly diabetics (P = 0.014), poor control of diabetes (P = 0.003), high serum ferritin levels (P = 0.043), duration between COVID-19 and mucormycosis of more than 20 days (P = 0.038), CTSS of more than 9/25 (P = 0.020), and steroid usage during COVID-19 infection (P = 0.034) are prone to develop orbital mucormycosis. On multivariate logistic regression analysis, these variables did not emerge as independent risk factors. Conclusions: Patients with severe COVID-19 infection along with other associated risk factors can be prone to develop severe forms of mucormycosis. We did not find them to be statistically significant on multivariate analysis. In the future, large scale studies are needed to know their significance.

Total severity score and age predict long-term hospitalization in COVID-19 pneumonia.

Background: Severe COVID-19 pneumonia implies increased oxygen demands and length of hospitalization (LOS). We aimed to assess a possible correlation between LOS and COVID-19 patients' clinical laboratory data of admission, including the total severity score (TSS) from chest computed tomography (CT). Methods: Data were assessed retrospectively at the General Hospital "Agios Pavlos" in Greece. Clinical laboratory data, TSS, and LOS were recorded. Results: A total of 317 patients, 136 women and 181 men, with a mean age of 66.58 ± 16.02 years were studied. Significant comorbidities were hypertension (56.5%), dyslipidemia (33.8%), type 2 diabetes mellitus (22.7%), coronary heart disease (12.9%), underlying pulmonary disease (10.1%), and malignancy (4.4%). Inpatient time was related to age (p < 0.001), TSS (p < 0.001), time from symptom onset to hospitalization (p = 0.006), inhaled oxygen fraction (p < 0.001), fibrinogen (p = 0.024), d-dimers (p < 0.001), and C-reactive protein (p = 0.025), as well as a history of hypertension (p < 0.001) and type 2 diabetes mellitus (p < 0.008). The multivariate analysis showed a significant association of the LOS with age (p < 0.001) and TSS (p < 0.001) independent of the above-mentioned factors. Conclusion: Early identification of disease severity using the TSS and patients' age could be useful for inpatient resource allocation and for maintaining vigilance for those requiring long-term hospitalizations.

Changes in Pediatric Non-accidental Trauma Emergency Department Visits During and Following the COVID-19 Lockdown.

A level 1 pediatric trauma registry database was examined for all non-accidental trauma (NAT) emergency department visits between 2016 and 2021, and average injury severity score assigned to those patients with physical injuries over 2019-2021. There was a decline in NAT visits in 2020 (267) from prior years (343 visits average over 2016-2019), with subsequent increase in 2021 (548). Injury severity score increased (ISS) in 2020 (7.3) when compared to 2019 (5.71), with a decline in average ISS in 2021 (5.42). This data highlights the potential for missed abuse during closures with increased detection following reopening. Our data regarding ISS demonstrates the pediatric population is at risk of more severe abuse during times of familial stress. We need increased awareness that periods of vulnerability to NAT exist, as seen during the COVID-19 pandemic.

Disease-Modifying Therapies, Outcomes, Risk Factors and Severity of COVID-19 in Multiple Sclerosis: A MENACTRIMS Registry Based Study

Background: Multiple sclerosis (MS) patients have been considered a higher-risk population for COVID-19 due to the high prevalence of disability and disease-modifying therapy use;however, there is little data in our Middle East and North Africa region (MENA) identifying clinical characteristics of MS associated with worse COVID-19 outcomes. Material(s) and Method(s): This a nationwide, multicenter, retrospective cohort study conducted between March 2020 and February 2021 and included MS patients with a suspected or confirmed COVID-19. Using data collected from the MENACTRIMS registry and local COVID-19 registries, the association of patient demographics, MS disease characteristics, and use of disease-modifying therapies with outcomes and severity of COVID-19 illness were evaluated by multivariate logistic models. Result(s): A total of 600 MS patients with suspected (n=58) or confirmed (n=542) COVID-19 (mean age: 36.4 +/- 10.16 years;414 (69%) females;mean disease duration: 8.3+/- 6.6 years) were analyzed. Seventy-three patients (12.2%) had a COVID-19 severity score of 3 or more, and 15 patients (2.5%) died of COVID-19. The median EDSS was 2.0 (range, 0-9.5), and 559 patients (93.2%) were receiving disease-modifying therapy (DMT). There was a higher proportion of patients with a COVID-19 severity score of 3 or more among patients treated with DMTs relative to untreated patients (82.9% vs 17.1%;P < .001), from whom the majority (n=117;19.7%) were maintained on anti-CD20 therapies such as ocrelizumab and rituximab. Comorbidities mainly hypertension and cardiovascular diseases, progressive MS, disease duration, and EDSS were associated with severe or worse COVID-19 disease outcome. Multivariate logistic regression analysis showed that older age (odds ratio per 10 years, 1.5 [95%CI, 1.1-2.0]), male gender (OR, 2.1 [95%CI. 1.2-3.8]), obesity (OR, 2.8 [95%CI, 1.3-5.8]), and treatment ocrelizumab/rituximab (OR for ocrelizumab, 4.6 [95%CI. 1.2-17.7], OR for rituximab, 14.1 [95%CI, 4.8-41.3]) or off-label immunosuppressive medications such as azathioprine or mycophenolate mofetil (OR, 8.8 [95%CI. 1.7-44.0]) were risk factors for moderate to severe COVID-19 requiring hospitalization. Surprisingly, smoking and diabetes were not identified as risk factors for severe COVID-19 disease in our cohort. Conclusion(s): In this registry-based cohort study of patients with MS, age, sex, EDSS, obesity, progressive MS were independent risk factors for severe COVID-19. Moreover, there was an association found between exposure to anti-CD20 DMTs and COVID-19 severity. Knowledge of these risk factors may help improve the clinical management of MS patients with COVID-19 infection.Copyright © 2022

Prognostic significance of chest CT severity score in mortality prediction of COVID-19 patients, a machine learning study

Background: The high mortality rate of COVID-19 makes it necessary to seek early identification of high-risk patients with poor prognoses. Although the association between CT-SS and mortality of COVID-19 patients was reported, its prognosis significance in combination with other prognostic parameters was not evaluated yet. Method(s): This retrospective single-center study reviewed a total of 6854 suspected patients referred to Imam Khomeini hospital, Ilam city, west of Iran, from February 9, 2020 to December 20, 2020. The prognostic performances of k-Nearest Neighbors (kNN), Multilayer Perceptron (MLP), Support Vector Machine (SVM), and J48 decision tree algorithms were evaluated based on the most important and relevant predictors. The metrics derived from the confusion matrix were used to determine the performance of the ML models. Result(s): After applying exclusion criteria, 815 hospitalized cases were entered into the study. Of these, 447(54.85%) were male and the mean (+/- SD) age of participants was 57.22(+/- 16.76) years. The results showed that the performances of the ML algorithms were improved when they are fed by the dataset with CT-SS data. The kNN model with an accuracy of 94.1%, sensitivity of 100. 0%, precision of 89.5%, specificity of 88.3%, and AUC around 97.2% had the best performance among the other three ML techniques. Conclusion(s): The integration of CT-SS data with demographics, risk factors, clinical manifestations, and laboratory parameters improved the prognostic performances of the ML algorithms. An ML model with a comprehensive collection of predictors could identify high-risk patients more efficiently and lead to the optimal use of hospital resources.Copyright © 2023, The Author(s).

Assessing the Severity of COVID-19 in the United States

The paper proposes a unique set of relatively simple-to-construct-and-use metrics to track the spread and severity of COVID-19 cases in the United States with respect to state-wise distribution. To our knowledge, such metrics have not been proposed by others. The proposed metrics and case study presented in the paper can serve as a template for public health officials to update the disease's severity and spread across states. Consequently, effective resources can be directed to the hard-hit states. Since the number of infections and deaths due to COVID-19 is dynamic, the proposed metrics along with the case study's approach can be easily updated to match new available data on the disease. The primary message of our work is to provide a unique perspective into investigating the current severity and spread of the pandemic in different states in the country and highlight states with a relatively high severity score. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Impact of lockdown policies during the COVID-19 outbreak on a trauma center of a tertiary hospital in China.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is a major and costly public health emergency. AIM: To investigate the impact of China's lockdown policies during the COVID-19 outbreak on the level I trauma center of a tertiary comprehensive hospital of Traditional Chinese Medicine. METHODS: All patients admitted to our trauma center during a lockdown in 2020 and the same period in 2019 were enrolled. We collected data on demographics, daily visits, injury type, injury mechanism, injury severity score, and patient management for comparative analysis. RESULTS: The total number of patients in the trauma center of our hospital decreased by 50.38% during the COVID-19 Lockdown in 2020 compared to the same period in 2019. The average number of trauma visits per day in 2019 was 47.94, compared to 23.79 in 2020. Comparing the patients' demographic data, loss of employment was the most predominate characteristic in 2020 compared to 2019, while there was no significant difference in gender, age, and marital status between both periods. During the lockdown period, the proportion of traffic accident-related injuries, injuries due to falls greater than 1.5 m, and mechanical injuries decreased significantly, whereas the proportion of injuries caused by falls less than 1.5 m, cuts, assault, bites, and suicidal tendencies and other injuries increased relatively. In addition, the proportion of patients with minor injuries increased and serious injuries decreased during the lockdown. The hospitalization rate increased significantly, and there was no significant difference in emergency surgery and death rates. CONCLUSION: The lockdown policies during the COVID-19 outbreak significantly altered the number and mechanism of traumatic events in our hospital, which can be monitored regularly. Our results suggest that mandatory public health prevention and control measures by the government can reduce the incidence of traumatic events and the severity of traumatic injuries. Emergency surgery and mortality rates remain high, increased because of factors such as family injury and penetrating injury, and hospitalization rates have increased significantly. Therefore, our trauma center still needs to be fully staffed. Finally, from the perspective of the injury mechanism, indoor trauma is a major risk during a lockdown, and it is particularly important to develop prevention strategies for such trauma to reduce the medical burden of the next catastrophic epidemic.

A Specific Pattern and Dynamics of Circulating Cytokines Are Associated with the Extension of Lung Injury and Mortality in Colombian Adults with Coronavirus Disease-19.

Increased systemic levels of inflammatory cytokines have been associated with the development of pathophysiologic events during severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. To further explore differences in the pattern and dynamics of plasma cytokines in individuals with coronavirus disease-19 (COVID-19), and the relationship with disease mortality, here we evaluated the plasma levels of proinflammatory and regulatory cytokines in Colombian patient survivors and nonsurvivors of SARS-CoV-2 infection. Individuals with confirmed COVID-19, with other respiratory diseases requiring hospitalization, and healthy controls, were included. Plasma levels of interleukin (IL)-6, tumor necrosis factor (TNF)-α, interferon-γ, IL-10, soluble tumor necrosis factor receptor I (sTNFRI), and transforming growth factor-ß1 were measured by a bead-based assay or enzyme-linked immunosorbent assay and clinical, laboratory, and tomographic parameters were registered during hospitalization. The levels of most of the evaluated cytokines were increased in COVID-19 individuals relative to healthy controls. The levels of IL-6, IL-10, and sTNFRI were directly associated with the development of respiratory failure, immune dysregulation, and coagulopathy, as well as with COVID-19 mortality. Particularly, the early, robust, and persistent increase of circulating IL-6 characterized COVID-19 nonsurvivors, while survivors were able to counteract the inflammatory cytokine response. In addition, IL-6 systemic levels positively correlated with the tomographic extension of lung damage in individuals with COVID-19. Thus, an exacerbated inflammatory cytokine response, particularly mediated by IL-6 added to the inefficiency of regulatory cytokines, distinguishes COVID-19-associated tissue disturbances, severity, and mortality in Colombian adults.

The outcome of pulmonary function tests and high-resolution computed tomography of chest in post-coronavirus disease 2019-confirmed cases after 3 months of recovery

Background: Coronavirus disease (COVID-19) is a recently prevalent infectious disease that is caused by a virus from the coronavirus family and causes acute respiratory syndrome. It is a pandemic catastrophe that has affected more than 60 million people around the world and has caused about 1.5 million deaths, as reported by the WHO. This disease affects the respiratory system and leads to different forms of symptoms and signs. Pneumonia is a common cause for hospitalization, with most patients treated in hospital wards and others requiring ICU. Although the number of complete recoveries from COVID-19 has increased, there is still concern about complications associated with the disease that appear after recovery. The studies that have looked at past types and other forms of coronavirus epidemics, such as SARS have shown that some cases had respiratory complications from the infection after being full recovered, as 36 and 30% of the entire study population had clinical and high-resolution computed tomography (HRCT) changes at 3 and 6 months after recovery, respectively. Mostly, the abnormalities seen in pulmonary function test (PFT) results are sequelae of diffusion capacity defect. In recovered cases of Middle East respiratory syndrome, 36% of patients showed HRCT sequelae at follow-up of 6 weeks, because of fibrosis. Data on COVID-19 indicate that prolonged disease and persistent symptoms show post-PFT affection and follow-up radiographic changes after recovery from COVID-19 as interstitial pulmonary changes and a degree of pulmonary vasculopathy. In recovered cases of COVID-19, capacity of diffusion is the commonest defect in lung function, followed by the restrictive pattern defects on spirometry;both are related to the degree of severity of pneumonic COVID-19. PFTs (involving spirometry as well as diffusion capacity) are considered as routine follow-up examinations for some of the recovered cases, especially severe cases. Rehabilitation programs of the respiratory system are an option strategy that might be considered. This study aims to show changes in pulmonary function and HRCT of chest in post-COVID-19-infected patients to detect long-term effects on the lungs after 3 months as obstructive or restrictive, or both, lung diseases. Patients and Methods: The study was conducted on 100 confirmed PCR-positive COVID-19 cases that were admitted to Ain Shams University Isolation Hospitals, and the follow-up was performed in the outpatient clinic. PCR samples (Combined nasopharyngeal and oropharyngeal swab) were taken after 3 months from discharge of patients above the age of 18 years who become negative with clinical improvement. PFT [spirometry and diffusion for carbon monoxide (DLCO)] and chest HRCT were done. All patients' clinical data were recorded, and CT chest imaging data of these patients were correlated with the clinical data. Result(s): A total of 100 patients were included in this study, where males represented 58% and female represented 42%. The mean+/-SD age of cases in this study was 45.05 +/- 11.80 years and ranged from 20 to 79 years. CT chest severity score (SS) of abnormality in COVID-19-infectedd patients based on HRCT chest findings before and after 3 months from treatment showed a highly significant correlation (P=0.000). The results of PFT in the studied group after 3 months of discharge showed restrictive pattern in 14.9%, obstructive pattern in 17.8%, and both obstructive and restrictive patterns in 5.9% of the total number of cases. There was a significant correlation between DLCO abnormality findings and age of studied group (P=0.032), a significant correlation between abnormality findings on PFT and HRCT chest SS after discharge of the studied group (P0.001). There was a significant correlation between abnormality findings of DLCO and HRCT chest SS after 3 months of the studied group (P=0.000) and before treatment (P=0.001), whereas there was no significant correlation between other findings of PFT and HRCT chest SS after 3 months and before. There was a significant correlation between H

COVID-19 Severity Index (SI): is it a sensitive predictor score for disease outcome in hospitalized patients?

Introduction. The COVID-19 pandemic showed the wide ranging of coronavirus disease prognosing, hence clinical identification of patients who are at risk of poor outcomes is a priority. But there is no proven prognostic scoring system yet. COVID-19 SI was developed as a triage tool, that could be used by healthcare personnel to identify highrisk patients. 1 Aim. To estimate whether COVID-19 SI could predict the disease outcome in hospitalized patients with coronavirus disease already on admission? Methods. The study was a single-center retrospective analysis based on data of 632 COVID-19 patients admitted to the City Hospital No 4 (Dnipro) from August to October 2021. The patients' SI on admission and disease outcome were analyzed and statistically processed. Results. Distribution of survivors and nonsurvivors regarding clinical risk in accordance with SI is presented in Table 1. The sensitivity of SI as prognostic score totaled 37 %;specificity - 52,7 %. Conclusions. The study confirmed COVID-19 SI as a good triage tool on admission, but it has low sensitivity and specificity as prognostic score. (Table Presented).

Effect of COVID-19 Pandemic on Major Trauma Treated at a Level I Trauma Centre.

PURPOSE OF THE STUDY The paper aims to evaluate the effect of COVID-19 pandemic on a change in the number of major trauma cases, their mechanism and length of hospital stay as seen by a Level I Trauma Centre. MATERIAL AND METHODS The retrospective study included a total of 755 major trauma patients (ISS >= 16) treated at our Level I Trauma Centre in the period 2018-2019 ("pre-COVID-19 time") and 2020-2021 ("COVID-19 time"). The effect of COVID-19 infection on the change in the number and nature of major trauma, mechanism of injury, length of treatment during prehospital care, length of hospital stay, and mortality. RESULTS Of the total number of 755 patients with major trauma, in the "pre-COVID-19 time" 399 patients were treated, while in the "COVID-19 time" it was 356 patients (p = 0.10). The mechanism of major trauma did not change, road traffic accidents prevailed (61% vs. 56%, p = 0.25), the proportion of injuries due to falls from height increased (25% vs. 32.5%, p = 0.08), a significant decrease was observed in the category of severe skiing injuries (7 vs. 2, p = 0.003). The severity of injuries evaluated by Injury Severity Score remained unchanged (25 vs. 25, p = 0.08), but an increased number of patients with trau-matic brain injury (TBI) marked by the Abbreviate Injury Score (AIS) >= 4 was observed (38 vs. 56, p = 0.03). The total length of a hospital stay shortened (18 vs. 15 days, p = 0.04), but the mortality rate spiked (52 vs. 73 patients, p = 0.08). DISCUSSION In the "COVID-19 time", the total number of major trauma cases dropped just like in the other European countries. Despite restrictive measures imposing mobility restrictions, no change was reported in the mechanism of injury, with traffic accidents still prevalent, except for skiing injuries. Unlike the US, we did not see an increase in penetrating injuries due to interpersonal violence or suicidal behaviour. However, there was an increase in the percentage of patients with an isolated TBI as a result of a fall from height. An increase in mortality was reported due to an increase in severe TBI. The length of hospital stay was reduced as a result of efforts to maintain hospital bed availability. CONCLUSIONS During the COVID-19 pandemic, compared to the two years immediately preceding, no significant decrease in the number of major trauma cases was reported, despite the introduction of restrictive measures. The proportion of road traffic injuries remained the same, whereas the number of falls from height slightly increased, which consequently led to an increase in the number of severe TBI. The number of penetrating injuries due to acts of violence did not increase, but due to the lockdown there was a significant decrease in severe skiing-related injuries. The anti-epidemic measures in place did not prolong the pre-hospital care for severely injured patients.Copyright © 2022, Galen s.r.o.. All rights reserved.