Comparison between original SARS-CoV-2 strain and omicron variant on thin-section chest CT imaging of COVID-19 pneumonia

OBJECTIVES

We investigated different computed tomography (CT) features between Omicron-variant and original-strain SARS-CoV‑2 pneumonia to facilitate the clinical management.

MATERIALS AND METHODS

Medical records were retrospectively reviewed to select patients with original-strain SARS-CoV‑2 pneumonia from February 22 to April 22, 2020, or Omicron-variant SARS-CoV‑2 pneumonia from March 26 to May 31, 2022. Data on the demographics, comorbidities, symptoms, clinical types, and CT features were compared between the two groups.

RESULTS

There were 62 and 78 patients with original-strain or Omicron-variant SARS-CoV‑2 pneumonia, respectively. There were no differences between the two groups in terms of age, sex, clinical types, symptoms, and comorbidities. The main CT features differed between the two groups (p = 0.003). There were 37 (59.7%) and 20 (25.6%) patients with ground-glass opacities (GGO) in the original-strain and Omicron-variant pneumonia, respectively. A consolidation pattern was more frequently observed in the Omicron-variant than original-strain pneumonia (62.8% vs. 24.2%). There was no difference in crazy-paving pattern between the original-strain and Omicron-variant pneumonia (16.1% vs. 11.6%). Pleural effusion was observed more often in Omicron-variant pneumonia, while subpleural lesions were more common in the original-strain pneumonia. The CT score in the Omicron-variant group was higher than that in the original-strain group for critical-type (17.00, 16.00-18.00 vs. 16.00, 14.00-17.00, p = 0.031) and for severe-type (13.00, 12.00-14.00 vs 12.00, 10.75-13.00, p = 0.027) pneumonia.

CONCLUSION

The main CT finding of the Omicron-variant SARS-CoV‑2 pneumonia included consolidations and pleural effusion. By contrast, CT findings of original-strain SARS-CoV‑2 pneumonia showed frequent GGO and subpleural lesions, but without pleural effusion. The CT scores were also higher in the critical and severe types of Omicron-variant than original-strain pneumonia.

Advances in natural product anti-coronavirus research (2002-2022)

COVID-19 is a severe acute respiratory syndrome caused by coronavirus that has triggered acute respiratory infections in countries around the world. In the last 20 years, there have been several outbreaks of coronaviruses, which have had a tremendous impact on productive life and globalization. Since coronaviruses are mutagenic and highly susceptible to mutation, there are no specific drugs against coronaviruses. Medicines made from natural products gains worldwide attention, and the mechanism and effectiveness of natural products for the treatment of coronavirus-related diseases have received much attention after the global pandemic of COVID-19 in 2020. The vitro research results and clinical data from various countries have shown protective effects of good effects against coronaviruses. This review summarizes representative natural products for the treatment of coronavirus-related diseases in the past 20 years, and demonstrates the promising prospects of natural products against coronavirus-related diseases by listing herbal formulas, Chinese patent medicines and natural small molecule compounds and their therapeutic mechanisms, providing references for subsequent related studies.

AMTLDC: a new adversarial multi-source transfer learning framework to diagnosis of COVID-19

In recent years, deep learning techniques have been widely used to diagnose diseases. However, in some tasks, such as the diagnosis of COVID-19 disease, due to insufficient data, the model is not properly trained and as a result, the generalizability of the model decreases. For example, if the model is trained on a CT scan dataset and tested on another CT scan dataset, it predicts near-random results. To address this, data from several different sources can be combined using transfer learning, taking into account the intrinsic and natural differences in existing datasets obtained with different medical imaging tools and approaches. In this paper, to improve the transfer learning technique and better generalizability between multiple data sources, we propose a multi-source adversarial transfer learning model, namely AMTLDC. In AMTLDC, representations are learned that are similar among the sources. In other words, extracted representations are general and not dependent on the particular dataset domain. We apply the AMTLDC to predict Covid-19 from medical images using a convolutional neural network. We show that accuracy can be improved using the AMTLDC framework, and surpass the results of current successful transfer learning approaches. In particular, we show that the AMTLDC works well when using different dataset domains, or when there is insufficient data.

Truncating fined-tuned vision-based models to lightweight deployable diagnostic tools for SARS-CoV-2 infected chest X-rays and CT-scans

In such a brief period, the recent coronavirus (COVID-19) already infected large populations worldwide. Diagnosing an infected individual requires a Real-Time Polymerase Chain Reaction (RT-PCR) test, which can become expensive and limited in most developing countries, making them rely on alternatives like Chest X-Rays (CXR) or Computerized Tomography (CT) scans. However, results from these imaging approaches radiated confusion for medical experts due to their similarities with other diseases like pneumonia. Other solutions based on Deep Convolutional Neural Network (DCNN) recently improved and automated the diagnosis of COVID-19 from CXRs and CT scans. However, upon examination, most proposed studies focused primarily on accuracy rather than deployment and reproduction, which may cause them to become difficult to reproduce and implement in locations with inadequate computing resources. Therefore, instead of focusing only on accuracy, this work investigated the effects of parameter reduction through a proposed truncation method and analyzed its effects. Various DCNNs had their architectures truncated, which retained only their initial core block, reducing their parameter sizes to <1 M. Once trained and validated, findings have shown that a DCNN with robust layer aggregations like the InceptionResNetV2 had less vulnerability to the adverse effects of the proposed truncation. The results also showed that from its full-length size of 55 M with 98.67% accuracy, the proposed truncation reduced its parameters to only 441 K and still attained an accuracy of 97.41%, outperforming other studies based on its size to performance ratio.

Relationship between coronavirus disease 2019 in pregnancy and maternal and fetal outcomes: Retrospective analytical cohort study

OBJECTIVE

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has caused many deaths and complications worldwide. However, limited data are available about COVID-19 during pregnancy. This study aimed to assess the epidemiological and clinical features of COVID-19, and the adverse maternal and fetal outcomes.

DESIGN

This retrospective analytical cohort study was conducted on all pregnant women with confirmed COVID-19 at Nekouei-Hedayati-Forghani Hospital in Qom, Iran from 15 March 2020 to 15 November 2020. For the same period, 165 pregnant women who did not have COVID-19 were selected at random and included in this study. All epidemiological and clinical features were collected from the medical records of the participants. A logistic regression model was used to determine associations between COVID-19 in pregnancy and maternal and fetal outcomes.

FINDINGS

The most common symptoms reported by pregnant women with COVID-19 were shortness of breath (60.9%), dry cough (59%) and fever (42.9%). After adjustment for potential confounding factors, COVID-19 in pregnancy was associated with a significantly higher risk of admission to the intensive care unit (ICU) [odds ratio (OR) 6.16, 95% confidence interval (CI) 1.23-31], caesarean section (OR 0.45, 95 CI 0.25-1.03), preterm birth (OR 3.01, 95% CI 1.4-6.54), fetal distress (OR 5.7, 95% CI 2.13-15.59) and admission to the neonatal intensive care unit (NICU) (OR 3.04, 95% CI 1.21-7.70).

KEY CONCLUSIONS

COVID-19 is associated with adverse maternal and fetal outcomes, including ICU admission, caesarean section, fetal distress, preterm birth and NICU admission.

Previous and First Detected Cardiovascular Diseases in Patients with New Coronavirus Pneumonia: Possible Mechanisms and Place in a Unified Prognostic Model

PURPOSE

The aim of this study is to evaluate the frequency of cardiac involvement in patients with coronavirus disease 2019 (COVID-19), possible immune mechanisms of myocardial injury, and the place of cardiovascular pathology among other prognostic factors.

METHODS

The study included 86 patients (48 male, 60.2 ± 16.6 years) with COVID-19. In addition to common investigation, examination of troponin T (n = 18) and anti-heart antibodies (AHA, n = 34) were used. The average hospital period was 14 [12; 18] days.

RESULTS

The incidence of cardiovascular disease and symptoms was 45.3%. Arrhythmias, heart failure, low-QRS voltage, repolarization disorders, and pericardial effusion were the typical for coronavirus cardiac injury. The level of AHA was increased in 73.5%. Significant (p < 0.05) correlations of AHA level with inflammatory activity, pneumonia, respiratory failure, cardiac symptoms, and death were found. D-dimer >0.5 μg/mL had a sensitivity of 79.2% and specificity of 60% in the prediction of cardiovascular manifestations. Cardiac failure was one of the causes of death in 3/8 patients (37.5%). Lethality in the presence of cardiovascular pathology was 17.9 versus 2.2% without it, p < 0.05. The most powerful prognostic model includes age, diabetes, oxygen therapy volume, maximum leukocyte level, C-reactive protein, and D-dimer (correlation coefficient 0.871, p < 0.001). The model with only age, diabetes, and cardiovascular disease included also had predictive power (correlation coefficient 0.568, p < 0.001).

CONCLUSIONS

The cardiovascular pathology is frequent in patients with COVID-19 and strong correlates with the D-dimer. It indicates the high significance of prothrombotic and ischemic mechanisms. High AHA levels may reflect an inflammatory heart injury. The cardiovascular pathology is associated with higher lethality.

Helmet CPAP to treat hypoxic pneumonia outside the ICU: an observational study during the COVID-19 outbreak

BACKGROUND

Respiratory failure due to COVID-19 pneumonia is associated with high mortality and may overwhelm health care systems, due to the surge of patients requiring advanced respiratory support. Shortage of intensive care unit (ICU) beds required many patients to be treated outside the ICU despite severe gas exchange impairment. Helmet is an effective interface to provide continuous positive airway pressure (CPAP) noninvasively. We report data about the usefulness of helmet CPAP during pandemic, either as treatment, a bridge to intubation or a rescue therapy for patients with care limitations (DNI).

METHODS

In this observational study we collected data regarding patients failing standard oxygen therapy (i.e., non-rebreathing mask) due to COVID-19 pneumonia treated with a free flow helmet CPAP system. Patients' data were recorded before, at initiation of CPAP treatment and once a day, thereafter. CPAP failure was defined as a composite outcome of intubation or death.

RESULTS

A total of 306 patients were included; 42% were deemed as DNI. Helmet CPAP treatment was successful in 69% of the full treatment and 28% of the DNI patients (P < 0.001). With helmet CPAP, PaO₂/FiO₂ ratio doubled from about 100 to 200 mmHg (P < 0.001); respiratory rate decreased from 28 [22-32] to 24 [20-29] breaths per minute, P < 0.001). C-reactive protein, time to oxygen mask failure, age, PaO₂/FiO₂ during CPAP, number of comorbidities were independently associated with CPAP failure. Helmet CPAP was maintained for 6 [3-9] days, almost continuously during the first two days. None of the full treatment patients died before intubation in the wards.

CONCLUSIONS

Helmet CPAP treatment is feasible for several days outside the ICU, despite persistent impairment in gas exchange. It was used, without escalating to intubation, in the majority of full treatment patients after standard oxygen therapy failed. DNI patients could benefit from helmet CPAP as rescue therapy to improve survival.

TRIAL REGISTRATION

NCT04424992.

Delirium in COVID-19: epidemiology and clinical correlations in a large group of patients admitted to an academic hospital

BACKGROUND

Delirium incidence and clinical correlates in coronavirus disease-19 (COVID-19) pneumonia are still poorly investigated.

AIM

To describe the epidemiology of delirium in patients hospitalized for suspect COVID-19 pneumonia during the pandemic peak in an academic hospital of Northern Italy, identify its clinical correlations and evaluate the association with mortality.

METHODS

The clinical records of 852 patients admitted for suspect COVID-19 pneumonia, defined as respiratory symptoms or fever or certain history of contact with COVID-19 patients, plus chest CT imaging compatible with alveolar-interstitial pneumonia, were retrospectively analyzed. Delirium was defined after careful revision of daily clinical reports in accordance with the Confusion Assessment Method criteria. Data on age, clinical presentation, comorbidities, drugs, baseline lab tests and outcome were collected. The factors associated with delirium, and the association of delirium with mortality, were evaluated through binary logistic regression models.

RESULTS

Ninety-four patients (11%) developed delirium during stay. They were older (median age 82, interquartile range, IQR 78-89, vs 75, IQR 63-84, p < 0.001), had more neuropsychiatric comorbidities and worse respiratory exchanges at baseline. At multivariate models, delirium was independently and positively associated with age [odds ratio (OR) 1.093, 95% confidence interval (CI) 1.046-1.143, p < 0.001], use of antipsychotic drugs (OR 4.529, 95% CI 1.204-17.027, p = 0.025), serum urea and lactate-dehydrogenase at admission. Despite a higher mortality in patients with delirium (57% vs 30%), this association was not independent of age and respiratory parameters.

CONCLUSIONS

Delirium represents a common complication of COVID-19 and a marker of severe disease course, especially in older patients with neuropsychiatric comorbidity.

Treatment of severe COVID-19 with human umbilical cord mesenchymal stem cells

Background

COVID-19 is a highly infectious respiratory disease. No therapeutics have yet been proven effective for treating severe COVID-19.

Objectives

To determine whether human umbilical cord mesenchymal stem cell infusion may be effective and safe for the treatment of severe COVID-19.

Methods

Patients with severe COVID-19 were randomly divided into 2 groups: the standard treatment group and the standard treatment plus hUC-MSC infusion group. The incidence of progression from severe to critical illness, 28-day mortality, clinical symptom improvement, time to clinical symptom improvement, hematologic indicators including C-reactive protein, lymphocyte number, and interleukin 6, and imaging changes were observed and compared between the two groups.

Measurements and main results

The incidence of progression from severe to critical illness and the 28-day mortality rate were 0 in the hUC-MSC treatment group, while 4 patients in the control group deteriorated to critical condition and received invasive ventilation; 3 of them died, and the 28-day mortality rate was 10.34%. In the hUC-MSC treatment group, the time to clinical improvement was shorter than that in the control group. Clinical symptoms of weakness and fatigue, shortness of breath, and low oxygen saturation obviously improved beginning on the third day of stem cell infusion and reached a significant difference on day 7. CRP and IL-6 levels were significantly lower from day 3 of infusion, the time for the lymphocyte count to return to the normal range was significantly faster, and lung inflammation absorption was significantly shorter on CT imaging in the hUC-MSC group than in the control group.

Conclusions

Intravenous transplantation of hUC-MSCs is a safe and effective method that can be considered a salvage and priority treatment option for severe COVID-19.

Trial registration

Chinese Clinical Trial Registration; ChiCTR2000031494; Registered on 2 April 2020; http://www.medresman.org

The diagnosis of pandemic coronavirus pneumonia: A review of radiology examination and laboratory test

Since the outbreak of novel coronavirus disease 2019 (COVID-19), epidemic prevention strategies have been implemented worldwide. For the sake of controlling the infectious coronavirus pneumonia, early diagnosis and quarantine play an imperative role. Currently, the mainstream diagnostic methods are imaging and laboratory diagnosis, which differ in their efficacy of diagnosis. To compare the detection rate, we reviewed numerous literature on pneumonia caused by coronaviruses (SARS, MERS, and SARS-CoV-2) and analyzed two different ways of diagnosis. The results showed that the detection rate of computed tomography (CT) diagnosis was significantly higher than that of real-time quantitative polymerase chain reaction (qPCR) (P = 0.00697). Still, clinicians should combine radiology and laboratory methods to achieve a higher detection rate, so that instant isolation and treatment could be effectively conducted to curb the rampant spread of the epidemic.

Lung Ultrasound in COVID-19 Pneumonia: Correlations with Chest CT on Hospital admission

Background

Lung ultrasound (LUS) is an accurate, safe, and cheap tool assisting in the diagnosis of several acute respiratory diseases. The diagnostic value of LUS in the workup of coronavirus disease-19 (COVID-19) in the hospital setting is still uncertain.

Objectives

The aim of this observational study was to explore correlations of the LUS appearance of COVID-19-related pneumonia with CT findings.

Methods

Twenty-six patients (14 males, age 64 ± 16 years) urgently hospitalized for COVID-19 pneumonia, who underwent chest CT and bedside LUS on the day of admission, were enrolled in this observational study. CT images were reviewed by expert chest radiologists, who calculated a visual CT score based on extension and distribution of ground-glass opacities and consolidations. LUS was performed by clinicians with certified competency in thoracic ultrasonography, blind to CT findings, following a systematic approach recommended by ultrasound guidelines. LUS score was calculated according to presence, distribution, and severity of abnormalities.

Results

All participants had CT findings suggestive of bilateral COVID-19 pneumonia, with an average visual scoring of 43 ± 24%. LUS identified 4 different possible ­abnormalities, with bilateral distribution (average LUS score 15 ± 5): focal areas of nonconfluent B lines, diffuse confluent B lines, small subpleural microconsolidations with pleural line irregularities, and large parenchymal consolidations with air bronchograms. LUS score was significantly correlated with CT visual scoring (r = 0.65, p < 0.001) and oxygen saturation in room air (r = −0.66, p < 0.001).

Conclusion

When integrated with clinical data, LUS could represent a valid diagnostic aid in patients with suspect COVID-19 pneumonia, which reflects CT findings.

Chest CT features of coronavirus disease 2019 (COVID-19) pneumonia: key points for radiologists

COVID-19 is an emerging infection caused by a novel coronavirus that is moving so rapidly that on 30 January 2020 the World Health Organization declared the outbreak a Public Health Emergency of International Concern and on 11 March 2020 as a pandemic. An early diagnosis of COVID-19 is crucial for disease treatment and control of the disease spread. Real-time reverse-transcription polymerase chain reaction (RT-PCR) demonstrated a low sensibility; therefore chest computed tomography (CT) plays a pivotal role not only in the early detection and diagnosis, especially for false negative RT-PCR tests, but also in monitoring the clinical course and in evaluating the disease severity. This paper reports the CT findings with some hints on the temporal changes over the course of the disease: the CT hallmarks of COVID-19 are bilateral distribution of ground glass opacities with or without consolidation in the posterior and peripheral lung, but the predominant findings in later phases include consolidations, linear opacities, “crazy-paving” pattern, “reversed halo” sign and vascular enlargement. The CT findings of COVID-19 overlap with the CT findings of other diseases, in particular the viral pneumonia including influenza viruses, parainfluenza virus, adenovirus, respiratory syncytial virus, rhinovirus, human metapneumovirus, etc. There are differences as well as similarities in the CT features of COVID-19 compared with those of the severe acute respiratory syndrome. The aim of this article is to review the typical and atypical CT findings in COVID-19 patients in order to help radiologists and clinicians to become more familiar with the disease.

Psychological status of medical workforce during the COVID-19 pandemic: A cross-sectional study

The pandemic of 2019 coronavirus disease (COVID-19) has burdened an unprecedented psychological stress on people around the world, especially the medical workforce. The study focuses on assess the psychological status of them. The authors conducted a single-center, cross-sectional survey via online questionnaires. Occurrence of fear, anxiety and depression were measured by the numeric rating scale (NRS) on fear, Hamilton Anxiety Scale (HAMA), and Hamilton Depression Scale (HAMD), respectively. A total of 2299 eligible participants were enrolled from the authors' institution, including 2042 medical staff and 257 administrative staff. The severity of fear, anxiety and depression were significantly different between two groups. Furthermore, as compared to the non-clinical staff, front line medical staff with close contact with infected patients, including working in the departments of respiratory, emergency, infectious disease, and ICU, showed higher scores on fear scale, HAMA and HAMD, and they were 1.4 times more likely to feel fear, twice more likely to suffer anxiety and depression. The medical staff especially working in above-mentioned departments made them more susceptible to psychological disorders. Effective strategies toward to improving the mental health should be provided to these individuals.

[Thinking of treatment strategies for colorectal cancer patients in tumor hospitals under the background of coronavirus pneumonia]

In December 2019, a new outbreak of coronavirus pneumonia began to occur. Its pathogen is 2019-nCoV, which has the characteristics of strong infectivity and general susceptibility. The current situation of prevention and control of new coronavirus pneumonia is severe. In this context, as front-line medical workers bearing important responsibilities and pressure, while through strict management strategy, we can minimize the risk of infection exposure. By summarizing the research progress and guidelines in recent years in the fields of colorectal cancer disease screening, treatment strategies(including early colorectal cancer, locally advanced colorectal cancer, obstructive colorectal cancer, metastatic colorectal cancer and the treatment of patients after neoadjuvant therapy), the choice of medication and time limit for adjuvant therapy, the protective measures for patients undergoing emergency surgery, the re-examination of postoperative patients and the protection of medical staff, etc., authors improve treatment strategies in order to provide more choices for patients to obtain the best treatment under the severe epidemic situation of new coronavirus pneumonia. Meanwhile we hope that it can also provide more timely treatment modeling schemes for colleagues.