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Asian Pacific Journal of Tropical Medicine 2023年第9期16卷 418-424页

作者： Bin Liu Liang Li Lei Liu Min Ye Wei Zhang Xiangdong Zhou Qi Li Department of Respiratory Medicine the First Affiliated Hospital of Hainan Medical UniversityHaikou 570100China Hainan Province Clinical Medical Center of Respiratory Disease Haikou 579199China International School of Nursing Hainan Medical UniversityHaikou 571199China Department of Respiratory and Critical Care Medicine the First Affiliated Hospital of Harbin Medical UniversityHarbin 150081China Kang'an Hospital of Mudanjiang Mudanjiang 157000China

Objective:To evaluate the clinical safety and efficacy of Lianhuaqingwen(LHQW)capsules in patients with high-risk common type covid-19 ***:A retrospective multicenter study on 383 high-risk common type covid-19 pneumonia cases was *** were categorized as the standard treatment(SDT)group(n=168)and the LHQW+SDT group(n=215).The primary endpoint was the rate of symptom(fever,fatigue,coughing)recovery and the secondary endpoints included the time to symptom recovery,the proportion of patients with improvement in chest CT images,the proportion of patients with clinical cure,the timing and rate of negative conversion of SARS-CoV-2 RNA ***:The recovery rate was significantly higher in the LHQW+SDT group as compared with the SDT group(89.7%vs.72.0%,P0.05).No serious adverse events were ***:LHQW capsules could be recommended to ameliorate clinical symptoms and reduce the rate of deteriorating to severe cases for high-risk common type covid-19 pneumonia.

关键词： Lianhuaqingwen capsules covid-19 pneumonia High-risk common type Clinical efficacy

A Case of Two Cardiac Arrests in a Pregnant Woman with Severe covid-19 pneumonia

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Open Journal of Emergency Medicine 2022年第4期10卷 168-175页

作者： Ravshan Ibadov Hilola Alimova Gavhar Voitova Sardor Ibragimov National Specialized Scientific and Practical Medical Center for Surgery Named after Academician V. Vakhidov Tashkent Uzbekistan National Specialized Infectious Diseases Hospital Zangiota 1 Tashkent Uzbekistan Tashkent City Centre for Women Reproductive Health Tashkent Uzbekistan

Background: covid-19 pneumonia increases the risk for pregnant women and the fetuses that often require intensive therapy. In addition to obvious therapeutic targets, ICU staff has to control the psycho-emotional conditions of covid-19 patients, e.g. intensive care unit syndrome and post-intensive care syndrome. Case presentation: Patient M., Uzbek, 24 years old, gravida 1 (27 weeks) was admitted to the Maternity Department of Zangiota hospital on 19.07.2021 with the diagnosis of extremely severe covid-19 pneumonia and respiratory failure with psychomotor agitation. On day 4 her general condition deteriorated due to the progression of pneumonia and involvement of abdominal organs associated with 27-week pregnancy. On that day the fetus had no signs of life, and the caesarean delivery was performed;the child was stillborn. For the next two weeks the patient had been in medical coma due to the progression of respiratory and multi-organ failure. The patient had two separate cardiac arrests. Cardio-pulmonary resuscitation was successful. By day 20, the dynamics of her cardiac activity has been completely restored. The brain function restored to 15 on the Glasgow Coma Scale. Conclusion: Special measures of prevention and treatment of multi-organ failure, intensive care unit syndrome and post-intensive care syndrome should be taken in an ICU for pregnant women with covid-19 pneumonia.

关键词： Cardiac Arrest Pregnant Women covid-19 pneumonia Psychomotor Agitation Intensive Care Unit Syndrome

Perspectives on mesenchymal stem/progenitor cells and their derivates as potential therapies for lung damage caused by covid-19

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World Journal of Stem Cells 2020年第9期12卷 1013-1022页

作者： Aleksandra Klimczak Laboratory of Biology of Stem and Neoplastic Cells Hirszfeld Institute of Immunology and Experimental Therapy Polish Academy of SciencesWrocław 53-114Poland

The new coronavirus,severe acute respiratory syndrome coronavirus-2(SARSCoV-2),which emerged in December 2019 in Wuhan,China,has reached worldwide pandemic proportions,causing coronavirus disease 2019(covid-19).The clinical manifestations of covid-19 vary from an asymptomatic disease course to clinical symptoms of acute respiratory distress syndrome and severe *** lungs are the primary organ affected by SARS-CoV-2,with a very slow turnover for ***-CoV-2 enters the lungs via angiotensinconverting enzyme 2 receptors and induces an immune response with the accumulation of immunocompetent cells,causing a cytokine storm,which leads to target organ injury and subsequent *** date,there is no effective antiviral therapy for covid-19 patients,and therapeutic strategies are based on experience treating previously recognized *** search of new treatment modalities of covid-19,cell-based therapy with mesenchymal stem cells(MSCs)and/or their secretome,such as soluble bioactive factors and extracellular vesicles,is considered supportive therapy for critically ill *** MSCs are able to differentiate into different types of cells of mesenchymal origin,including alveolar epithelial cells,lung epithelial cells,and vascular endothelial cells,which are severely damaged in the course of covid-19 ***,MSCs secrete a variety of bioactive factors that can be applied for respiratory tract regeneration in covid-19 patients thanks to their trophic,anti-inflammatory,immunomodulatory,anti-apoptotic,pro-regenerative,and proangiogenic properties.

关键词： Mesenchymal stem cells Stem/progenitor cells Lung damage Mesenchymal stem cell secretome covid-19 disease covid-19 pneumonia

Explainable Analysis of Deep Learning Models for Coronavirus Disease (covid-19) Classification with Chest X-Ray Images: Towards Practical Applications

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Open Journal of Medical Imaging 2022年第3期12卷 83-102页

作者： Eri Matsuyama Haruyuki Watanabe Noriyuki Takahashi Faculty of Informatics University of Fukuchiyama Kyoto Japan School of Radiological Technology Gunma Prefectural College of Health Sciences Gunma Japan School of Hearth Sciences Fukushima Medical University Fukushima Japan

In recent years, with numerous developments of convolutional neural network (CNN) classification models for medical diagnosis, the issue of misrecognition/misclassification has become more and more important. Thus, research on misrecognition/misclassification has been progressing. This study focuses on the problem of misrecognition/misclassification of CNN classification models for coronavirus disease (covid-19) using chest X-ray images. We construct two models for covid-19 pneumonia classification by fine-tuning ResNet-50 architecture, i.e., a model retrained with full-sized original images and a model retrained with segmented images. The present study demonstrates the uncertainty (misrecognition/misclassification) of model performance caused by the discrepancy in the shapes of images at the phase of model construction and that of clinical applications. To achieve it, we apply three XAI methods to demonstrate and explain the uncertainty of classification results obtained from the two constructed models assuming for clinical applications. Experimental results indicate that the performance of classification models cannot be maintained when the type of constructed model and the geometric shape of input images are not matched, which may bring about misrecognition in clinical applications. We also notice that the effect of adversarial attack might be induced if the method of image segmentation is not performed properly. The results suggest that the best approach to obtaining a highly reliable prediction in the classification of covid-19 pneumonia is to construct a model using full-sized original images as training data and use full-sized original images as the input when utilized in clinical applications.

关键词： Explainable AI CNN CXR Image covid-19 pneumonia

Applications of artificial intelligence in lung ultrasound:Review of deep learning methods for covid-19 fighting

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Artificial Intelligence in Medical Imaging 2022年第2期3卷 42-54页

作者： Laura De Rosa Serena L'Abbate Claudia Kusmic Francesco Faita Institute of Clinical Physiology Consiglio Nazionale delle RicerchePisa 56124Italy

BACKGROUND The pandemic outbreak of the novel coronavirus disease(covid-19)has highlighted the need to combine rapid,non-invasive and widely accessible techniques with the least risk of patient’s cross-infection to achieve a successful early detection and surveillance of the *** this regard,the lung ultrasound(LUS)technique has been proved invaluable in both the differential diagnosis and the follow-up of covid-19 patients,and its potential may be destined to ***,indeed,LUS has been empowered through the development of automated image processing *** To provide a systematic review of the application of artificial intelligence(AI)technology in medical LUS analysis of covid-19 patients using the preferred reporting items of systematic reviews and meta-analysis(PRISMA)*** A literature search was performed for relevant studies published from March 2020-outbreak of the pandemic-to 30 September *** articles were included in the result synthesis of this *** As part of the review,we presented the main characteristics related to AI techniques,in particular deep learning(DL),adopted in the selected articles.A survey was carried out on the type of architectures used,availability of the source code,network weights and open access datasets,use of data augmentation,use of the transfer learning strategy,type of input data and training/test datasets,and *** Finally,this review highlighted the existing challenges,including the lack of large datasets of reliable covid-19-based LUS images to test the effectiveness of DL methods and the ethical/regulatory issues associated with the adoption of automated systems in real clinical scenarios.

关键词： Lung ultrasound Deep learning Neural network covid-19 pneumonia Medical imaging

Comparison of Chest Computed Tomography Findings between Pregnant and Non-Pregnant Women with covid-19 Infection in Douala Gyneco-Obstetric and Pediatric Hospital, Cameroon

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Open Journal of Medical Imaging 2021年第4期11卷 132-144页

作者： Yannick Onana Joshua Tambe Adamou Dodo Balkissou Mohamadou Aminou Samuel Mbozo’o Mvondo Dominique Tamchom Djomo Alphonse Nyong Ngalame Rakya Inna Bilkissou Moustapha Francis Ateba Ndongo Robert Tchounzou Jean Claude Mballa Amougou Jérémie Mbo Amvene Mathurin Neossi Guena Emile Telesphore Mboudou Douala Gyneco-Obstetric and Pediatric Hospital Douala Cameroon Faculty of Medicine and Biomedical Sciences of Garoua University of Ngaoundere Garoua Cameroon Faculty of Health Sciences University of Buea Buea Cameroon Faculty of Medicine and Pharmaceutical Sciences University of Douala Douala Cameroon Faculty of Sciences University of Ngaoundere Ngaoundere Cameroon Faculty of Medicine and Biomedical Sciences University of Yaoundé 1 Yaoundé Cameroon

Introduction: Pregnancy is a physiologic state associated with decreased immunity, and the use of medical imaging modalities with ionizing radiation must be justified as potential benefits must outweigh the risk of any harm. However, in the wake of SARS-CoV-2 virus pandemic, chest computed tomography (CT) is necessary to assess the severity of the disease. The objective of this study was to compare the chest CT findings of pregnant and non-pregnant women with SARS-CoV-2 viral pneumonia at a tertiary hospital setting. Materials and Methods: This was a cross-sectional, retrospective, descriptive study of admission records of pregnant and non-pregnant patients aged 15 - 49 years during a three (3) months period (April-July 2020) in DGOPH. Logistic regression was used to search for predictors of lung involvement during covid-19. Results: A total of 31 patient files were studied of which 9 (29%) were those of pregnant women. The pregnant women mostly had a combination of lung ground-glass opacities and consolidation on CT compared to the non-pregnant women (7 out of 9 cases, 77.8%, vs. 6 out of 22 cases, 22.7%;p = 0.01). The group of pregnant women had more than 3 affected lobes (50.0% vs. 22.7%, p = 0.04) with a middle lobe predilection (77.8% vs. 31.8%, p = 0.02). CT predictors of covid-19 pneumonia in the group of pregnant women after the multivariable logistic regression analysis were the presence of nodules (aOR = 13.9;95% CI: 1.25 - 134.2;p = 0.032) and linear bands of interlobular septal thickening (aOR = 17.8;95% CI: 1.46 - 217.6;p = 0.024). Conclusion: In this study, the chest CT of pregnant women with covid-19 pneumonia revealed mostly a combination of findings compared to non-pregnant women, with more affected lobes. These findings suggest the likelihood of a greater CT severity of covid-19 pneumonia among pregnant women and therefore the need for timely and appropriate management.

关键词： covid-19 pneumonia Pregnancy Computed Tomography

Clinical Analysis on 205 Cases of covid-19

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Chinese Journal of Biomedical Engineering(English Edition) 2020年第1期29卷 39-42页

作者： Zhengfeng Lin Yanfeng Shao The Third Affiliated People's Hospital of Fujian University of Traditional Medicine Fuzhou Fujian 350108

Objective To understand basic features of the epidemic of novel coronavirus(covid-19),and to provide a scientific basis for its prevention and to formulate reasonable measures for its prevention and *** The history of epidemiology,clinical features,laboratory results,and imaging results of 205 cases of covid-19 that were admitted and confirmed in the Third People’s Hospital of Yichang city from January to March 2020 were collected,and a database was set up and a retrospective analysis was *** The mean age of the 205 confirmed cases was 56.0±16.2 years *** confirmed cases at the early phase had the contact history with Wuhan epidemic region;most confirmed cases at the later phase were from the local with unclear contact history;and most of these cases were of the general type and minor *** statistical analysis,the age,gender,occupation,and contact history all had no statistically significant correlation with the severity of the disease(P>0.05).There was a statistical significant correlation between the underlying diseases and the severity of the disease(χ~2=31,Ppneumonia,pleural thickening and adhesion,and increased lactic *** far,the epidemic al Yichang city has been under control,but the special emphasis on prevention and control still has to be made in the future.

关键词： covid-19 pneumonia epidemiology clinical symptoms retrospective analysis