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1.
Annals of Translational Medicine ; 10(5), 2022.
Article in English | EuropePMC | ID: covidwho-1781650

ABSTRACT

Background Highly pathogenic avian influenza A (H5N6) virus poses a continuous threat to human health since 2014. Although neuraminidase inhibitors (NAIs) are prescribed in most patients infected with the H5N6 virus, the fatality remains high, indicating the need for an improved treatment regimen. Sirolimus, an inhibitor of the mammalian target of rapamycin (mTOR), has been reported to reduce viral replication and improve clinical outcomes in severe H1N1 infections when combined with oseltamivir. Here, we report the first case of severe H5N6 pneumonia successfully treated by sirolimus and NAIs. Case Description A 22-year-old man developed high fever and chills on September 24, 2018 (Day-0) and was hospitalized on Day-3. Influenza A (H5N6) was identified on Day-6 from a throat swab specimen. Despite the administration of NAIs and other supportive measures, the patient’s clinical conditions and lung images showed continued deterioration, accompanied by persistently high viral titers. Consequently, sirolimus administration (rapamycin;2 mg per day for 14 days) was started on Day-12. His PaO2/FiO2 values and Sequential Organ Failure Assessment (SOFA) score gradually improved, and imaging outcomes revealed the resolution of bilateral lung infiltrations. The viral titer gradually decreased and turned negative on Day-25. Sirolimus and NAIs were stopped on the same day. The patient was discharged on Day-65. Based on observations from a 2-year follow-up, the patient was found to be in a good condition without complications. Conclusions In conclusion, sirolimus might be a novel and practical therapeutic approach to severe H5N6-associated pneumonia in humans.

2.
Iran J Immunol ; 19(1): 11, 2022 Mar.
Article in English | MEDLINE | ID: covidwho-1744451

ABSTRACT

COVID-19 is a new acute respiratory infectious disease caused by a novel Coronavirus (2019-COV-2) infection. On November 26, 2021, the World Health Organization announced a new 2019-COV-2 variant strain Omicron (B.1.1.529). Omicron's emergence added further uncertainty to the outbreak. Here we report the first case infected with Omicron in China, a 17-year-old female student. In this paper, the clinical symptoms, laboratory and imaging examinations and treatment of the first Omicron-infected patient in China were analyzed. This report might provide a reference for the diagnosis and treatment of patients infected with Omicron strain across the world. The novel Coronavirus antibody tests were performed on the day of admission: IgM level was normal, novel Coronavirus antibody IgG was 132.666s /CO and IgG was 148.47s /CO on the 7th day of admission. IgG showed an increasing trend, which is consistent with the results of multiple novel Coronavirus non-Omicron strain infections.


Subject(s)
COVID-19 , Adolescent , China/epidemiology , Female , Humans , Immunoglobulin G , SARS-CoV-2
3.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-324137

ABSTRACT

The rapid spread of COVID-19 results in a pandemic throughout the world, however, there are currently no specific treatments available. We report the first case of ozonated autohemotherapy for a critically ill patient with COVID-19. The patient was diagnosed with severe acute respiratory distress syndrome (ARDS) and life-threatening refractory hypoxemia within 72 hours of the intensive-care unit (ICU) admission. To improve the oxygen delivery, the ozonated autohemotherapy was performed with 40 µg/ml of ozone in 100 ml of blood for 5 days on this patient, who then recovered from ARDS uneventfully and discharged from hospital after viral clearance. This case suggests ozonated autohemotherapy might be an alternative non-invasive medical treatment for critically ill COVID-19 patients.

4.
Brain Behav ; 12(2): e2492, 2022 02.
Article in English | MEDLINE | ID: covidwho-1640676

ABSTRACT

BACKGROUND: Post-traumatic stress disorder (PTSD) is a serious mental health condition that is triggered by a terrifying event. We aimed to investigate the occurrence and risk factors of PTSD among discharged COVID-19 patients. METHODS: This study included 144 discharged COVID-19 patients. PTSD was assessed by using validated cut-offs of the impact of event scale-revised (IES-R, score ≥25). All patients completed a detailed questionnaire survey, and clinical parameters were routinely measured in the hospital. Binary logistic regression models were applied to identify factors associated with PTSD. RESULTS: Of the 144 participants with laboratory-confirmed COVID-19, the occurrence of PTSD was 16.0%. In multivariable analyses, age above 40 years (adjusted OR [95% CI], 5.19 [2.17-12.32]), female sex (adjusted OR [95% CI], 7.82 [3.18-18.21]), current smoker (adjusted OR [95% CI], 6.72 [3.23-15.26]), and ≥3 involved pulmonary lobes (adjusted OR [95% CI], 5.76 [1.19-15.71]) were significantly associated with a higher risk of PTSD. Conversely, history of hypertension and serum hemoglobin levels were significantly associated with a lower risk of PTSD with adjusted ORs (95% CI) of 0.37 (0.12-0.87) and 0.91 (0.82-0.96), respectively. CONCLUSION: Old age, gender (being female), current smoking, bacterial pneumonia, and ≥3 involved pulmonary lobes were associated with an increased occurrence of PTSD among discharged COVID-19 patients.


Subject(s)
COVID-19 , Stress Disorders, Post-Traumatic , Adult , China/epidemiology , Female , Humans , Patient Discharge , Risk Factors , SARS-CoV-2 , Stress Disorders, Post-Traumatic/epidemiology
5.
Int J Cardiol Heart Vasc ; 38: 100938, 2022 Feb.
Article in English | MEDLINE | ID: covidwho-1587657

ABSTRACT

Purpose: This study evaluated the diagnostic values of the extent of lung injury manifested in non-contrast enhanced CT (NCCT) images, the inflammatory and immunological biomarkers C-reactive protein (CRP) and lymphocyte for detecting acute cardiac injury (ACI) in patients with COVID-19. The correlations between the NCCT-derived parameters and arterial blood oxygen level were also investigated. Methods: NCCT lung images and blood tests were obtained in 143 patients with COVID-19 in approximately two weeks after symptom onset, and arterial blood gas measurement was also acquired in 113 (79%) patients. The diagnostic values of normal, moderately and severely abnormal lung parenchyma volume relative to the whole lungs (RVNP, RVMAP, RVSAP, respectively) measured from NCCT images for detecting the heart injury confirmed with high-sensitivity troponin I assay was determined. Results: RVNP, RVMAP and RVSAP exhibited similar accuracy for detecting ACI in COVID-19 patients. RVNP was significantly lower while both RVMAP and RVSAP were significantly higher in the patients with ACI. All of the NCCT-derived parameters exhibited poor linear and non-linear correlations with PaO2 and SaO2. The patients with ACI had a significantly higher CRP level but a lower lymphocyte level compared to the patients without ACI. Combining one of these two biomarkers with any of the three NCCT-derived parameter further improved the accuracy for predicting ACI in patients with COVID-19. Conclusion: The NCCT-delineated normal and abnormal lung parenchmyma tissues were statistically significant predictors of ACI in patients with COVID-19, but both exhibited poor correlations with the arterial blood oxygen level. The incremental diagnostic values of lymphocyte and CRP suggested viral infection and inflammation were closely related to the heart injury during the acute stage of COVID-19.

6.
IEEE/ACM Trans Comput Biol Bioinform ; 18(6): 2775-2780, 2021.
Article in English | MEDLINE | ID: covidwho-1559565

ABSTRACT

A novel coronavirus (COVID-19) recently emerged as an acute respiratory syndrome, and has caused a pneumonia outbreak world-widely. As the COVID-19 continues to spread rapidly across the world, computed tomography (CT) has become essentially important for fast diagnoses. Thus, it is urgent to develop an accurate computer-aided method to assist clinicians to identify COVID-19-infected patients by CT images. Here, we have collected chest CT scans of 88 patients diagnosed with COVID-19 from hospitals of two provinces in China, 100 patients infected with bacteria pneumonia, and 86 healthy persons for comparison and modeling. Based on the data, a deep learning-based CT diagnosis system was developed to identify patients with COVID-19. The experimental results showed that our model could accurately discriminate the COVID-19 patients from the bacteria pneumonia patients with an AUC of 0.95, recall (sensitivity) of 0.96, and precision of 0.79. When integrating three types of CT images, our model achieved a recall of 0.93 with precision of 0.86 for discriminating COVID-19 patients from others. Moreover, our model could extract main lesion features, especially the ground-glass opacity (GGO), which are visually helpful for assisted diagnoses by doctors. An online server is available for online diagnoses with CT images by our server (http://biomed.nscc-gz.cn/model.php). Source codes and datasets are available at our GitHub (https://github.com/SY575/COVID19-CT).


Subject(s)
COVID-19/diagnostic imaging , COVID-19/diagnosis , Deep Learning , Diagnosis, Computer-Assisted/statistics & numerical data , Tomography, X-Ray Computed/statistics & numerical data , Case-Control Studies , China , Computational Biology , Diagnosis, Differential , Humans , Models, Statistical , Pneumonia, Bacterial/diagnosis , Pneumonia, Bacterial/diagnostic imaging , SARS-CoV-2
7.
IET Image Process ; 2021 Nov 18.
Article in English | MEDLINE | ID: covidwho-1526114

ABSTRACT

The rapid spread of the novel coronavirus disease 2019 (COVID-19) causes a significant impact on public health. It is critical to diagnose COVID-19 patients so that they can receive reasonable treatments quickly. The doctors can obtain a precise estimate of the infection's progression and decide more effective treatment options by segmenting the CT images of COVID-19 patients. However, it is challenging to segment infected regions in CT slices because the infected regions are multi-scale, and the boundary is not clear due to the low contrast between the infected area and the normal area. In this paper, a coarse-refine segmentation network is proposed to address these challenges. The coarse-refine architecture and hybrid loss is used to guide the model to predict the delicate structures with clear boundaries to address the problem of unclear boundaries. The atrous spatial pyramid pooling module in the network is added to improve the performance in detecting infected regions with different scales. Experimental results show that the model in the segmentation of COVID-19 CT images outperforms other familiar medical segmentation models, enabling the doctor to get a more accurate estimate on the progression of the infection and thus can provide more reasonable treatment options.

8.
Sci Rep ; 10(1): 14856, 2020 09 09.
Article in English | MEDLINE | ID: covidwho-1493156

ABSTRACT

The problem of indoor odors can greatly affect a room's occupants. To identify odorants and comprehensively evaluate emissions from wooden materials, emissions and odors from Choerospondias axillaris (Roxb.) Burtt et Hill with different moisture content percentages and lacquer treatments were investigated in this study. Thermal desorption-gas chromatography-mass spectroscopy/olfactometry was used to analyze the release characteristics. In total, 11 key odor-active compounds were identified as moisture content gradually decreased, concentrating between 15 and 33 min. Total volatile organic compounds, total very volatile organic compounds, and total odor intensity decreased as moisture content decreased. In addition, 35 odor-active compounds, including aromatics, alkenes, aldehydes, esters, and alcohols, were identified in the odor control list. Polyurethane (PU), ultraviolet (UV), and waterborne coatings had a good inhibitory effect on eight odor characteristics, but some scents arose after lacquer treatment. For equilibrium moisture content, the major characteristics of Choerospondias axillaris were fragrant (9.4) and mint-like (3.0) compared with the fragrant (8.2), fruity (7.8), and pleasant (5.8) characteristics of PU coating; the flowery (5.9), fragrant (5.0), glue-like (4.3), and pineapple-like (4.3) characteristics of UV coating; and the antiseptic solution (3.6), fragrant (2.9), cigarette-like (2.8), and fruity (2.5) characteristics of waterborne coating. Based on multicomponent evaluation, a Choerospondias axillaris board with waterborne coating was suggested for use indoors.


Subject(s)
Anacardiaceae/chemistry , Odorants/analysis , Volatile Organic Compounds/analysis , Wood/chemistry , China , Humans , Lacquer , Olfactory Perception
9.
Infect Dis Ther ; 11(1): 165-174, 2022 Feb.
Article in English | MEDLINE | ID: covidwho-1482329

ABSTRACT

INTRODUCTION: Since the global outbreak of COVID-19, there has been a significant reduction in pediatric outpatient and emergency visits for infectious diseases. The purpose of this study was to analyze the changes in respiratory viruses in children with community-acquired pneumonia (CAP) in Shanghai in the past 10 years, especially in the first year after COVID-19. METHODS: We conducted a retrospective, observational study; the results for eight common respiratory viruses (respiratory syncytial virus (RSV), influenza virus A and B, parainfluenza virus 1-3 (PIV), adenovirus (ADV) and human metapneumovirus) tested by direct fluorescent antibody assays in hospitalized CAP cases in Children's Hospital of Fudan University during 2010-2020 were analyzed. RESULTS: Of the 5544 hospitalized CAP patients included in this study, 20.2% (1125/5544) were positive for the eight respiratory viruses. The top three pathogens were RSV, PIV3 and ADV, detected from 9.8% (543/5544), 5.3% (294/5544) and 2.0% (111/5544) of the samples, respectively. RSV had the highest positive rates among children < 2 years old. In 2020, the detection rate of all viruses showed a sharp decline from February to August compared with the previous 9 years. When the Shanghai community reopened in August 2020, the detection rate of eight viruses rebounded significantly in September. CONCLUSIONS: These eight respiratory viruses, especially RSV and PIV, were important pathogens of CAP in Shanghai children in the past 10 years. The COVID-19 pandemic had a significant impact on the detection rates for eight respiratory viruses in children with CAP in Shanghai.

11.
World J Clin Cases ; 9(12): 2731-2738, 2021 Apr 26.
Article in English | MEDLINE | ID: covidwho-1215740

ABSTRACT

BACKGROUND: Emerging infectious diseases are a constant threat to the public's health and health care systems around the world. Coronavirus disease 2019 (COVID-2019), which was defined by the World Health Organization as pandemic, has rapidly emerged as a global health threat. Outbreak evolution and prevention of international implications require substantial flexibility of frontline health care facilities in their response. AIM: To explore the effect of the implementation and management strategy of pre-screening triage in children during COVID-19. METHODS: The standardized triage screening procedures included a standardized triage screening questionnaire, setup of pre-screening triage station, multi-point temperature monitoring, extensive screenings, and two-way protection. In order to ensure the implementation of the pre-screening triage, the prevention and control management strategies included training, emergency exercise, and staff protection. Statistical analysis was performed on the data from all the children hospitalized from January 20, 2020 to March 20, 2020 at solstice during the pandemic period. Data were obtained from questionnaires and electronic medical record systems. RESULTS: A total of 17561 children, including 2652 who met the criteria for screening, 192 suspected cases, and two confirmed cases without omission, were screened from January 20, 2020 to March 20, 2020 at solstice during the pandemic period. There was zero transmission of the infection to any medical staff. CONCLUSION: The effective strategies for pre-screening triage have an essential role in the prevention and control of hospital infection.

12.
J Trauma Acute Care Surg ; 89(6): 1092-1098, 2020 12.
Article in English | MEDLINE | ID: covidwho-1214720

ABSTRACT

BACKGROUND: Invasive mechanical ventilation (IMV) is a lifesaving strategy for critically ill patients with coronavirus disease 2019 (COVID-19). We aim to report the case series of critical patients receiving IMV in Wuhan and to discuss the timing of IMV in these patients. METHODS: Data of 657 patients admitted to emergency intensive care unit of Zhongnan Hospital and isolated isolation wards of Wuhan Union Hospital from January 1 to March 10, 2020, were retrospectively reviewed. All medical records of 40 COVID-19 patients who required IMV were collected at different time points, including baseline (at admission), before receiving IMV, and before death or hospital discharge. RESULTS: Among 40 COVID-19 patients with IMV, 31 died, and 9 survived and was discharged. The median age was 70 years (interquartile range [IQR], 62-76 years), and nonsurvivors were older than survivors. The median period from the noninvasive mechanic ventilation (NIV) or high-flow nasal cannula oxygen therapy (HFNC) to intubation was 7 hours (IQR, 2-42 hours) in IMV survivors and 54 hours (IQR, 28-143 hours) in IMV nonsurvivors. We observed that, when the time interval from NIV/HFNC to intubation was less than 50 hours (about 2 calendar days), together with Acute Physiology and Chronic Health Evaluation II (APACHE II) score of less than 10 or pneumonia severity index (PSI) score of less than 100, mortality can be reduced to 60% or less. Prolonged interval from NIV/HFNC to intubation and high levels of APACHE II and PSI before intubation were associated with higher mortality in critically ill patients. Multiple organ damage was common among these nonsurvivors in the course of treatment. CONCLUSION: Early initial intubation after NIV/HFNC might have a beneficial effect in reducing mortality for critically ill patients meeting IMV indication. Considering APACHE II and PSI scores might help physicians in decision making about timing of intubation for curbing subsequent mortality. LEVEL OF EVIDENCE: Therapeutic, level V.


Subject(s)
Coronavirus Infections/therapy , Critical Illness/therapy , Hospital Mortality , Noninvasive Ventilation/methods , Oxygen/administration & dosage , Pneumonia, Viral/therapy , APACHE , Aged , Betacoronavirus , COVID-19 , China , Coronavirus Infections/mortality , Critical Illness/mortality , Female , Hospitalization , Humans , Intensive Care Units , Male , Middle Aged , Oxygen Inhalation Therapy/methods , Pandemics , Pneumonia, Viral/mortality , Retrospective Studies , SARS-CoV-2 , Time Factors
13.
Nat Biomed Eng ; 5(6): 509-521, 2021 06.
Article in English | MEDLINE | ID: covidwho-1189229

ABSTRACT

Common lung diseases are first diagnosed using chest X-rays. Here, we show that a fully automated deep-learning pipeline for the standardization of chest X-ray images, for the visualization of lesions and for disease diagnosis can identify viral pneumonia caused by coronavirus disease 2019 (COVID-19) and assess its severity, and can also discriminate between viral pneumonia caused by COVID-19 and other types of pneumonia. The deep-learning system was developed using a heterogeneous multicentre dataset of 145,202 images, and tested retrospectively and prospectively with thousands of additional images across four patient cohorts and multiple countries. The system generalized across settings, discriminating between viral pneumonia, other types of pneumonia and the absence of disease with areas under the receiver operating characteristic curve (AUCs) of 0.94-0.98; between severe and non-severe COVID-19 with an AUC of 0.87; and between COVID-19 pneumonia and other viral or non-viral pneumonia with AUCs of 0.87-0.97. In an independent set of 440 chest X-rays, the system performed comparably to senior radiologists and improved the performance of junior radiologists. Automated deep-learning systems for the assessment of pneumonia could facilitate early intervention and provide support for clinical decision-making.


Subject(s)
COVID-19/diagnostic imaging , Databases, Factual , Deep Learning , SARS-CoV-2 , Tomography, X-Ray Computed , Diagnosis, Differential , Female , Humans , Male , Severity of Illness Index
14.
Int J Endocrinol ; 2021: 6616069, 2021.
Article in English | MEDLINE | ID: covidwho-1140370

ABSTRACT

COVID-19 is a kind of pneumonia with new coronavirus infection, and the risk of death in COVID-19 patients with diabetes is four times higher than that in healthy people. It is unclear whether there is a difference in chest CT images between type 2 diabetes mellitus (T2DM) and non-diabetes mellitus (NDM) COVID-19 patients. The aim of this study was to investigate the differences in chest CT images between T2DM and NDM patients with COVID-19 based on a quantitative method of artificial intelligence. A total of 62 patients with COVID-19 pneumonia were retrospectively enrolled and divided into group A (T2DM COVID-19 pneumonia group, n = 15) and group B (NDM COVID-19 pneumonia group, n = 47). The clinical and laboratory examination information of the two groups was collected. Quantitative features (volume of consolidation shadows and ground glass shadows, proportion of consolidation shadow (or ground glass shadow) to lobe volume, total volume, total proportion, and number) of chest spiral CT images were extracted using Dr. Wise @Pneumonia software. The results showed that among the 26 CT image features, the total volume and proportion of bilateral pulmonary consolidation shadow in group A were larger than those in group B (P=0.031 and 0.019, respectively); there was no significant difference in the total volume and proportion of bilateral pulmonary ground glass density shadow between the two groups (P > 0.05). In group A, the blood glucose level was correlated with the volume of consolidation shadow and the proportion of consolidation shadow to right middle lobe volume, and higher than those patients in group B. In conclusion, the inflammatory exudation in the lung of COVID-19 patients with diabetes is more serious than that of patients without diabetes based on the quantitative method of artificial intelligence. Moreover, the blood glucose level is positively correlated with pulmonary inflammatory exudation in COVID-19 patients.

15.
Interdiscip Sci ; 13(2): 273-285, 2021 Jun.
Article in English | MEDLINE | ID: covidwho-1103577

ABSTRACT

Computed tomography (CT) is one of the most efficient diagnostic methods for rapid diagnosis of the widespread COVID-19. However, reading CT films brings a lot of concentration and time for doctors. Therefore, it is necessary to develop an automatic CT image diagnosis system to assist doctors in diagnosis. Previous studies devoted to COVID-19 in the past months focused mostly on discriminating COVID-19 infected patients from healthy persons and/or bacterial pneumonia patients, and have ignored typical viral pneumonia since it is hard to collect samples for viral pneumonia that is less frequent in adults. In addition, it is much more challenging to discriminate COVID-19 from typical viral pneumonia as COVID-19 is also a kind of virus. In this study, we have collected CT images of 262, 100, 219, and 78 persons for COVID-19, bacterial pneumonia, typical viral pneumonia, and healthy controls, respectively. To the best of our knowledge, this was the first study of quaternary classification to include also typical viral pneumonia. To effectively capture the subtle differences in CT images, we have constructed a new model by combining the ResNet50 backbone with SE blocks that was recently developed for fine image analysis. Our model was shown to outperform commonly used baseline models, achieving an overall accuracy of 0.94 with AUC of 0.96, recall of 0.94, precision of 0.95, and F1-score of 0.94. The model is available in https://github.com/Zhengfudan/COVID-19-Diagnosis-and-Pneumonia-Classification .


Subject(s)
COVID-19/diagnostic imaging , Deep Learning , Diagnosis, Computer-Assisted , Lung/diagnostic imaging , Multidetector Computed Tomography , Pneumonia, Bacterial/diagnostic imaging , Pneumonia, Viral/diagnostic imaging , Radiographic Image Interpretation, Computer-Assisted , COVID-19/virology , Case-Control Studies , Diagnosis, Differential , Humans , Lung/microbiology , Lung/virology , Pneumonia, Bacterial/microbiology , Pneumonia, Viral/virology , Predictive Value of Tests , Reproducibility of Results
16.
BMC Immunol ; 22(1): 14, 2021 02 17.
Article in English | MEDLINE | ID: covidwho-1088580

ABSTRACT

BACKGROUND: SARS-CoV-2 is a novel coronavirus first recognized in late December 2019 that causes coronavirus disease 19 (COVID-19). Due to the highly contagious nature of SARS-CoV-2, it has developed into a global pandemic in just a few months. Antibody testing is an effective method to supplement the diagnosis of COVID-19. However, multicentre studies are lacking to support the understanding of the seroprevalence and kinetics of SARS-CoV-2 antibodies in COVID-19 epidemic regions. METHOD: A multicentre cross-sectional study of suspected and confirmed patients from 4 epidemic cities in China and a cohort study of consecutive follow-up patients were conducted from 29/01/2020 to 12/03/2020. IgM and IgG antibodies elicited by SARS-CoV-2 were tested by a chemiluminescence assay. Clinical information, including basic demographic data, clinical classification, and time interval from onset to sampling, was collected from each centre. RESULTS: A total of 571 patients were enrolled in the cross-sectional study, including 235 COVID-19 patients and 336 suspected patients, each with 91.9%:2.1% seroprevalence of SARS-CoV-2 IgG and 92.3%:5.4% seroprevalence of SARS-CoV-2 IgM. The seroprevalence of SARS-CoV-2 IgM and IgG in COVID-19 patients was over 70% less than 7 days after symptom onset. Thirty COVID-19 patients were enrolled in the cohort study and followed up for 20 days. The peak concentrations of IgM and IgG were reached on the 10th and 20th days, respectively, after symptom onset. The seroprevalence of COVID-19 IgG and IgM increased along with the clinical classification and treatment time delay. CONCLUSION: We demonstrated the kinetics of IgM and IgG SARS-CoV-2 antibodies in COVID-19 patients and the association between clinical classification and antibodies, which will contribute to the interpretation of IgM and IgG SARS-CoV-2 antibody tests and in predicting the outcomes of patients with COVID-19.


Subject(s)
COVID-19/immunology , SARS-CoV-2/physiology , Adult , Antibodies, Viral/blood , Antibody Formation , COVID-19/diagnosis , China , Cross-Sectional Studies , Disease Progression , Female , Humans , Immunoglobulin G/blood , Immunoglobulin M/blood , Male , Middle Aged , Prognosis , Seroepidemiologic Studies
17.
IEEE Trans Ultrason Ferroelectr Freq Control ; 68(4): 1296-1304, 2021 04.
Article in English | MEDLINE | ID: covidwho-998673

ABSTRACT

During the COVID-19 pandemic, an ultraportable ultrasound smart probe has proven to be one of the few practical diagnostic and monitoring tools for doctors who are fully covered with personal protective equipment. The real-time, safety, ease of sanitization, and ultraportability features of an ultrasound smart probe make it extremely suitable for diagnosing COVID-19. In this article, we discuss the implementation of a smart probe designed according to the classic architecture of ultrasound scanners. The design balanced both performance and power consumption. This programmable platform for an ultrasound smart probe supports a 64-channel full digital beamformer. The platform's size is smaller than 10 cm ×5 cm. It achieves a 60-dBFS signal-to-noise ratio (SNR) and an average power consumption of ~4 W with 80% power efficiency. The platform is capable of achieving triplex B-mode, M-mode, color, pulsed-wave Doppler mode imaging in real time. The hardware design files are available for researchers and engineers for further study, improvement or rapid commercialization of ultrasound smart probes to fight COVID-19.


Subject(s)
Signal Processing, Computer-Assisted/instrumentation , Transducers , Ultrasonography/instrumentation , COVID-19/diagnostic imaging , Equipment Design , Humans , Image Interpretation, Computer-Assisted , Lung/diagnostic imaging , Pandemics , Phantoms, Imaging , SARS-CoV-2 , Signal-To-Noise Ratio , Ultrasonography/methods
18.
Med Sci Monit ; 26: e928835, 2020 Dec 18.
Article in English | MEDLINE | ID: covidwho-994262

ABSTRACT

BACKGROUND This study summarizes the characteristics of children screened for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and reports the case of 1 child who was diagnosed with SARS-CoV-2 infection in Guangzhou Women and Children's Medical Center and the cases of his family members. MATERIAL AND METHODS The medical records of 159 children who were admitted to our hospital from January 23 to March 20, 2020, were retrospectively analyzed. Samples from pharyngeal or/and anal swabs were subjected to reverse-transcription polymerase chain reaction (RT-PCR) testing for SARS-CoV-2 within 12 h of patient admission; a second RT-PCR test was done 24 h after the first test. RESULTS Of the 159 patients, 151 patients had epidemiological histories, 14 patients had cluster onset, and 8 patients had no epidemiological history but had symptoms similar to coronavirus disease 2019 (COVID-19). The most common symptom was fever (n=125), followed by respiratory and gastrointestinal symptoms. A 7-year-old boy in a cluster family from Wuhan was confirmed with asymptomatic SARS-CoV-2 infection with ground-glass opacity shadows on his lung computed tomography scan, and his swab RT-PCR test had not turned negative until day 19 of his hospitalization. In patients who did not test positive for SARS-CoV-2, influenza, respiratory syncytial virus, and adenovirus were observed. A total of 158 patients recovered, were discharged, and experienced no abnormalities during follow-up. CONCLUSIONS For SARS-CoV-2 nosocomial infections, taking a "standard prevention & contact isolation & droplet isolation & air isolation" strategy can prevent infection effectively. Children with clustered disease need close monitoring.


Subject(s)
COVID-19/diagnosis , COVID-19/epidemiology , COVID-19 Nucleic Acid Testing/methods , Child , Child, Preschool , China/epidemiology , Coronavirus/metabolism , Coronavirus/pathogenicity , Cross Infection/epidemiology , Female , Fever , Hospitalization , Hospitals , Humans , Male , Medical Records , Patient Discharge , Retrospective Studies , SARS-CoV-2/metabolism , SARS-CoV-2/pathogenicity
19.
Can Respir J ; 2020: 5328267, 2020.
Article in English | MEDLINE | ID: covidwho-926979

ABSTRACT

Objective: To investigate the dissipation and outcomes of pulmonary lesions at the first follow-up of patients who recovered from moderate and severe cases of COVID-19. Methods: From January 21 to March 3, 2020, a total of 136 patients with COVID-19 were admitted to our hospital. According to inclusion and exclusion criteria, 52 patients who recovered from COVID-19 were included in this study, including 33 moderate cases and 19 severe cases. Three senior radiologists independently and retrospectively analyzed the chest CT imaging data of 52 patients at the last time of admission and the first follow-up after discharge, including primary manifestations, concomitant manifestations, and degree of residual lesion dissipation. Results: At the first follow-up after discharge, 16 patients with COVID-19 recovered to normal chest CT appearance, while 36 patients still had residual pulmonary lesions, mainly including 33 cases of ground-glass opacity, 5 cases of consolidation, and 19 cases of fibrous strip shadow. The proportion of residual pulmonary lesions in severe cases (17/19) was statistically higher than in moderate cases (19/33) (χ 2 = 5.759, P < 0.05). At the first follow-up, residual pulmonary lesions were dissipated to varying degrees in 47 cases, and lesions remained unchanged in 5 cases. There were no cases of increased numbers of lesions, enlargement of lesions, or appearance of new lesions. The dissipation of residual pulmonary lesions in moderate patients was statistically better than in severe patients (Z = -2.538, P < 0.05). Conclusion: Clinically cured patients with COVID-19 had faster dissipation of residual pulmonary lesions after discharge, while moderate patients had better dissipation than severe patients. However, at the first follow-up, most patients still had residual pulmonary lesions, which were primarily ground-glass opacity and fibrous strip shadow. The proportion of residual pulmonary lesions was higher in severe cases of COVID-19, which required further follow-up.


Subject(s)
COVID-19 Testing/methods , COVID-19/diagnostic imaging , Lung/diagnostic imaging , Multidetector Computed Tomography , SARS-CoV-2 , Adult , Aftercare , Aged , COVID-19/therapy , Female , Follow-Up Studies , Hospitalization , Humans , Male , Middle Aged , Retrospective Studies , Severity of Illness Index
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