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1.
Medicine (Baltimore) ; 100(36): e26855, 2021 Sep 10.
Article in English | MEDLINE | ID: covidwho-2191052

ABSTRACT

ABSTRACT: Coronavirus disease (COVID-19) has spread worldwide. X-ray and computed tomography (CT) are 2 technologies widely used in image acquisition, segmentation, diagnosis, and evaluation. Artificial intelligence can accurately segment infected parts in X-ray and CT images, assist doctors in improving diagnosis efficiency, and facilitate the subsequent assessment of the severity of the patient infection. The medical assistant platform based on machine learning can help radiologists make clinical decisions and helper in screening, diagnosis, and treatment. By providing scientific methods for image recognition, segmentation, and evaluation, we summarized the latest developments in the application of artificial intelligence in COVID-19 lung imaging, and provided guidance and inspiration to researchers and doctors who are fighting the COVID-19 virus.


Subject(s)
COVID-19/diagnostic imaging , Machine Learning , Pneumonia, Viral/diagnostic imaging , SARS-CoV-2 , Humans , Radiography , Tomography, X-Ray Computed
3.
Medicine (Baltimore) ; 100(18): e25837, 2021 May 07.
Article in English | MEDLINE | ID: covidwho-2191001

ABSTRACT

BACKGROUND: There are large knowledge gaps regarding how transmission of 2019 novel coronavirus disease (COVID-19) occurred in different settings across the world. This study aims to summarize basic reproduction number (R0) data and provide clues for designing prevention and control measures. METHODS: Several databases and preprint platforms were retrieved for literature reporting R0 values of COVID-19. The analysis was stratified by the prespecified modeling method to make the R0 values comparable, and by country/region to explore whether R0 estimates differed across the world. The average R0 values were pooled using a random-effects model. RESULTS: We identified 185 unique articles, yielding 43 articles for analysis. The selected studies covered 5 countries from Asia, 5 countries from Europe, 12 countries from Africa, and 1 from North America, South America, and Australia each. Exponential growth rate model was most favored by researchers. The pooled global R0 was 4.08 (95% CI, 3.09-5.39). The R0 estimates for new and shifting epicenters were comparable or even higher than that for the original epicenter Wuhan, China. CONCLUSIONS: The high R0 values suggest that an extraordinary combination of control measures is needed for halting COVID-19.


Subject(s)
Basic Reproduction Number , COVID-19/epidemiology , Global Health , Pneumonia, Viral/epidemiology , Humans , Pandemics , Pneumonia, Viral/virology , SARS-CoV-2
4.
Oncology (Williston Park) ; 34(9): 377-378, 2020 09 15.
Article | MEDLINE | ID: covidwho-2206550

ABSTRACT

The telehealth explosion was facilitated by the onset of the coronavirus disease 2019 (COVID-19) pandemic, but what happens when the crisis is over? Will there be lasting changes to the practice of medicine and delivery of care, or will providers and patients alike be eager to go back to the "old way" of doing things? Jeremy Gabrysch, MD, a physician and CEO of Remedy, an on-demand urgent care service that delivers doctors right to your front door, discusses what the future of telehealth may hold.


Subject(s)
Delivery of Health Care , Reimbursement Mechanisms , Standard of Care , Telemedicine/trends , Betacoronavirus , COVID-19 , Coronavirus Infections/epidemiology , Humans , Pandemics , Pneumonia, Viral/epidemiology , SARS-CoV-2 , Telemedicine/economics , Telemedicine/methods , Telemedicine/standards
8.
mSphere ; 5(3)2020 06 24.
Article in English | MEDLINE | ID: covidwho-2193484

ABSTRACT

The contamination of patients' surroundings by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remains understudied. We sampled the surroundings and the air of six negative-pressure non-intensive care unit (non-ICU) rooms in a designated isolation ward in Chengdu, China, that were occupied by 13 laboratory-confirmed coronavirus disease 2019 (COVID-19) patients who had returned from overseas travel, including 2 asymptomatic patients. A total of 44 of 112 (39.3%) surface samples were positive for SARS-CoV-2 as detected by real-time PCR, suggesting extensive contamination, although all of the air samples were negative. In particular, in a single room occupied by an asymptomatic patient, four sites were SARS-CoV-2 positive, highlighting that asymptomatic COVID-19 patients do contaminate their surroundings and impose risks for others with close contact. Placement of COVID-19 patients in rooms with negative pressure may bring a false feeling of safety, and the importance of rigorous environment cleaning should be emphasized.IMPORTANCE Although it has been well recognized that the virus SARS-CoV-2, the causative agent of COVID-19, can be acquired by exposure to fomites, surprisingly, the contamination of patients' surroundings by SARS-CoV-2 is largely unknown, as there have been few studies. We performed an environmental sampling study for 13 laboratory-confirmed COVID-19 patients and found extensive contamination of patients' surroundings. In particular, we found that asymptomatic COVID-19 patients contaminated their surroundings and therefore imposed risks for other people. Environment cleaning should be emphasized in negative-pressure rooms. The findings may be useful to guide infection control practice to protect health care workers.


Subject(s)
Asymptomatic Infections/epidemiology , Betacoronavirus/isolation & purification , Coronavirus Infections/epidemiology , Environmental Exposure , Environmental Microbiology , Pneumonia, Viral/epidemiology , COVID-19 , Containment of Biohazards/methods , Coronavirus Infections/pathology , Environment , Humans , Pandemics , Pneumonia, Viral/pathology , SARS-CoV-2
9.
Transfusion ; 60(5): 908-911, 2020 05.
Article in English | MEDLINE | ID: covidwho-2193291

ABSTRACT

BACKGROUND: The first coronavirus (COVID-19) case was reported in United States in the state of Washington, approximately 3 months after the outbreak in Wuhan, China. Three weeks later, the US federal government declared the pandemic a national emergency. The number of confirmed COVID-19 positive cases increased rather rapidly and changed routine daily activities of the community. STUDY DESIGN AND METHODS: This brief report describes the response from the hospital, the regional blood center, and the hospital-based transfusion services to the events that took place in the community during the initial phases of the pandemic. RESULTS: In Washington State, the first week of March started with four confirmed cases and ended with 150; by the end of the second week of March there were more than 700 cases of confirmed COVID-19. During the first week, blood donations dropped significantly. Blood units provided from blood centers of nonaffected areas of the country helped keep inventory stable and allow for routine hospital operations. The hospital-based transfusion service began prospective triaging of blood orders to monitor and prioritize blood usage. In the second week, blood donations recovered, and the hospital postponed elective procedures to ensure staff and personal protective equipment were appropriate for the care of critical patients. CONCLUSION: As community activities are disrupted and hospital activities switch from routine operations to pandemic focused and urgent care oriented, the blood supply and usage requires a number of transformations.


Subject(s)
Betacoronavirus , Blood Transfusion , Coronavirus Infections , Pandemics , Pneumonia, Viral , Blood Donors , COVID-19 , Coronavirus Infections/epidemiology , Coronavirus Infections/physiopathology , Hospital Planning , Humans , Pneumonia, Viral/epidemiology , Pneumonia, Viral/physiopathology , SARS-CoV-2 , Washington/epidemiology
15.
Theranostics ; 12(10): 4779-4790, 2022.
Article in English | MEDLINE | ID: covidwho-2203050

ABSTRACT

New variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are continuing to spread globally, contributing to the persistence of the COVID-19 pandemic. Increasing resources have been focused on developing vaccines and therapeutics that target the Spike glycoprotein of SARS-CoV-2. Recent advances in microfluidics have the potential to recapitulate viral infection in the organ-specific platforms, known as organ-on-a-chip (OoC), in which binding of SARS-CoV-2 Spike protein to the angiotensin-converting enzyme 2 (ACE2) of the host cells occurs. As the COVID-19 pandemic lingers, there remains an unmet need to screen emerging mutations, to predict viral transmissibility and pathogenicity, and to assess the strength of neutralizing antibodies following vaccination or reinfection. Conventional detection of SARS-CoV-2 variants relies on two-dimensional (2-D) cell culture methods, whereas simulating the micro-environment requires three-dimensional (3-D) systems. To this end, analyzing SARS-CoV-2-mediated pathogenicity via microfluidic platforms minimizes the experimental cost, duration, and optimization needed for animal studies, and obviates the ethical concerns associated with the use of primates. In this context, this review highlights the state-of-the-art strategy to engineer the nano-liposomes that can be conjugated with SARS-CoV-2 Spike mutations or genomic sequences in the microfluidic platforms; thereby, allowing for screening the rising SARS-CoV-2 variants and predicting COVID-19-associated coagulation. Furthermore, introducing viral genomics to the patient-specific blood accelerates the discovery of therapeutic targets in the face of evolving viral variants, including B1.1.7 (Alpha), B.1.351 (Beta), B.1.617.2 (Delta), c.37 (Lambda), and B.1.1.529 (Omicron). Thus, engineering nano-liposomes to encapsulate SARS-CoV-2 viral genomic sequences enables rapid detection of SARS-CoV-2 variants in the long COVID-19 era.


Subject(s)
COVID-19 , Coronavirus Infections , Pneumonia, Viral , Animals , Antibodies, Neutralizing , Antibodies, Viral , COVID-19/complications , COVID-19/diagnosis , Coronavirus Infections/prevention & control , Genomics , Humans , Liposomes , Microfluidics , Mutation , Pandemics/prevention & control , Peptidyl-Dipeptidase A/metabolism , SARS-CoV-2/genetics , Spike Glycoprotein, Coronavirus
16.
researchsquare; 2023.
Preprint in English | PREPRINT-RESEARCHSQUARE | ID: ppzbmed-10.21203.rs.3.rs-2458402.v1

ABSTRACT

Background: The nerves in the legs and feet are most frequently damaged by diabetic neuropathy. The COVID-19 infection is associated with a high risk of neuropathy symptoms. Case Presentation: On July 12, 2022, a 58-year-old black female retiree with significant symptoms of numbness and muscle weakness in the hands and legs was brought into the emergency room. 17 years prior, she received a type 2 diabetes mellitus diagnosis. Metformin 1.5 g twice a day and glibenclamide 10 mg twice a day were part of her therapy regimen. When she was admitted to the emergency room, she described a one-day history of shortness of breath, frequent urination, excessive thirst, hyperglycemia, excessive appetite, fever, headache, and dehydration. A chest X-ray showed bilateral diffuse, patchy airspace opacities that could be caused by multifocal pneumonia or viral pneumonia. She started receiving 1000 mL of fluid resuscitation (0.9% normal saline) as soon as she was moved to the critical care unit, along with a drip-in insulin infusion. Conclusion: Diabetes, infections like COVID-19, poor vitamin levels, and other factors can all contribute to diabetic neuropathies. According to the Centers for Disease Control and Prevention, patients with type 2 diabetes mellitus are much more likely to experience severe morbidity and death from coronavirus disease-19. Symptoms of diabetic neuropathy continued for months after a COVID-19 infection test resulted in a positive result.


Subject(s)
Pneumonia , Diabetes Mellitus, Type 2 , Hypesthesia , COVID-19 , Pneumonia, Viral , Headache , Death , Nervous System Diseases , Dyspnea , Fever , Hyperglycemia , Muscle Weakness , Dehydration , Diabetes Mellitus , Diabetic Neuropathies
17.
arxiv; 2023.
Preprint in English | PREPRINT-ARXIV | ID: ppzbmed-2301.02468v1

ABSTRACT

In medical practice, the contribution of information technology can be considerable. Most of these practices include the images that medical assistance uses to identify different pathologies of the human body. One of them is X-ray images which cover much of our work in this paper. Chest x-rays have played an important role in Covid 19 identification and diagnosis. The Covid 19 virus has been declared a global pandemic since 2020 after the first case found in Wuhan China in December 2019. Our goal in this project is to be able to classify different chest X-ray images containing Covid 19, viral pneumonia, lung opacity and normal images. We used CNN architecture and different pre-trained models. The best result is obtained by the use of the ResNet 18 architecture with 94.1% accuracy. We also note that The GPU execution time is optimal in the case of AlexNet but what requires our attention is that the pretrained models converge much faster than the CNN. The time saving is very considerable. With these results not only will solve the diagnosis time for patients, but will provide an interesting tool for practitioners, thus helping them in times of strong pandemic in particular.


Subject(s)
Pneumonia, Viral
18.
Elife ; 92020 08 21.
Article in English | MEDLINE | ID: covidwho-2155740

ABSTRACT

We conducted voluntary Covid-19 testing programmes for symptomatic and asymptomatic staff at a UK teaching hospital using naso-/oro-pharyngeal PCR testing and immunoassays for IgG antibodies. 1128/10,034 (11.2%) staff had evidence of Covid-19 at some time. Using questionnaire data provided on potential risk-factors, staff with a confirmed household contact were at greatest risk (adjusted odds ratio [aOR] 4.82 [95%CI 3.45-6.72]). Higher rates of Covid-19 were seen in staff working in Covid-19-facing areas (22.6% vs. 8.6% elsewhere) (aOR 2.47 [1.99-3.08]). Controlling for Covid-19-facing status, risks were heterogenous across the hospital, with higher rates in acute medicine (1.52 [1.07-2.16]) and sporadic outbreaks in areas with few or no Covid-19 patients. Covid-19 intensive care unit staff were relatively protected (0.44 [0.28-0.69]), likely by a bundle of PPE-related measures. Positive results were more likely in Black (1.66 [1.25-2.21]) and Asian (1.51 [1.28-1.77]) staff, independent of role or working location, and in porters and cleaners (2.06 [1.34-3.15]).


Subject(s)
Coronavirus Infections/epidemiology , Health Personnel/statistics & numerical data , Pneumonia, Viral/epidemiology , Adolescent , Adult , Age Factors , Aged , Asymptomatic Infections/epidemiology , Betacoronavirus/isolation & purification , COVID-19 , Coronavirus Infections/transmission , Coronavirus Infections/virology , Female , Hospitals, Teaching/statistics & numerical data , Humans , Incidence , Infectious Disease Transmission, Patient-to-Professional/statistics & numerical data , Intensive Care Units/statistics & numerical data , Male , Middle Aged , Pandemics , Pneumonia, Viral/transmission , Pneumonia, Viral/virology , Risk , SARS-CoV-2 , Surveys and Questionnaires , United Kingdom/epidemiology , Young Adult
19.
Elife ; 92020 08 17.
Article in English | MEDLINE | ID: covidwho-2155739

ABSTRACT

Temporal inference from laboratory testing results and triangulation with clinical outcomes extracted from unstructured electronic health record (EHR) provider notes is integral to advancing precision medicine. Here, we studied 246 SARS-CoV-2 PCR-positive (COVIDpos) patients and propensity-matched 2460 SARS-CoV-2 PCR-negative (COVIDneg) patients subjected to around 700,000 lab tests cumulatively across 194 assays. Compared to COVIDneg patients at the time of diagnostic testing, COVIDpos patients tended to have higher plasma fibrinogen levels and lower platelet counts. However, as the infection evolves, COVIDpos patients distinctively show declining fibrinogen, increasing platelet counts, and lower white blood cell counts. Augmented curation of EHRs suggests that only a minority of COVIDpos patients develop thromboembolism, and rarely, disseminated intravascular coagulopathy (DIC), with patients generally not displaying platelet reductions typical of consumptive coagulopathies. These temporal trends provide fine-grained resolution into COVID-19 associated coagulopathy (CAC) and set the stage for personalizing thromboprophylaxis.


Subject(s)
Betacoronavirus/isolation & purification , Blood Coagulation Disorders/diagnosis , Blood Coagulation Tests , Blood Coagulation , Clinical Laboratory Techniques , Coronavirus Infections/diagnosis , Pneumonia, Viral/diagnosis , Aged , Betacoronavirus/pathogenicity , Biomarkers/blood , Blood Coagulation Disorders/blood , Blood Coagulation Disorders/virology , COVID-19 , COVID-19 Testing , Coronavirus Infections/blood , Coronavirus Infections/virology , Disease Progression , Female , Fibrinogen/metabolism , Host Microbial Interactions , Humans , Leukocyte Count , Longitudinal Studies , Male , Middle Aged , Pandemics , Platelet Count , Pneumonia, Viral/blood , Pneumonia, Viral/virology , Predictive Value of Tests , Reproducibility of Results , Retrospective Studies , SARS-CoV-2 , Time Factors
20.
Elife ; 92020 08 13.
Article in English | MEDLINE | ID: covidwho-2155738

ABSTRACT

As of 1 May 2020, there had been 6808 confirmed cases of COVID-19 in Australia. Of these, 98 had died from the disease. The epidemic had been in decline since mid-March, with 308 cases confirmed nationally since 14 April. This suggests that the collective actions of the Australian public and government authorities in response to COVID-19 were sufficiently early and assiduous to avert a public health crisis - for now. Analysing factors that contribute to individual country experiences of COVID-19, such as the intensity and timing of public health interventions, will assist in the next stage of response planning globally. We describe how the epidemic and public health response unfolded in Australia up to 13 April. We estimate that the effective reproduction number was likely below one in each Australian state since mid-March and forecast that clinical demand would remain below capacity thresholds over the forecast period (from mid-to-late April).


Subject(s)
Betacoronavirus , Coronavirus Infections/epidemiology , Pandemics , Pneumonia, Viral/epidemiology , Adolescent , Adult , Age Distribution , Aged , Aged, 80 and over , Australia/epidemiology , COVID-19 , Child , Child, Preschool , Communicable Disease Control/methods , Communicable Disease Control/organization & administration , Communicable Disease Control/statistics & numerical data , Coronavirus Infections/prevention & control , Female , Forecasting , Geography, Medical , Hospitalization/statistics & numerical data , Humans , Infant , Infant, Newborn , Male , Middle Aged , Pandemics/prevention & control , Pneumonia, Viral/prevention & control , Public Health , Quarantine , SARS-CoV-2 , Travel , Young Adult
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