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1.
Pamukkale Medical Journal ; 15(4):804-812, 2022.
Article in Turkish | Scopus | ID: covidwho-20240817

ABSTRACT

Purpose: The present study aims to compare the results of the COVID-19 rapid antigen test (ExacTest™ COVID-19 Antigen Rapid Test) and real-time polymerase chain reaction (RT-PCR) test in samples of people suspected of coronavirus disease (COVID-19). Materials and methods: Among the samples submitted between January 2022 and March 2022 with suspicion of COVID-19, 299 samples subject to simultaneous COVID-19 RADT (Rapid Antigen Detection Test) and RT- PCR were evaluated retrospectively. The Real-Time PCR test was studied with the DS CORONEX COVID-19 Multiplex Real time-qPCR Test Kit (DS Nano and Biotechnology Product Tracing and Tracking Co., Turkey) and the rapid antigen test was studied by the immunochromatographic method with ExacTest™ COVID-19 Antigen Rapid Test Cassette kit (General Diagnostica inc., California, USA). Ag-RDT test results were evaluated with the fluorescent immunoassay analyzer (FIATEST Analyzer, Hangzhou Alltest Biotech Co., Ltd. China). Results: RT-PCR test was positive in 53 (17.7%) samples. The RADT's sensitivity was found 88.7 (95% Cl 77.0-95.7), specificity 98.0 (95% Cl 95.3-99.3), positive predictive value 90.4 (95% Cl 79.7-95.8), negative predictive value 97.6 (95% Cl 95.0-98.8), and accuracy 96.3 (95% Cl 93.5-98.2). Sample sensitivities of patients under and over 18 years of age have been identified as 75 (95% Cl 19.4-99.4) and 89.8 (95% Cl 77.8-96.6), respectively. The sensitivity of patients with and without symptoms was 95.5 (95% Cl 77.2-99.9) and 83.9 (95% Cl 66.3-94.6), respectively. For samples with a cycle threshold (Ct) of <20, 20-<25, 25-<30 and 30-<35, the concordance of testing was 100%, 92.9%, 78.9% and 80%, respectively. Conclusion: The rapid antigen kit studied complies with the use criteria recommended by the World Health Organization and is quite useful for the rapid diagnosis of symptomatic patients in COVID-19. © 2022, Pamukkale University. All rights reserved.

2.
Germs ; 12(4):507-518, 2022.
Article in English | EMBASE | ID: covidwho-20234801

ABSTRACT

Introduction In this study, we aimed to monitor anti-spike and anti-nucleocapsid antibodies positivity in healthcare workers (HCWs) vaccinated with two doses of inactivated CoronaVac (Sinovac, China) vaccine. Methods Overall, 242 volunteer HCWs were included. Of the participants, 193 were HCWs without history of prior documented COVID-19 (Group 1), while 49 had history of prior documented COVID-19 before vaccination (Group 2). The participants were followed up for SARS-CoV-2 antibodies positivity at four different blood sampling time points (immediately before the second vaccine dose and at the 1st, 3rd months and 141-150 days after the second dose). We investigated the serum IgG class antibodies against SARS-CoV-2 RBD region and IgG class antibodies against SARS-CoV-2 nucleocapsid antigen by chemiluminescent microparticle immunoassay (CMIA) method using commercial kits. Results We found positive serum anti-RBD IgG antibody in 76.4% of the participants (71% in Group 1;98% in Group 2) 28 days after the first dose. When the antibody levels of the groups were compared at the four blood sampling time points, Group 2 anti-RBD IgG levels were found to be significantly higher than those in Group 1 at all follow-up time points. Although anti-RBD IgG positivity persisted in 95.6% of all participants in the last blood sampling time point, a significant decrease was observed in antibody levels compared to the previous blood sampling time point. Anti-nucleocapsid IgG antibody was positive in 12 (6.2%) of participants in Group 1 and 32 (65.3%) in Group 2 at day 28 after the first dose. At the fourth blood sampling time point, anti-nucleocapsid antibodies were found to be positive in a total of 20 (9.7%) subjects, 10 (6.1%) in Group 1 and 10 (23.8%) in Group 2. Conclusions In this study, it was determined that serum antibody levels decreased in both groups after the third month after the second dose in HCWs vaccinated with CoronaVac vaccine.Copyright © GERMS 2022.

3.
Gogus-Kalp-Damar Anestezi ve Yogun Bakim Dernegi Dergisi ; 28(2):164-171, 2022.
Article in English | EMBASE | ID: covidwho-2251695

ABSTRACT

Objectives: Objective of the study was to examine the laboratory findings with clinical characteristics and treatments of patients who were hospitalized in a tertiary intensive care unit with the diagnosis of coronavirus disease 2019 (COVID-19) and developed pneumothorax and to determine epidemiology and risks of pneumothorax. Method(s): The study was conducted by retrospectively examining the electronic records of 681 COVID-19 patients who were followed up between 1 April 2020 and 1 January 2021 in 3 tertiary intensive care units (each was 24 beds). Patients demographic and clinical characteristics, laboratory findings, mechanical ventilator parameters and chest imaging were evaluated retrospectively. Result(s): Pneumothorax in 22 (3.2%) of 681 with COVID-19 patients was detected and acute respiratory distress syndrome (ARDS) in 481 (70.6). All the study patients met ARDS diagnostic criterias. Mortality rates were 43.4% (296/681) in all patients, 52.8% (254/481) in patients with ARDS, and 86.3% (19/22) in patients with pneumothorax. Pneumothorax occurred in the patients within a mean of 17.4+/-4.8 days. The computed tomographies of patients were observed common ground-glass opacities, heterogenic distribution with patch infiltrates, alveolar exudates, interstitial thickening in the 1st week of their symptom onset. Conclusion(s): We observed that pneumothorax significantly increased mortality in COVID-19 patients with ARDS. We believe that understanding and preventing the characteristics of pneumothorax will make an important contribution to mortality reduction.Copyright © 2022 by The Cardiovascular Thoracic Anaesthesia and Intensive Care.

4.
16th IEEE International Conference on Semantic Computing, ICSC 2022 ; : 91-98, 2022.
Article in English | Scopus | ID: covidwho-1788732

ABSTRACT

We introduce novel applications of the word embedding association test (WEAT)-a method for assessing differential biases and attitudes in word embeddings-for identifying correlations of human attitudes and behaviors with word embedding associations, and for automatically detecting words associated with a concept. We assess our methods by measuring the evolution of associations related to COVID-19, using survey data from the COVID States project as validation, along with a set of COVID-19 validation words developed based on surveys and sample responses created by expert psychologists studying COVID-19 behavior. We first show that word associations measured using the WEAT correlate with the behaviors and attitudes of the population which produced an embedding's training corpus. We take Pearson's \rho between word embedding associations from a diachronic set of English-language word embeddings with COVID States survey data related to COVID-19 attitudes and behaviors. We find statistically significant correlations between WEAT associations and survey results for 19 of 23 survey questions, with Pearson's \rho as high as.96. Survey responses for 10 questions correlate with WEAT associations in embeddings trained on Twitter data from several weeks prior to the survey. We also introduce the unipolar word embedding association test (U-WEAT), which measures strength of association with a single attribute word group, rather than between two opposing polar attribute groups. In an embedding trained on Twitter data from Oregon, the U-WEAT returns a positive effect size for 88% of validation words based on their association with a COVID-19 concept group, where less than 20% of the embedding vocabulary has a positive effect size, despite the prevalence of language related to COVID-19 during the time period in which the corpus was trained. A qualitative analysis of other words identified by the U-WEAT reveals a wide array of people, places, behaviors, and attitudes related to COVID-19. © 2022 IEEE.

5.
Turkish Journal of Biochemistry-Turk Biyokimya Dergisi ; 46(3):245-253, 2021.
Article in English | Web of Science | ID: covidwho-1332042

ABSTRACT

Objectives: Coronavirus disease 2019 (COVID-19) is a kind of viral pneumonia which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). MicroRNAs (miRNA) are small non-coding RNAs consisting of 19-25 nucleotides and play a role in post-transcriptional gene regulation. We have focused on serum expression levels of microRNA (miRNA) a novel concept of in host-virus interactions. MicroRNA expression profiles were investigated in serum samples of COVID-19 patients. Materials and methods: The samples were collected from 40 patients diagnosed with COVID-19 patients and from 10 healthy controls. Expression profile of 20 miRNAs were examined using a quantitative real-time polymerase chain reaction (qPCR). Results: Statistically significant expression level differences (p < 0.05) were detected in nine miRNAs in COVID-19 patients and healthy controls. 7 miRNAs (hsa-let-7d, hsa-miR-17, hsa-miR-34b, hsa-miR-93, hsa-miR-200b, hsa-miR-200c, hsa-miR-223) expression levels were found to be significantly decreased and the expression levels of 2 miRNAs (hsa-miR-190a and hsa-miR-203) significantly increased respect to healthy controls. Conclusions: We expect that a miRNA profile can be beneficial for the diagnosis of the COVID-19. Our result revealed that the increase in hsa-miR-190a level may be a prognostic factor related to the COVID-19 disease.

6.
Proc. - IEEE Int. Conf. Semant. Comput., ICSC ; : 82-83, 2021.
Article in English | Scopus | ID: covidwho-1145232

ABSTRACT

This paper considers the problem of automatically characterizing biases that may be associated with emerging information operations via artificial intelligence. Accurate analysis of these emerging topics usually requires laborious, manual analysis by experts to annotate millions of tweets to identify biases in new topics. We introduce adaptations of the Word Embedding Association Test [1] to a new domain: information operations. We validate our method using known information operation-related tweets from Twitter's Transparency Reports, and we perform a case study on the COVID-19 pandemic to evaluate our method's performance on non-labeled Twitter data, demonstrating its usability in emerging domains. © 2021 IEEE.

7.
Signa Vitae ; 16(1):147-151, 2020.
Article in English | EMBASE | ID: covidwho-679195

ABSTRACT

Background: There is gobal concern regarding the prognosis of COVID-19 patients requiring care in the Intensive Care Unit (ICU). The aim of this study is to report the demographics, clinical features, comorbidities, imaging findings, and prognosis among critically ill patients with COVID-19 in the ICU. Methods: This retrospective study included patients with laboratory-confirmed COVID-19 infection or clinical and radiological confirmed COVID-19 infection who were admitted to adult ICUs between March 18 and April 22, 2020. Demographic data, the recent exposure history, clinical symptoms, laboratory findings and comorbidities were recorded. Acute Physiology and Chronic Health Evaluation II (APACHE II) and Sequential Organ Failure Assessment (SOFA) scores were calculated. as well as mechanical ventilation parameters and blood gas results. Results: Twenty-four adult patients were admitted to the ICU with laboratory-confirmed COVID-19 (n = 15) or clinical and radiological confirmed COVID-19 (n = 9). One or more comorbidities were detected in 22/24 of the patients. All patients had abnormal radiography imaging on admission. Twenty patients had bilateral ground-glass opacification on computerized tomography (CT) scan. Almost all patients (23/24) underwent invasive mechanical ventilation therapy. Three patients underwent noninvasive mechanical ventilation. Ten patients died. The mean length of ICU stay in patients who died was 9.6 ± 9 days (2-18 days). The mean length of ICU stay of the four patients who were discharged from the ICU to the floor was 17 ± 12.9 days. The mean length of ICU stay of patients still in the ICU was (n = 10) was 13.36 ± 10.92 days. Conclusion: The vast majority of patients admitted to the ICU with the diagnosis of COVID-19 have multiple co-morbidities, require ventilator support, and experience a high mortality rate.

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